NOAA Technical Memorandum NMFS-AFSC-365

C. M. Guthrie III, Hv. T. Nguyen, A. E. Thomson, K. Hauch, 

and J. R. Guyon

Genetic Stock Composition Analysis 

of the Chinook Salmon 

(Oncorhynchus tshawytscha) Bycatch 

from the 2016 Bering Sea Walleye 

Pollock (Gadus chalcogrammus) 

Trawl Fishery

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

Alaska Fisheries Science Center

January 2018

doi:10.7289/V5/TM-AFSC-365
NOAA Technical Memorandum NMFS

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.

The NMFS-AFSC Technical Memorandum series of the Alaska Fisheries 

Science Center continues the NMFS-F/NWC series established in 1970 by the 

Northwest Fisheries Center. The NMFS-NWFSC series is currently used by 

the Northwest Fisheries Science Center. 

This document should be cited as follows:

C. M. Guthrie III, Hv. T. Nguyen, A. E. Thomson, K. Hauch,

and J. R. Guyon. 2018. Genetic stock composition analysis of the 

Chinook salmon (Oncorhynchus tshawytscha) bycatch from the 2016 

Bering Sea walleye pollock (Gadus chalcogrammus) trawl fishery. U.S. 

Dep. Commer., NOAA Tech. Memo. NMFS-AFSC-365, 32 p.

Document available: http://www.afsc.noaa.gov/Publications/AFSC-TM/NOAA-TM-AFSC-365.pdf

Reference in this document to trade names does not imply endorsement by 

the National Marine Fisheries Service, NOAA.
January 2018

NOAA Technical Memorandum NMFS-AFSC-365

by

C. M. Guthrie III, Hv. T. Nguyen, A. E. Thomson, K. Hauch, 

and J. R. Guyon

Auke Bay Laboratories

Alaska Fisheries Science Center 

National Marine Fisheries Service

National Oceanic and Atmospheric Administration

17109 Pt. Lena Loop Road

Juneau, AK 99801

www.afsc.noaa.gov

U.S. DEPARTMENT OF COMMERCE

Wilbur L. Ross Jr., Secretary

National Oceanic and Atmospheric Administration

 RDML Timothy Gallaudet (ret.), Acting Under Secretary and Administrator

National Marine Fisheries Service

 Chris Oliver, Assistant Administrator for Fisheries 

doi:10.7289/V5/TM-AFSC-365

Genetic Stock Composition Analysis of 

the Chinook Salmon 

(Oncorhynchus tshawytscha) Bycatch 

from the 2016 Bering Sea Walleye 

Pollock (Gadus chalcogrammus) 
This document is available to the public through: 

National Technical Information Service 

U.S. Department of Commerce 

5285 Port Royal Road 

Springfield, VA 22161 

www.ntis.gov 
 

 

iii 

ABSTRACT 

A genetic analysis of samples from the Chinook salmon (Oncorhynchus tshawytscha) 

bycatch of the 2016 Bering Sea-Aleutian Island (BSAI) trawl fishery for walleye pollock (Gadus 

chalcogrammus) was undertaken to determine the overall stock composition of the bycatch. 

Samples were genotyped for 43 single nucleotide polymorphism (SNP) DNA markers and results 

were estimated using the Alaska Department of Fish and Game (ADF&G) SNP baseline. In 

2016, genetic samples from the Bering Sea were collected using a systematic random sampling 

protocol where one out of every 10 Chinook salmon encountered was sampled. Based on the 

analysis of 1,910 Chinook salmon bycatch samples collected throughout the 2016 BSAI walleye 

pollock trawl fishery, Coastal Western Alaska and British Columbia regions (34% and 29% 

respectively) dominated the sample set with smaller contributions from West Coast US (14%), 

and North Alaska Peninsula (13%) regions. Analysis of temporal groupings within the pollock 

“A” and “B” seasons revealed changes in stock composition during the course of the year with 

lower contributions of Coastal Western Alaska and North Alaska Peninsula regions and higher 

contributions of West Coast US, British Columbia, and NW Gulf of Alaska, regions during the 

“B” season when compared to the “A” season. 

 

v 

CONTENTS 

ABSTRACT _________________________________________________________________ iii 

CONTENTS _________________________________________________________________ v 

INTRODUCTION ____________________________________________________________ 1 

SAMPLE DISTRIBUTION _____________________________________________________ 3 

LABORATORY ANALYSIS ___________________________________________________ 8 

GENETIC STOCK COMPOSITION RESULTS_____________________________________ 9 

COMPARISON WITH PREVIOUS ESTIMATES __________________________________ 19 

SUMMARY ________________________________________________________________ 19 

Sampling Issues___________________________________________________________________ 20 

Stock Composition Estimates ________________________________________________________ 20 

Application of These Estimates_______________________________________________________ 21 

ACKNOWLEDGMENTS _____________________________________________________ 23 

CITATIONS ________________________________________________________________ 29 

APPENDICES ______________________________________________________________ 31 
 

 

INTRODUCTION 

Pacific salmon (Oncorhynchus spp.) are prohibited species in the federally managed 

Bering Sea and Gulf of Alaska (GOA) groundfish fisheries, which are subject to complex 

management rules (NPMFC 2017a,b) that are in part designed to reduce prohibited species catch 

(PSC; hereafter referred to as “bycatch”). It is important to understand the stock composition of 

Pacific salmon caught in these fisheries, which take place in areas that are known feeding habitat 

for multiple brood years of Chinook salmon (Oncorhynchus tshawytscha) from many different 

localities in North America and Asia (Myers et al. 2007, Davis et al. 2009). Chinook salmon are 

economically valuable and highly prized in commercial, subsistence and sport fisheries. 

Determining the geographic origin of salmon caught in federally managed fisheries is essential to 

understanding the effects that fishing has on Chinook salmon stocks, especially those with 

conservation concerns (NPFMC 2012). This report provides genetic stock identification results 

for the Chinook salmon bycatch samples collected from the U.S. Bering Sea (BS) walleye 

pollock (Gadus chalcogrammus) trawl fishery. National Marine Fisheries Service (NMFS) 

geographical statistical areas (NMFS area) associated with the BS groundfish fishery (areas 509-

524) and Alaska Department of Fish and Game (ADF&G) statistical areas (for details see 

http://www.adfg.alaska.gov/static/fishing/PDFs/commercial/chart03_bs.pdf) are shown in Figure 

1 and are used later in the report to describe the spatial distribution of the Chinook salmon 

bycatch and genetic samples. 

Amendment 91 to the North Pacific Fishery Management Council (NPFMC) Fishery 

Management Plan (FMP) for groundfish of the BSAI Management Area was enacted in 2010 and 

included retention of the all salmon caught in the pollock fishery. In 2011, a systematic random 

sampling design recommended by Pella and Geiger (2009) was implemented by the Alaska 
2 

Fisheries Science Center’s (AFSC) Fisheries Management and Analysis (FMA) North Pacific 

Groundfish and Halibut Observer Program (Observer Program) to collect genetic samples from 

one out of every 10 Chinook salmon encountered as bycatch in the BS pollock fishery. 

In 2016, genetic samples were collected by the Observer Program from the Chinook 

salmon bycatch of the BS pollock fishery by using the systematic sampling protocols 

recommended previously (Pella and Geiger 2009). The number of available samples and the 

unbiased sampling methodology facilitated the extrapolation of the sample stock composition to 

the overall Chinook bycatch from the BS pollock trawl fishery in 2016. Stock composition 

analyses were performed using the single nucleotide polymorphism (SNP) baseline provided by 

the ADF&G (Templin et al. 2011), the same baseline that was used previously to estimate stock 

composition of samples from the 2005-2015 Chinook salmon bycatch (NMFS 2009; Guyon et al. 

2010a, b; Guthrie et al. 2012-2017; Larson et al. 2013). For additional information regarding 

background and methodology, refer to the Chinook salmon bycatch report prepared previously 

for the 2008 Bering Sea trawl fishery (Guyon et al. 2010a). 
3 

Figure 1. -- NMFS (outlined in black) and ADF&G (outlined in light gray) statistical areas associated 

with the Bering Sea and Gulf of Alaska groundfish fisheries. 

SAMPLE DISTRIBUTION 

Samples were collected from the Chinook salmon bycatch by the Observer Program for 

analysis at AFSC’s Auke Bay Laboratories (ABL). Samples of axillary process tissue and scales 

were collected from the Chinook salmon bycatch throughout 2016. Axillary process tissues were 

stored in coin envelopes which were labeled, frozen, and shipped to ABL for analysis. Scales 

were collected as an additional source for genetic analysis, and for ageing if funding is available. 

In 2016, an estimated 21,926 Chinook salmon were taken in the bycatch of BSAI pollock 

trawl fisheries (NMFS 2017). The Chinook salmon bycatch estimate is 38% below the historical 
 

4 

average (35,309) for the Bering Sea between 1991 and 2015 (Fig. 2) (Table 1). Since 1991, and 

far below the highest overall Chinook bycatch in 2007 (Fig. 2) when an estimated 121,770 fish 

were taken. Of the total 2016 bycatch, 16,828 were from the trawl “A” season (01/01/16 to 

6/10/16) and 5,098 were from the “B” season (6/11/16 to 12/31/16). 

Figure 2. -- Yearly, “A” and “B” season estimates for the Chinook salmon bycatch from the Bering Sea 

pollock trawl fishery (NMFS 2017). 

In 2016, there were 2,148 genetic samples received from the BS Chinook salmon bycatch 

collected by the observer program; of those 1,910 were successfully genotyped for an overall 

genotyped sampling rate of 8.7% (“A” season had 1,488 fish, 8.8% sampling rate; “B” season 

had 422 fish, 8.3% sampling rate). 
5 

Table 1. -- Annual, “A” and “B” season estimates for the Chinook salmon bycatch from the 

Bering Sea-Aleutian Island pollock trawl fishery (NMFS 2017).

 Year Total "A" Season "B" Season 

1991 40,906 38,791 2,114

1992 35,950 25,691 10,259

1993 38,516 17,264 21,252

1994 33,136 28,451 4,686

1995 14,984 10,579 4,405

1996 55,623 36,068 19,554

1997 44,909 10,935 33,973

1998 51,322 15,193 36,130

1999 11,978 6,352 5,627

2000 4,961 3,422 1,539

2001 33,444 18,484 14,961

2002 34,495 21,794 12,701

2003 45,586 32,609 12,977

2004 51,696 23,093 28,603

2005 67,362 27,331 40,030

2006 82,695 58,391 24,304

2007 121,770 69,420 52,350

2008 21,480 16,638 4,842

2009 12,369 9,711 2,658

2010 9,697 7,630 2,067

2011 25,499 7,137 18,362

2012 11,344 7,765 3,579

2013 13,034 8,237 4,797

2014 15,031 11,539 3,492

2015 18,329 12,304 6,025

2016 21,926 16,828 5,098

Potential biases primarily introduced through spatial and temporal aspects of genetic sample 

collection from the bycatch are well documented and have the potential to affect resulting stock 

composition estimates (Pella and Geiger 2009). The distributions of 2016 Chinook salmon 

bycatch genetic samples were evaluated by comparing the collection of genetic samples with the 

overall bycatch distribution (Figs. 3 and 4). The temporal distribution of samples collected and 

successfully genotyped was evaluated across the two fishing seasons (Fig. 3). The sample spatial 

distribution was compared with the total bycatch by NMFS statistical area (NMFS area) over 
6 

time (Fig. 4). 2016 was the sixth year that systematic random sampling was employed for 

collecting genetic tissue from the Bering Sea Chinook salmon bycatch and Figure 4 shows the 

resulting genetic samples were spatially and temporally representative of the total Chinook 

bycatch (i.e., those fish not sampled for bycatch).. As in 2011-2015, the sample spatial and 

temporal distribution were well aligned in 2016 compared to previous years when samples were 

collected more opportunistically (Guyon et al. 2010a,b; Guthrie et al. 2012-2017). 

Figure 3. -- Number of Chinook salmon bycatch and genetic samples successfully genotyped graphed by 

statistical week. Weeks 4-18 correspond to the groundfish “A” season, whereas weeks 24-43 

correspond to the “B” season, the demarcation of which is a vertical line. 
7 

Figure 4. -- Comparison of the Chinook salmon bycatch by time and area with the distribution of available 

genetic samples. Top panel: Distribution of the 1,910 successfully genotyped samples from the 

2016 bycatch. Not graphed were 11 fish from NMFS area 523. Bottom panel: Distribution of the 

Chinook salmon caught in the 2016 Bering Sea pollock trawl fishery. Not graphed were 136 fish 

each from NMFS area 523, and 5 fish from NMFS area 524. Weeks 4-18 correspond to the 

groundfish “A” season, whereas weeks 24-43 correspond to the “B” season, the demarcation of 

which is a vertical line. 
 

 

8 

LABORATORY ANALYSIS 

DNA was extracted from axillary process tissue and genotyping was performed by using 

TaqmanTM chemistries Applied Biosystems Inc. on a Life Technologies QuantStudioTM or by 

matrix-assisted laser desorption/ionization - time of flight (MALDI-TOF) (Guyon et al. 2010a) 

on a Sequenom MassARRAY iPLEX platform (Gabriel et al. 2009) for the 43 SNP DNA 

markers represented in the Chinook salmon baseline (Templin et al. 2011). The SNP baseline 

contains genetic information for 172 populations of Chinook salmon grouped into 11 geographic 

regions (also known as stock groups or reporting groups) (Appendix 1). Proof tests performed 

previously have shown the baseline to be suitable for stock composition analysis (Templin et al. 

2011). TaqmanTM assays were compared to internal controls for both open array (OA) and 384-

well formats using the QuantStudioTM. The concordance rate between OA and 384 formats was 

99.99%. In addition to internal MALDI-TOF chip controls, 10 (out of 384 on a chip) previously 

genotyped samples from ADF&G, which used TaqManTM chemistries were included on each 

chip during the analyses and resulting genotypes were compared. Concordance rates of 99.9% 

between the two chemistries for the 2016 controls confirmed the utility and compatibility of both 

genotyping methods. 

From the 2016 Chinook salmon bycatch from the Bering Sea pollock trawl fishery, a total 

of 2,148 samples were analyzed of which 1,910 samples were successfully genotyped for 35 or 

more of the 43 SNP loci, a success rate of 88.9%. The remaining 1,910 successfully genotyped 

samples had genetic information for an average of 42 of 43 markers. Stock composition 

estimates were derived from BAYES software (Bayesian analysis; Pella and Masuda 2001; 

Appendix 2). The BAYES results were compared to SPAM software, (maximum likelihood 

analysis; ADF&G 2003) and both methods yielded almost identical stock composition estimates, 
9 

so only the BAYES results are reported here. BAYES software uses a Bayesian algorithm to 

produce stock composition estimates and can account for missing alleles in the baseline (Pella 

and Masuda 2001). For each BAYES analysis, 11 Monte Carlo chains starting at disparate values 

of stock proportions were configured such that 95% of the stocks came from one designated 

region with weights equally distributed among the stocks of that region. The remaining 5% were 

equally distributed among remaining stocks from all other regions. For all estimates, a flat prior 

of 0.005814 (calculated as 1/172) was used for all 172 baseline populations. The analyses were 

completed for a chain length of 10,000 with the first 5,000 deleted during the burn-in phase when 

determining overall stock compositions. Convergence of the chains to posterior distributions of 

stock proportions was determined with Gelman and Rubin shrink statistics (Gelman and Rubin 

1992), which were 1.02 or less for all the estimates, conveying strong convergence to a single 

posterior distribution (Pella and Masuda 2001). 

STOCK COMPOSITION RESULTS 

Results (BAYES) suggest that 60% of the 1,488 samples from the “A” season originated 

from Alaska river systems flowing into the Bering Sea (all regions north of the Aleutian Islands 

except for Russia) with the Coastal Western Alaska region contributing the most (39%), 

followed by the North Alaska Peninsula (17%), and Upper Yukon (2%). The other major 

contributors were British Columbia (26%), West Coast US (9%), and Coastal Southeast Alaska 

(4%) (Appendix 2). For the “B” season, over 81% of the 422 samples originated from regions 

south of the Aleutian chain with the British Columbia region contributing the most (37%), 

followed by the West Coast US (30%), Coastal Western Alaska 17%, Coastal Southeast Alaska 

(7%) and Northwest GOA (6%) regions, (Appendix 2). 
 

 

 

10 

For the entire year, 50% of the bycatch samples were estimated to be from Alaska river 

systems flowing into the Bering Sea with the Coastal Western Alaska region contributing the

most (34%), trailed by the North Alaska Peninsula (13%), Upper Yukon (2%) and Middle Yukon 

(2%). Other contributors were British Columbia (29%), West Coast US (14%), Coastal 

Southeast Alaska (4%), and Northwest GOA (2%) (Appendix 2). 

To investigate how stock compositions might vary among smaller areas, “A” season 

estimates were developed for five strata with sufficient numbers of samples as follows 

(Appendix 2, Figs. 1, 5-8): Saint George Island (335 samples, Fig. 6), Northwest Bering (554

samples, Fig. 7), Catcher Vessel Operation Area (CVOA) (715 samples, Fig. 8), Southeast 

Bering (934 samples, Fig. 7), and NMFS area 509 (501 samples, Fig. 1, 6) (NMFS 2017). It 

should be noted that some of these strata overlap. For the Saint George and Northwest Bering 

strata, the resulting stock compositions showed that 83% and 85% respectively were estimated to 

be from Alaska river systems flowing into the Bering Sea. The largest contributors were Coastal 

Western Alaska (51% for Saint George, 49% for Northwest Bering) and North Alaska Peninsula 

(23% for Saint George, 24% for Northwest Bering), followed by Upper Yukon (6% for Saint 

George and Northwest Bering). Fifteen percent of the samples from Saint George and 17% for

Northwest Bering strata were from regions south of the Aleutians, where the largest contributors 

were British Columbia (8% for Saint George, 11% for Northwest Bering), and Coastal Southeast 

Alaska (4% for Saint George, 3% for Northwest Bering). For the Catcher Vessel Operational 

Area (CVOA), Southeast Bering, and NMFS area 509 strata, more than half of the resulting 

stock composition estimates were from regions south of the Aleutians. The largest contributors 

were British Columbia (36% for CVOA, 35% for Southeast Bering, 39% for NMFS area 509),

West Coast US (14% for CVOA, 13% for Southeast Bering, 15% for NMFS area 509), and 
 

11 

Coastal Southeast Alaska (5% for CVOA, Southeast Bering and NMFS area 509). At least 40% 

of CVOA (42%), Southeast Bering strata (46%), and NMFS area 509 (40%) were estimated to 

be from Alaskan river systems flowing into the Bering Sea. The largest contributors were 

Coastal Western Alaska (34% for CVOA, 34% for Southeast Bering, and 22% for NMFS area 

509), and North Alaska Peninsula (8% for CVOA, 12% for Southeast Bering, 18% for NMFS 

area 509). 

Bering Sea "A" Season Area and Time 

Comparison 

All "A" 

70% 

60% 

50% 

40% 

30% 

20% 

10% 

0% 

St.George 

NW Bering 

CVOA 

SE Bering 

509 

All "B" 

2016 

Russia Coast W Mid Up N AK NW Copper NE GOA Coast SE BC West 

AK Yukon Yukon Pen GOA AK Coast US 

Figure 5. -- Comparison of area and time stock composition estimates from the 2016 Bering Sea Chinook 

salmon bycatch for “A” season: All (1,488 samples), Saint George Island (335 samples, Fig. 

6), Northwest Bering (554 samples, Fig. 7), CVOA (715 samples, Fig. 8), Southeast Bering 

(934 samples, Fig. 7), and NMFS area 509 (501 samples, Fig. 6). Bering Sea “B” season (422 

samples) and 2016 overall included for comparison. BAYES 95% credible intervals are plotted 

for estimates. 
12 

Figure 6. -- Location of Saint George Island (ADF&G Statistical Areas 705600, 695600, 685600, 705630, 

695631, and 685630) and NMFS area 509 strata used in comparative stock composition 

estimates from the 2016 Bering Sea Chinook salmon bycatch for “A” season (NMFS 2016). 
 

13 

Figure 7. -- Location of Northwest Bering and Southeast Bering strata used in comparative stock 

composition estimates from the 2016 Bering Sea Chinook salmon bycatch for “A” season 

(NMFS 2016). 
 

 

14 

Figure 8. -- Location of Catcher Vessel Operational Area (CVOA) stratum used in comparative stock 

composition estimates from the 2016 Bering Sea Chinook salmon bycatch for “A” season 

(NMFS 2016). 

For the “B” season, stock composition estimates were developed for NMFS areas 517 

and 519 combined(334 samples, Figs. 1, 9, 10, Table 10) (NMFS 2016). Unlike for the 2015 

samples, no estimates were developed for NMFS area 521 due to the small sample size and 

reduced fishing effort in this area. NMFS areas 517 and 519 had a slightly higher proportion of 

fish from regions southeast of the Aleutian Islands (84%), than the “B” season overall (81%). 
 

 

15 

Bering Sea "B" Season Area and Time 

Comparison 

All "B" 

0% 

5% 

10% 

15% 

20% 

25% 

30% 

35% 

40% 

45% 

50% 

517&519 

All "A" 

2016 

Russia Coast W Mid Up N AK NW Copper NE GOA Coast SE BC West 

AK Yukon Yukon Pen GOA AK Coast US 

Figure 9. -- Comparison of area and time stock composition estimates from the 2016 Bering Sea Chinook 

salmon bycatch for “B” season: All (422 samples), and NMFS Areas 517/519 (334 samples). 

Bering Sea “A” season (1,488 samples) and 2016 overall included for comparison. BAYES 

95% credible intervals are plotted for estimates. 
 

16 

Figure 10. -- Location of samples from NMFS Statistical Areas 517 and 519 used in comparative stock 

composition estimates from the 2016 Bering Sea Chinook salmon bycatch for “B” season 

(NMFS 2016). 

COMPARISON WITH PREVIOUS ESTIMATES 

In contrast to 2011 and similar to most other previous years studied, most of the Chinook 

salmon bycatch occurred in 2016 during the “A” season. Stock compositions from the analysis of 

the 2016 “A” season Chinook salmon bycatch showed that most samples continued to originate 

from river systems directly flowing into the Bering Sea but were lower than in previous years, 
 

17 

with an increase from GOA, BC, and West Coast US (Fig. 11). The Coastal Western Alaska 

region continued to be the largest contributor in the 2016 “A” season, but was lower than in all 

previous years. 

Figure 11. -- Comparison of “A” season (top) and “B” season (bottom) genetic stock composition 

estimates for 2011-2016 from the Bering Sea Chinook salmon bycatch. The same genetic 

baseline and regional groupings were used in all analyses. 

The 2016 “B” season stock composition estimates from Coastal Western Alaska 

continued to drop as observed across 2011-2015, a 57% decline since 2011 (Fig. 11). The 2016 

“B” season estimates continued the trend of increased contributions from British Columbia, West 

Coast US, and Coastal Southeast Alaska regions. The estimated relative contributions from these 

more southern regions have increased 61% since 2011 (Fig. 11). 

As in previous years since 2011, systematic random sampling was employed in 2016, 

where genetic samples were collected from one of every 10 Chinook salmon encountered. While 

changes in sampling protocols prior to 2011 necessitate caution in comparing analyses across 

longer time periods, when the stock compositions were analyzed for the entire year, the Coastal 
 

 

 

 

18 

Western Alaska region contribution trended downward between 2008 and 2010 but increased in 

2011, and then trended downward again through 2016 (Fig. 12). The North Alaska Peninsula 

regional contribution composed 13% of the bycatch in 2016, a slight increase from 2015 (Fig. 

12). The upper and middle Yukon River, GOA, and Coastal Southeast Alaska contributions 

continued to be low in 2016, while contributions from the British Columbia, and West Coast US 

regions have trended upward (Fig. 12). 

Figure 12. -- Comparison of yearly stock composition estimates (2008-2016) from the Bering Sea Chinook 

salmon bycatch. Estimates from 2011-2016 are overall bycatch estimates, whereas earlier 

estimates are of available sample sets. The same genetic baseline and general regional 

groupings were used in all analyses. Gulf of Alaska (GOA) group consists of combined values 

for Northwest GOA, Copper, and Northeast GOA. BAYES 95% credible intervals are plotted 

for yearly estimates. 

There was interest from the NPFMC Science and Statistical Committee (SSC) April 2017 

meeting on how smaller strata stock compositions might change between years so “A” season 

estimates were developed for the Northwest and Southeast Bering strata (Fig. 7) for which we 

had an adequate number of samples (Fig. 13) for analyses (NPFMC 2017c). In the Northwest 
 

19 

Bering stratum there is a downward trend in the Coastal Western Alaska region contribution and 

an upward trend in the British Columbia and North Alaska Peninsula region contributions, 

especially between 2015 and 2016. The trend in the Southeast Bering stratum is similar except 

for 2014, when the Coastal Western Alaska and North Alaska Peninsula contribution increased, 

with a reciprocal decline in British Columbia and West Coast US regions. 

Figure 13. -- Comparison of yearly stock composition estimates (2013-2016) from the Bering Sea Chinook 

“A” season Northwest Bering and Southeast Bering strata. Gulf of Alaska (GOA) group 

consists of combined values for Northwest GOA, Copper, and Northeast GOA. BAYES 95% 

credible intervals are plotted for yearly estimates. 

SUMMARY 

Salmon-dependent communities have expressed concern regarding the numbers of 

salmon caught as bycatch in the Bering Sea trawl fishery (Gisclair 2009). The incidental harvest 

of Chinook salmon in the Bering Sea pollock fishery averaged 35,309 salmon per year between 

1991 and 2016, with a peak of 121,770 in 2007 (NMFS 2017). The Bering Sea Chinook salmon 

bycatch has abated in more recent years dropping to a total of 21,926 Chinook salmon in 2016, 
20 

well below the 26-year average. Stock composition estimates of the Chinook salmon bycatch are 

needed for pollock and salmon fishery managers to understand the biological effects of the 

incidental take of salmon in the trawl fishery (Ianelli and Stram 2015). This report provides stock 

composition estimates of the Chinook salmon bycatch from the 2016 Bering Sea pollock trawl 

fishery. The results and limitations of this analysis are summarized below. 

Sampling Issues 

With the implementation of systematic random sampling in 2011, 2016 is the sixth 

year from which representative samples have been collected from the Chinook salmon bycatch. 

This represents a lot of effort over many years to develop standardized protocols for collecting 

sets of samples from numerous observers both at sea and in shore-based processing plants, the 

efforts of which are clearly apparent in the representative nature of the sample sets (Figs. 3 and 

4). The number of successfully genotyped Chinook salmon from the Bering Sea bycatch samples 

was 1,910, corresponding to an overall sampling rate in 2016 of 8.7%. 

Stock Composition Estimates 

Genetic stock composition analysis showed the majority of bycatch samples collected in 

the Bering Sea were from Alaska originating from river systems directly flowing into the Bering 

Sea. The stock composition of the Chinook salmon bycatch during the 2016 “A” season differed 

from the 2016 “B” season, demonstrating temporal differences (Appendix 2; Fig.11). This was 

especially apparent in the Coastal Western Alaska (39% vs. 17%), North Alaska Peninsula (17% 

vs. 1%), NW GOA (1% vs. 6%), British Columbia (26% vs. 37%), and West Coast US (9% vs. 

30%) stock groups. Spatial analysis showed that the stock compositions varied within season 

depending upon where the salmon in the bycatch were caught. For example, during the “A” 
 

 

21 

season there was a higher concentration of Western Alaska origin Chinook intercepted in the 

northern areas of the Bering Sea, and southern (south of the Aleutians) origin Chinook 

intercepted in the southern areas of the Bering Sea (Fig. 5). One must also consider that the 

bycatch in the “A” season is over three times greater than the “B” season, and that the stock 

composition differences may be due to seasonal migration of stocks. For example, the estimated 

number of West Coast US fish only slightly increases from 1,506 in the “A” season to 1,524 in 

the “B” season (Appendix 2), while its proportion increases from 9% to 30%, likely due to the 

absence or lower proportion of other stock groups. 

Application of Estimates 

The extent to which any salmon stock is impacted by the bycatch of the Bering Sea trawl 

fishery is dependent on many factors including 1) the overall size of the bycatch, 2) the age of 

the salmon caught in the bycatch, 3) the age of the returning salmon, and 4) the total annual 

escapement of the affected stocks. As such, a higher contribution of a particular stock one year 

does not necessarily imply greater impact than a smaller estimate the next. Stock composition 

estimates for the 2016 Bering Sea Chinook salmon bycatch were considered to be representative 

of the overall bycatch for this year. 
 
 

23 

ACKNOWLEDGMENTS 

We are grateful for the help from the AFSC’s FMA Program, the many participating 

observers who provided genetic samples. Thanks to Rob Ames and Bob Ryznar for developing 

AKFIN Answer reports that helped us develop new strata for genetic analyses. We are grateful to 

Chris Habicht, Andrew Munro and Dani Evenson of ADF&G, and AFSC’s Drs. Christine 

Kondzela and Jordan Watson for their thoughtful reviews of this report. Special thanks to AFSC 

Communications Program staff, especially James Lee, for their rapid and thorough editorial 

review of this document. 
 
25 

CITATIONS 

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for Analyzing Mixtures. Alaska Department of Fish and Game, Commercial Fisheries 

Division, Gene Conservation Laboratory, Anchorage, Alaska. 

Davis, N. D., A. V. Volkov, A. Y. Efimkin, N. A. Kuznetsova, J. L. Armstrong, and O. Sakai. 

2009. Review of BASIS salmon food habits studies. N. Pac. Anadr. Fish. Comm. Bull. 

5:197-208. 

Gabriel, S., L. Ziaugra, and D. Tabbaa. 2009. SNP genotyping using the Sequenom 

MassARRAY iPLEX platform. Current Protocols in Human Genetics Chapter 2, Unit 

212. 

Gelman, A., and D. B. Rubin. 1992. Inference from iterative simulation using multiple 

sequences. Stat. Sci. 7:457-511. 

Gisclair, B.R. 2009. Salmon bycatch management in the Bering Sea walleye pollock fishery: 

Threats and opportunities for Western Alaska. Am. Fish. Soc. Symp. 70:799–816. 

Guthrie, C. M. III, H. Nguyen, and J. R. Guyon. 2012. Genetic stock composition analysis of 

Chinook salmon bycatch samples from the 2010 Bering Sea trawl fisheries. U.S. Dep. 

Commer., NOAA Tech. Memo. NMFS-AFSC-232, 22 p. 

Guthrie, C. M. III, H. Nguyen, and J. R. Guyon. 2013. Genetic stock composition analysis of 

Chinook salmon bycatch samples from the 2011 Bering Sea and Gulf of Alaska trawl 

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Guthrie, C. M. III, Nguyen, Hv.T., and J. R. Guyon. 2015. Genetic stock composition analysis of 

the Chinook salmon bycatch from the 2013 Bering Sea walleye pollock (Gadus 

chalcogrammus) trawl fishery. U.S. Dep. Commer., NOAA Tech. Memo. NMFS-AFSC290, 21 p. 

Guthrie, C. M. III, Nguyen, Hv.T., and J. R. Guyon. 2016. Genetic stock composition analysis of 

the Chinook salmon bycatch from the 2014 Bering Sea walleye pollock (Gadus 

chalcogrammus) trawl fishery. U.S. Dep. Commer., NOAA Tech. Memo. NMFS-AFSC310, 25 p. 
 

26 

Guthrie, C. M. III, Nguyen, Hv.T., A. E. Thomson, and J. R. Guyon. 2017. Genetic stock 

composition analysis of the Chinook salmon bycatch from the 2015 Bering Sea walleye 

pollock (Gadus chalcogrammus) trawl fishery. U.S. Dep. Commer., NOAA Tech. Memo. 

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Bugaev, and L. W. Seeb. 2013. Single-nucleotide polymorphisms reveal distribution and 

migration of Chinook salmon (Oncorhynchus tshawytscha) in the Bering Sea and North 

Pacific Ocean. Can. J. Fish. Aquat. Sci. 70(1):128-141. 

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changes, and oceanographic conditions. N. Pac. Anadr. Fish. Comm. Bull. 4: 159-177. 

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PSC management measures, initial review draft environmental assessment. North Pacific 

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27 

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Ecol. Res. 11 (Suppl. 1):226–246. 
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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APPENDICES 

Appendix 1. -- Chinook salmon populations in the ADF&G SNP baseline with the regional 

designations used in the analyses of this report. S.= South, R.= River, H.= Hatchery, and 

L.= Lake. 

Reg Reg 

Population name num. Region Population name num. Region 

Bistraya River 1 Russia Henshaw Creek 3 Mid Yukon 

Bolshaya River 1 Russia Kantishna River 3 Mid Yukon 

Kamchatka River late 1 Russia Salcha River 3 Mid Yukon 

Pakhatcha River 1 Russia Sheenjek River 3 Mid Yukon 

Andreafsky River 2 Coast W AK S. Fork Koyukuk River 3 Mid Yukon 

Aniak River 2 Coast W AK Big Salmon River 4 Up Yukon 

Anvik River 2 Coast W AK Blind River 4 Up Yukon 

Arolik River 2 Coast W AK Chandindu River 4 Up Yukon 

Big Creek 2 Coast W AK Klondike River 4 Up Yukon 

Cheeneetnuk River 2 Coast W AK Little Salmon River 4 Up Yukon 

Eek River 2 Coast W AK Mayo River 4 Up Yukon 

Gagaryah River 2 Coast W AK Nisutlin River 4 Up Yukon 

George River 2 Coast W AK Nordenskiold River 4 Up Yukon 

Gisasa River 2 Coast W AK Pelly River 4 Up Yukon 

Golsovia River 2 Coast W AK Stewart River 4 Up Yukon 

Goodnews River 2 Coast W AK Takhini River 4 Up Yukon 

Kanektok River 2 Coast W AK Tatchun Creek 4 Up Yukon 

Kisaralik River 2 Coast W AK Whitehorse Hatchery 4 Up Yukon 

Kogrukluk River 2 Coast W AK Black Hills Creek 5 N AK Pen 

Kwethluk River 2 Coast W AK King Salmon River 5 N AK Pen 

Mulchatna River 2 Coast W AK Meshik River 5 N AK Pen 

Naknek River 2 Coast W AK Milky River 5 N AK Pen 

Nushagak River 2 Coast W AK Nelson River 5 N AK Pen 

Pilgrim River 2 Coast W AK Steelhead Creek 5 N AK Pen 

Salmon R. -Pitka Fork 2 Coast W AK Anchor River 6 NW GOA 

Stony River 2 Coast W AK Ayakulik River 6 NW GOA 

Stuyahok River 2 Coast W AK Benjamin Creek 6 NW GOA 

Takotna River 2 Coast W AK Chignik River 6 NW GOA 

Tatlawiksuk River 2 Coast W AK Crescent Creek 6 NW GOA 

Togiak River 2 Coast W AK Crooked Creek 6 NW GOA 

Tozitna River 2 Coast W AK Deception Creek 6 NW GOA 

Tuluksak River 2 Coast W AK Deshka River 6 NW GOA 

Unalakleet River 2 Coast W AK Funny River 6 NW GOA 

Beaver Creek 3 Mid Yukon Juneau Creek 6 NW GOA 

Chandalar River 3 Mid Yukon Karluk River 6 NW GOA 

Chena River 3 Mid Yukon Kasilof River mainstem 6 NW GOA 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

30 

Reg Reg 

Population name num. Region Population name num. Region 

Kenai River mainstem 6 NW GOA Kowatua River 9 Coast SE AK 

Killey Creek 6 NW GOA Little Tatsemenie River 9 Coast SE AK 

Ninilchik River 6 NW GOA Macaulay Hatchery 9 Coast SE AK 

Prairie Creek 6 NW GOA Medvejie Hatchery 9 Coast SE AK 

Slikok Creek 6 NW GOA Nakina River 9 Coast SE AK 

Talachulitna River 6 NW GOA Tahltan River 9 Coast SE AK 

Willow Creek 6 NW GOA Unuk R.-Deer Mountain H. 9 Coast SE AK 

Bone Creek 7 Copper Unuk River - LPW 9 Coast SE AK 

E. Fork Chistochina River 7 Copper Upper Nahlin River 9 Coast SE AK 

Gulkana River 7 Copper Big Qualicum River 10 BC 

Indian River 7 Copper Birkenhead River spring 10 BC 

Kiana Creek 7 Copper Bulkley River 10 BC 

Manker Creek 7 Copper Chilko River summer 10 BC 

Mendeltna Creek 7 Copper Clearwater River summer 10 BC 

Otter Creek 7 Copper Conuma River 10 BC 

Sinona Creek 7 Copper Damdochax Creek 10 BC 

Tebay River 7 Copper Ecstall River 10 BC 

Tonsina River 7 Copper Harrison River 10 BC 

Big Boulder Creek 8 NE GOA Kateen River 10 BC 

Kelsall River 8 NE GOA Kincolith Creek 10 BC 

King Salmon River 8 NE GOA Kitimat River 10 BC 

Klukshu River 8 NE GOA Klinaklini River 10 BC 

Situk River 8 NE GOA Kwinageese Creek 10 BC 

Tahini River 8 NE GOA Louis River spring 10 BC 

Tahini River - Pullen Creek H. 8 NE GOA Lower Adams River fall 10 BC 

Andrews Creek 9 Coast SE AK Lower Atnarko River 10 BC 

Blossom River 9 Coast SE AK Lower Kalum River 10 BC 

Butler Creek 9 Coast SE AK Lower Thompson River fall 10 BC 

Chickamin River 9 Coast SE AK Marble Creek 10 BC 

Chickamin River-LPW 9 Coast SE AK Middle Shuswap R. summer 10 BC 

Chickamin R.Whitman L. H. 9 Coast SE AK Morkill River summer 10 BC 

Clear Creek 9 Coast SE AK Nanaimo River 10 BC 

Cripple Creek 9 Coast SE AK Nechako River summer 10 BC 

Crystal Lake Hatchery 9 Coast SE AK Nitinat River 10 BC 

Dudidontu River 9 Coast SE AK Oweegee Creek 10 BC 

Genes Creek 9 Coast SE AK Porteau Cove 10 BC 

Hidden Falls Hatchery 9 Coast SE AK Quesnel River summer 10 BC 

Humpy Creek 9 Coast SE AK Quinsam River 10 BC 

Kerr Creek 9 Coast SE AK Robertson Creek 10 BC 

Keta River 9 Coast SE AK Salmon River summer 10 BC 

King Creek 9 Coast SE AK Sarita River 10 BC 
 

 

 

 

 

 

 

 

31 

Reg Reg 

Population name num. Region Population name num. Region 

Stuart River summer 10 BC Lower Deschutes R. fall 11 West Coast US 

Sustut River 10 BC Lyons Ferry H. summer/fall 11 West Coast US 

Torpy River summer 10 BC Makah National Fish H. fall 11 West Coast US 

Wannock River 10 BC McKenzie River spring 11 West Coast US 

Alsea River fall 11 West Coast US Sacramento River winter 11 West Coast US 

Carson Hatchery spring 11 West Coast US Siuslaw River fall 11 West Coast US 

Eel River fall 11 West Coast US Soos Creek Hatchery fall 11 West Coast US 

Forks Creek fall 11 West Coast US Upper Skagit River summer 11 West Coast US 

Hanford Reach 11 West Coast US 

Klamath River 11 West Coast US 
 

 

 

 

 

 

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32 

Appendix 2. -- Regional BAYES stock composition percentage estimates and estimated numbers of different strata of Chinook salmon from

 the 2016 Bering Sea pollock trawl fisheries. The BAYES mean estimates are also provided with standard deviations (SD), 95% 

credible intervals, and the median estimate. Sample sizes are adjacent to stratum designation. Total catch is the actual catch for 

 each stratum from AKFIN reports (NMFS 2017). Figures 1, 3, 6, 7, 8 and 10 show strata locations and timing. 

"A" Season (N=1,488) "B" Season (N=422) Bering Sea all (N=1.910) 

Est. # Mean SD 95% PI Est. # Mean SD 95% PI Est. # Mean SD 95% PI 

Russia 108 0.6 0.25 (0.2,1.2) 12 0.2 0.24 (0.0,0.9) 114 0.5 0.19 (0.2,1.0) 

Coast W AK 6,570 39.0 1.46 (36.2,41.9) 843 16.5 2.14 (12.5,20.8) 7,372 33.6 1.28 (31.2,36.2) 

Mid Yukon 283 1.7 0.40 (1.0,2.5) 18 0.4 0.60 (0.0,2.0) 327 1.5 0.34 (0.9,2.2) 

Up Yukon 365 2.2 0.43 (1.4,3.1) 34 0.7 0.48 (0.0,1.8) 406 1.9 0.35 (1.2,2.6) 

N AK Pen 2,839 16.9 1.17 (14.6,19.2) 56 1.1 0.72 (0.0,2.8) 2,927 13.4 0.96 (11.5,15.3) 

NW GOA 94 0.6 0.46 (0.0,1.6) 298 5.9 1.54 (3.1,9.1) 458 2.1 0.62 (1.0,3.4) 

Copper 3 0.0 0.06 (0.0,0.2) 90 1.8 0.73 (0.6,3.4) 75 0.3 0.18 (0.1,0.8) 

NE GOA 2 0.0 0.07 (0.0,0.2) 2 0.0 0.13 (0.0,0.3) 2 0.0 0.07 (0.0,0.1) 

Coast SE AK 663 3.9 0.72 (2.6,5.4) 333 6.5 1.70 (3.6,10.2) 971 4.4 0.64 (3.3,5.8) 

BC 4,394 26.1 1.26 (23.7,28.6) 1,888 37.0 2.68 (31.8,42.3) 6,312 28.8 1.14 (26.6,31.0) 

West Coast US 1,506 9.0 0.81 (7.4,10.6) 1,524 29.9 2.33 (25.4,34.5) 2,960 13.5 0.82 (11.9,15.1) 

Total Catch 16,828 5,098 21,926 

Saint George I. "A" (N=335) Area 509 "A" (N=501) CVOA "A" (N=715) 

Est. # Mean SD 95% PI Est. # Mean SD 95% PI Est. # Mean SD 95% PI 

Russia 0 0.0 0.05 (0.0,0.1) 1 0.0 0.03 (0.0,0.1) 126 1.6 0.54 (0.7,2.8) 

Coast W AK 1,969 51.2 3.15 (44.9,57.4) 1,208 22.4 2.07 (18.5,26.6) 2,684 33.6 1.96 (29.8,37.4) 

Mid Yukon 219 5.7 1.45 (3.2,8.8) 1 0.0 0.09 (0.0,0.3) 30 0.4 0.30 (0.0,1.1) 

Up Yukon 222 5.8 1.44 (3.3,8.9) 1 0.0 0.06 (0.0,0.2) 1 0.0 0.05 (0.0,0.2) 

N AK Pen 873 22.7 2.64 (17.7,28.0) 949 17.6 1.94 (13.9,21.5) 668 8.4 1.22 (6.1,10.9) 

NW GOA 14 0.4 0.61 (0.0,2.2) 13 0.2 0.43 (0.0,1.5) 84 1.1 0.81 (0.0,2.9) 

Copper 1 0.0 0.10 (0.0,0.3) 1 0.0 0.08 (0.0,0.2) 7 0.1 0.20 (0.0,0.7) 

NE GOA 1 0.0 0.11 (0.0,0.3) 2 0.0 0.15 (0.0,0.5) 2 0.0 0.13 (0.0,0.3) 

Coast SE AK 156 4.1 1.32 (1.8,6.9) 287 5.3 1.45 (2.8,8.5) 424 5.3 1.20 (3.2,7.9) 

BC 298 7.8 1.62 (4.9,11.2) 2,117 39.2 2.44 (34.5,44.0) 2,885 36.1 2.05 (32.1,40.1) 

West Coast US 94 2.4 0.87 (1.0,4.4) 816 15.1 1.72 (11.9,18.6) 1,083 13.6 1.40 (10.9,16.4) 

Total Catch 3,847 5,395 7,996 

SE Bering S. "A" (N=934) NW Bering S. "A" (N=554) Areas 517/519 "B" (N=334) 

Est. # Mean SD 95% PI Est. # Mean SD 95% PI Est. # Mean SD 95% PI 

Russia 112 1.1 0.40 (0.5,2.0) 1 0.0 0.03 (0.0,0.1) 13 0.3 0.30 (0.0,1.1) 

Coast W AK 3,457 33.6 1.78 (30.2,37.2) 3,177 48.6 2.49 (43.7,53.4) 548 13.6 2.30 (9.3,18.3) 

Mid Yukon 28 0.3 0.22 (0.0,0.8) 258 3.9 0.96 (2.3,6.0) 14 0.3 0.64 (0.0,2.2) 

Up Yukon 1 0.0 0.04 (0.0,0.1) 401 6.1 1.14 (4.1,8.5) 12 0.3 0.36 (0.0,1.3) 

N AK Pen 1,227 11.9 1.28 (9.5,14.6) 1,567 24.0 2.10 (19.9,28.2) 63 1.6 0.92 (0.2,3.7) 

NW GOA 87 0.9 0.77 (0.0,2.7) 14 0.2 0.41 (0.0,1.4) 252 6.2 1.87 (3.0,10.3) 

Copper 5 0.1 0.12 (0.0,0.4) 1 0.0 0.06 (0.0,0.2) 74 1.8 0.80 (0.6,3.7) 

NE GOA 4 0.0 0.13 (0.0,0.5) 1 0.0 0.10 (0.0,0.2) 2 0.0 0.22 (0.0,0.5) 

Coast SE AK 494 4.8 1.03 (2.9,7.0) 220 3.4 0.98 (1.6,5.5) 277 6.9 1.85 (3.7,10.9) 

BC 3,567 34.7 1.79 (31.2,38.3) 708 10.8 1.42 (8.2,13.8) 1,541 38.2 2.98 (32.4,44.1) 

West Coast US 1,295 12.6 1.22 (10.3,15.1) 195 3.0 0.76 (1.7,4.6) 1,241 30.8 2.64 (25.7,36.1) 

Total Catch 10,277 6,541 4,034 

RECENT TECHNICAL MEMORANDUMS

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AFSC- 

 

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platforms by the California sea lion (Zalophus californianus), 72 p. NTIS No.PB2018-100078. 

361 MCCONNAUGHEY, R. A., K. E. BLACKHART , M. P. EAGELTON , and J. MARSH. 2017. 

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360 TURNER, K., C. N. ROOPER, E. A. LAMAN, S. C. ROONEY, D. W. COOPER, and M. 

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359 RODGVELLER, C. J., P. W. MALECHA, and C. R. LUNSFORD. 2017. Long-term survival and 

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358 FAUNCE, C., J. SULLIVAN, S. BARBEAUX, J. CAHALAN, J. GASPER, S. LOWE, and 

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357 LAMAN, E. A., C. N. ROOPER, S. C. ROONEY, K. A. TURNER, D. W. COOPER, and 

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