Genetic data were collected and prepared with the use of protein electrophoresis from 52 spawning locations in southeastern Alaska and northern British Columbia. Genetic relationships were examined from principal components analysis and unrooted trees constructed from genetic distances between collections. These descriptive analyses suggest a geographic basis to genetic divergence among populations. This geographic basis was confirmed using log-likelihood-ratio analysis and analyses of variance. Three groups of populations were observed: one from systems that drain into the inside waters of northern and central southeast Alaska; another from the far southeastern islands (including Prince of Wales Island); and the third in systems of the southern inside waters. Although the geographic structure was a statistically significant component of the overall genetic structure, gene diversity analysis indicates that only about 4.7% of the total genetic variability was attributable to genetic differences among those regions, whereas about 8.4% of the total was due to differences among populations within each region. The other 87.0% of the variation occurred, on average, within each collection.

Genetic stock identification techniques were used to identify the origin and provide stock-specific migration and distribution patterns of juvenile chum (Oncorhynchus keta) salmon caught during annual fall surveys (2002) along the eastern Bering Sea (Fig. 1). Preliminary results indicate that: 1) Yukon River Fall chum salmon are widely distributed from offshore of the Yukon River, eastward to 62B0N, 172B0W, and as far south as Nunivak Island (60B0N), suggesting a southwesterly migration pathway along the Bering Sea shelf; 2) juvenile chum salmon from the Kuskokwim River are narrowly distributed south of Nunivak Island from the mouth of the Kuskokwim River, south to 58B0N, and as far west as 168B0W, suggesting a westerly migration pathway along the Bering Sea shelf; and 3) northern Russia juvenile chum salmon stocks (mainly stocks from rivers draining into the Gulf of Anadyr) are distributed as far east as 62B0N, 171B0W (Fig. 2). These results are unique in that they represent the first attempt to identify early marine distribution and migration of juvenile chum salmon stocks on the eastern Bering Sea shelf.

Allozymes from 46 loci were analyzed from chum salmon (Oncorhynchus keta) collected at 61 locations in southeast Alaska and northern British Columbia. Of the 42 variable loci, 21 had a common allele frequency <0.95. We observed significant heterogeneity within and among six regional groups: central southeast Alaska, Prince of Wales Island area, southern southeast Alaska b?? northern British Columbia, north-central British Columbia, and two groups in the Queen Charlotte Islands. Genetic variation among regions was significantly greater than within regions. The three island groups were distinct from each other and from the mainland populations. Allele frequencies were stable over time in 14 of 15 locations sampled for more than 1 yr. The geographic basis for heterogeneity among regions is confounded in part by spawning-time differences. The Prince of Wales and Queen Charlotte populations spawn in the fall; the mainland populations spawn mainly in the summer, although some overlap exists. Overall, most genetic diversity (97%) occurred within sampling locations; the remaining diversity was distributed almost equally within and among regions. Our genetic data may provide fishery managers a means to estimate stock composition in the mixed-stock fisheries near this boundary between the United States and Canada.

Immature chum salmon were collected by the F/V Northwest Explorer between September 5 and October 8, during the 2002 BASIS survey across the eastern Bering Sea shelf and Aleutian Islands (for details, see Murphy et al. 2003). Approximately 1,600 fish were aged, checked for the presence of hatchery thermal marks, and genotyped for allozyme loci. Scale aging and otolith mark identification were done by the Alaska Department of Fish and Gameb??s Mark, Tag, and Age Laboratory in Juneau, Alaska. Otoliths with thermal marks were compared with voucher specimens to verify hatchery of origin. Heart, liver, and muscle tissues were extracted and then analyzed with protein electrophoresis to identify genotypes for the 20 allozyme loci in the chum salmon coastwide genetic baseline (Kondzela et al. 2002). Genetic data were pooled into one of four geographic areasb??western Aleutian Islands, eastern Aleutian Islands, southeastern Bering Sea shelf, and northeastern Bering Sea shelf. In the eastern and western Aleutian Islands, the catches were large enough to further stratify the data by ocean age. Regional origin estimates were made for each mixture collection using a conditional maximum likelihood method (Pella and Masuda model in SPAM v. 3.7, ADF&G 2001) and the full 356-population genetic baseline. The 95% nonsymmetric confidence intervals were determined from 1000 bootstrap estimates in which the baseline and mixture were re-sampled.

A genetic analyses of samples from the Chinook salmon (Oncorhynchus tshawytscha) bycatch from the 2007-2013 Bering Sea-Aleutian Island and Gulf of Alaska trawl fisheries for walleye pollock (Gadus chalcogrammus) were 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.

Genetic data of salmon bycatch samples collected by fisheries observers are used for mixed-stock analyses to determine geographic region of origin. This work is done at the Auk Bay Lab in Juneau Alaska. The data are loaded to the the North Pacific Halibut and Groundfish database maintained by FMA Division at the Alaska Fisheries Science Center in Seattle Washington

Electrophoretic analysis of Asian even brood-year pink salmon stocks has shown regional heterogeneity (Noll et al. in review). Hypothetical mixed fisheries were created using data from 24 variable loci from Noll et al. in review. The mixture was analyzed to test the accuracy and precision of this baseline data for potential use in mixed fishery analyses. Thirteen stocks were separated into four management regions: Japan, Sakhalin, eastern Kamchatka, and western Kamchatka. Simulations were varied in sample size, number of loci, and percent regional contribution. The simulated mixtures were analyzed using the Conditional Maximum Likelihood Estimate (MLE). The mean estimate, standard deviation, and coefficient of variation were calculated for standardized comparison by both stock and region. Computed MLEs showed that estimates for the Noll et al. baseline improved in accuracy and precision with increased sample size and retention of important loci. When 24 loci and a minimum of 200 samples in a mixture were used, the baseline was approximately 80% accurate in its ability to distinguish regions from a mixture.

This project evaluates data from coded wire tagging with that from parental based tagging to identify stock of origin for Chinook salmon landed in Washington state commercial troll fishery.

This project evaluates data from coded wire tagging with that from parental based tagging to identify stock of origin for Chinook salmon landed in Washington state commercial troll fishery.

This project genetically analyzed 1,620 chinook salmon samples from the 2009 spring salmon excluder device test. These samples were collected over a short period of time from a limited geographical area and thus represent a unique sample set.