Chum Salmon Genetic Diversity in the Northeastern Pacific Ocean Assessed with Single Nucleotide Polymorphisms (SNPs): Applications to Fishery Management

Abstract

We examined genetic diversity patterns among 55 collections of Chum Salmon from the northeastern Pacific Ocean using 89 single nucleotide polymorphisms (SNPs). The distribution of Chum Salmon samples extended from the Nass River along the coast of British Columbia and along the coast of Washington as far south as the Columbia River. Chum Salmon represented three previously defined run-groups: fall (primarily), summer, and winter. Genetic variation at SNP loci, as measured by F ST , ranged from 0.002 to 0.279 over all collections and averaged 0.062 over all loci. Similar to the genetic patterns detected with microsatellites and allozymes, genetic variation followed a regional structure along geographic distance, with genetic diversity being highest in the north and decreasing southward, then increasing in and near the Columbia River. Within Puget Sound, Washington, genetic variation was structured further according to run timing (fall, summer, and winter) and shared ancestry. Simulations indicated that this suite of SNPs is powerful for identifying regional components in a Chum Salmon mixed fishery. Because of the transferability of SNP data, the growing SNP baseline for Chum Salmon will be useful for multiple agencies managing Chum Salmon around the Pacific Rim.

Congruent population structure across paralogous and nonparalogous loci in Salish Sea chum salmon (Oncorhynchus keta)

“…Observed population structure was consistent with Small et al. () and shows that both geographic and temporal proximity contribute to reproductive isolation between chum salmon populations in the Salish Sea. The large genetic difference of the Hamma Hamma River collection on the first two PC axes (Figure ) is consistent with previous results showing this population is distinct from other local chum salmon populations (Johnson et al., ).…”

“…We also investigate the genetic associations with life history variation in both paralogous and nonparalogous loci. Our analysis focuses on chum salmon ( Oncorhynchus keta ) from a portion of the Salish Sea in the Pacific Northwest region of North America; populations of this anadromous species are characterized by distinct life history variation in time of spawning including summer, fall and winter runs (Small, Johnson, Bowman, & Martinez, ; Small et al., ). Time of spawning is an ecologically important trait in salmon that contributes to reproductive isolation and resilience (Schindler et al., ).…”

Stock composition of adult chum salmon Oncorhynchus keta caught in a setnet fishery estimated using genetic identification, scale patterns, and otolith thermal marking

“…The application of molecular techniques to stock identification of Pacific salmon has provided high resolution of stock-composition estimations (Beacham et al 2005). For example, Small et al (2015) demonstrated that a panel of 89 SNPs, representing 55 populations of chum salmon along the coasts of British Columbia and Washington State, was powerful for identifying regional components in a fishery of mixed-origin chum salmon collected from the Canada-US border region. DNAbased genetic markers, SNPs and microsatellites are effective tools for the evaluation of regional stock compositions of mixed-fishery chum salmon samples and provide useful information for fisheries management.…”

Genetic Stock Identification and Relative Contribution of Arctic Char (<i>Salvelinus alpinus</i>) from the Hornaday and Brock Rivers to Subsistence Fisheries in Darnley Bay, Northwest Territories + Supplementary Appendix Tables S1 to S4 (See Article Tools)

“…Fisheries managers use this method extensively to estimate the proportional contribution of stocks to mixed-stock fisheries. This is especially true on the west coast of North America, where mixed-stock analysis has been routinely used for decades on all Pacific salmon species (Seeb and Crane, 1999;Habicht et al, 2010;Beacham et al, 2011Beacham et al, , 2012Small et al, 2015). Assessments of the utility of MSA in Canadian Arctic fisheries are only recently emerging (but see Harris and Taylor, 2010).…”

“…These fractional proportions are allocated to the corresponding baseline sampling locations, and the overall mixture proportions are estimated as the sum of all fractional assignments. This method is thought to be more accurate than traditional assignment tests (e.g., Hedgecock et al, 2001) and provides a powerful tool for resolving proportional contributions to mixed-stock fisheries, especially when coupled with genetic markers that resolve fine-scale patterns of genetic stock structure (e.g., Ruzzante et al, 2000;Harris and Taylor, 2010;Beacham et al, 2012;Small et al, 2015).…”