An international multi‐laboratory project was conducted to develop a standardized DNA database for Chinook salmon (Oncorhynchus tshawytscha). This project was in response to the needs of the Chinook Technical Committee of the Pacific Salmon Commission to identify stock composition of Chinook salmon caught in fisheries during their oceanic migrations. Nine genetics laboratories identified 13 microsatellite loci that could be reproducibly assayed in each of the laboratories. To test that the loci were reproducible among laboratories, blind tests were conducted to verify scoring consistency for the nearly 500 total alleles. Once standardized, a dataset of over 16,000 Chinook salmon representing 110 putative populations was constructed ranging throughout the area of interest of the Pacific Salmon Commission from Southeast Alaska to the Sacramento River in California. The dataset differentiates the major known genetic lineages of Chinook salmon and provides a tool for genetic stock identification of samples collected from mixed fisheries. A diverse group of scientists representing the disciplines of fishery management, genetics, fishery administration, population dynamics, and sampling theory are now developing recommendations for the integration of these genetic data into ocean salmon management.
The dynamic Quaternary geology of the Pacific Ring of Fire created substantial challenges for biogeography. Fish life history and population genetic variation were shaped by climate change, repeated formation and subsidence of ice sheets, sea-level change, volcanism and tectonics, isostatic rebound, and now human activities. It is widely recognized in Chinook salmon (Oncorhynchus tshawytscha) that parallel evolution and phenotypic plasticity have obscured range-wide patterns of life-history segregation with evolutionary lineage, yet the idea of the lineages themselves persists. We employed a large, internationally standardized, microsatellite data set to explore population structure at coast-wide scale and test for two divergent lineages, whether or not related to life history. We found at least 27 distinct lineages. However, relationships among groups were poorly resolved — essentially a star phylogeny. We found pervasive isolation by distance among groups, complicating cluster analysis. Only in the interior Columbia River (east of the Cascade Mountains) is there a deep genetic bifurcation that supports both the two-lineage hypothesis and the life-history segregation hypothesis. This broad-scale perspective helps reconcile different views of Chinook salmon phylogeography and life-history distribution.
It is widely recognized that genetic diversity within species is shaped by dynamic habitats. The quantitative and molecular genetic patterns observed are the result of demographics, mutation, migration, and adaptation. The populations of rainbow trout Oncorhynchus mykiss in the Columbia River basin (including both resident and anadromous forms and various subspecies) present a special challenge to understanding the relative roles of those factors. Standardized microsatellite data were compiled for 226 collections (15,658 individuals) from throughout the Columbia and Snake River basins to evaluate the genetic patterns of structure and adaptation. The data were primarily from fish of the anadromous life history form, and we used a population grouping procedure based on principal components and hierarchical k‐means clustering to cluster populations into eight aggregates or groups with similar allele frequencies. These aggregates approximated geographic regions, and the two largest principal components corresponded to ancestral lineages of Sacramento redband trout O. m. stonei, coastal rainbow trout O. m. irideus, and interior Columbia River redband trout O. m. gairdneri. Genetic data were partitioned among primary aggregates (lower Columbia, middle–upper Columbia, and Snake rivers), and the magnitude of genetic divergence relative to genetic diversity was analyzed (per locus) to test for evidence of selection and subsequent signals of adaptation. Two loci showed higher divergence than expected by chance (i.e., positive selection); however, both of these loci were on the fringe of the 99% confidence level and are potential false positives. Genetic patterns were also significantly correlated with certain environmental and habitat parameters (e.g., precipitation), but the extent to which those correlations are causal as opposed to effectual remains unclear. Despite the remaining questions, these data provide a foundation for more detailed investigations of harvest, admixture, and introgression between hatchery‐ and natural‐origin fish and differences in reproductive success among individuals as well as monitoring trends in productivity.
Due to the challenges associated with monitoring in riverine environments, unbiased and precise spawner abundance estimates are often lacking for populations of Pacific salmon Oncorhynchus spp. listed under the Federal Endangered Species Act. We investigated genetic approaches to estimate the 2009 spawner abundance for a population of Columbia River Chinook Salmon Oncorhynchus tshawytscha via genetic mark–recapture and rarefaction curves. The marks were the genotyped carcasses collected from the spawning area during the first sampling event. The second sampling event consisted of a collection of juveniles from a downstream migrant trap located below the spawning area. The parents that assigned to the juveniles through parentage analysis were considered the recaptures, which was a subset of the genotypes captured in the second sample. Using the Petersen estimator, the genetic mark–recapture spawner abundance estimates based on the binomial and hypergeometric models were 910 and 945 Chinook Salmon, respectively. These results were in agreement with independently derived spawner abundance estimates based on redd counts, area‐under‐the‐curve methods, and carcass tagging based on the Jolly–Seber model. Using a rarefaction curve approach, which required only the juvenile offspring sample, our estimate of successful breeders was 781 fish. Our genetic‐based approaches provide new alternatives to estimate adult Pacific salmon abundance in challenging environmental conditions or for populations with poor or unknown estimates of precision.
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