Application of genetic stock identification and parentage-based tagging in a mixed-stock recreational chinook salmon fishery
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Abstract
Genetic methods can guide and improve the management of recreational mixed-stock fisheries by informing stock-specific estimates of harvest. We applied genetic stock identification and parentage-based tagging to a recreational Chinook Salmon Oncorhynchus tshawytscha fishery in the Columbia River to illustrate the value of genetic analysis in management. We sampled landed catch in 2017 and 2018, assigned the fish to genetic reporting groups, explored temporal trends in harvest composition within and between seasons, and assessed the accuracy and precision of genetic methods against estimates from conventional tagging methodology. The genetic stock identification and parentage-based tagging produced concordant stock assignments, and the harvest composition estimates were validated with independent data. High assignment rates, relative to expended sampling effort, and precise harvest composition estimates with adequate sample sizes demonstrate that both genetic methods can be complementary, effective tools in advancing harvest assessment and recreational fisheries management. The success of genetic stock identification and parentage-based tagging supports the expanded application of genetics to similar fisheries, potentially alongside existing or emerging assessment methods, and guides future improvements in data collection and analysis.
Study Area
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Application of genetic stock identification and parentage-based tagging in a mixed-stock recreational chinook salmon fishery |
Series title | North American Journal of Fisheries Management |
DOI | 10.1002/nafm.10542 |
Volume | 41 |
Issue | 1 |
Year Published | 2021 |
Language | English |
Publisher | American Fisheries Society |
Contributing office(s) | Coop Res Unit Seattle |
Description | 12 p. |
First page | 130 |
Last page | 141 |
Country | United States |
State | Oregon, Washington |
Google Analytic Metrics | Metrics page |