Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the future
Abstract Modern fisheries management strives to balance opposing goals of protection for weak stocks and opportunity for harvesting healthy stocks. Test fisheries can aid management of anadromous fishes if they can forecast the strength and timing of an annual run with adequate time to allow fisheri...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-03-01
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| Series: | Evolutionary Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/eva.13667 |
| _version_ | 1797242537421832192 |
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| author | Jon E. Hess Bethany M. Deacy Michelle W. Rub Donald M. Van Doornik John M. Whiteaker Jeffrey K. Fryer Shawn R. Narum |
| author_facet | Jon E. Hess Bethany M. Deacy Michelle W. Rub Donald M. Van Doornik John M. Whiteaker Jeffrey K. Fryer Shawn R. Narum |
| author_sort | Jon E. Hess |
| collection | DOAJ |
| description | Abstract Modern fisheries management strives to balance opposing goals of protection for weak stocks and opportunity for harvesting healthy stocks. Test fisheries can aid management of anadromous fishes if they can forecast the strength and timing of an annual run with adequate time to allow fisheries planning. Integration of genetic stock identification (GSI) can further maximize utility of test fisheries by resolving run forecasts into weak‐ and healthy‐stock subcomponents. Using 5 years (2017–2022) of test fishery data, our study evaluated accuracy, resolution, and lead time of predictions for stock‐specific run timing and abundance of Columbia River spring Chinook salmon (Oncorhynchus tshawytscha). We determined if this test fishery (1) could use visual stock identification (VSI) to forecast at the coarse stock resolution (i.e., classification of “lower” vs. “upriver” stocks) upon which current management is based and (2) could be enhanced with GSI to forecast at higher stock resolution. VSI accurately identified coarse stocks (83.3% GSI concordance), and estimated a proxy for abundance (catch per unit effort, CPUE) of the upriver stock in the test fishery that was correlated (R2 = 0.90) with spring Chinook salmon abundance at Bonneville dam (Rkm 235). Salmon travel rates (~8.6 Rkm/day) provided predictions with 2‐week lead time prior to dam passage. Importantly, GSI resolved this predictive ability as finely as the hatchery broodstock level. Lower river stock CPUE in the test fishery was correlated with abundance at Willamette Falls (Rkm 196, R2 = 0.62), but could not be as finely resolved as achieved for upriver stocks. We described steps to combine VSI and GSI to provide timely in‐season information and with prediction accuracy of ~12.4 mean absolute percentage error and high stock resolution to help plan Columbia River mainstem fisheries. |
| first_indexed | 2024-04-24T18:40:48Z |
| format | Article |
| id | doaj.art-35bde0e2e07d4062833db1ed09b05c5a |
| institution | Directory Open Access Journal |
| issn | 1752-4571 |
| language | English |
| last_indexed | 2024-04-24T18:40:48Z |
| publishDate | 2024-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Evolutionary Applications |
| spelling | doaj.art-35bde0e2e07d4062833db1ed09b05c5a2024-03-27T11:48:33ZengWileyEvolutionary Applications1752-45712024-03-01173n/an/a10.1111/eva.13667Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the futureJon E. Hess0Bethany M. Deacy1Michelle W. Rub2Donald M. Van Doornik3John M. Whiteaker4Jeffrey K. Fryer5Shawn R. Narum6Columbia River Inter‐Tribal Fish Commission Portland Oregon USAWashington Department of Fish and Wildlife Ridgefield Washington USAFish Ecology Division, Northwest Fisheries Science Center National Marine Fisheries Service, National Oceanic and Atmospheric Administration Seattle Washington USAConservation Biology Division, Northwest Fisheries Science Center National Marine Fisheries Service, National Oceanic and Atmospheric Administration Port Orchard Washington USAColumbia River Inter‐Tribal Fish Commission Portland Oregon USAColumbia River Inter‐Tribal Fish Commission Portland Oregon USAColumbia River Inter‐Tribal Fish Commission Hagerman Idaho USAAbstract Modern fisheries management strives to balance opposing goals of protection for weak stocks and opportunity for harvesting healthy stocks. Test fisheries can aid management of anadromous fishes if they can forecast the strength and timing of an annual run with adequate time to allow fisheries planning. Integration of genetic stock identification (GSI) can further maximize utility of test fisheries by resolving run forecasts into weak‐ and healthy‐stock subcomponents. Using 5 years (2017–2022) of test fishery data, our study evaluated accuracy, resolution, and lead time of predictions for stock‐specific run timing and abundance of Columbia River spring Chinook salmon (Oncorhynchus tshawytscha). We determined if this test fishery (1) could use visual stock identification (VSI) to forecast at the coarse stock resolution (i.e., classification of “lower” vs. “upriver” stocks) upon which current management is based and (2) could be enhanced with GSI to forecast at higher stock resolution. VSI accurately identified coarse stocks (83.3% GSI concordance), and estimated a proxy for abundance (catch per unit effort, CPUE) of the upriver stock in the test fishery that was correlated (R2 = 0.90) with spring Chinook salmon abundance at Bonneville dam (Rkm 235). Salmon travel rates (~8.6 Rkm/day) provided predictions with 2‐week lead time prior to dam passage. Importantly, GSI resolved this predictive ability as finely as the hatchery broodstock level. Lower river stock CPUE in the test fishery was correlated with abundance at Willamette Falls (Rkm 196, R2 = 0.62), but could not be as finely resolved as achieved for upriver stocks. We described steps to combine VSI and GSI to provide timely in‐season information and with prediction accuracy of ~12.4 mean absolute percentage error and high stock resolution to help plan Columbia River mainstem fisheries.https://doi.org/10.1111/eva.13667fisheries managementmigratory speciesparentagepopulation genetics – empirical |
| spellingShingle | Jon E. Hess Bethany M. Deacy Michelle W. Rub Donald M. Van Doornik John M. Whiteaker Jeffrey K. Fryer Shawn R. Narum Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the future Evolutionary Applications fisheries management migratory species parentage population genetics – empirical |
| title | Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the future |
| title_full | Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the future |
| title_fullStr | Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the future |
| title_full_unstemmed | Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the future |
| title_short | Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the future |
| title_sort | visual and genetic stock identification of a test fishery to forecast columbia river spring chinook salmon stocks 2 weeks into the future |
| topic | fisheries management migratory species parentage population genetics – empirical |
| url | https://doi.org/10.1111/eva.13667 |
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