Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the future
[1];
[5]
- Columbia River Inter‐Tribal Fish Commission Portland Oregon USA
- Washington Department of Fish and Wildlife Ridgefield Washington USA
- Fish Ecology Division, Northwest Fisheries Science Center National Marine Fisheries Service, National Oceanic and Atmospheric Administration Seattle Washington USA
- Conservation Biology Division, Northwest Fisheries Science Center National Marine Fisheries Service, National Oceanic and Atmospheric Administration Port Orchard Washington USA
- Columbia River Inter‐Tribal Fish Commission Hagerman Idaho USA
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 ( R 2 = 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, R 2 = 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.
- Sponsoring Organization:
- USDOE
- OSTI ID:
- 2325483
- Journal Information:
- Evolutionary Applications, Journal Name: Evolutionary Applications Journal Issue: 3 Vol. 17; ISSN 1752-4571
- Publisher:
- Wiley-BlackwellCopyright Statement
- Country of Publication:
- United Kingdom
- Language:
- English
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