Visual and genetic stock identification of a test fishery to forecast Columbia River spring chinook salmon stocks 2 weeks into the future

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 five 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” versus “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 two-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.