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 reso..., Tissue samples were dried on Whatman filter paper, and DNA was extracted using the same methods described by Hess et al. (2013) before applying protocols for genotyping-in-thousands by sequencing (GT-seq) custom amplicon methods (Campbell et al. 2015) on an Illumina sequencer.  The primers for all GT-seq loci were published previously and publicly available (Koch et al. 2019).  Genotypes of all individuals were organized using the R package EFGLmh (https://github.com/delomast/EFGLmh/) to create input formats required for all analytical programs used in this study.  A baseline of reference collections was compiled from a set of 61 reference collections that were classified into 19 reporting groups to use genetic stock identification (GSI) to assign the most likely reporting group of origin without a minimum threshold for assignment probabilities (observed genetic stock, “GenStock_obs”) using the R package, rubias (https://github.com/eriqande/rubias).  “Columbia River Basin Chinook Salmon..., , # Visual and genetic stock identification of a test fishery to forecast Columbia River spring Chinook salmon stocks 2 weeks into the future

This is a data file containing the individual metadata and genotypic data required to analyze the test fishery mixtures from 2017 - 2022 and the mixture data from the Adult Fish Facility at Bonneville Dam for the same time series. The genotypic data were used to perform parentage and genetic stock identification analyses, and the metadata are needed to recreate the weekly strata used in the abundance estimation.

## Description of the data and file structure

This is an excel file containing three tabs: \"BONAFF_IndData\", \"TestFishery_IndData\", and \"Chinook sorted_genotypes\". The \"BONAFF_IndData\" is the individual metadata for Chinook salmon collected at Bonneville Dam. The 18 field headings include \"Order\" (unique number to sort the individuals to correspond with the genotypes), \"Rear\" (H, HNC, W corresponds with clipped and unclipped hatchery...