In-season assessment and management of salmon stocks using a Bayesian time-density model

We document a time-density model for in-season assessment of salmon stocks that integrates both relative and absolute indicators of abundance and incorporates preseason information on run-size and migration timing using a Bayesian framework. We evaluate different data collection programs for Fraser River sockeye salmon (Oncorhynchus nerka) by examining the precision, bias and timeliness of resulting run-size estimates with a retrospective analysis. We quantify the run-size bias if migration was early versus late and evaluate the impact of run-size uncertainty on the ability to reach management objectives. In-season assessments greatly improve the accuracy and precision of run-size estimates compared to preseason forecasts. For the in-season assessment of Fraser River sockeye, CPUE data from seaward marine test fisheries, although less precise, were more informative at the peak marine migration than more precise terminal, in-river hydroacoustic data obtained on the same date, but conveying information of an earlier stage in the migration. Throughout the season, the best fisheries management results were obtained by relying on in-season assessments using both marine CPUE data as well as marine reconstructed abundance estimates derived from in-river hydroacoustic estimates, thereby taking advantage of the benefits of both sources of information.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author