In-Season Forecasting of Coho Salmon Marine Survival via Coded Wire Tag Recoveries

Abstract

Calculation of in-season marine survival rate forecasts for coho salmon Oncorhynchus kisutch can provide valuable support for in-season harvest management decisions because annual variability in marine survival accounts for a large proportion of total recruitment variability. We present a new forecasting model that utilizes coded wire tag (CWT) recovery information from early occurring fisheries to provide in-season marine survival forecasts that are timely enough to inform harvest management decisions for subsequent fisheries. We evaluate performance of the CWT model by using retrospective analyses on four coho salmon indicator stocks from northern British Columbia, Canada. For each stock, model selection analysis was used to identify which of three time-varying fishery catchability models used within the CWT model maximized forecasting performance. A Bayesian approach to parameter estimation was then applied to the best CWT model to generate probabilistic forecasts of marine survival rate for six consecutive weeks of in-season forecasting in each year. Although forecasted posterior distributions were wide in some cases, the posterior mode tracked marine survival relatively well in comparison with postseason marine survival estimates based on recoveries from all fisheries and the spawning grounds. Average percent forecast biases based on posterior modes were −1, −4, 19, and 57% for the four indicator stocks in the final week of forecasting. The lower tails of the posterior distributions were well defined, which is most relevant to identifying years of conservation concern due to extremely low marine survival. We conclude that timely in-season recovery and analysis of CWT information could improve the level of information available to inform in-season harvest management decisions.