Evaluation of management performance of a new state-space model for pink salmon (Oncorhynchus gorbuscha) stock–recruitment analysis

Abstract

A new state-space model (XSR) was developed to treat observation errors in spawner and catch data, and nonstationarity in productivity for pink salmon (Oncorhynchus gorbuscha). Closed-loop simulation was used to evaluate the management performance of XSR and compare its performance with that of a traditional stock-recruitment (SR) model (TSR) and a Kalman Filter SR model (KF). XSR produced higher expected catch than TSR and KF over a wide range of conditions. In some situations, TSR was preferred for reducing conservation concerns. However, large “outcome uncertainty" or implementation error in achieving desired management objectives can substantially reduce the management benefits of all assessment methods. Thus, outcome uncertainty should be considered in all management strategy evaluations, otherwise results will be misleading. Reducing outcome uncertainty may better help achieve objectives.

Can regime shifts in reproduction be explained by changing climate and food availability?

“…Examples are the Peterman's productivity method (Peterman et al, 2000;Silvar-Viladomiu et al, 2022a), state-space models whereby variation in productivity is stochastically assessed over time (e.g. Nishijima et al, 2021;Stock and Miller, 2021;Su, 2023), and the truncation of the recruitment time series to recent productivity conditions (Van Deurs et al, 2021;Silvar-Viladomiu et al, 2022b). Environmentally mediated SR models were, contrastingly, used in most of the scientific advice for rebuilding plans in the NEA (24 out of 30, Trenkel et al, 2023).…”