Statement of the Problem: Climate is a dominant driver of fish population dynamics and while substantial work has been conducted on the impacts of climate, integrating this information into management has been limited. Meanwhile, annual catch limits must be set for many stocks that are thought to be impacted by climate, but without a mechanism for incorporating climate information. Therefore, an approach is needed to identify harvest-control rules that are resilient to climate-induced changes in productivity and that can be applied across a broad set of stocks.
Rationale: While climate impacts on fish stocks are increasingly apparent, existing management systems are predicated on stationary production relationships. As a result, management decisions are unable to keep pace with a changing environment, or they are made on an ad hoc basis. Recent research results indicate that harvest strategies can be designed that respond rapidly to measured changes in stock productivity. Measures of forecast accuracy suggest that climate-resilient harvest strategies can perform well even when the mechanism underpinning the change is not fully understood.
Brief summary of work: (A) We will test for changes in productivity by applying time-varying stock-recruitment models to 73 stocks in five geographic regions of the U.S. (B) For stocks without age-structured assessment models, we will fit time-varying parameter surplus production and two-stage (recruit and post-recruit) models. (C) For stocks that are identified to have time varying dynamics, we will test for linear drift and incorporate environmental covariates in the state-space estimation. (D) The model results will be used to calculate dynamic reference points for comparison to existing reference points, which may be based on MSY proxies or other approaches. (E) Finally, we will develop climate-informed harvest control rules that are compatible with harvest rules used by the regional fishery management councils.
