Climate-readiness of fishery management procedures with application to the southeast US Atlantic

Global climate change threatens the assumption of stationarity inherent in many fisheries management decisions. This heightens the importance of developing management strategies that are robust to future uncertainty. Management strategy evaluation (MSE) is a framework in which management procedures (MPs) can be developed and tested using closed-loop simulation. We explored the performance of various model-based and empirical MPs with nonstationary future projections for three commercially and recreationally important fish stocks in the southeast US Atlantic. Using openMSE, we tested candidate MP performance across projections designed to emulate plausible future conditions, including regime shifts, nonstationarity, and observation error shifts in the survey index. Candidate MP performance was primarily measured based on its ability to maintain a healthy stock biomass. Results of this MSE demonstrate that several empirical MPs may be better able to adapt to regime shifts and nonstationary dynamics compared to traditional model-based MPs that employ full age-structured stock assessments, though empirical MPs struggle to maintain stock biomass when facing artificial index observation error shifts. Relative performance of model-based versus empirical MPs varied by stock and climate-change scenario. These findings highlight the value that adaptive MPs may hold for climate-ready fisheries management.