Predicting Population Recruitment Under Selective Fishing Pressure

Many fish stocks have been found to display nonlinear behavior in life-history related and population dynamics related traits including spawning biomass, recruitment and abundances at age. Empirical Dynamic Modeling (EDM) framework provides a tool to make use of the nonlinear behavior of those traits and do forecast under various scenarios of future climate and management options. Compared to other methods, the EDM framework does not assume linearity in the model structure and does not restrict any functional form in the stock recruitment relationship. In this study, we extend the current application of EDM to incorporate specific dynamics of the population structure and present it as a framework to investigate the impacts of stock structure on recruitment. We further explore different selective fishing strategies and predict the corresponding change in recruitment based on nonlinear forecasting using several exploited species from North America.