Non-parametric modeling reveals environmental effects on bluefin tuna recruitment in Atlantic, Pacific, and Southern Oceans

Abstract

Environment–recruitment relationships can be difficult to delineate with parametric statistical models and can be prone to misidentification. We use non-parametric time-series modeling which makes no assumptions about functional relationships between variables, to reveal environmental influences on early life stages of bluefin tuna and demonstrate improvement in prediction of subsequent recruitment. The influence of sea surface temperature, which has been previously associated with larval growth and survival, was consistently detected in recruitment time series of bluefin tuna stocks that spawn in the Mediterranean Sea, the North Pacific, and the Southern Ocean. Short time series for the Gulf of Mexico stock may have precluded a clear determination of environmental influences on recruitment fluctuations. Because the non-parametric approach does not require specification of equations to represent system dynamics, predictive models can likely be developed that appropriately reflect the complexity of the ecological system under investigation. This flexibility can potentially overcome methodological challenges of specifying structural relationships between environmental conditions and fish recruitment. Consequently, there is potential for non-parametric time series modeling to supplement traditional stock recruitment models for fisheries management.