Predicting Temporal and Spatial Shifts in Bluefin Tuna (Thunnus thynnus) Diets in the Atlantic Ocean Using a Bagged Classification Tree Approach

Atlantic bluefin tuna (Thunnus thynnus) is a pelagic predator, which is seasonally distributed throughout the Gulf of Mexico, North Atlantic Ocean, and Mediterranean Sea. Bluefin tuna diet and trophic ecology have been characterized for individual feeding areas throughout its range, but a comprehensive foraging analysis is lacking for this highly migratory species. Here, we used a modified (bagged) classification and regression tree modeling approach to evaluate the influence of a suite of environmental and biological variables on broad-scale spatial and temporal shifts in bluefin tuna foraging habits. Diet data from over 3,700 non-empty bluefin tuna stomachs were compiled from individual datasets spanning the Atlantic coast of the U.S., Gulf of Mexico, central North Atlantic Ocean, Iceland, Bay of Biscay, and the Mediterranean Sea over a 55-year time-period (1957 - 2012). In addition, quantile and least squares regression techniques were used to evaluate trends in regional predator-prey body size relationships among 2,700 individual prey items. Results from this study will improve ecosystem-based management of bluefin tuna by providing a comprehensive evaluation of food web and climatic factors influencing the migration and foraging patterns of this economically and ecologically valuable predator.