Common thresher shark Alopias vulpinus movement: Bayesian inference on a data-limited species

Within the fields of biology and ecology, animal movement is arguably one of the most basic, and yet, often one of the most difficult areas of study. Where and why animals migrate, and what patterns can be derived from individual movements in order to make population-level inferences are key areas when attempting to define basic population dynamics. These questions are of equal interest to biologists and managers, with many species assessments identifying improvements in the understanding of population-level movement as a key research need. We aimed to improve our understanding of population level movement for common thresher sharks Alopias vulpinus by leveraging the largest satellite tagging dataset available for this species. Using a Bayesian approach specifically designed to address population-level questions with sparse telemetry data, we identified that A. vulpinus off the west coast of North America are partial migrators which conditionally migrate, based on a combination of fixed intrinsic states (size, sex) and variable extrinsic states (e.g. season, environment). Waters of the Southern California Bight were identified as an area where, seasonally, a large variety of sizes of A. vulpinus can be found. While smaller juveniles can be found throughout the year, larger sub-adults and adults often move out of the Bight during certain seasons (spring and winter). Knowledge of how A. vulpinus distribute along the coast, and that season, size, and to some extent sex, play important roles in where and what type of animals are likely to be found, are key pieces of information when attempting to accurately characterize basic biological parameters like age, growth, and reproduction, as well as understanding the effects of variable fishing pressures across the species’ range.