The role of oceanographic scales in shaping highly mobile marine predator distributions.

Marine animals live in a dynamic environment, where a wide range of drivers and processes impact their movements and distributions. These processes occur over multiple spatio-temporal scales, from fine scale phytoplankton blooms and zooplankton patches to larger scale climatic events such as El Niño or climate change. In a dynamic ocean, the predictability of ocean features and processes vary across multiple scales. Marine animals interact with all these processes, and they all have the potential to impact animal distribution. However, which processes and scales predominantly predict the distributions of highly mobile predators is currently unknown. Here, we use electronic tagging data (265 sharks tagged in the Pacific) to investigate the scales of environmental selection of three pelagic shark species (the salmon shark Lamna ditropis, the blue shark Prionace glauca, and the shortfin mako Isurus oxyrinchus) across an array of spatio-temporal resolutions (from 9 km - 1 day to 500 km - climatology) for both Eulerian and Lagrangian variables. While Eulerian and Lagrangian variables at all scales tested have predictive power, we find that the 100 km - 1 year scale best predicted predator locations, indicating that larger scale, annually averaged signals outperform the other scales in predicting predator location.