Changepoint analysis: A new approach for revealing animal movements and behaviors from satellite telemetry data

Abstract

While telemetry is an invaluable tool for tracking animal movement patterns, the data generated by this technique is often challenging to interpret. Here, we addressed this issue by developing a novel method, based on changepoint analysis, which incorporated both the horizontal and vertical movement metrics and compared this output to that from a switching state-space model (SSSM) that categorized behavior based on horizontal movement metrics. We deployed 20 satellite transmitters on postnesting loggerhead turtles at Rethymno, Crete, Greece between 2010 and 2011 to monitor their at-sea behavior. We used both models to identify behavioral changes, such as the switches from migration to foraging, and from foraging to overwintering. The satellite-tracked turtles exhibited three discrete migratory strategies, with 9 turtles migrating southwards to the coast of northern Africa, 6 turtles migrating northwards into the Aegean Sea, and 4 turtles remaining resident in the waters of Crete. The SSSM readily identified the switch from transiting to ARS behavior in most animals, but the CPA model was able to distinguish multiple modes and more subtle shifts in behavior corresponding with shifts from migration to foraging to overwintering behaviors. We have shown that by incorporating vertical movement metrics into the analysis of telemetry data, previously hidden shifts in behavior can be revealed. The resulting increase in ability to discern complex behavioral patterns of animals remotely will likely yield better management and conservation decisions for a wide array of organisms.