Hidden Markov models reveal temporal patterns and sex differences in killer whale behavior

Abstract

Behavioral data can be important for effective management of endangered marine predators, but can be challenging to obtain. We utilized suction cup-attached biologging tags equipped with stereo hydrophones, triaxial accelerometers, triaxial magnetometers, pressure and temperature sensors, to characterize the subsurface behavior of an endangered population of killer whales (Orcinus orca). Tags recorded depth, acoustic and movement behavior on fish-eating killer whales in the Salish Sea between 2010–2014. We tested the hypotheses that (a) distinct behavioral states can be characterized by integrating movement and acoustic variables, (b) subsurface foraging occurs in bouts, with distinct periods of searching and capture temporally separated from travel, and (c) the probabilities of transitioning between behavioral states differ by sex. Using Hidden Markov modeling of two acoustic and four movement variables, we identified five temporally distinct behavioral states. Persistence in the same state on a subsequent dive had the greatest likelihood, with the exception of deep prey pursuit, indicating that behavior was clustered in time. Additionally, females spent more time at the surface than males, and engaged in less foraging behavior. These results reveal significant complexity and sex differences in subsurface foraging behavior, and underscore the importance of incorporating behavior into the design of conservation strategies.