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

Area of Science:

• Marine Biology
• Behavioral Ecology
• Conservation Science

Background:

• Effective management of endangered species requires detailed behavioral data.
• Obtaining such data for marine predators like killer whales presents significant challenges.

Purpose of the Study:

• To characterize the subsurface behavior of endangered fish-eating killer whales (Orcinus orca).
• To identify distinct behavioral states using movement and acoustic data.
• To investigate sex-specific differences in foraging and diving patterns.

Main Methods:

• Utilized suction cup-attached biologging tags with stereo hydrophones, accelerometers, magnetometers, and pressure/temperature sensors.
• Collected data on depth, acoustics, and movement from killer whales in the Salish Sea (2010-2014).
• Employed Hidden Markov modeling to analyze acoustic and movement variables and define behavioral states.

Main Results:

• Identified five distinct, temporally clustered behavioral states, including deep prey pursuit.
• Found that killer whales tend to persist in the same behavioral state during dives.
• Observed significant sex differences: females spent more time at the surface and foraged less than males.

Conclusions:

• Subsurface foraging behavior in killer whales is complex and exhibits sex-specific patterns.
• Behavioral state transitions and dive patterns vary between males and females.
• Integrating detailed behavioral data is crucial for developing effective conservation strategies for endangered marine predators.