Capturing foraging and resting behavior using nested multivariate Markov models in an air-breathing marine vertebrate

Area of Science:

• Marine Biology
• Animal Movement Ecology
• Bio-logging

Background:

• Accurately linking animal movement patterns to life history behaviors requires integrating diverse data streams.
• Animal-borne dataloggers provide high-frequency 3D movement data, enabling more complex behavioral models.
• Nested movement models offer a flexible framework to integrate data with varying spatial and temporal resolutions.

Purpose of the Study:

• To develop and apply a nested movement model to infer Humpback whale behaviors.
• To combine 2D geographic and 3D vertical movement data for refined behavioral state analysis.
• To investigate the relationship between whale movement, foraging, and environmental factors.

Main Methods:

• Utilized a two-layer nested model to integrate geographic and vertical movement data.
• Applied the model to Humpback whale tracking data from the West Antarctic Peninsula.
• Differentiated between traveling, foraging, and resting behavioral states.

Main Results:

• The nested model refined behavioral state delineation compared to geographic data alone.
• Observed increased foraging intensity in late-season whales preparing for migration.
• Identified strong diel variations in movement states, correlated with prey availability.

Conclusions:

• Combined 2D and 3D movement data successfully linked whale movement to krill availability.
• Demonstrated the complex spatial patterns of Humpback whale foraging in productive polar waters.
• Highlighted the utility of nested models for understanding animal behavior and ecology.