Running on empty: recharge dynamics from animal movement data.

Area of Science:

• Ecology
• Movement Ecology
• Physiological Ecology

Background:

• Vital rates like survival and recruitment are key in population and community ecology.
• Individual-level energetics are crucial for biomechanics and movement ecology, influencing food webs.
• Current telemetry models lack explicit links to physiological dynamics, hindering understanding of movement-vital rate relationships.

Purpose of the Study:

• To present a novel framework for modeling telemetry data that mechanistically links animal movement to aggregated physiological processes.
• To provide a flexible approach accommodating various movement and physiological specifications in heterogeneous environments.
• To enable direct inference about physiological gains and losses based on movement patterns.

Main Methods:

• Developed a statistical framework for telemetry data incorporating aggregated physiological processes.
• Formulated a continuous-time model to infer physiological gains and losses from movement data.
• Extended the framework to incorporate auxiliary data and demonstrated with case studies.

Main Results:

• The framework successfully infers physiological recharge dynamics in mountain lions and African buffalo.
• The model provides direct inference on physiological processes influencing movement decisions.
• Demonstrated the model's applicability in heterogeneous environments using real-world data.

Conclusions:

• The presented framework offers a mechanistic link between individual movement and physiological dynamics.
• This approach enhances our understanding of how energetics shape animal behavior and population ecology.
• The model is adaptable and can be extended for broader applications in ecological research.