Calibrating animal-borne proximity loggers

Area of Science:

• Animal Behavior
• Ecology
• Bio-logging Technology

Background:

• Growing interest in animal social networks necessitates reliable automated tracking.
• Animal-attached proximity loggers record spatial associations via radio communication.
• Field calibration of proximity loggers is challenging due to heterogeneous environments.

Purpose of the Study:

• To calibrate the 'Encounternet' digital proximity-logging system for wild New Caledonian crows (Corvus moneduloides).
• To develop a quantitative model for estimating crow-to-crow distances from logger signal strength.
• To enable robust post hoc analysis of social dynamics using proximity data.

Main Methods:

• Combined theoretical analyses, field experiments, statistical modeling, behavioral observations, and computer simulations.
• Focused on radio communication between crow-borne loggers.
• Developed a multi-step calibration exercise for accurate distance estimation.

Main Results:

• Signal strength data reliably assigned crow encounters to predefined distance classes.
• Enabled filtering of raw data to focus on close-range encounters (within meters).
• Demonstrated the system's potential for analyzing social learning through direct observation.

Conclusions:

• Well-calibrated proximity loggers can map social associations of free-ranging animals across meaningful distances.
• Study-specific calibrations are crucial to account for environmental and technological complexities.
• The calibration methodology is applicable to diverse tracking systems and study species.