Modeling abundance, distribution, movement and space use with camera and telemetry data.

Area of Science:

• Ecology
• Wildlife Biology
• Statistical Modeling

Background:

• Animal abundance and movement studies are often independent, despite their interconnectedness.
• Movement influences animal density and detection probability, impacting abundance estimations.
• Technological advances in camera traps and GPS telemetry offer new research opportunities.

Purpose of the Study:

• To develop and apply a hierarchical model integrating spatial capture-recapture (SCR) and GPS telemetry data.
• To simultaneously estimate animal abundance, distribution, and movement patterns.
• To address limitations of independent analyses and standard SCR models.

Main Methods:

• Developed a joint hierarchical model conditioning on animal movement.
• Utilized data from 60 camera traps and 23,572 GPS telemetry locations for 17 white-tailed deer.
• Modeled movement paths using an Ornstein-Uhlenbeck process with individual-specific random effects.

Main Results:

• Estimated white-tailed deer abundance at 126 (95% CI: 88-177) in a 228 km² area.
• The joint model captured individual heterogeneity in movement and space use, which standard SCR models could not.
• Abundance estimates were similar to standard SCR, but the joint model provided richer movement insights.

Conclusions:

• Joint modeling of movement and abundance data provides a more holistic understanding of animal ecology.
• This integrated approach leverages modern technologies for improved demographic and behavioral inference.
• The model offers potential for extensions to study resource selection, survival, and recruitment.