State space and movement specification in open population spatial capture-recapture models.

Area of Science:

• Ecology and Conservation Biology
• Wildlife Population Dynamics
• Statistical Modeling in Ecology

Background:

• Global environmental changes necessitate robust methods for monitoring threatened species.
• Capture-recapture techniques, particularly spatial capture-recapture (SCR) models, are effective for estimating population size and dynamics.
• Open SCR models offer flexibility but require careful definition and parameterization.

Purpose of the Study:

• To investigate the impact of state-space definition and between-primary-period movement models on demographic parameter estimation in open SCR models.
• To assess these effects using simulation studies and a real-world tiger camera-trap dataset.

Main Methods:

• Development of simulation studies to test various state-space definitions and movement models.
• Application of open SCR models to a 10-year camera-trap dataset of tigers in India.
• Analysis of how movement and state-space choices influence survival and density estimates.

Main Results:

• Simulation results indicate that unmodeled between-primary-period animal movements can bias survival estimates in open SCR models.
• The definition of the state-space boundary can also lead to biased survival estimates under specific conditions.
• Analysis of the tiger data confirmed that both state-space definition and movement models significantly affected survival estimates (0.71–0.89).

Conclusions:

• Open SCR models provide a flexible framework for long-term population monitoring.
• Accurate modeling of between-primary-period movements is essential for obtaining unbiased survival and density estimates.
• Careful consideration of state-space definition is also critical for reliable demographic parameter estimation in open SCR models.