Examining Temporal Sample Scale and Model Choice with Spatial Capture-Recapture Models in the Common Leopard Panthera...

Area of Science:

• Wildlife Ecology
• Conservation Biology
• Population Dynamics

Background:

• Large carnivores face significant threats, including habitat loss and human-wildlife conflict.
• Accurate population density and trend estimation is crucial for effective conservation.
• The elusive nature and low densities of these animals hinder detection and monitoring.

Purpose of the Study:

• To investigate the impact of different sampling interval lengths on density estimates using spatial capture-recapture (SCR) models.
• To evaluate the effectiveness of Bayesian SCR methods and Bayes factors for ecological model selection.
• To estimate the population density of leopards (Panthera pardus) in Royal Manas National Park, Bhutan.

Main Methods:

• Application of Bayesian spatial capture-recapture (SCR) models to simulated and real camera-trapping data.
• Analysis of data from 22 leopards captured 82 times over a winter season.
• Development and application of Bayes factors for selecting ecological models integrating multiple factors.

Main Results:

• Sample interval length (daily, weekly, monthly, quarterly) did not significantly affect median abundance or density estimates but influenced precision.
• Precision gains were largest when moving from quarterly to shorter sampling intervals.
• Evidence of sex-specific movement distributions in leopards was found, impacting density estimation.

Conclusions:

• Daily sampling intervals are recommended for monitoring rare or elusive species when feasible, though monthly or quarterly intervals can also be informative.
• Bayesian SCR methods with Bayes factors effectively identify ecological drivers of population dynamics.
• The study estimated a leopard density of 10.0 leopards/100 km², providing valuable data for conservation management.