Estimating spatially variable and density-dependent survival using open-population spatial capture-recapture models

Area of Science:

• Ecology
• Population Biology
• Spatial Statistics

Background:

• Open-population spatial capture-recapture (OPSCR) models are valuable for estimating population density and demographic parameters using spatial detection data.
• While OPSCR models can estimate spatial variation in vital rates, their application and testing for such complex scenarios remain limited.

Purpose of the Study:

• To develop and test a Bayesian OPSCR model that integrates spatial covariates to analyze spatial variation in survival.
• To investigate density-dependent effects on survival within a unified spatial framework.
• To assess the impact of ignoring spatial heterogeneity in survival on abundance estimates.

Main Methods:

• Developed a Bayesian open-population spatial capture-recapture (OPSCR) model incorporating spatial covariates to analyze survival.
• Utilized simulations to evaluate the model's performance in estimating the effects of spatial covariates on survival and density-dependent survival.
• Applied the model to empirical data on female wolverines (Gulo gulo) in Sweden and Norway to estimate cause-specific mortality.

Main Results:

• The developed OPSCR model accurately infers the effects of spatial covariates on survival, even with multiple mortality sources.
• Estimating local density-dependent survival was feasible but demanded more extensive data due to model complexity.
• Failure to account for spatial heterogeneity in survival resulted in a positive bias of up to 10% in abundance estimates.

Conclusions:

• The Bayesian OPSCR model provides a robust framework for analyzing spatial variation in survival and its drivers.
• Incorporating spatial covariates into OPSCR models is essential for accurate population estimates and understanding survival dynamics.
• This research is a significant step towards fully spatially explicit OPSCR models for disentangling complex spatial influences on population dynamics.