Spatial capture-recapture for investigating an elusive species’ ecology
Understanding the population size of a species is critical for effective conservation policy. In the case of the snow leopard (Panthera uncia), it is the difference between it being classified as a vulnerable versus an endangered species in the IUCN Red list. Spatial capture-recapture (SCR) is a robust statistical framework for estimating population size, and extensions of the model have enabled inference on ecological parameters beyond density.
This talk will serve as a gentle introduction to SCR models, explaining their structure and illustrating how they are robust when density is the primary parameter of interest. After many attempts at breaking the model, I identify one instance where it can fail, and propose a way to resolve it.
Surveying snow leopards in their rugged habitat presents significant challenges, making it difficult to implement multiple surveys. I will illustrate how extensions of SCR models can be leveraged to infer ecological parameters beyond density, focusing on applications with direct management implications. Finally, I will discuss recent advances in integrating movement into SCR models, research I aim to build on during my postdoc at ESPM.