Estimating demographic rates to improve monitoring of highly mobile species

Abstract

Estimating demographic rates of wildlife species, such as survival and fecundity, is crucial for monitoring wildlife populations and informing management of these species. Monitoring highly mobile species is especially challenging, as their life histories and behaviors (e.g., migration) can affect inference on demographic rates and ultimately render monitoring less effective. Species’ movements can expose them to a variety of hazards and opportunities, creating spatial and temporal variation in demographic rates that must be accounted for in models. Furthermore, the movement behaviors of many highly mobile species can violate key assumptions of the standard statistical models used to estimate demographic rates, so that new monitoring frameworks and models need to be designed to minimize violations of model assumptions or relax those assumptions. In this dissertation, I used several case studies to demonstrate how novel models and monitoring frameworks can improve demographic rate estimation, ecological inference, and population monitoring capabilities for highly mobile species.