Population size is one of the most important pieces of information for monitoring conservation efforts and setting sustainable harvest limits, but it is often difficult and labor intensive to estimate. Close kin mark-recapture (CKMR) is a promising new method for estimating population size from genetic data that identifies related pairs of individuals in a sample and estimates population size from these pairs. Unlike widely used capture-recapture methods, CKMR does not rely on recapturing the same individual multiple times. This means that CKMR can be used when recaptures are difficult or impossible, such as studies involving lethal sampling, sampling at a single time point, or highly elusive species. However, a major shortcoming of current CKMR methods is that they do not model the complex spatial and social dynamics that are important in many species of conservation concern.

I develop a novel spatially explicit CKMR method that models limited dispersal, spatial bias in sampling, complex social structure, and uncertainty in kin estimation. I test the method on simulations and demonstrate that it is accurate and robust to misspecified population trend. I then apply the method to elephants in Kibale National Park in Uganda and explore the feasibility of using CKMR methods to improve monitoring.