Modeling spatiotemporal variations in the density of unmarked populations using camera trap data: An application to free-roaming cats

Abstract

Camera traps have revolutionized wildlife monitoring, providing reliable information on animal occupancy and abundance. In recent years, several models have been developed to estimate the absolute density of unmarked populations (i.e., those lacking individually recognizable markings), which was previously challenging. By refining these models, they may become efficient monitoring tools applicable to a wide range of species. In this study, we extended one such model, the Random Encounter and Staying Time (REST) model, within a state-space framework to explicitly account for spatiotemporal variations in animal density. We applied this model to free-roaming cats using data obtained from 209 camera traps deployed across a study area (836 km²) over a two-year period (June 2018–May 2020). The estimated cat density was generally <0.3 cats per km², with higher densities observed near human settlements and occasional excursions into deeper forested areas (>500 m). Densities also exhibited seasonal variation, with higher values in winter and spring compared to summer. Our model estimates the “average” density of animal individuals available to camera traps over the temporal duration of interest. Although this metric differs from conventional population density measures and requires careful interpretation, it remains a valuable indicator of the ecological impact or functioning of animals, including free-roaming cats.