Estimating the density of small population of leopard Panthera pardus using multi-session photographic-sampling data

West Asian drylands host a number of threatened large carnivores, including the leopard (Panthera pardus) which is limited to spatially scattered landscapes with generally low primary productivity. While conservation efforts have focused on these areas for several decades, reliable population density estimates are missing. Spatially-explicit capture-recapture (SECR) methodology, incorporating animal movement in density estimates, is widely used to monitor populations of large carnivores. We employed multi-session SECR modeling to estimate the density of a small population of leopard (Panthera pardus) in a mountainous stretch surrounded by deserts in central Iran. During 6724 camera trap nights, we detected eight and five independent leopards in 2012 and 2016 sessions, respectively. The top performing model demonstrated density estimates of 1.6 (95% CI = 0.9-2.9) and 1.0 (95% CI = 0.6-1.6) independent leopards/100 km2 in 2012 and 2016, respectively. Both sex and season had substantial effects on spatial scale ({sigma}), with larger movements for males and during winter. Currently available estimates in arid regions represent some of the lowest densities across the leopard global range. These small populations are vulnerable to demographic stochasticity. Monitoring temporal changes in population density and composition can inform conservation priorities.