The population densities of leopards vary widely across their global range, influenced by prey availability, intraguild competition and human persecution. In Asia, particularly the Middle East and the Caucasus, they generally occur at the lower extreme of densities recorded for the species. Reliable estimates of population density are important for understanding their ecology and planning their conservation. We used a photographic spatial capture-recapture (SCR) methodology incorporating animal movement to estimate density for the endangered Persian leopard Panthera pardus saxicolor in three montane national parks, northeastern Iran. We combined encounter history data arising from images of bilaterally asymmetrical left- and right-sided pelage patterns using a Bayesian spatial partial identity model accommodating multiple “non-invasive” marks. We also investigated the effect of camera trap placement on detection probability. Surprisingly, considering the subspecies’ reported low abundance and density based on previous studies, we found relatively high population densities in the three national parks, varying between 3.10 ± SD 1.84 and 8.86 ± SD 3.60 individuals/100 km2. The number of leopards detected in Tandoureh National Park (30 individuals) was larger than estimated during comparable surveys at any other site in Iran, or indeed globally. Capture and recapture probabilities were higher for camera traps placed near water resources compared with those placed on trails. Our results show the benefits of protecting even relatively small mountainous areas, which accommodated a high density of leopards and provided refugia in a landscape with substantial human activity.

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Land-use change has led to substantial range contractions for many species. Such contractions are particularly acute for wide-ranging large carnivores in Asia’s high altitude areas, which are marked by high spatiotemporal variability in resources. Current conservation planning for human-dominated landscapes often takes one of two main approaches: a “coexistence” (land sharing) approach or a “separation” (land sparing) approach. In this study, we evaluated the effects of land-use management on a guild of large carnivores in a montane ecosystem located in northeastern Iran. We used interview surveys to collect data on Persian leopard Panthera pardus saxicolor and grey wolf Canis lupus and modeled the areas occupied by these species in a Bayesian framework. After accounting for imperfect detection, we found that wolves had a higher probability of occupying the study area than leopards (82%; 95% CI 73–90% vs. 63%; 95% CI 53–73%). Importantly, each predator showed contrasting response to land-use management. National Parks (i.e. human-free areas) had a positive association with leopard occupancy (αNational Park = 2.56, 95% CI 0.22–5.77), in contrast to wolves, which displayed a negative association with National Parks (αNational Park = − 1.62, 95% CI − 2.29 to 0.31). An opposite pattern was observed for human-dominated areas (i.e. Protected Areas and Communal Lands), where occupancy was higher for wolves but lower for leopards. Our study suggests that to protect these large carnivores, a combination of land sharing and land sparing approaches is desirable within Iran montane landscapes. Any recovery program for big cats in Iranian mountains, and likely similar mountainous landscapes in west Asia, should take into account other sympatric carnivores and how they can affect adjacent human communities. For example, conflict mitigation and compensation efforts are required to include the guild of large carnivores, instead of solely targeting the charismatic big cats.

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West Asian drylands host a number of threatened large carnivores, including the leopard (Panthera pardus) which is limited generally to areas with low primary productivity. While conservation efforts have focused on these areas for several decades, reliable population density estimates are missing for many of them. Spatially explicit capture–recapture (SECR) methodology is a widely accepted population density estimation tool to monitor populations of large carnivores and it incorporates animal movement in the statistical estimation process. We employed multi-session maximum-likelihood SECR modeling to estimate the density of a small population of leopard in a mountainous environment surrounded by deserts in central Iran. During 6724 camera trap nights, we detected 8 and 5 independent leopards in 2012 and 2016 sessions, respectively. The top-performing model produced 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 (σ), with larger movements recorded for males, and during winter. The estimates from our density estimation exercise represent some of the lowest densities across the leopard global range and strengthen the notion that arid habitats support low densities of the species. These small populations are vulnerable to demographic stochasticity, and monitoring temporal changes in their population density and composition is a critical tool in assisting conservation managers to better understand their population performance.