Abstract: Knowledge of the abundance and density of large carnivores, such as the globally vulnerable snow leopard
(Panthera uncia), is crucial for their conservation and for evaluating management measures. The snow leopard
inhabits remote and harsh terrain in high-altitude regions of South and Central Asia across 12 countries. It is one of the least studied large mammals in Pakistan, and reliable data on its populations are scarce across its range. The current study adopted a new noninvasive genetics approach—a snow leopard-specific SNP (single-nucleotide polymorphism) panel designed for individual identification. Over one thousand putative snow leopard scats were collected along transects across the species' distribution range in Pakistan from 2017 to 2023, of which 235 were genetically identified as belonging to snow leopards. A total of 179 snow leopard samples were successfully genotyped, yielding 56 unique individuals, comprising 63% males. Model averaging over top Spatially Explicit Capture-Recapture (SECR) model predicted an average density of 0.17 snow leopards per 100 km2 potential habitat (95% CL 0.130–0.225) across the species' range in Pakistan, with an estimated population of 167.9 (95% CI 129.0–220.6). Current study findings suggest that the new SNP panel, in combination with SECR, provides an effective means of monitoring snow leopard populations. The results validate camera trap-derived population estimates and establish a reliable baseline for monitoring the snow leopard population in Pakistan. Additionally, we recommend enhancing the surveillance of protected areas, which are home to most of the snow leopard populations, to decrease poaching and facilitate the growth of both snow leopards and their prey.