Mapping the ghost: Estimating probabilistic snow leopard distribution across Mongolia

Abstract

Aim Snow leopards are distributed across the mountains of 12 countries spread across 1.8 million km2 in Central and South Asia. Previous efforts to map snow leopard distributions have relied on expert opinions and modelling of presence‐only data. Expert opinion is subjective and its reliability is difficult to assess, while analyses of presence‐only data have tended to ignore the imperfect detectability of this elusive species. The study was conducted to prepare the first ever probabilistic distribution map of snow leopards across Mongolia addressing the challenge of imperfect detection. Location We conducted sign‐based occupancy surveys across 1,017 grid‐cells covering 406,800 km2 of Mongolia's potential snow leopard range. Methods Using a candidate model set of 31 ecologically meaningful models that used six site and seven sampling covariates, we estimate the probability of sites being used by snow leopards across the entire country. Results Occupancy probability increased with greater terrain ruggedness, with lower values of vegetation indices, with less forest cover, and were highest at intermediate altitudes. Detection probability was higher for segments walked on foot, and for those in more rugged terrain. Our results showed broad agreement with maps developed using expert opinion and presence‐only data but also highlighted important differences, for example in northern areas of Mongolia deemed largely unfavourable by previous expert opinion and presence‐only analyses. Main conclusions This study reports the first national‐level occupancy survey of snow leopards in Mongolia and highlights methodological opportunities that can be taken to scale and support national‐level conservation planning. Our assessments indicated that <12% of its entire land mass, and 42% of the potential snow leopard habitat in Mongolia has a high (>0.5) probability of being used by snow leopards. We emphasize the utility of occupancy modelling, which jointly models detection and site use, in achieving these goals.

Seasonal space use and habitat selection of GPS collared snow leopards (Panthera uncia) in the Mongolian Altai range

“…Mongolia is estimated to support the second largest numbers of snow leopards in central Asia, where approximately 1000 individuals reside [ 32 ]. More specifically, the Altai Mountains of western Mongolia are the largest continuous area of snow leopard habitat in Mongolia and believed to hold the country’s largest population [ 32 , 33 ]. These mountains contain one of the largest and most important remaining landscapes globally for snow leopard conservation [ 5 ].…”

Spatial density estimate of the snow leopard,Panthera uncia, in the Central Tibetan Plateau, China

“…In 2021, Mongolia became the first one who has completed nation‐wide snow leopard abundance surveys using methods compliant to the PAWS guidelines (Bayandonoi et al. 2021). Before that, Bhutan and Russia finished their national programs for monitoring snow leopard populations (Lham et al.…”

Conservation of rare and cryptic species: Challenges of uncertainty and opportunities for progress

“…An exemplar of the value of collaboration is the collective effort to better understand the status of the snow leopard ( Panthera uncia ), which has a small global population (<9000 individuals; McCarthy et al, 2016) spread across 12 countries (Rosen & Zahler, 2016). Some aspects of snow leopard ecology remain largely unknown (Riordan et al, 2016), yet recent research has rapidly improved knowledge due to collaborations that often spanned political or geographic boundaries (Atzeni et al, 2021; Bayandonoi et al, 2021; Rovero et al, 2020; Yang et al, 2021). Collaborative studies present opportunities to establish connections between diverse stakeholders, which can include government agencies, academic institutions, indigenous groups, non‐profit organizations, and industry (Lamb et al, 2022; Miththapala et al, 2022).…”