Estimating snow leopard and prey populations at large spatial scales.

Published online
25 Jan 2022
Content type
Journal article
Journal title
Ecological Solutions and Evidence

Kulbhushansingh Suryawanshi & Abinand Reddy & Manvi Sharma & Munib Khanyari & Ajay Bijoor & Devika Rathore & Harman Jaggi & Abhirup Khara & Aditya Malgaonkar & Abhishek Ghoshal & Jenis Patel & Charudutt Mishra
Contact email(s)

Publication language
India & Himachal Pradesh


Effective management of charismatic large carnivores requires robust monitoring of their population at local, regional and global scales. While enormous progress has been made to estimate carnivore populations at local scales, estimates at regional and global scales remain elusive. In the first systematic effort at a large regional scale, we estimated the population of the elusive snow leopard Panthera uncia over an area of 26,112 km2 in the Indian state of Himachal Pradesh. 2. We stratified the entire snow leopard habitat in Himachal Pradesh based on an occupancy survey. Subsequently,we conducted camera trapping surveys at 10 sites distributed proportionately, that is with similar coverage probability across the three strata. We conducted simulations to understand how unidentified captures could affect our model estimate.We also assessed populations of the primary wild ungulate prey of snowleopards - blue sheep Pseudois nayaur and Siberian ibex Capra sibirica. 3. Our results yielded amean estimated density of 0.19 (95% confidence interval [CI]: 0.12-0.31) snow leopards per 100 km2 and population size of 51 (95% CI: 34- 73) snow leopards in Himachal Pradesh. The density estimates for individual sites ranged from 0.08 to 0.37 snow leopards per 100 km2. Simulations showed that unidentified snow leopard captures did not seem to affect the accuracy of our model estimate but could have affected the precision. Wild ungulate prey density ranged from 0.11 to 1.09 per km2. Snow leopard density showed a positive linear relationship with prey density (slope = 0.25, SE = 0.08, P = 0.01, R2 = 0.51). 4. Our study shows the earlier opinion-based estimate for Himachal Pradesh to have been significantly positively biased. Using occupancy surveys to stratify large areas in order to design camera trap surveys addresses one of the common spatial sampling biases, that is limited sampling of only prime snow leopard habitats. Our work validates two-step approach recommended in the ongoing initiative of the 12 snow leopard range countries for Population Assessment of World's Snow leopards (PAWS program), and cautions against the use of opinionbased estimates for assessing the status of species of critical conservation importance.

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