Abstract: Conservation and management of snow leopards (Uncia uncial) has largely relied on anecdotal evidence and presence-absence data due to their cryptic nature and the difficult terrain they inhabit. These methods generally lack the scientific rigor necessary to accurately estimate population size and monitor trends. We evaluated the use of photography in capture-mark-recapture (CMR) techniques for estimating snow leopard population abundance and density within Hemis National Park, Ladakh, India. We placed infrared camera traps along actively used travel paths, scent-sprayed rocks, and scrape sites within 16-30 kmý sampling grids in successive winters during January and March 2003-2004. We used head-on, oblique, and side-view camera configurations to obtain snow leopard photographs at varying body orientations. We calculated snow leopard abundance estimates using the program CAPTURE. We obtained a total of 66 and 49 snow leopard captures resulting in 8.91 and 5.63 individuals per 100 trap nights during 2003 and 2004, respectively. We identified snow leopards based on the distinct pelage patters located primarily on the forelimbs, flanks, and dorsal surface of the tail. Capture probabilities ranged from 0.33 to 0.67. Density estimates ranged from 8.49 (SE+0.22) individuals per 100 kmý in 2003 to 4.45 (SE+0.16) in 2004. We believe the density disparity between years is attributable to different trap density and placement rather than to an actual decline in population size. Our results suggest that photographic capture-mark-recapture sampling may be a useful tool for monitoring demographic patterns. However, we believe a larger sample size would be necessary for generating a statistically robust estimate of population density and abundance based on CMR models.

Abstract: Surveying snow leopard prey species such as argali, ibex or blue sheep through traditional ground-based observations is time-consuming, expensive, and challenging. Aerial drones present a promising alternative. We tested using thermal-sensor- equipped drones to count ungulate populations in Mongolia’s Ikh Nart Nature Reserve, surveying ~400km of transects along five fixed routes for forty-three missions. Drones detected 235 prey animals and 209 livestock; 26% of all sightings were in areas that would not have been visible to hypothetical ground-based observers. Our tests reinforced the utility of drones for counting snow leopard prey and highlighted important issues and future advances for supporting largely autonomous prey surveys. We recommend biologists build upon existing technology to attain an inexpensive, easy to use, and field ready set of equipment and procedures that can reliably improve or replace traditional transect or point count methods for large prey species.

Abstract: A snow leopard project is underway to study snow leopards in Mongolia. The project, called the Mongolian-American Snow Leopard Project, involves the Wildlife Conservation Society, the Mongolian Association for the Conservation of Nature and Environment, the National Geographic Society, the Mongolian Ministry of Nature and the Environment, the U.S. National Biological Service, and the International Snow Leopard Trust. The objective of the study is to survey the distribution and status of Mongolia's snow leopards, including those living in the Gobi Desert. klf.