Our field team from Spiti Valley in Himachal Pradesh assisted a team of local researchers in conducting this population survey as part of the PAWS (Population Assessment of the World’s Snow Leopards) initiative. This study brings us closer to the ultimate goal of a reliable global population estimate of snow leopards. These results provide a baseline for evaluating the effectiveness of future conservation efforts and inspire hope for the future of snow leopard conservation.
Similar to previous population studies conducted by our teams, including one in the nearby state of Himachal Pradesh, camera traps were the primary tool used to estimate the population size of snow leopards in KHANP.
Surveying here is no easy feat – with rugged cliffs and long, narrow valleys that must be traversed on foot. Getting to snow leopard landscapes is a 2-3 day trek, and since the study was conducted in spring, most of the land was still covered in snow and at risk of avalanches. In addition, decades of political instability in the region meant that researchers needed permits to enter most areas. We are deeply grateful to the incredible teams for their determination to achieve this goal.
Across the three valleys surveyed (Kibber, Nanth & Kiyar), at least four individual snow leopards were identified from 175 photos across nine camera locations over 45 days. This corresponds to an estimated density of 0.5 snow leopards per 100 km2 (95% confidence intervals of 0.13-1.86 snow leopards per 100 km2) and a small estimated population of four individuals (statistical confidence limits ranging from 4-9).
The survey also recorded 15 other species of mammals during the study (see table below), including the Asiatic ibex and the Himalayan brown bear. Ibex, the main prey of snow leopards, had a low relative abundance. However, camera trap surveys are known to underestimate ungulate populations, so a more robust estimation is necessary. Further investigation should focus on the spatial overlap between snow leopards and brown bears, the largest mammal in the region, to better understand how the species interact given their partially overlapping diets.
Other interesting observations included the sizeable population of long-tailed marmots, which may constitute a seasonal prey species for snow leopards, and the rare and endangered Kashmir musk deer. “This survey sets the baseline for this important region, which has a hostile past and faces an uncertain future for snow leopards. Kishtwar National Park is a beautiful landscape. We hope this is just the start of our explorations here.” – Dr. Munib Khanyari
This region (Greater Himalayas of Kishtwar) has had considerably fewer conservation resources and attention focused on it compared to other parts of the snow leopard range in India because of its location at the nexus of various international borders and a prolonged military presence resulting from decades of geopolitical conflicts. The area is home to multiple glaciers melting at an alarming rate. Additionally, this region is undergoing rapid infrastructure development that could result in significant habitat loss. All of these factors contribute to biodiversity loss, placing increased importance on renewing research in the region. Our first robust population estimate for snow leopards in the KHANP (as well as our first photographic evidence of the species here, see below) is a catalyst for prioritizing research in the area.
This population assessment in Kishwar High Altitude National Park marks a significant milestone in snow leopard conservation efforts. The study provides valuable baseline data for future conservation initiatives and sheds light on the biodiversity of this understudied region.
Read the full paper here.
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Acknowledgments:
This work would not have been possible without the support of local researchers and residents, officials from the Wildlife Protection Department and the staff from the National Park. This work was generously funded by the Panthera Sabin Grant and the National Geographic Meridian Grant to researchers at Nature Conservation Foundation.