The conservation world is often a race against time, especially for threatened species like the snow leopard, often called the ghost of the mountains because of its elusive nature. These big cats live in some of the most remote and challenging places on Earth, high up in the snowy peaks of Asia. Although an endangered species, getting an accurate idea of how many there are and where they live has been incredibly difficult due to our inability to track them across vast, rugged, blizzard covered mountains. This lack of solid information makes it tough to figure out the best ways to protect them.
Now, a new study in Trans-Himalaya region of Ladakh, by researchers from Wildlife Institute of India, Aarhus University, Denmark, National Tiger Conservation Authority, Conservation Research, Cambridge, United Kingdom, Indian National Science Academy, and National Centre for Biological Sciences (NCBS) has used modern tools and old-fashioned fieldwork to provide the most comprehensive look yet at one of the world's largest snow leopard populations.
Did you know? Snow leopards are solitary animals, only coming together during mating season or when raising cubs. Their fur blends seamlessly with the rocky, snowy terrain, making them nearly invisible. |
Researchers embarked on the largest and most intensive snow leopard survey ever conducted in India, covering 59,000 square kilometres of Ladakh's challenging terrain. Their goal was to develop a reliable, repeatable method that could be used across the snow leopard's entire range and so decided to use a double-sampling method.
First, in phase 1, they wanted to figure out where snow leopards were likely to be found across the whole region. To do this, they trained teams, including local community members, to do occupancy surveys, where they walk thousands of kilometers of trails (over 6,100 km) looking for signs like paw prints, scat, and scrape marks. They used a special mobile app called MSTrIPES that automatically recorded the location and time of every sign they found, even letting them take geotagged photos as proof. They also recorded signs of the snow leopards' prey, like sheep and ibex, and even human activity, as these factors influence where the big cats live. This phase covered a vast area and helped them map out the places snow leopards were likely using.
Phase 2 was about getting a precise count in key areas. Based on the occupancy data, they selected seven large blocks, each over 900 square kilometres. These blocks represented areas where snow leopards were likely to be found at different densities. Here, they deployed motion-activated camera trap that snap a photo when an animal passes by. But their thick fur can obscure the spot patterns on their flanks, which are usually used to identify individuals. Wind can also ruffle the fur, making the same cat look different in different photos.
To overcome this, the researchers focused on capturing photos of the snow leopards' foreheads. Like using facial recognition software, they strategically placed cameras and even used a scent lure to encourage the cats to approach and look down, exposing their unique forehead patterns. They then used a sophisticated AI program called Extract-Compare, to analyse over 26,000 snow leopard photos and identify individual cats based on these patterns. This method significantly improves traditional methods, requiring fewer cameras and providing more reliable individual identification.
Using the data from the camera traps and a statistical technique called Spatially Explicit Capture-Recapture (SECR), which accounts for how animals move across the landscape, the scientists were able to estimate the density of snow leopards in each sampled block. The study estimated that snow leopards occupy about 72% of the sampled area in Ladakh.
By combining the occupancy data with environmental factors like terrain, climate, and the presence of prey, they were able to model the potential distribution of snow leopards across the entire Ladakh region, identifying about 47,572 square kilometres of suitable habitat. Within this vast area, they estimated a total population of 477 snow leopards, with a confidence range between 380 and 598. This number represents a significant portion – about 68% – of India's total estimated snow leopard population.
The study also revealed that Ladakh has some of the highest snow leopard densities ever recorded globally. Hemis National Park, a protected area, showed the highest density. Surprisingly, areas used by both wildlife and people, called multi-use areas, in Kargil and Leh also had very high densities, comparable to the highest previously reported anywhere. This suggests that snow leopards are successfully coexisting with humans and their livestock in these areas, which are often more productive habitats than the protected zones.
The presence of both wild prey and domestic livestock seems to support these high densities. However, the study also found that snow leopard presence decreased in areas with very intensive human settlement. This highlights a delicate balance: land sharing with traditional practices like pastoralism seems possible, but intensive development could pose a threat.
Knowing the true population size and distribution allows for better-informed conservation planning and investment. The high densities in multi-use areas underscore the importance of working with local communities who share the landscape with these cats. Supporting traditional practices and community-based ecotourism can provide economic benefits that encourage wildlife protection. Furthermore, the technological tools developed, like the mobile app and the AI identification software, can be used elsewhere, helping other countries and regions improve their wildlife monitoring efforts. This study not only gives us a clearer picture of the snow leopard's status in Ladakh but also offers a blueprint for better protecting such species across its global range.
This research article was written with the help of generative AI and edited by an editor at Research Matters.