The Ghost Trackers: How Indigenous Women are Leading Snow Leopard Conservation in the Himalayas

Thanks to a new initiative by our partner organization, the Nature Conservation Foundation, a growing group of Indigenous women has transitioned from viewing snow leopards as threats to actively tracking them, identifying individuals by their rosette patterns and contributing to vital population estimates. Led by conservationist Deepshikha Sharma, this initiative recently launched its own website and is transforming attitudes and perceptions of snow leopards.

Camera Trapping

The program began with 11 women from Kibber village in Spiti Valley learning to monitor wildlife in their traditional pastures during winter using camera traps. Camera trapping is a non‑invasive method that captures images of animals as they move through the landscape, providing insights into species diversity, population size and behaviour without disturbing the wildlife.

The all-woman team places camera traps at 10 locations covering 144 sq km of snow leopard landscape at the start of November each year, during the onset of winter, when animals may exhibit different behaviours or utilise different areas than in other seasons. Using snow‑leopard micro‑habitat clues—scat, scent marks, and scrape marks—the team identifies ten strategic spots, such as cliff faces and ridgelines, where cats are most likely to travel. The women trek back to each site, verify that cameras are still functioning, and swap out batteries or memory cards as needed. By March, as the snow begins to melt, the team collects the cameras and prepares for the next step of image processing.

In just two years of operation, the project has already produced a valuable archive of winter wildlife activity—documenting snow leopards, ibex, blue sheep, and a host of smaller mammals using the landscape. These images are now feeding into long‑term studies that track population trends, habitat use, and seasonal shifts in behaviour.

Image Tagging

Camera trapping generates thousands of raw images, which require additional information to be added to make them useful for analysis. The women manually tag each image to identify which species appear in each image, along with other important observations. While cameras automatically record details like time and location, identifying the animal itself requires a trained human eye. This meticulous work transforms thousands of random photos into organized data that can be readily filtered, sorted and analyzed. It’s the foundation for understanding how animals use their habitat, estimating population sizes, tracking species interactions, and revealing patterns in wildlife activity across the winter landscape.

After retrieving the winter camera traps, the team painstakingly processes thousands of photographs, assigning species tags to each file. Their efforts have revealed a rich tapestry of wildlife. Alongside the iconic snow leopard, the cameras have captured wolves, red foxes, stone martens, ibex, blue sheep, mountain weasels and birds such as chukars and Himalayan snowcocks. To date, the women have tagged close to 100,000 images from their own winter surveys in the Spiti Valley. Their contribution extends far beyond the local area. They have also tagged more than one million images collected across the Greater Himalayan and Trans‑Himalayan regions of Himachal Pradesh and Jammu & Kashmir as part of the larger rangewide PAWS (Population Assessment of the World’s Snow Leopards) effort. This extensive, meticulously curated image library now serves as a valuable resource for researchers studying high‑altitude ecosystems and the species that depend on them.

Rosette ID and Population Assessment

To estimate the population of snow leopards in a region, the first step is to identify individual snow leopards from camera-trap image data. Individual snow leopards are identified by unique rosette patterns on their bodies, especially on the head, flanks, rump, and upper parts of the tail. To determine whether two images depict the same leopard, researchers compare at least three distinct markings; if the patterns match, the images are assigned to the same individual, whereas differing patterns indicate unique individuals.

Time-lapse of a full day’s work!

Although software tools exist for identifying individuals of other wildlife, snow leopards present a unique challenge. Their long, dense and often ruffled fur obscures fine details, making automated pattern‑recognition algorithms unreliable. Consequently, the identification process is largely manual, relying on the keen eyes and meticulous attention of trained observers. Any mistake at this stage introduces significant bias into subsequent population estimates, underscoring the importance of precision, patience, skill and attention to detail.

The women have examined thousands of snow leopard images from a high‑density area, comparing every image to identify distinct individuals and build profiles for each snow leopard. As more profiles are built across the landscape, they will serve as the foundation for accurate population assessments of snow leopards, with the team continually refining their methods to maximise precision.

Dog Population Monitoring

In human-dominated landscapes around the world, dogs are the most abundant terrestrial carnivores. While many are beloved companions, free‑ranging dogs can threaten livestock, disturb native wildlife and create new challenges for local livelihoods. In the last few years, the free-ranging dog population in the Spiti Valley has been rising—an increase closely tied to the region’s booming tourism industry. Understanding these dynamics is essential for protecting both people and the fragile ecosystem.

In Spiti Valley, monitoring the dog population is a critical community effort. While residents across the region help track dog numbers, the villages of Kibber and Chicham have taken this responsibility a step further: local women conduct the annual dog population surveys. They track trends over time and evaluate the effectiveness of community-run sterilization camps, which are coordinated in partnership with local authorities. This work provides essential data to mitigate threats posed by livestock and protect native wildlife.

The impact of this work extends far beyond data collection. Knowledge is power. By engaging women as monitors, researchers, and decision-makers, the women involved now have data, information, and agency. They can advocate for snow leopards and wildlife protection in their own villages. They’re sharing what they learn with neighbors, creating connections between the whole community and the natural world. This sense of ownership—of both the problems and the solutions—is what makes conservation truly sustainable.

Deepshikha is excited to share that 30 more women from the villages of Chicham, Mane, and Demul have recently received training and joined this initiative. What started as a winter snow leopard monitoring program has the potential to become something much larger. Deepshikha’s goal is to expand this model beyond Spiti Valley, creating a network of women-led conservation across the entire trans-Himalayan region.

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Photo credits: Wildlife Wing of Himachal Pradesh Forest Department and Nature Conservation Foundation, NCF-India

Acknowledgements: Women in Conservation is an initiative of the Nature Conservation Foundation (NCF). This initiative would not have been possible without the support of the indigenous communities of the trans-Himalayan landscape and our supporters: Conservation Nation, Disney Conservation Fund and Snow Leopard Trust.

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