Focus Area
Environmental Conservation
Location
Tost Uul region, South Gobi, Mongolia
Beneficiaries
Snow leopard populations, conservation scientists, and the global biodiversity community
Safavi's Role
Partner-funded initiative in collaboration with the Snow Leopard Conservancy
Key Impact
Improved population tracking methodology; non-invasive identification of individual snow leopards using camera trap technology; thousands of images captured, contributing to global conservation data
Project Overview
Snow leopards are among the world’s most elusive big cats, making accurate population estimates difficult—especially in the rugged Himalayan and Central Asian terrain. To address this challenge, the Snow Leopard Conservancy, with funding support from Safavi, implemented a groundbreaking non-invasive tracking method using remote infrared-triggered camera traps. This initiative improves conservation efforts by enabling more accurate, ethical, and consistent monitoring of snow leopard populations without physical capture or tagging.
Beneficiary Profile
This initiative directly benefits conservationists, researchers, and endangered snow leopards across Mongolia’s Tost Uul region. The remote terrain is home to wild snow leopard populations under threat from habitat loss and poaching. Local conservation teams and global scientists gain vital insights into species numbers, behavior, and territory, helping guide strategic wildlife protection efforts.
Safavi's Role
Safavi provided strategic funding and advocacy support to the Snow Leopard Conservancy, enabling the deployment of advanced digital camera traps in the field. While the initiative is managed by the Conservancy, Safavi’s backing helped expand its reach into Mongolia’s South Gobi. This partnership also supported the analysis and sharing of critical data through publications and global conservation networks.
Media
Project Gallery
Photo Credit: Camera Trapping
Impact Achieved
Successful deployment of camera traps in extreme winter conditions, operating for months without disturbance
Thousands of images captured and cataloged, allowing researchers to identify individual snow leopards using unique spot and rosette patterns
Enabled more accurate population estimates via capture-mark-recapture algorithms—without physical animal tagging
Published findings in peer-reviewed journals and contributed data to international conservation networks like Cat NEWS and the Wildlife Society Bulletin
Purpose & Signifigance
Safavi supports conservation efforts that blend scientific innovation with ecological responsibility. This initiative aligns with its core belief in sustainable environmental stewardship through low-impact, data-driven solutions. By backing non-invasive research methods, Safavi ensures that wildlife remains undisturbed while critical conservation data continues to advance the global understanding of endangered species like the snow leopard.
Future Outlook
The initiative is ongoing. Safavi remains committed to following the progress of future expansions into other high-altitude habitats. Snow Leopard Trust's planned next steps include increasing camera coverage, refining AI-based image analysis, and investing in community-based conservation training to equip local stewards with long-term wildlife monitoring tools.
