Mongolia 2020 National Survey Used Over 2,000 Camera Trap Stations to Count Snow Leopards

An endangered predator required thousands of hidden cameras across mountains to prove it still exists.

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🤯 Did You Know (click to read)

Each snow leopard’s spot pattern is unique, functioning like a fingerprint for identification.

Mongolia conducted one of the most extensive snow leopard surveys in 2020, deploying over 2,000 camera trap stations across key habitats. The effort aimed to produce a more accurate national population estimate. Sparse distribution and rugged terrain make direct observation nearly impossible. Camera traps capture unique spot patterns, allowing individual identification. The scale of deployment reflects the difficulty of counting a low-density apex predator. Data from thousands of images feed into statistical models estimating abundance. Such surveys require coordination across vast landscapes and multiple agencies. Proving presence demands technological networks spread over mountain systems.

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💥 Impact (click to read)

Large-scale monitoring provides baseline data critical for policy decisions. Without reliable numbers, conservation planning risks misallocation of resources. Mongolia’s investment demonstrates commitment to evidence-based management. However, surveys are resource-intensive and must be repeated periodically. Data gaps can emerge quickly in dynamic ecosystems. Monitoring also informs transboundary cooperation with neighboring countries. Scientific infrastructure becomes as important as physical habitat.

For the global public, the idea that thousands of cameras are required to glimpse a single species underscores its elusiveness. The snow leopard’s survival depends on remaining unseen, yet its protection depends on being documented. This tension defines modern conservation. A predator adapted to vanish into rock faces now leaves digital traces across memory cards. Its continued existence is confirmed not by rumor, but by data points stitched across mountains.

Source

Snow Leopard Trust

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