Advanced camera trap networks provide individual-level welfare data for wild snow leopards, revealing condition, behavior, and territorial responses to climate and human pressure.
Advanced camera trap monitoring for snow leopards has transformed welfare science for this elusive, high-altitude predator. The ability to identify individuals, track their condition across seasons, and detect behavioral changes indicating stress or food insecurity without any handling or disturbance represents a breakthrough in non-invasive welfare monitoring. Camera-based condition scoring — assessing body fat, coat quality, and posture — provides welfare data that would otherwise require capture and examination, eliminating the handling stress that compromised earlier welfare assessment approaches. This non-invasive monitoring model is increasingly transferable to other cryptic species whose welfare had been largely invisible to science.