🧬 The Felid Wiki — 3,000 research summaries

The African golden cat is a secretive, rarely seen forest felid of Central and West Africa whose ecology was almost unknown until camera traps began capturing it. This overview surveys how camera surv…

The Andean cat is one of the world's rarest and least-known felids, a small cat of the high Andes and Patagonian steppe whose study depends heavily on camera traps. This overview surveys the difficult…

Camtrap DP (Camera Trap Data Package) is a community data-exchange standard that defines a consistent structure for organizing deployments, media, and observations, enabling camera-trap datasets to be…

Beyond scientific monitoring, dedicated wildlife photographers build custom DSLR camera-trap rigs to capture high-resolution, artfully lit images of elusive cats in their natural environment. This ove…

Every camera-trap image carries embedded metadata, timestamps, camera settings, and sometimes temperature or moon phase, and the integrity of this information is foundational to nearly all analysis. T…

The Eurasian lynx ranges across forests of Europe and Asia, and its spotted coat enables individual identification, making it a frequent subject of camera-trap capture-recapture density studies. This…

The Iberian lynx, once the world's most endangered cat, has been the focus of an intensive recovery program in which camera trapping plays a central monitoring role. This overview surveys how camera t…

India conducts one of the world's largest wildlife monitoring exercises, a periodic national tiger assessment that combines landscape-scale occupancy surveys with intensive camera trapping to estimate…

MegaDetector is a widely used, freely available object-detection model that locates animals, people, and vehicles in camera-trap images regardless of species, primarily to filter out the empty frames…

N-mixture models estimate abundance from repeated counts of unmarked animals at multiple sites by separating true abundance from imperfect detection, assuming counts arise from a binomial sampling of…

Pallas's cat, or manul, is a stocky, dense-furred small felid of the cold steppes and montane grasslands of Central Asia, whose cryptic coloration and low density make it difficult to survey by any me…

Snapshot Safari and Snapshot USA are large collaborative camera-trap networks that aggregate standardized surveys across many sites, in African reserves and across the United States respectively, to s…

Zooniverse hosts citizen-science projects, such as Snapshot Serengeti and its successors, where volunteers worldwide classify camera-trap images, collectively processing millions of photos that would…

Because labeling camera-trap images is costly and pretrained models falter on new projects, active-learning and human-in-the-loop workflows aim to maximize model improvement per unit of human effort.…

Researchers sometimes attract animals to cameras using food bait, scent lures, visual attractants, or scratching posts to increase detection rates and obtain better-posed, identifiable images. This ov…

Camera traps are intended to observe wildlife unobtrusively, but white flashes, audible shutter or focus sounds, and infrared glow can be detected by animals and alter their behavior, raising both dat…

Bobcats and Canada lynx are widespread North American felids studied extensively with camera traps, though their relatively subtle coat patterns complicate reliable individual identification. This ove…

Before spatially explicit methods became standard, camera-trap density estimation relied on converting capture-recapture abundance into density by buffering the camera polygon with a strip, often half…

How a camera is mounted, its height above ground, vertical and horizontal angle, and orientation relative to expected animal paths, strongly shapes which animals trigger it and how well they are photo…

Camera traps placed in accessible areas face theft, vandalism, and damage by people and animals, a chronic problem that can devastate data collection and budgets, especially in human-frequented or con…

Camera-trap distance sampling adapts classical distance-sampling theory to estimate density of unmarked animals from the distances at which they are detected within the camera's field of view. This ov…

Cheetahs carry distinctive spot patterns that allow individual identification, but their low densities, wide ranging, and preference for open habitats pose particular challenges for camera trapping. T…

Citizen science underpins much large-scale camera-trap work, from running cameras to classifying images, but harnessing volunteers reliably requires attention to data quality and sustained engagement.…

Clouded leopards, both the mainland and Sunda species, are secretive, partly arboreal forest cats whose cloud-shaped coat blotches allow individual identification from camera-trap images. This overvie…

Identifying individual cats from their unique stripe, spot, or rosette patterns is the cornerstone of capture-recapture, and software increasingly assists this once wholly manual task. This overview s…

Much camera-trap research occurs on Indigenous and community lands, raising questions of consent, benefit-sharing, and who owns and controls the resulting data. This overview surveys the principles of…

Emerging deep-learning methods aim to automate not just species classification but individual identification, re-identifying specific cats from their coat patterns to build capture histories for captu…

A foundational concept across camera-trap science is that animals present at a site are often not photographed, so raw detections undercount true occurrence and abundance. This overview surveys why de…

Wild cats span a spectrum of daily activity, from strongly nocturnal to crepuscular, diurnal, or flexibly cathemeral, and camera-trap timestamps are the primary tool for documenting these patterns at…

Beyond counting animals, camera traps capture rare and revealing behavior, hunting, feeding at kills, scent-marking, social interactions, denning, and play, providing windows into the secretive lives…