Research overview: detection probability and imperfect detection in camera-trap surveys

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 detection is imperfect, driven by animal density, movement, body size, behavior, camera placement, sensor sensitivity, vegetation, weather, and survey duration, and how unmodeled detection biases distribution maps, trend estimates, and density figures. It explains how repeated sampling occasions let occupancy and capture-recapture models separate the probability of presence from the probability of detection given presence. For wildlife photographers turned citizen scientists, understanding detection probability clarifies why more cameras and longer deployments capture more species, and why a blank card does not mean a cat is absent. The principle underlies virtually all rigorous camera-trap analysis.