Spatially explicit models for inference about density in unmarked or partially marked populations

Chandler and Royle developed spatial count models that estimate density from spatially correlated counts of unmarked individuals, extending spatially explicit capture-recapture to populations where no animals, or only some, can be individually identified. By exploiting the spatial pattern of detections across an array of detectors, the models infer how many activity centers best explain the counts, even without individual identities. This was a major advance for camera trapping of cats and other species lacking reliable natural marks, offering a path to density estimation where classic SECR is impossible. The framework underlies later unmarked and partial-identity SECR methods. It is an important methodological reference for recognition-free spatial density estimation and broadened the reach of SECR-style inference.