Spatially explicit maximum likelihood methods for capture-recapture studies
David L. Borchers, Murray G. Efford · Biometrics · 2008
View source ↗Borchers and Efford provided the rigorous likelihood-based foundation for spatially explicit capture-recapture, formalizing how to estimate density when detectors such as camera stations have fixed locations. They derived a full likelihood treating animal activity centers as a spatial point process and detection as a declining function of distance to each detector, accommodating different detector types including proximity detectors like cameras. This gave practitioners a statistically efficient, model-based alternative to Bayesian implementations and ad hoc buffering, with estimable detection parameters (sigma and baseline encounter rate). The framework is implemented in the widely used secr R package. It is the standard maximum-likelihood reference for SECR and is cited throughout camera-trap density studies of tigers, jaguars, leopards, and other individually identifiable cats.
Category:camera-trap-methods
Related articles
- Wildlife Insights: a platform to maximize the potential of camera trap and passive sensor datacamera-trap-methods
- Wildlife camera trapping: a review and recommendations for linking surveys to ecological processescamera-trap-methods
- A review of camera trapping for conservation behaviour researchcamera-trap-methods
- Spatially explicit models for inference about density in unmarked or partially marked populationscamera-trap-methods
- Random versus game trail-based camera trap placement for monitoring terrestrial mammal communitiescamera-trap-methods
- Density, habitat use and activity patterns of ocelots in the Atlantic Forest of Misiones, Argentinacamera-trap-methods
AI-curated summaries for the pride’s library — verify citations independently before citing.