Research overview: the Random Encounter Model for density without recognition

The Random Encounter Model estimates animal density for species that cannot be individually identified by relating the rate at which they trigger cameras to their density, using the physics of random encounters between moving animals and a fixed detection zone. This overview explains the model's logic and its required inputs: the trapping rate, the camera detection zone's radius and angle, and the animals' average daily movement distance, often the hardest parameter to obtain. It surveys validations, extensions, and the practical challenges of measuring movement speed and detection geometry accurately, since errors propagate into density. The REM opened density estimation to the many cats and prey lacking distinctive marks. The overview situates it among recognition-free estimators and notes when alternative methods like REST or distance sampling may be preferable.