More than one way to count a cat: estimation of ocelot population density using frameworks for marked and unmarked species

Camera-traps have become one of the most common tools for studying wildlife abundance and population density. Traditionally, absolute density could be estimated only for species with individual markings, using capture–recapture frameworks. Newer methods allow to estimate density of unmarked species, but these have yet to be thoroughly tested and compared against capture–recapture methods. To make this comparison requires an identifiable species, for which both types of frameworks can be used. Here, we estimate the population density of ocelots (Leopardus pardalis) in the Osa peninsula, Costa Rica, comparing methods for marked and unmarked species. We deployed camera-trap grids between 2017 and 2019, identified individuals and determined spatially resolved individual detection histories, station-specific detection frequencies and times to first detection. Estimates obtained with methods for unmarked species (Time-to-Event and Random Encounter Model) varied widely among surveys, from 11 to 169 individuals/100 km2, and were significantly different from spatial capture–recapture estimates (28.1 individuals/100 km2). Differences were largely driven by the non-random placement of cameras on human-made trails, which inflated the detection frequency. Maximizing the number of encounters benefits methods based on capture–recapture but is detrimental for methods based on random detections. Our results highlight the incompatibility between surveys designed for capture–recapture analyses, and those that assume random movement of animals. For recently developed unmarked species methods to be used for a larger and more diverse set of species, it is necessary to further test and define the requirements and factors that affect their calculations. This information will ultimately allow for a greater diversity of population and community studies.