Abstract

AbstractDetermining the abundance of cryptic carnivores is central to building successful conservation management to mitigate conflicts and support coexistence strategies. For these reasons, there is considerable investment in developing reliable, cost‐effective tools for estimating the abundance of wildlife. Nevertheless, field‐based comparisons of abundance methods remain uncommon, even while essential to refining methods and coming to consensus around best practices. Here, we compare two approaches still being tested in real‐world application for an emblematic puma (Puma concolor) population in the Torres del Paine UNESCO Biosphere Reserve in southern Chile: (1) the unmarked estimator, space‐to‐event model (STE), which utilizes photographs gathered with camera traps, and (2) the genotype spatial partial identity model (gSPIM), which is an adaptation of the more established spatially explicit genetic capture‐recapture method (SECR) based on genetic data extracted from scats collected in systematic surveys. We show the tremendous variation in resulting STE estimates depending upon the start time of the analysis and length of the sampling window, and showcase a refined iterative sampling approach in a Bayesian framework to both utilize the full camera data and to stabilize density estimates for a given sampling window. Across all sampling, estimates from the STE model ranged from 3.19 (1.6–5.1 representing 10th and 90th percentile of credible intervals) to 7.38 (3.3–11.6) independent pumas 100 km−2. By comparison, our gSPIM model estimated 5.1 independent pumas 100 km−2 (excluding kittens) (with credible intervals of 2.2–10.3). Neither method was compared with any known density to determine their accuracy. Nevertheless, we provide initial density estimates to guide conservation strategies for wildlife agencies and local communities overseeing and hosting nascent puma tourism and livestock ranching, as well as guidelines for the use of these methods for any wildlife species.

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