Ecosphere (Oct 2022)
A comparison of density estimation methods for monitoring marked and unmarked animal populations
Abstract
Abstract Effective monitoring of wildlife populations forms the foundation of modern‐day conservation biology. Without reliable estimates of population size, it is not possible to determine population trends, a key requirement in determining species status under international legislation. Carnivores are one of the more difficult taxonomic groups to monitor due to low population densities and elusive behavior. Here, we compare conventional live trapping and two more modern, noninvasive field methods of population estimation: genetic fingerprinting from hair tube sampling and camera trapping for the pine marten (Martes martes). We apply marked spatial capture–recapture (SCR) models to the genetic and live‐trapping data where individuals were identifiable, and unmarked SCR (uSCR), camera‐trap distance sampling (CT‐DS), and random encounter models (REMs) to the camera‐trap data where individual ID was not possible. All five approaches produced plausible and relatively consistent point estimates (0.49–1.20 individuals/km2) despite differences in precision, cost, and effort being apparent. Genetic fingerprinting produced the most precise estimate out of the two approaches for marked animal populations and had the key benefit of being noninvasive but was the most expensive of all the methods. Live trapping produced the highest point estimate while being cheapest, but the most labor intensive and least precise. The camera‐trapping methods for unmarked animal populations were the most time efficient and precise except uSCR with a moderately informative prior (uSCRm), which produced the second least precise density estimate of all the methods compared. The CT‐DS produced the most precise estimate of all the methods, followed by REM and then uSCR with a strongly informative prior (uSCRs). While choice of method of density estimation depends on objectives and funding constraints, as well as the species of interest, we demonstrate the importance of using a priori knowledge of target species and consideration of planned statistical analysis to produce appropriate experimental designs with critical consideration required regarding trap spacing and spatial extent. Such considerations broaden the comparability and applicability of these methods and will serve to provide key reference estimates for researchers, wildlife managers, and non‐governmental organizations involved in monitoring wildlife populations.
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