Density Estimation of Unmarked Populations Using Camera Traps in Heterogeneous Space
Gai Luo, Weideng Wei, Qiang Dai, Jianghong Ran
Abstract
ABSTRACT Camera traps are commonly used to monitor animal populations, but statistical estimators of density from camera‐trap data for species that cannot be individually identified are still in development, and few models take space use into account. We present a model to estimate the density of unmarked populations, which considers species’ space use. The model assumes that animal movements depend on space use probability. Using a hypothetical animal population, we carried out a set of computer simulations on individual movements and camera‐trap monitoring to estimate population density with sampling data. Our results demonstrated that the model performed well, and highlighted the importance of adding space use information into density estimation approaches. We also tested the effect of multiple variables (i.e., day range, no. of camera traps, time span of monitoring duration) on density estimates. Increasing the number of camera traps and monitoring duration may reduce the variance of density estimate. Precision of density estimates increased when the species’ day range increased. Subject to accurate measurement of model parameters, this method provides a potential approach to estimate unmarked population density using camera‐trap data. © 2020 The Wildlife Society.