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Random Encounter and Staying Time Model Testing with Human Volunteers
Authors:Laura Garland  Eric Neilson  Tal Avgar  Erin Bayne  Stan Boutin
Institution:1. University of Alberta, 116 Street and 85 Avenue, Edmonton, AB, T6G 2R3 Canada;2. Canadian Forest Service Natural Resources Canada, 5320-122 Street, Edmonton, AB, T6H 3S5 Canada;3. Utah State University, Old Main Hill, Logan, UT, 84322 USA
Abstract:Ecology and management programs designed to track population trends over time increasingly are using passive monitoring methods to estimate terrestrial mammal densities. Researchers use motion-sensing cameras in mammal studies because they are cost-effective and advances in statistical methods incorporate motion-sensing camera data to estimate mammal densities. Density estimation involving unmarked individuals, however, remains challenging and empirical tests of statistical models are relatively rare. We tested the random encounter and staying time model (REST), a new means of estimating the density of an unmarked population, using human volunteers and simulated camera surveys. The REST method produced unbiased estimates of density, regardless of changes in human abundance, movement rates, home range sizes, or simulated camera effort. These advances in statistical methods when applied to motion-sensing camera data provide innovative avenues of large-mammal monitoring that have the potential to be applied to a broad spectrum of conservation and management studies, provided assumptions for the REST method are rigorously tested and met. © 2020 The Wildlife Society.
Keywords:density  human volunteers  mammals  motion-sensing camera  random encounter and staying time method  REST
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