Statistical Development of Animal Density Estimation Using Random Encounter Modelling

N. O. A. S. Jourdain (), D. J. Cole, M. S. Ridout and J. Marcus Rowcliffe
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N. O. A. S. Jourdain: Institute of Marine Research
D. J. Cole: University of Kent
M. S. Ridout: University of Kent
J. Marcus Rowcliffe: Institute of Zoology, Zoological Society of London

Journal of Agricultural, Biological and Environmental Statistics, 2020, vol. 25, issue 2, No 2, 148-167

Abstract: Abstract Camera trapping is widely used in ecological studies to estimate animal density, although these studies are largely restricted to animals that can be identified to the individual level. The random encounter model, developed by Rowcliffe et al. (J Anal Ecol 45(4):1228–1236, 2008), estimates animal density from camera-trap data without the need to identify animals. Although the REM can provide reliable density estimates, it lacks the potential to account for the multiple sources of variance in the modelling process. The density estimator in REM is a ratio, and since the variance of a ratio estimator is intractable, we examine and compare the finite sample performance of many approaches for obtaining confidence intervals via simulation studies. We also propose an integrated random encounter model as a parametric alternative, which is flexible and can incorporate covariates and random effects. A data example from Whipsnade Wild Animal Park, Bedfordshire, south England, is used to demonstrate the application of these methods. Supplementary materials accompanying this paper appear on-line.

Keywords: Abundance estimation; Random encounter model; Unmarked species (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s13253-020-00385-4

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