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Review article - Peer-reviewed, 2020

A review of factors to consider when using camera traps to study animal behavior to inform wildlife ecology and conservation

Caravaggi, Anthony; Burton, A. Cole; Clark, Douglas A.; Fisher, Jason T.; Grass, Amelia; Green, Sian; Hobaiter, Catherine; Hofmeester, Tim R.; Kalan, Ammie K.; Rabaiotti, Daniella; Rivet, Danielle

Abstract

Camera traps (CTs) are an increasingly popular method of studying animal behavior. However, the impact of cameras on detected individuals-such as from mechanical noise, odor, and emitted light-has received relatively little attention. These impacts are particularly important in behavioral studies in conservation that seek to ascribe changes in behavior to relevant environmental factors. In this article, we discuss three sources of bias that are relevant to conservation behavior studies using CTs: (a) disturbance caused by cameras; (b) variation in animal-detection parameters across camera models; and (c) biased detection across individuals and age, sex, and behavioral classes. We propose several recommendations aimed at mitigating responses to CTs by wildlife. Our recommendations offer a platform for the development of more rigorous and robust behavioral studies using CT technology and, if adopted, would result in greater applied benefits for conservation and management.

Keywords

conservation behavior; management; observer bias; remote sensing; wildlife

Published in

Conservation science and practice
2020, volume: 2, number: 8, article number: e239
Publisher: WILEY

Authors' information

Caravaggi, Anthony
University of South Wales
Burton, A. Cole
University of British Columbia
Clark, Douglas A.
University of Saskatchewan
Fisher, Jason T.
University of Victoria
Grass, Amelia
University of South Wales
Green, Sian
Durham University
Hobaiter, Catherine
University of St Andrews
Swedish University of Agricultural Sciences, Department of Wildlife, Fish and Environmental Studies
Kalan, Ammie K.
Max Planck Society
Rabaiotti, Daniella
Zoological Society of London
Rivet, Danielle
University of Saskatchewan

UKÄ Subject classification

Ecology

Publication Identifiers

DOI: https://doi.org/10.1111/csp2.239

URI (permanent link to this page)

https://res.slu.se/id/publ/109708