Abstract

Camera traps (CTs) are an increasingly popular tool for wildlife survey and monitoring. Estimating relative abundance in unmarked species is often done using detection rate as an index of relative abundance, which assumes that detection rate has a positive linear relationship with true abundance. This assumption may be violated if movement behavior varies with density, but the degree to which movement behavior is density‐dependent across taxa is unclear. The potential confounding of population‐level relative abundance indices by movement would depend on how regularly, and by what magnitude, movement rate and home‐range size vary with density. We conducted a systematic review and meta‐analysis to quantify relationships between movement rate, home‐range size, and density, across terrestrial mammalian taxa. We then simulated animal movements and CT sampling to test the effect of contrasting movement scenarios on CT detection rate indices. Overall, movement rate and home‐range size were negatively correlated with density and positively correlated with one another. The strength of the relationships varied significantly between taxa and populations. In simulations, detection rates were related to true abundance but underestimated change, particularly for slower moving species with small home ranges. In situations where animal space use changes markedly with density, we estimate that up to thirty percent of a true change in relative abundance may be missed due to the confounding effect of movement, making trend estimation more difficult. The common assumption that movement remains constant across densities is therefore violated across a wide range of mammal species. When studying unmarked species using CT detection rates, researchers and managers should explicitly consider that such indices of relative abundance reflect both density and movement. Practitioners interpreting changes in camera detection rates should be aware that observed differences may be biased low relative to true changes in abundance. Further information on animal movement, or methods that do not depend on assumptions of density‐independent movement, may be required to make robust inferences on population trends.

Highlights

  • Accurate abundance estimation is at the core of wildlife management, and camera traps (CTs) are an increasingly popular monitoring tool (Burton et al, 2015; O'Connell, Nichols, & Karanth, 2011)

  • This paper aims to quantify how home-range size, movement rate, and density covary across mammalian taxa, and to explore the effect, this covariation might have on CT-based relative abundance estimates

  • Our meta-analysis indicated that higher population densities were associated with significantly slower movement rates and smaller home ranges across multiple species

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Summary

| INTRODUCTION

Accurate abundance estimation is at the core of wildlife management, and camera traps (CTs) are an increasingly popular monitoring tool (Burton et al, 2015; O'Connell, Nichols, & Karanth, 2011). The camera trapping technique has been successful in the study of large species whose coat patterns allow individuals to be identified Identification of such “marked” species allows for standard capture–recapture methods to be applied (Karanth & Nichols, 1998), and accurate density estimation of such populations has been further improved with the development of spatially explicit capture–recapture methods (Efford, 2004; Royle, Chandler, Sollmann, & Gardner, 2014). Harmsen, Foster, Silver, Ostro, & Doncaster, 2010; Sollmann, Mohamed, et al, 2013) Violation of this assumption poses a problem for the use of detection rates as an index of relative abundance when encounter probability covaries with density (Harmsen et al, 2010; Jennelle, Runge, & MacKenzie, 2002). If home-range size and movement rate are density-dependent, this could obscure true change in abundance inferred from a relative abundance index. We chose space-use scenarios that span the range of variation found in the meta-analysis, so as to reveal the full extent by which movement could confound relative abundance estimates from detection rates

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