Quantifying levels of animal activity using camera-trap data

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Quantifying levels of animal activity using camera-trap data

Rowcliffe, M; Kays, R; Kranstauber, B; Carbone, C; Jansen, PA; (2014) Quantifying levels of animal activity using camera-trap data. Methods in Ecology and Evolution , 5 (11) pp. 1170-1179. 10.1111/2041-210X.12278. Green open access

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Abstract

1. Activity level (the proportion of time that animals spend active) is a behavioural and ecological metric that can provide an indicator of energetics, foraging effort and exposure to risk. However, activity level is poorly known for free-living animals because it is difficult to quantify activity in the field in a consistent, cost-effective and non-invasive way. 2. This paper presents a new method to estimate activity level with time-of-detection data from camera-traps (or more generally any remote sensors), fitting a flexible circular distribution to these data in order to describe the underlying activity schedule, and calculating overall proportion of time active from this. 3. Using simulations and a case study for a range of small to medium-sized mammal species, we find that activity level can reliably be estimated using the new method. 4. The method depends on the key assumption that all individuals in the sampled population are active at the peak of the daily activity cycle. We provide theoretical and empirical evidence suggesting that this assumption is likely to be met for many species, but may be less likely in large predators, or in high latitude winters. Further research is needed to establish stronger evidence on the validity of this assumption in specific cases, however, the approach has the potential to provide an effective, non invasive alternative to existing methods for quantifying population activity levels.

Type:	Article
Title:	Quantifying levels of animal activity using camera-trap data
Open access status:	An open access version is available from UCL Discovery
DOI:	10.1111/2041-210X.12278
Publisher version:	http://dx.doi.org/10.1111/2041-210X.12278
Language:	English
Additional information:	© 2014 The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Keywords:	circular kernel, weighted kernel, Von Mises distribution, proportion active, activity time, activity level, remote sensors
UCL classification:	UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment
URI:	https://discovery.ucl.ac.uk/id/eprint/1446917