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Quantifying levels of animal activity using camera trap data

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ROWCLIFFE, J. Marcus, Roland KAYS, Bart KRANSTAUBER, Chris CARBONE, Patrick A. JANSEN, 2014. Quantifying levels of animal activity using camera trap data. In: Methods in Ecology and Evolution. 5(11), pp. 1170-1179. ISSN 2041-2096. eISSN 2041-210X. Available under: doi: 10.1111/2041-210X.12278

@article{Rowcliffe2014Quant-30366, title={Quantifying levels of animal activity using camera trap data}, year={2014}, doi={10.1111/2041-210X.12278}, number={11}, volume={5}, issn={2041-2096}, journal={Methods in Ecology and Evolution}, pages={1170--1179}, author={Rowcliffe, J. Marcus and Kays, Roland and Kranstauber, Bart and Carbone, Chris and Jansen, Patrick A.} }

eng Kranstauber, Bart 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.<br />2. This article 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 to describe the underlying activity schedule, and calculating overall proportion of time active from this.<br />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.<br />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 met 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. Carbone, Chris Attribution-NonCommercial 3.0 Unported Jansen, Patrick A. Jansen, Patrick A. Kays, Roland Carbone, Chris 2015-03-18T08:58:08Z Rowcliffe, J. Marcus Kranstauber, Bart 2014 Rowcliffe, J. Marcus 2015-03-18T08:58:08Z Quantifying levels of animal activity using camera trap data Kays, Roland

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