Quantifying levels of animal activity using camera trap data
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 i...
Published in: | Methods in Ecology and Evolution |
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2014
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Online Access: | https://research.wur.nl/en/publications/quantifying-levels-of-animal-activity-using-camera-trap-data https://doi.org/10.1111/2041-210X.12278 |
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ftunivwagenin:oai:library.wur.nl:wurpubs/479146 2024-02-04T09:59:41+01:00 Quantifying levels of animal activity using camera trap data Rowcliffe, J.M. Kays, R. Kranstauber, B. Carbone, C. Jansen, P.A. 2014 application/pdf https://research.wur.nl/en/publications/quantifying-levels-of-animal-activity-using-camera-trap-data https://doi.org/10.1111/2041-210X.12278 en eng https://edepot.wur.nl/323994 https://research.wur.nl/en/publications/quantifying-levels-of-animal-activity-using-camera-trap-data doi:10.1111/2041-210X.12278 info:eu-repo/semantics/restrictedAccess Wageningen University & Research Methods in Ecology and Evolution 5 (2014) 11 ISSN: 2041-210X activity pattern circadian activity common vole determinants ecology food home-range size microtus-arvalis predator avoidance time info:eu-repo/semantics/article Article/Letter to editor info:eu-repo/semantics/publishedVersion 2014 ftunivwagenin https://doi.org/10.1111/2041-210X.12278 2024-01-10T23:19:41Z 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 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. 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 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. Article in Journal/Newspaper Common vole Microtus arvalis Wageningen UR (University & Research Centre): Digital Library Methods in Ecology and Evolution 5 11 1170 1179 |
institution |
Open Polar |
collection |
Wageningen UR (University & Research Centre): Digital Library |
op_collection_id |
ftunivwagenin |
language |
English |
topic |
activity pattern circadian activity common vole determinants ecology food home-range size microtus-arvalis predator avoidance time |
spellingShingle |
activity pattern circadian activity common vole determinants ecology food home-range size microtus-arvalis predator avoidance time Rowcliffe, J.M. Kays, R. Kranstauber, B. Carbone, C. Jansen, P.A. Quantifying levels of animal activity using camera trap data |
topic_facet |
activity pattern circadian activity common vole determinants ecology food home-range size microtus-arvalis predator avoidance time |
description |
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 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. 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 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. |
format |
Article in Journal/Newspaper |
author |
Rowcliffe, J.M. Kays, R. Kranstauber, B. Carbone, C. Jansen, P.A. |
author_facet |
Rowcliffe, J.M. Kays, R. Kranstauber, B. Carbone, C. Jansen, P.A. |
author_sort |
Rowcliffe, J.M. |
title |
Quantifying levels of animal activity using camera trap data |
title_short |
Quantifying levels of animal activity using camera trap data |
title_full |
Quantifying levels of animal activity using camera trap data |
title_fullStr |
Quantifying levels of animal activity using camera trap data |
title_full_unstemmed |
Quantifying levels of animal activity using camera trap data |
title_sort |
quantifying levels of animal activity using camera trap data |
publishDate |
2014 |
url |
https://research.wur.nl/en/publications/quantifying-levels-of-animal-activity-using-camera-trap-data https://doi.org/10.1111/2041-210X.12278 |
genre |
Common vole Microtus arvalis |
genre_facet |
Common vole Microtus arvalis |
op_source |
Methods in Ecology and Evolution 5 (2014) 11 ISSN: 2041-210X |
op_relation |
https://edepot.wur.nl/323994 https://research.wur.nl/en/publications/quantifying-levels-of-animal-activity-using-camera-trap-data doi:10.1111/2041-210X.12278 |
op_rights |
info:eu-repo/semantics/restrictedAccess Wageningen University & Research |
op_doi |
https://doi.org/10.1111/2041-210X.12278 |
container_title |
Methods in Ecology and Evolution |
container_volume |
5 |
container_issue |
11 |
container_start_page |
1170 |
op_container_end_page |
1179 |
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1789964639809830912 |