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Estimating effective survey duration in camera trap distance sampling surveys
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dc.contributor.author | Kühl, Hjalmar S. | |
dc.contributor.author | Buckland, Stephen T. | |
dc.contributor.author | Henrich, Maik | |
dc.contributor.author | Howe, Eric | |
dc.contributor.author | Heurich, Marco | |
dc.date.accessioned | 2023-11-10T12:30:09Z | |
dc.date.available | 2023-11-10T12:30:09Z | |
dc.date.issued | 2023-10-13 | |
dc.identifier | 295292089 | |
dc.identifier | 9b04fbb6-3617-4098-a1b7-3f6b91e92e85 | |
dc.identifier | 85174452581 | |
dc.identifier.citation | Kühl , H S , Buckland , S T , Henrich , M , Howe , E & Heurich , M 2023 , ' Estimating effective survey duration in camera trap distance sampling surveys ' , Ecology and Evolution , vol. 13 , no. 10 , e10599 . https://doi.org/10.1002/ece3.10599 | en |
dc.identifier.issn | 2045-7758 | |
dc.identifier.other | ORCID: /0000-0002-9939-709X/work/145516740 | |
dc.identifier.uri | https://hdl.handle.net/10023/28671 | |
dc.description | This study was funded by the German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig and the Bavarian State Ministry of the Environment and Consumer Protection (project ID 77262). The field work was financed by the program Ziel ETZ FreeState of Bavaria—Czech Republic 2014–2020 (INTERREG V, project number 184). We thank our interns for their support with the field work and data processing. Open Access funding enabled and organized by Projekt DEAL. | en |
dc.description.abstract | Among other approaches, camera trap distance sampling (CTDS) is used to estimate animal abundance from unmarked populations. It was formulated for videos and observation distances are measured at predetermined ‘snapshot moments’. Surveys recording still images with passive infrared motion sensors suffer from frequent periods where animals are not photographed, either because of technical delays before the camera can be triggered again (i.e. ‘camera recovery time’) or because they remain stationary and do not immediately retrigger the camera following camera recovery time (i.e. ‘retrigger delays’). These effects need to be considered when calculating temporal survey effort to avoid downwardly biased abundance estimates. Here, we extend the CTDS model for passive infrared motion sensor recording of single images or short photo series. We propose estimating ‘mean time intervals between triggers’ as combined mean camera recovery time and mean retrigger delays from the time interval distribution of pairs of consecutive pictures, using a Gamma and Exponential function, respectively. We apply the approach to survey data on red deer, roe deer and wild boar. Mean time intervals between triggers were very similar when estimated empirically and when derived from the model-based approach. Depending on truncation times (i.e. the time interval between consecutive pictures beyond which data are discarded) and species, we estimated mean time intervals between retriggers between 8.28 and 15.05 s. Using a predefined snapshot interval, not accounting for these intervals, would lead to underestimated density by up to 96% due to overestimated temporal survey effort. The proposed approach is applicable to any taxa surveyed with camera traps. As programming of cameras to record still images is often preferred over video recording due to reduced consumption of energy and memory, we expect this approach to find broad application, also for other camera trap methods than CTDS. | |
dc.format.extent | 5617201 | |
dc.language.iso | eng | |
dc.relation.ispartof | Ecology and Evolution | en |
dc.subject | Animal abundance | en |
dc.subject | Camera recovery time | en |
dc.subject | Camera trap distance sampling | en |
dc.subject | Retrigger delay | en |
dc.subject | Still images | en |
dc.subject | Video | en |
dc.subject | Ecology, Evolution, Behavior and Systematics | en |
dc.subject | Ecology | en |
dc.subject | Nature and Landscape Conservation | en |
dc.subject | DAS | en |
dc.title | Estimating effective survey duration in camera trap distance sampling surveys | en |
dc.type | Journal article | en |
dc.contributor.institution | University of St Andrews. Statistics | en |
dc.contributor.institution | University of St Andrews. School of Mathematics and Statistics | en |
dc.identifier.doi | https://doi.org/10.1002/ece3.10599 | |
dc.description.status | Peer reviewed | en |
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