Applying and testing a novel method to estimate animal density from motion‐triggered cameras

Abstract Estimating animal abundance and density are fundamental goals of many wildlife monitoring programs. Camera trapping has become an increasingly popular tool to achieve these monitoring goals due to recent advances in modeling approaches and the capacity to simultaneously collect data on mult...

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Published in:Ecosphere
Main Authors: Becker, Marcus, Huggard, David J., Dickie, Melanie, Warbington, Camille, Schieck, Jim, Herdman, Emily, Serrouya, Robert, Boutin, Stan
Other Authors: Alberta Environment and Parks
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2022
Subjects:
Online Access:http://dx.doi.org/10.1002/ecs2.4005
https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.4005
https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.4005
https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.4005
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spelling crwiley:10.1002/ecs2.4005 2024-09-15T17:36:17+00:00 Applying and testing a novel method to estimate animal density from motion‐triggered cameras Becker, Marcus Huggard, David J. Dickie, Melanie Warbington, Camille Schieck, Jim Herdman, Emily Serrouya, Robert Boutin, Stan Alberta Environment and Parks 2022 http://dx.doi.org/10.1002/ecs2.4005 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.4005 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.4005 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.4005 en eng Wiley http://creativecommons.org/licenses/by/4.0/ Ecosphere volume 13, issue 4 ISSN 2150-8925 2150-8925 journal-article 2022 crwiley https://doi.org/10.1002/ecs2.4005 2024-07-04T04:31:20Z Abstract Estimating animal abundance and density are fundamental goals of many wildlife monitoring programs. Camera trapping has become an increasingly popular tool to achieve these monitoring goals due to recent advances in modeling approaches and the capacity to simultaneously collect data on multiple species. However, estimating the density of unmarked populations continues to be problematic due to the difficulty in implementing complex modeling approaches, low precision of estimates, and absence of rigor in testing of model assumptions and their influence on results. Here, we describe a novel approach that uses still image camera traps to estimate animal density without the need for individual identification, based on the time spent in front of the camera (TIFC). Using results from a large‐scale multispecies monitoring program with nearly 3000 cameras deployed over 6 years in Alberta, Canada, we provide a reproducible methodology to estimate parameters and we test key assumptions of the TIFC model. We compare moose ( Alces alces ) density estimates from aerial surveys and TIFC, including incorporating correction factors for known TIFC assumption violations. The resulting corrected TIFC density estimates are comparable to aerial density estimates. We discuss the limitations of the TIFC method and areas needing further investigation, including the need for long‐term monitoring of assumption violations and the number of cameras necessary to provide precise estimates. Despite the challenges of assumption violations and high measurement error, cameras and the TIFC method can provide useful alternative or complementary animal density estimates for multispecies monitoring when compared to traditional monitoring methods. Article in Journal/Newspaper Alces alces Wiley Online Library Ecosphere 13 4
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
description Abstract Estimating animal abundance and density are fundamental goals of many wildlife monitoring programs. Camera trapping has become an increasingly popular tool to achieve these monitoring goals due to recent advances in modeling approaches and the capacity to simultaneously collect data on multiple species. However, estimating the density of unmarked populations continues to be problematic due to the difficulty in implementing complex modeling approaches, low precision of estimates, and absence of rigor in testing of model assumptions and their influence on results. Here, we describe a novel approach that uses still image camera traps to estimate animal density without the need for individual identification, based on the time spent in front of the camera (TIFC). Using results from a large‐scale multispecies monitoring program with nearly 3000 cameras deployed over 6 years in Alberta, Canada, we provide a reproducible methodology to estimate parameters and we test key assumptions of the TIFC model. We compare moose ( Alces alces ) density estimates from aerial surveys and TIFC, including incorporating correction factors for known TIFC assumption violations. The resulting corrected TIFC density estimates are comparable to aerial density estimates. We discuss the limitations of the TIFC method and areas needing further investigation, including the need for long‐term monitoring of assumption violations and the number of cameras necessary to provide precise estimates. Despite the challenges of assumption violations and high measurement error, cameras and the TIFC method can provide useful alternative or complementary animal density estimates for multispecies monitoring when compared to traditional monitoring methods.
author2 Alberta Environment and Parks
format Article in Journal/Newspaper
author Becker, Marcus
Huggard, David J.
Dickie, Melanie
Warbington, Camille
Schieck, Jim
Herdman, Emily
Serrouya, Robert
Boutin, Stan
spellingShingle Becker, Marcus
Huggard, David J.
Dickie, Melanie
Warbington, Camille
Schieck, Jim
Herdman, Emily
Serrouya, Robert
Boutin, Stan
Applying and testing a novel method to estimate animal density from motion‐triggered cameras
author_facet Becker, Marcus
Huggard, David J.
Dickie, Melanie
Warbington, Camille
Schieck, Jim
Herdman, Emily
Serrouya, Robert
Boutin, Stan
author_sort Becker, Marcus
title Applying and testing a novel method to estimate animal density from motion‐triggered cameras
title_short Applying and testing a novel method to estimate animal density from motion‐triggered cameras
title_full Applying and testing a novel method to estimate animal density from motion‐triggered cameras
title_fullStr Applying and testing a novel method to estimate animal density from motion‐triggered cameras
title_full_unstemmed Applying and testing a novel method to estimate animal density from motion‐triggered cameras
title_sort applying and testing a novel method to estimate animal density from motion‐triggered cameras
publisher Wiley
publishDate 2022
url http://dx.doi.org/10.1002/ecs2.4005
https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.4005
https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.4005
https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.4005
genre Alces alces
genre_facet Alces alces
op_source Ecosphere
volume 13, issue 4
ISSN 2150-8925 2150-8925
op_rights http://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.1002/ecs2.4005
container_title Ecosphere
container_volume 13
container_issue 4
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