Applying and testing a novel method to estimate animal density from motion‐triggered cameras. Issue 4 (15th April 2022)
- Record Type:
- Journal Article
- Title:
- Applying and testing a novel method to estimate animal density from motion‐triggered cameras. Issue 4 (15th April 2022)
- Main Title:
- Applying and testing a novel method to estimate animal density from motion‐triggered cameras
- Authors:
- Becker, Marcus
Huggard, David J.
Dickie, Melanie
Warbington, Camille
Schieck, Jim
Herdman, Emily
Serrouya, Robert
Boutin, Stan - Abstract:
- 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.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. … (more)
- Is Part Of:
- Ecosphere. Volume 13:Issue 4(2022)
- Journal:
- Ecosphere
- Issue:
- Volume 13:Issue 4(2022)
- Issue Display:
- Volume 13, Issue 4 (2022)
- Year:
- 2022
- Volume:
- 13
- Issue:
- 4
- Issue Sort Value:
- 2022-0013-0004-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-04-15
- Subjects:
- Alberta -- camera trap -- density estimation -- effective detection distance -- moose -- multispecies monitoring -- population monitoring -- relative density -- time in front of the camera -- unmarked population
Ecology -- Periodicals
Ecology
Periodicals
577.05 - Journal URLs:
- http://bibpurl.oclc.org/web/50453 ↗
http://esajournals.onlinelibrary.wiley.com/hub/journal/10.1002/(ISSN)2150-8925/ ↗
http://www.esajournals.org/loi/ecsp ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/ecs2.4005 ↗
- Languages:
- English
- ISSNs:
- 2150-8925
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21447.xml