Density Estimation of Unmarked Populations Using Camera Traps in Heterogeneous Space
ABSTRACT Camera traps are commonly used to monitor animal populations, but statistical estimators of density from camera‐trap data for species that cannot be individually identified are still in development, and few models take space use into account. We present a model to estimate the density of un...
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| Format: | Article |
| Language: | English |
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Wiley
2020-03-01
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| Series: | Wildlife Society Bulletin |
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| Online Access: | https://doi.org/10.1002/wsb.1060 |
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| author | Gai Luo Weideng Wei Qiang Dai Jianghong Ran |
| author_facet | Gai Luo Weideng Wei Qiang Dai Jianghong Ran |
| author_sort | Gai Luo |
| collection | DOAJ |
| description | ABSTRACT Camera traps are commonly used to monitor animal populations, but statistical estimators of density from camera‐trap data for species that cannot be individually identified are still in development, and few models take space use into account. We present a model to estimate the density of unmarked populations, which considers species’ space use. The model assumes that animal movements depend on space use probability. Using a hypothetical animal population, we carried out a set of computer simulations on individual movements and camera‐trap monitoring to estimate population density with sampling data. Our results demonstrated that the model performed well, and highlighted the importance of adding space use information into density estimation approaches. We also tested the effect of multiple variables (i.e., day range, no. of camera traps, time span of monitoring duration) on density estimates. Increasing the number of camera traps and monitoring duration may reduce the variance of density estimate. Precision of density estimates increased when the species’ day range increased. Subject to accurate measurement of model parameters, this method provides a potential approach to estimate unmarked population density using camera‐trap data. © 2020 The Wildlife Society. |
| format | Article |
| id | doaj-art-5d4cca6a584044a0a983b53b28622f4c |
| institution | Kabale University |
| issn | 2328-5540 |
| language | English |
| publishDate | 2020-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Wildlife Society Bulletin |
| spelling | doaj-art-5d4cca6a584044a0a983b53b28622f4c2024-12-16T13:35:57ZengWileyWildlife Society Bulletin2328-55402020-03-0144117318110.1002/wsb.1060Density Estimation of Unmarked Populations Using Camera Traps in Heterogeneous SpaceGai Luo0Weideng Wei1Qiang Dai2Jianghong Ran3Key Laboratory of Bio‐resource and Eco‐environment of Ministry of Education, College of Life Sciences Sichuan University Chengdu 610065 ChinaKey Laboratory of Bio‐resource and Eco‐environment of Ministry of Education, College of Life Sciences Sichuan University Chengdu 610065 ChinaChengdu Institute of Biology Chinese Academy of Sciences Chengdu 610041 ChinaKey Laboratory of Bio‐resource and Eco‐environment of Ministry of Education, College of Life Sciences Sichuan University Chengdu 610065 ChinaABSTRACT Camera traps are commonly used to monitor animal populations, but statistical estimators of density from camera‐trap data for species that cannot be individually identified are still in development, and few models take space use into account. We present a model to estimate the density of unmarked populations, which considers species’ space use. The model assumes that animal movements depend on space use probability. Using a hypothetical animal population, we carried out a set of computer simulations on individual movements and camera‐trap monitoring to estimate population density with sampling data. Our results demonstrated that the model performed well, and highlighted the importance of adding space use information into density estimation approaches. We also tested the effect of multiple variables (i.e., day range, no. of camera traps, time span of monitoring duration) on density estimates. Increasing the number of camera traps and monitoring duration may reduce the variance of density estimate. Precision of density estimates increased when the species’ day range increased. Subject to accurate measurement of model parameters, this method provides a potential approach to estimate unmarked population density using camera‐trap data. © 2020 The Wildlife Society.https://doi.org/10.1002/wsb.1060computer simulationdistribution patternoccupancypopulation densityspace use |
| spellingShingle | Gai Luo Weideng Wei Qiang Dai Jianghong Ran Density Estimation of Unmarked Populations Using Camera Traps in Heterogeneous Space Wildlife Society Bulletin computer simulation distribution pattern occupancy population density space use |
| title | Density Estimation of Unmarked Populations Using Camera Traps in Heterogeneous Space |
| title_full | Density Estimation of Unmarked Populations Using Camera Traps in Heterogeneous Space |
| title_fullStr | Density Estimation of Unmarked Populations Using Camera Traps in Heterogeneous Space |
| title_full_unstemmed | Density Estimation of Unmarked Populations Using Camera Traps in Heterogeneous Space |
| title_short | Density Estimation of Unmarked Populations Using Camera Traps in Heterogeneous Space |
| title_sort | density estimation of unmarked populations using camera traps in heterogeneous space |
| topic | computer simulation distribution pattern occupancy population density space use |
| url | https://doi.org/10.1002/wsb.1060 |
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