Title |
Developing recommendations for monitoring wildlife underpass usage using trail cameras
|
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Published in |
Environmental Monitoring and Assessment, June 2018
|
DOI | 10.1007/s10661-018-6794-0 |
Pubmed ID | |
Authors |
Dorian Pomezanski, Lorne Bennett |
Abstract |
The growing rate of wildlife underpass use for the mitigation of road-induced wildlife mortality necessitates the development of low-cost monitoring tools for determination of mitigation success. Trail cameras are one such tool that can provide valuable insight into the usage patterns and effectiveness of wildlife underpasses. We deployed trail cameras in wildlife underpasses in Guelph, ON, to develop recommendations for camera monitoring protocols. The trail cameras used high interval time lapse and motion sensors from April to October of 2016 to capture crossing by a variety of species through two slotted, small animal underpasses. Daily and seasonal underpass usage patterns of 21 species and species groups suggest that to comprehensively monitor underpass usage, cameras must be active continuously and utilize high frequency time lapse and motion sensors simultaneously to capture crossing events by both endothermic and ectothermic species. Although these recommendations are dependent on the specific objectives and target conservation species, these results can be used to guide a range of underpass monitoring programs. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 41 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 6 | 15% |
Student > Bachelor | 5 | 12% |
Researcher | 5 | 12% |
Other | 4 | 10% |
Student > Ph. D. Student | 2 | 5% |
Other | 3 | 7% |
Unknown | 16 | 39% |
Readers by discipline | Count | As % |
---|---|---|
Environmental Science | 9 | 22% |
Agricultural and Biological Sciences | 9 | 22% |
Biochemistry, Genetics and Molecular Biology | 2 | 5% |
Veterinary Science and Veterinary Medicine | 1 | 2% |
Psychology | 1 | 2% |
Other | 3 | 7% |
Unknown | 16 | 39% |