Pfeffer, Sabine and Spitzer, Robert and Allen, Andrew and Hofmeester, Tim and Ericsson, Göran and Widemo, Fredrik and Singh, Navinder and Cromsigt, Joris
(2018).
Pictures or pellets? Comparing camera trapping and dung counts as methods for estimating population densities of ungulates.
Remote Sensing in Ecology and Conservation. 4
, 173-183
[Journal article]
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Available under License Creative Commons Attribution Non-commercial. 535kB |
Official URL: http://dx.doi.org/10.1002/rse2.67
Abstract
Across the northern hemisphere, land use changes and, possibly, warmer winters are leading to more abundant and diverse ungulate communities causing increased socioeconomic and ecological consequences. Reliable population estimates are crucial for sustainable management, but it is currently unclear which monitoring method is most suitable to track changes in multi-species assemblages. We compared dung counts and camera trapping as two non-invasive census methods to estimate population densities of moose Alces alces and roe deer Capreolus capreolus in Northern Sweden. For camera trapping, we tested the random encounter model (REM) which can estimate densities without the need to recognize individual animals. We evaluated different simplification options of the REM in terms of estimates of detection distance and angle (raw data vs. modelled) and of daily movement rate (camera trap based vs. telemetry based). In comparison to density estimates from camera traps, we found that, dung counts appeared to underestimate population density for roe deer, but not for moose. Estimates of detection distance and angle from modelled versus raw camera data resulted in nearly identical outcomes. The telemetry-derived daily movement rate for moose and roe deer resulted in much higher density estimates than the camera trap-derived estimates. We suggest that camera trapping may be a robust complement to dung counts when monitoring ungulate communities, particularly when similarities between dung pellets from sympatric deer species make unambiguous assignment difficult. Moreover, we show that a simplified use of the REM method holds great potential for large-scale citizen science-based programmes (e.g. involving hunters) that can track the rapidly changing European wildlife landscape. We suggest to include camera trapping in management programmes, where the analysis can be verified via web-based applications.
Authors/Creators: | Pfeffer, Sabine and Spitzer, Robert and Allen, Andrew and Hofmeester, Tim and Ericsson, Göran and Widemo, Fredrik and Singh, Navinder and Cromsigt, Joris | ||||
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Title: | Pictures or pellets? Comparing camera trapping and dung counts as methods for estimating population densities of ungulates | ||||
Series/Journal: | Remote Sensing in Ecology and Conservation (2056-3485) | ||||
Year of publishing : | 2018 | ||||
Volume: | 4 | ||||
Page range: | 173-183 | ||||
Number of Pages: | 11 | ||||
Publisher: | John Wiley & Sons Ltd. | ||||
ISSN: | 2056-3485 | ||||
Language: | English | ||||
Publication Type: | Journal article | ||||
Refereed: | Yes | ||||
Article category: | Scientific peer reviewed | ||||
Version: | Published version | ||||
Copyright: | Creative Commons: Attribution-Noncommercial 4.0 | ||||
Full Text Status: | Public | ||||
Subjects: | (A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing (A) Swedish standard research categories 2011 > 1 Natural sciences > 106 Biological Sciences (Medical to be 3 and Agricultural to be 4) > Ecology | ||||
Agrovoc terms: | ungulates, population ecology, camera trapping, faeces | ||||
Keywords: | ungulates, population estimates, camera traps, dung counting, moose, roe deer, Alces alces, Capreolus capreolus, Northern Sweden, random encounter model (REM) | ||||
URN:NBN: | urn:nbn:se:slu:epsilon-e-4962 | ||||
Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-4962 | ||||
Additional ID: |
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ID Code: | 15552 | ||||
Faculty: | S - Faculty of Forest Sciences | ||||
Department: | (S) > Dept. of Wildlife, Fish and Environmental Studies | ||||
Deposited By: | SLUpub Connector | ||||
Deposited On: | 16 Aug 2018 13:06 | ||||
Metadata Last Modified: | 09 Sep 2020 14:17 |
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