Use of a novel camera trapping approach to measure small mammal responses to peatland restoration
Small mammals, such as small rodents (Rodentia: Muroidea) and shrews (Insectivora: Soricidae), present particular challenges in camera trap surveys. Their size is often insufficient to trigger infra-red sensors, whilst resultant images may be of inadequate quality for species identification. The con...
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Veröffentlicht in: | European journal of wildlife research 2021-02, Vol.67 (1), Article 12 |
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Sprache: | eng |
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Zusammenfassung: | Small mammals, such as small rodents (Rodentia: Muroidea) and shrews (Insectivora: Soricidae), present particular challenges in camera trap surveys. Their size is often insufficient to trigger infra-red sensors, whilst resultant images may be of inadequate quality for species identification. The conventional survey method for small mammals, live-trapping, can be both labour-intensive and detrimental to animal welfare. Here, we describe a method for using camera traps for monitoring small mammals. We show that by attaching the camera trap to a baited tunnel, fixing a close-focus lens over the camera trap lens, and reducing the flash intensity, pictures or videos can be obtained of sufficient quality for identifying species. We demonstrate the use of the method by comparing occurrences of small mammals in a peatland landscape containing (i) plantation forestry (planted on drained former blanket bog), (ii) ex-forestry areas undergoing bog restoration, and (iii) unmodified blanket bog habitat. Rodents were detected only in forestry and restoration areas, whilst shrews were detected across all habitat. The odds of detecting small mammals were 7.6 times higher on camera traps set in plantation forestry than in unmodified bog, and 3.7 times higher on camera traps in restoration areas than in bog. When absolute abundance estimates are not required, and camera traps are available, this technique provides a low-cost survey method that is labour-efficient and has minimal animal welfare implications. |
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ISSN: | 1612-4642 1439-0574 |
DOI: | 10.1007/s10344-020-01449-z |