霊長類研究
Online ISSN : 1880-2117
Print ISSN : 0912-4047
霊長類学におけるカメラトラップ研究
本郷 峻
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論文ID: 34.014

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Camera trapping is a new method widely used to assess animal distribution, density and behaviour. Although recent studies have reviewed general patterns in camera trap studies and provided recommendations in their usage, primate studies using camera traps have yet to be thoroughly reviewed. Here, I conducted a systematic search for studies using camera traps in primatology (camera trap primate studies [CTPS]). Finding 57 papers published between 2001 and 2017, I recorded their study objectives and methodologies. The number of CTPS started to increase from 2010, and more than half of CTPS (64.9 %) focused on behaviours. The majority of behavioural CTPS investigated foraging behaviours, including tool use, geophagy and predation, while we also found studies exploring activity rhythms, terrestrial behaviour, habitat use and social behaviours. Some studies used camera traps to complete mammal checklists in study areas and confirm the presence of focal primate species. Some ecological CTPS estimated population density using spatial capture-recapture models and capture rates, and I also found a study calculating occupancy probabilities of arboreal primates. I then point out several issues we have to consider when deploying cameras (sensor sensitivity, image type and camera placement) and analysing images obtained (definitions of independent events and potential biases in detection probability). Unfortunately, several CTPS were not designed to test their study questions sufficiently, and many articles failed to report essential information to facilitate repeatability. I argue that future researchers conducting CTPS should focus on nocturnal primates, explore novel methodologies to use the camera-trap images themselves for primate colour and morphology, develop methodologies for density estimation of arboreal primates, and use sophisticated study designs and reporting. Primatologists will be able to test their existing hypotheses using new technologies.

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