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Cameras do not always take a full picture: wolf activity patterns revealed by accelerometers versus road-positioned camera traps

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Bojarska, Katarzyna
Zmihorski, Michal
Naderi, Morteza
Blount, J. David
Chynoweth, Mark
Coban, Emrah
Kusak, Josip

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While animal-attached devices provide the most detailed information on animal behaviour, camera traps have become an increasingly popular non-invasive alternative in wildlife ecology. Here, we compared activity patterns of wolves (Canis lupus) assessed with accelerometers and road-positioned camera traps in two study areas in Croatia and north-eastern T & uuml;rkiye. We used accelerometer data from 37 wolves and camera trap data from 82,375 camera trap days at 358 road locations from 2010 to 2021. We fitted generalised additive mixed models to determine the times of day and parts of the year with the highest and lowest wolf activity and correlated the predictions between accelerometer- and camera-based models. Wolf activity patterns predicted from road-positioned camera traps and accelerometer data were significantly positively correlated, but the strength of the correlation varied among areas, times of day and seasons. The lowest and highest activity periods showed little overlap between the two methods. In both study areas, camera trap data failed to detect the increase in daylight activity during the pup-rearing season evident in accelerometer data. Overall, camera traps proved adequate for describing general daily and seasonal wolf activity patterns, while discrepancies between the two methods may largely be attributed to camera placement on roads. In light of the increasing use of camera traps in ecological research, our results highlight the value of animal-attached devices for tracking individuals and recommend caution when interpreting activity patterns from road-mounted cameras.

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Wiley

Subject

Ecology, Remote sensing

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Remote Sensing in Ecology and Conservation

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10.1002/rse2.70045

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CC BY-NC (Attribution-NonCommercial)

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Except where otherwised noted, this item's license is described as CC BY-NC (Attribution-NonCommercial)

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