Abstract
Camera trapping is widely used in different ecological studies and is particularly important for remote locations and extreme environments. However, the application of camera traps in Arctic regions remains very limited. One of the challenges is the formation of hoar on the lens of cameras. In this article, we propose a solution to address this problem by changing the camera parameters and its position in order to optimize the camera trap for long-term subnivean deployment in the Canadian Arctic. Preliminary field tests show that this approach allows tracking lemmings in the frozen environment without natural light or external electrical power supply, where the direct observations are impossible for the most part of the year. We obtained the first videos of lemmings under the snow during the Arctic winter. Extending the observational network of the newly designed camera traps will help to better understand lemming population dynamics. The demonstrated approach is also promising for other polar applications.
Highlights
Remote monitoring using automated camera traps is a non-invasive method to observe wild animals in their natural habitat and is currently widely used in many ecological studies [Caravaggi et al, 2017, O’Connell et al, 2011, Burton et al, 2015]
We believe that videos without animals may be explained by a short delay between the motion trigger and start of the recording or by motion detector triggered by an animal outside of the field of view (FOV) of the camera
We have demonstrated a new design for camera traps, based on an inexpensive and user friendly Raspberry Pi (RPi) camera, which provided promising results
Summary
Remote monitoring using automated camera traps is a non-invasive method to observe wild animals in their natural habitat and is currently widely used in many ecological studies [Caravaggi et al, 2017, O’Connell et al, 2011, Burton et al, 2015]. By analyzing the obtained images, it is possible to understand animal behaviour and their interactions without introducing biases caused by the presence of a human observer. This can help to evaluate animal’s role in ecosystems and to optimize the conservation programs aimed at reducing the negative effect of human activities and preventing population decrease or species extinction [Caravaggi et al, 2017]. Many challenges remain and new approaches are still needed to defeat certain limitations, as it will be discussed in the current article
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