Studying the movement behavior of benthic macroinvertebrates with automated video tracking

利用自动视频追踪技术研究底栖大型无脊椎动物的运动行为

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Abstract

Quantifying and understanding movement is critical for a wide range of questions in basic and applied ecology. Movement ecology is also fostered by technological advances that allow automated tracking for a wide range of animal species. However, for aquatic macroinvertebrates, such detailed methods do not yet exist. We developed a video tracking method for two different species of benthic macroinvertebrates, the crawling isopod Asellus aquaticus and the swimming fresh water amphipod Gammarus pulex. We tested the effects of different light sources and marking techniques on their movement behavior to establish the possibilities and limitations of the experimental protocol and to ensure that the basic handling of test specimens would not bias conclusions drawn from movement path analyses. To demonstrate the versatility of our method, we studied the influence of varying population densities on different movement parameters related to resting behavior, directionality, and step lengths. We found that our method allows studying species with different modes of dispersal and under different conditions. For example, we found that gammarids spend more time moving at higher population densities, while asellids rest more under similar conditions. At the same time, in response to higher densities, gammarids mostly decreased average step lengths, whereas asellids did not. Gammarids, however, were also more sensitive to general handling and marking than asellids. Our protocol for marking and video tracking can be easily adopted for other species of aquatic macroinvertebrates or testing conditions, for example, presence or absence of food sources, shelter, or predator cues. Nevertheless, limitations with regard to the marking protocol, material, and a species' physical build need to be considered and tested before a wider application, particularly for swimming species. Data obtained with this approach can deepen the understanding of population dynamics on larger spatial scales and of the effects of different management strategies on a species' dispersal potential.

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