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利用地震探测大象的咆哮声作为监测手段。

Seismic localization of elephant rumbles as a monitoring approach.

机构信息

Department of Zoology, University of Oxford, Oxford, UK.

Department of Computer Science, University of Oxford, Oxford, UK.

出版信息

J R Soc Interface. 2021 Jul;18(180):20210264. doi: 10.1098/rsif.2021.0264. Epub 2021 Jul 14.

Abstract

African elephants () are sentient and intelligent animals that use a variety of vocalizations to greet, warn or communicate with each other. Their low-frequency rumbles propagate through the air as well as through the ground and the physical properties of both media cause differences in frequency filtering and propagation distances of the respective wave. However, it is not well understood how each mode contributes to the animals' abilities to detect these rumbles and extract behavioural or spatial information. In this study, we recorded seismic and co-generated acoustic rumbles in Kenya and compared their potential use to localize the vocalizing animal using the same multi-lateration algorithms. For our experimental set-up, seismic localization has higher accuracy than acoustic, and bimodal localization does not improve results. We conclude that seismic rumbles can be used to remotely monitor and even decipher elephant social interactions, presenting us with a tool for far-reaching, non-intrusive and surprisingly informative wildlife monitoring.

摘要

非洲象是有感知力和智慧的动物,它们会使用各种声音来打招呼、警告或相互交流。它们的低频隆隆声不仅可以在空气中传播,还可以在地面上传播,而这两种介质的物理特性会导致频率滤波和各自波的传播距离的差异。然而,人们并不清楚每种模式如何帮助动物检测到这些隆隆声,并从中提取出行为或空间信息。在这项研究中,我们在肯尼亚记录了地震和共发声的隆隆声,并使用相同的多点定位算法比较了它们在定位发声动物方面的潜在用途。对于我们的实验设置,地震定位比声学定位更准确,而双模态定位并不能提高结果。我们得出结论,地震隆隆声可用于远程监测,甚至破译大象的社会互动,为我们提供了一种用于远程、非侵入性且信息丰富的野生动物监测的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/829d/8277467/df8194638c20/rsif20210264f01.jpg

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