Thinking small: Next-generation sensor networks close the size gap in vertebrate biologging
Thinking small: Next-generation sensor networks close the size gap in vertebrate biologging
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DOI：
10.1371/journal.pbio.3000655
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发表时间：
2020-04-01
期刊：
影响因子：
9.8
通讯作者：
Mayer, Frieder
中科院分区：
文献类型：
--
作者：
Ripperger, Simon P.;Carter, Gerald G.;Mayer, Frieder
动物追踪技术的最新进展开启了生物记录的新纪元。然而，许多复杂的生物记录设备的相当大的尺寸限制了它们在较大动物中的应用，而较旧的技术通常仍然代表着研究小型脊椎动物的最先进技术。在工业应用中，低功耗无线传感器网络(WSNs)满足了高分辨率和低标签质量下监控动物行为的要求。我们开发了一种无线生物记录网络(WBN)，它能够以1到2克的标签质量同时进行直接近距离感知、高分辨率跟踪和远程远程数据下载。研究野生蝙蝠的部署创造了前所未有的社会网络和飞行轨迹。我们的发展突显了WBN的巨大能力及其在缩小生物记录方面的一个重要差距方面的潜力：以高空间和时间分辨率对小动物进行全自动跟踪和接近检测，即使在封闭的栖息地也是如此。
Recent advances in animal tracking technology have ushered in a new era in biologging. However, the considerable size of many sophisticated biologging devices restricts their application to larger animals, whereas older techniques often still represent the state-of-the-art for studying small vertebrates. In industrial applications, low-power wireless sensor networks (WSNs) fulfill requirements similar to those needed to monitor animal behavior at high resolution and at low tag mass. We developed a wireless biologging network (WBN), which enables simultaneous direct proximity sensing, high-resolution tracking, and long-range remote data download at tag masses of 1 to 2 g. Deployments to study wild bats created social networks and flight trajectories of unprecedented quality. Our developments highlight the vast capabilities of WBNs and their potential to close an important gap in biologging: fully automated tracking and proximity sensing of small animals, even in closed habitats, at high spatial and temporal resolution.