Red Butte Garden, Conservation Dept., University of Utah, Salt Lake City, UT, 84108, USA.
Tumbling Dice Ltd., Gosforth, Newcastle upon Tyne, UK.
Curr Opin Insect Sci. 2020 Apr;38:15-25. doi: 10.1016/j.cois.2020.01.008. Epub 2020 Jan 28.
Our review looks at recent advances in technologies applied to studying pollinators in the field. These include RFID, radar and lidar for detecting and tracking pollinators; wireless sensor networks (e.g. 'smart' hives); automated visual and audio monitoring systems including vision motion software for monitoring fine-scale pollinator behaviours over extended periods; and automated species identification systems based on machine learning that can vastly reduce the bottleneck in (big) data analysis. An improved e-ecology platform that leverages these tools is needed for ecologists to acquire and understand large spatiotemporal datasets, and thus inform knowledge gaps in environmental policy-making. Developing the next generation of e-ecology tools will require synergistic partnerships between academia and industry and significant investment in a cross-disciplinary scientific consortia.
我们的综述着眼于应用于田间传粉媒介研究的新技术的最新进展。这些技术包括用于探测和追踪传粉媒介的 RFID、雷达和激光雷达;无线传感器网络(例如“智能”蜂箱);自动视觉和音频监测系统,包括用于监测长时间内精细尺度传粉媒介行为的视觉运动软件;以及基于机器学习的自动物种识别系统,它可以大大减少(大数据)分析中的瓶颈。生态学家需要一个改进的利用这些工具的电子生态学平台来获取和理解大时空数据集,从而为环境决策中的知识空白提供信息。开发下一代电子生态学工具需要学术界和工业界的协同伙伴关系,并需要对跨学科科学联盟进行大量投资。