Technological advances in field studies of pollinator ecology and the future of e-ecology

• Published in: Current opinion in insect science Vol. 38; pp. 15 - 25
• Main Authors: Barlow, Sarah E, O’Neill, Mark A
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.04.2020
• Subjects: artificial intelligence; automation; computer software; data collection; ecology; industry; lidar; monitoring; pollinators; radar; radio frequency identification; species identification
• ISSN: 2214-5745; 2214-5745; 2214-5753
• DOI: 10.1016/j.cois.2020.01.008

•Ecologists need technological solutions for acquiring large datasets in the field.•Field-deployed e-ecology tools are constrained by power draw and reliability issues.•Progress has been made in radio tracking, and automated monitoring and identification.•E-ecology will be driven by IoT and AI resulting from innovation and enterprise.•E-ecology needs cross-disciplinary scientific consortia and industry partners. 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.