Ecosystems are at increasing risk from the global pollination crisis. Gaining better knowledge about pollinators and their interactions with plants is an urgent need. However, conventional methods of manually recording pollinator activity in the field can be time- and cost-consuming in terms of labour. Field-deployable video recording systems have become more common in ecological studies as they enable the capture of plant-insect interactions in fine detail. Standard video recording can be effective, although there are issues with hardware reliability under field-conditions (e.g. weatherproofing), and reviewing raw video manually is a time-consuming task. Automated video monitoring systems based on motion detection partly overcome these issues by only recording when activity occurs hence reducing the time needed to review footage during post-processing. Another advantage of these systems is that the hardware has relatively low power requirements. A few systems have been tested in the field which permit the collection of large datasets. Compared with other systems, automated monitoring allows vast increases in sampling at broad spatiotemporal scales. Some tools such as post-recording computer vision software and data-import scripts exist, further reducing users’ time spent processing and analysing the data. Integrated computer vision and automated species recognition using machine learning models have great potential to further the study of pollinators in the field. Together, it is predicted that future advances in technology-based field monitoring methods will contribute significantly to understanding the causes underpinning pollinator declines and, hence, developing effective solutions for dealing with this global challenge.
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July 2020
Issue Editors
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Cover Image
Cover Image
The cover of this issue of
Emerging Topics in Life Sciences: New Directions in Pollinator Research , features an illustration from the review by Kessler and Chautá. In their review, they discuss how herbivory can affect the outcome of plant-pollinator interactions through plant metabolic changes induced by herbivores.
Review Article|
February 12 2020
Automated video monitoring of insect pollinators in the field
Luca Pegoraro
;
1Comparative Plant and Fungal Biology Department, Royal Botanic Gardens, Kew, Richmond, Surrey TW9 3AB, U.K.
2Organismal Biology Department, Queen Mary University of London, Mile End Road, London E1 4NS, U.K.
Correspondence: Luca Pegoraro (l.pegoraro@kew.org)
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Oriane Hidalgo;
Oriane Hidalgo
1Comparative Plant and Fungal Biology Department, Royal Botanic Gardens, Kew, Richmond, Surrey TW9 3AB, U.K.
3Laboratori de Botànica, Facultat de Farmàcia i Ciències de L'Alimentació, Universitat de Barcelona, Av Joan XXII 27-31, Barcelona 08028, Spain
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Ilia J. Leitch;
Ilia J. Leitch
1Comparative Plant and Fungal Biology Department, Royal Botanic Gardens, Kew, Richmond, Surrey TW9 3AB, U.K.
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Jaume Pellicer;
Jaume Pellicer
1Comparative Plant and Fungal Biology Department, Royal Botanic Gardens, Kew, Richmond, Surrey TW9 3AB, U.K.
4Departament de Biodiversitat, Institut Botànic de Barcelona (IBB, CSIC – Ajuntament de Barcelona), Passeig del Migdia sn, Barcelona 08038, Spain
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Sarah E. Barlow
Sarah E. Barlow
5Red Butte Garden and Arboretum, University of Utah, Salt Lake City, UT 84108, U.S.A.
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Publisher: Portland Press Ltd
Received:
November 06 2019
Revision Received:
January 16 2020
Accepted:
January 23 2020
Online ISSN: 2397-8562
Print ISSN: 2397-8554
© 2020 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society and the Royal Society of Biology
2020
Emerg Top Life Sci (2020) 4 (1): 87–97.
Article history
Received:
November 06 2019
Revision Received:
January 16 2020
Accepted:
January 23 2020
Citation
Luca Pegoraro, Oriane Hidalgo, Ilia J. Leitch, Jaume Pellicer, Sarah E. Barlow; Automated video monitoring of insect pollinators in the field. Emerg Top Life Sci 2 July 2020; 4 (1): 87–97. doi: https://doi.org/10.1042/ETLS20190074
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