Shedding light on pollination deficits: cueing into plant spectral reflectance signatures to monitor pollination delivery across landscapes
Author(s)
Parry, Catherine
Turnbull, Colin
Barter, Laura
Gill, Richard
Type
Journal Article
Abstract
Pollination underlies plant yield, health and reproductive success in agricultural and natural systems worldwide. It is therefore concerning that declining animal pollinator populations compounded by growing demands for food are leading to rising pollination deficits, with globally significant economic and environmental implications.
Despite this urgent issue, accurate and scalable tools to quantify and track pollination across useful spatiotemporal scales are lacking. Here, we propose to shed new light on pollination deficits, looking to remote sensing platforms as a transformative mapping and monitoring tool and a solution for pollinator conservation and crop management.
Providing a synthesis of our current understanding of pollination-triggered floral senescence and underlying ultrastructural and metabolic changes, we propose how spectral reflectance technologies could be applied to accurately detect pollination events in real-time and at the landscape scale.
Synthesis and applications: We highlight where research efforts can be targeted to produce scalable methods for identifying field-relevant bioindicators of pollination. We provide guidance on how spectral imaging accompanied by machine learning and coupled with autonomous operation technologies will enable applications to detect pollination delivery across complex landscapes. Ultimately, such an ecological application will transform our quantitative understanding of pollination services and, by directly linking plant yields and health, will reveal pollination deficits at high resolution to help mitigate risks to food security and ecosystem functioning.
Despite this urgent issue, accurate and scalable tools to quantify and track pollination across useful spatiotemporal scales are lacking. Here, we propose to shed new light on pollination deficits, looking to remote sensing platforms as a transformative mapping and monitoring tool and a solution for pollinator conservation and crop management.
Providing a synthesis of our current understanding of pollination-triggered floral senescence and underlying ultrastructural and metabolic changes, we propose how spectral reflectance technologies could be applied to accurately detect pollination events in real-time and at the landscape scale.
Synthesis and applications: We highlight where research efforts can be targeted to produce scalable methods for identifying field-relevant bioindicators of pollination. We provide guidance on how spectral imaging accompanied by machine learning and coupled with autonomous operation technologies will enable applications to detect pollination delivery across complex landscapes. Ultimately, such an ecological application will transform our quantitative understanding of pollination services and, by directly linking plant yields and health, will reveal pollination deficits at high resolution to help mitigate risks to food security and ecosystem functioning.
Date Issued
2024-12
Date Acceptance
2024-10-07
Citation
Journal of Applied Ecology, 2024, 61 (12), pp.2873-2883
ISSN
0021-8901
Publisher
Wiley
Start Page
2873
End Page
2883
Journal / Book Title
Journal of Applied Ecology
Volume
61
Issue
12
Copyright Statement
© 2024 The Author(s). Journal of Applied Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2664.14807
Publication Status
Published
Date Publish Online
2024-10-30