Plants, pollinators and their interactions under global ecological change: The role of pollen DNA metabarcoding
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Anthropogenic activities are triggering global changes in the environment, causing entire communities of plants, pollinators and their interactions to restructure, and ultimately leading to species declines. To understand the mechanisms behind community shifts and declines, as well as monitoring and managing impacts, a global effort must be made to characterize plant–pollinator communities in detail, across different habitat types, latitudes, elevations, and levels and types of disturbances. Generating data of this scale will only be feasible with rapid, high-throughput methods. Pollen DNA metabarcoding provides advantages in throughput, efficiency and taxonomic resolution over traditional methods, such as microscopic pollen identification and visual observation of plant–pollinator interactions. This makes it ideal for understanding complex ecological networks and their responses to change. Pollen DNA metabarcoding is currently being applied to assess plant–pollinator interactions, survey ecosystem change and model the spatiotemporal distribution of allergenic pollen. Where samples are available from past collections, pollen DNA metabarcoding has been used to compare contemporary and past ecosystems. New avenues of research are possible with the expansion of pollen DNA metabarcoding to intraspecific identification, analysis of DNA in ancient pollen samples, and increased use of museum and herbarium specimens. Ongoing developments in sequencing technologies can accelerate progress towards these goals. Global ecological change is happening rapidly, and we anticipate that high-throughput methods such as pollen DNA metabarcoding are critical for understanding the evolutionary and ecological processes that support biodiversity, and predicting and responding to the impacts of change.
|Status||Udgivet - 2023|
KLB was supported by internal funding from the University of Western Australia and CSIRO. KJT was supported by USDA‐NIFA grant no. 2021‐67012‐35153. RML was supported by the Biotechnology and Biological Sciences Research Council (BBSRC), part of UK Research and Innovation, through Core Strategic Programme Grant BB/CSP1720/1.
The manuscript was improved with comments from Olly Berry, Liz Milla, Dylan T. Simpson, four anonymous reviewers and the editors of the special issue. KLB was supported by internal funding from the University of Western Australia and CSIRO. KJT was supported by USDA‐NIFA grant no. 2021‐67012‐35153. RML was supported by the Biotechnology and Biological Sciences Research Council (BBSRC), part of UK Research and Innovation, through Core Strategic Programme Grant BB/CSP1720/1. Open access publishing facilitated by The University of Western Australia, as part of the Wiley ‐ The University of Western Australia agreement via the Council of Australian University Librarians.
© 2022 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.