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Using individual-based trait frequency distributions to forecast plant-pollinator network responses to environmental change
Georgina Mace Centre for The Living Planet, Department of Life Sciences, Silwood Park, Imperial College London, Ascot, United Kingdom.
Georgina Mace Centre for The Living Planet, Department of Life Sciences, Silwood Park, Imperial College London, Ascot, United Kingdom; Bioprotection Aotearoa, School of Biological Sciences, Private Bag 4800, University of Canterbury, Christchurch, New Zealand.
Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.ORCID iD: 0000-0001-7089-524X
Georgina Mace Centre for The Living Planet, Department of Life Sciences, Silwood Park, Imperial College London, Ascot, United Kingdom.
2024 (English)In: Ecology Letters, ISSN 1461-023X, E-ISSN 1461-0248, Vol. 27, no 1, article id e14368Article in journal (Refereed) Published
Abstract [en]

Determining how and why organisms interact is fundamental to understanding ecosystem responses to future environmental change. To assess the impact on plant-pollinator interactions, recent studies have examined how the effects of environmental change on individual interactions accumulate to generate species-level responses. Here, we review recent developments in using plant-pollinator networks of interacting individuals along with their functional traits, where individuals are nested within species nodes. We highlight how these individual-level, trait-based networks connect intraspecific trait variation (as frequency distributions of multiple traits) with dynamic responses within plant-pollinator communities. This approach can better explain interaction plasticity, and changes to interaction probabilities and network structure over spatiotemporal or other environmental gradients. We argue that only through appreciating such trait-based interaction plasticity can we accurately forecast the potential vulnerability of interactions to future environmental change. We follow this with general guidance on how future studies can collect and analyse high-resolution interaction and trait data, with the hope of improving predictions of future plant-pollinator network responses for targeted and effective conservation.

Place, publisher, year, edition, pages
John Wiley & Sons, 2024. Vol. 27, no 1, article id e14368
Keywords [en]
environmental filtering, functional traits, global change, interactions, intraspecific variation, plasticity
National Category
Ecology
Identifiers
URN: urn:nbn:se:umu:diva-220170DOI: 10.1111/ele.14368ISI: 001145966800001PubMedID: 38247047Scopus ID: 2-s2.0-85182814815OAI: oai:DiVA.org:umu-220170DiVA, id: diva2:1834523
Funder
NERC - the Natural Environment Research Council, NE/S007415/1EU, Horizon 2020, 730938Available from: 2024-02-05 Created: 2024-02-05 Last updated: 2024-02-06Bibliographically approved

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Larson, Keith

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