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Using Metabarcoding to Investigate the Strength of Plant-Pollinator Interactions From Surveys of Visits to DNA Sequences

Abstract : The ongoing decline in pollinators and increasing concerns about pollination services require a better understanding of complex pollination networks, particularly their response to global climate change. While metabarcoding is increasingly used for the identification of taxa in DNA mixtures, its reliability in providing quantitative information on plant-pollinator interactions is still the subject of debate. Combining metabarcoding and microscopy, we investigated the relationships between the number and composition of sequences and the abundance and composition of pollen in insect pollen loads (IPL) and how the two are linked to insect visits. Our findings confirm that metabarcoding is more effective than microscopy in identifying plant species in IPL. For a given species, we found a strong positive relationship between the amount of pollen in IPL and the number of sequences. The relationship was stable across species even if the abundance of co-occurring species in IPL (hereafter “co-occurring pollen”) tended to reduce the sequence yield (number of sequences obtained from one pollen grain) of a given species. We also found a positive relationship between the sequence count and the frequency of visits,and between the frequency and the amounts of pollen in IPL. Our results demonstrate the reliability of metabarcoding in assessing the strength of plant-pollinator interactions and in providing a broader perspective for the analyses of plant-pollinator interactions and pollination networks.
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Contributor : Emilie Gil Connect in order to contact the contributor
Submitted on : Wednesday, March 30, 2022 - 4:27:37 PM
Last modification on : Monday, July 4, 2022 - 9:49:59 AM


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Sandra Baksay, Christophe Andalo, Didier Galop, Monique Burrus, Nathalie Escaravage, et al.. Using Metabarcoding to Investigate the Strength of Plant-Pollinator Interactions From Surveys of Visits to DNA Sequences. Frontiers in Ecology and Evolution, Frontiers Media S.A, 2022, 10, pp.735588. ⟨10.3389/fevo.2022.735588⟩. ⟨hal-03625112⟩



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