English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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.

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