Abstract/Summary

Motivation: Pollinators play a crucial role in maintaining Earth's terrestrial biodiversity. However, rapid human‐induced environmental changes are compromising the long‐term persistence of plant‐pollinator interactions. Unfortunately, we lack robust, generalisable data capturing how plant‐pollinator communities are structured across space and time. Here, we present the EuPPollNet (European Plant‐Pollinator Networks) database, a fully open European‐level database containing harmonised taxonomic data on plant‐pollinator interactions referenced in both space and time, along with other ecological variables of interest. In addition, we evaluate the taxonomic and sampling coverage of EuPPollNet, and summarise key structural properties in plant‐pollinator networks. We believe EuPPollNet will stimulate research to address data gaps in plant‐pollinator interactions and guide future efforts in conservation planning. Main Types of Variables Included: EuPPollNet contains 1,162,109 interactions between plants and pollinators from 1864 distinct networks, which belong to 52 different studies distributed across 23 European countries. Information about sampling methodology, habitat type, biogeographic region and additional taxonomic rank information (i.e. order, family, genus and species) is also provided. Spatial Location and Grain: The database contains 1214 different sampling locations from 13 different natural and anthropogenic habitats that fall in 7 different biogeographic regions. All records are geo‐referenced and presented in the World Geodetic System 1984 (WGS84). Time Period and Grain: Species interaction data was collected between 2004 and 2021. Major Taxa and Level of Measurement: The database contains interaction data at the species level for 94% of the records, including a total of 1411 plant and 2223 pollinator species. The database includes data on 6% of the European species of flowering plants, 34% of bees, 26% of butterflies and 33% of syrphid species at the European level. Software Format: The database was built with R and is stored in ‘.rds’ and ‘.csv’ formats. Its construction is fully reproducible and can be accessed at: https://doi.org/10.5281/zenodo.14747448.