Data on visitation records from wild bees and plants along a land use gradient in Germany and Belgium: laboratory work and protocol description for barcoding

The dataset contains information on plant-bee interactions in an agricultural landscape with diverse intensities of land use management, in Germany and Belgium. It was collected during spring and early summer in 2020 and 2021 using two complementary types of sampling: standardized transects (5 transects of 50 m long in 1 h of netting) and targeted sampling in which flowers were observed for diverse periods of times, anywhere in an area of 50 to 150 m<sup>2</sup>. The species identity was obtained with field keys and DNA barcoding. The dataset is of use for building pollinator networks and in combination with other datasets on environmental characteristics of the area to better understand species distributions and interactions. Indeed, we include in the dataset information on environmental parameters from the plots of sampling (spatial coordinates, land use intensity index, landscape heterogeneity index, plant diversity), which can support further correlational analyses.

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Publication Details

Journal
Data in Brief
Published
2025-05-19
DOI
https://doi.org/10.1016/j.dib.2025.111672
Citations
1
Primary Topic
Plant and animal studies
Type
article
Field-Weighted Citation Impact
3.03

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article

Data on visitation records from wild bees and plants along a land use gradient in Germany and Belgium: laboratory work and protocol description for barcoding

Ivan Meeus, Niels Piot, Alexander Keller, Jean‐Luc Brunet et al.
1 citations
Data in Brief
Plant and animal studies
3.03
article

Data on visitation records from wild bees and plants along a land use gradient in Germany and Belgium: laboratory work and protocol description for barcoding

Ivan Meeus, Niels Piot, Alexander Keller, Jean‐Luc Brunet, J. Spitz, Michael Kuhlmann, Clémentine Leroy, Cédric Alaux, Sean F. Werle, Nils Schumacher, Louella Buydens, María Alejandra Parreño, Baturalp Arisoy, Carmen A. Nebauer, René Tänzler, Michał Filipiak, Sara D. Leonhardt, Birte Peters, Mickaël Henry, Alexandra‐Maria Klein, Fabian A. Ruedenauer, Melanie Seiler, Fabrice Réquier, Philipp Reiter, Matthias Reese, Marius Buydens, Qingming Feng-Spitz, Ragna Borchardt, Tuyen Phung, Katharina Schildt, Jeremias Montoya, Regina Seiler, Andrea C. Ferrari, Sumeer Koirala, Franz Härtl, Nicolas Proessl, Stefanie Siebler, Jessica Ebensberger, Stephanie Beelaert, Jerome Moreniere
article en
1 citations

Abstract

The dataset contains information on plant-bee interactions in an agricultural landscape with diverse intensities of land use management, in Germany and Belgium. It was collected during spring and early summer in 2020 and 2021 using two complementary types of sampling: standardized transects (5 transects of 50 m long in 1 h of netting) and targeted sampling in which flowers were observed for diverse periods of times, anywhere in an area of 50 to 150 m<sup>2</sup>. The species identity was obtained with field keys and DNA barcoding. The dataset is of use for building pollinator networks and in combination with other datasets on environmental characteristics of the area to better understand species distributions and interactions. Indeed, we include in the dataset information on environmental parameters from the plots of sampling (spatial coordinates, land use intensity index, landscape heterogeneity index, plant diversity), which can support further correlational analyses.

Data in BriefVol. 61
Jagiellonian University (PL), Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (DE), Centre National de la Recherche Scientifique (FR), Helmholtz Centre for Environmental Research (DE), University of Freiburg (DE), University of Würzburg (DE), Université Paris-Saclay (FR), Christian-Albrechts-Universität zu Kiel (DE), Ghent University (BE), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Évolution, Génomes, Comportement, Écologie (FR), Molecular Networks (Germany) (DE), Oldham Council (GB), Institut de Recherche pour le Développement (FR), Technical University of Munich (DE), University of Milano-Bicocca (IT), Deutsche Post (Germany) (DE), Ludwig-Maximilians-Universität München (DE), Leipzig University (DE)
Uniwersytet Jagielloński Collegium Medicum, UK Research and Innovation, Biodiversa+, Deutsche Forschungsgemeinschaft, Agence Nationale de la Recherche, Fonds Wetenschappelijk Onderzoek, Narodowe Centrum Nauki, Universiteit Gent, Narodowym Centrum Nauki, Vlaamse regering, Biotechnology and Biological Sciences Research Council, Natural Environment Research Council, Bijzonder Onderzoeksfonds UGent
Openalex Percentile: Top 11%
Plant and animal studies
3.03
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