Parreño Maria Alejandra, Werle Susanne, Buydens Louella, Spitz Joshua, Härtl Franz, Montoya Jeremias, Ruedenauer Fabian, Arisoy Baturalp, Seiler Regina, Leroy Clementine, Feng-Spitz Qingming, Nebauer Carmen Alexandra, Ferrari Andrea, Proessl Nicolas, Borchardt Ragna, Peters Birte, Siebler Stefanie, Reese Matthias, Schumacher Nils, Phung Tuyen, Schildt Katharina, Ebensberger Jessica, Seiler Maximilian, Reiter Philipp, Beelaert Stephanie, Buydens Marius, Koirala Sumeer, Moreniere Jerome, Tänzler Rene, Alaux Cedric, Filipiak Michał, Meeus Ivan, Piot Niels, Kuhlmann Michael, Requier Fabrice, Klein Alexandra, Brunet Jean Luc, Henry Mickael, Keller Alexander, Leonhardt Sara Diana
Plant-Insect Interactions, TUM School of Life Science Systems, Technical University of Munich (TUM), Freising, Germany.
Agricultural Entomology, Acarology, Nematology, Department of Plants and Crops, Ghent University, Ghent, Belgium.
Data Brief. 2025 May 19;61:111672. doi: 10.1016/j.dib.2025.111672. eCollection 2025 Aug.
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. 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.
该数据集包含德国和比利时农业景观中不同土地利用管理强度下植物与蜜蜂相互作用的信息。它是在2020年和2021年的春季和初夏期间,通过两种互补的采样类型收集的:标准化样带(在1小时的网捕中设置5条50米长的样带)和目标采样,即在50至150米区域内的任何地方对花朵进行不同时间段的观察。通过野外鉴定和DNA条形码确定物种身份。该数据集可用于构建传粉者网络,并与该地区环境特征的其他数据集结合使用,以更好地了解物种分布和相互作用。实际上,我们在数据集中包含了采样地块的环境参数信息(空间坐标、土地利用强度指数、景观异质性指数、植物多样性),这可以支持进一步的相关性分析。