Script and data from: Beetle communities in agricultural landscapes: relative influences of climate, landscape, plant communities and agricultural practices

Publication abstract Agricultural field margins are semi-natural habitats that play a key role in conservation and restoration, supporting threatened biodiversity of agroecosystems. However, most research on field margin biodiversity has focused on plant communities, while insect populations remain largely understudied. To address this gap, we leveraged a national monitoring network across France to provide a comprehensive taxonomic and functional characterisation of beetles, a highly diverse insect group of significant agricultural interest. We examined how climate, landscape, vegetation and agricultural practices influence the structure of field margin beetle communities. Using a combination of molecular and morphological approaches and multivariate analyses, we investigated beetle communities within the herbaceous field margins of 374 agricultural sites across continental France sampled between 2020 and 2023. Our surveys revealed a high diversity of beetles, with 797 species recorded, including hundreds of flower visitors and auxiliary species. Estimates based on accumulation curves suggest a richness of up to 1200 species, corresponding to approximately 10 % of the French beetle fauna. We also identified five community types, each having specific taxonomic and functional characteristics and associated with specific climatic, soil, landscape and agricultural environments. While large-scale climatic gradients were the main drivers shaping these community types, local vegetation played a key role in determining species richness. By contrast, agricultural practices appear to be an important structuring factor for both community types and richness. Finally, this study provides the first in-depth characterisation of beetle communities in French field margins, offering a solid baseline for future research and improving our understanding of the complex interactions among climatic, landscape, vegetation, and agricultural drivers. https://doi.org/10.1016/j.agee.2026.110252 File description: Beetle_trait_database.xlsx is the database of functional traits for the beetles used in this study. The second page of this Excel is a metadata explaining the different traits and possible values. All .qmd files are R (Quarto) scripts developed to characterize beetle communities in field margins across metropolitan France, in connection with the ANR AGRIBIODIV project and based on the 500ENI monitoring network. All scripts are executed within the R project AEE_characterisation_of_beetle_community.Rproj. 0-Accumulation_curves.qmd: Explores sampling effort through species accumulation curves. 1-Characterisation_Taxo_&_Function.qmd and 1-bis-Characterisation_Taxo_&_Function.qmd: Explore, at national-scale, the taxonomic and functional diversity of the beetle communities. 2-Cluster_coleop.qmd: Identifies community typologies and their features using clustering methods and Catdes analysis. 3-BRT.qmd: Investigates the interplay of climatic, pedological, landscape, agricultural, and vegetation factors in shaping beetle richness and abundance through Boosted Regression Trees (BRT) analysis. The "input.zip" folder contains all datasets required to run the scripts. It includes 10 CSV files, a folder with the shapefile of France, and a metadata file (0-READ_ME_metadata_dataset.xlsx) describing the content and structure of the data. The "before-3-Autocorrelation.zip" folder is a sub-R project designed to account for spatial autocorrelation in the BRT models, when necessary. It must be run prior to the "3-BRT.qmd".研究论文摘要：农田边际带为半自然生境，在生物多样性保护与生态修复中发挥关键作用，可为农业生态系统中的受胁生物多样性提供支撑。然而，当前针对农田边际带生物多样性的研究多聚焦于植物群落，昆虫类群的相关调查仍存在大量研究空白。为填补这一缺口，本研究依托法国国家级监测网络，对兼具极高物种多样性与重要农业研究价值的甲虫（beetles）开展了全面的分类学与功能性状表征工作，旨在探究气候、景观、植被与农业耕作方式如何影响农田边际带甲虫群落的结构特征。本研究结合分子与形态学研究手段及多元统计分析方法，对2020至2023年间采样的法国本土374个农业样地的草本型农田边际带甲虫群落展开了调查。 调查结果显示甲虫类群物种多样性极高，共记录到797个物种，其中包含数百种花访昆虫与辅助类群物种。基于物种累积曲线的估算结果显示，实际物种丰富度可达1200种，约占法国甲虫区系总量的10%。本研究还识别出5种甲虫群落类型，各类群均具备独特的分类学与功能性状特征，并与特定的气候、土壤、景观及农业生境条件相关联。尽管大尺度的气候梯度是塑造这些群落类型的主要驱动因素，但局地植被条件对物种丰富度的决定作用同样关键；相较而言，农业耕作方式则是影响群落类型与物种丰富度的重要结构因子。本研究首次对法国农田边际带的甲虫群落开展了系统性深入表征，可为后续相关研究提供坚实的基础数据，并有助于深化我们对气候、景观、植被与农业驱动因子间复杂交互作用的认知。 https://doi.org/10.1016/j.agee.2026.110252 文件说明： Beetle_trait_database.xlsx 为本研究中所用甲虫的功能性状数据库。该Excel文件的第二工作表为元数据（metadata），用于说明各类功能性状及其可选取值。 所有.qmd格式文件均为针对法国本土农田边际带甲虫群落开展表征工作的R（Quarto）脚本，本研究依托500ENI监测网络开展，与ANR AGRIBIODIV项目相关。所有脚本均需在R项目AEE_characterisation_of_beetle_community.Rproj中运行。 0-Accumulation_curves.qmd：通过物种累积曲线探究采样工作强度。 1-Characterisation_Taxo_&_Function.qmd与1-bis-Characterisation_Taxo_&_Function.qmd：在国家尺度上探究甲虫群落的分类学与功能多样性。 2-Cluster_coleop.qmd：采用聚类方法与Catdes分析识别甲虫群落类型及其特征。 3-BRT.qmd：通过提升回归树（Boosted Regression Trees, BRT）分析，探究气候、土壤、景观、农业与植被因子对甲虫物种丰富度及个体丰度的综合影响。 "input.zip"文件夹包含运行脚本所需的全部数据集，内含10个CSV文件、一个存放法国行政区划矢量文件（shapefile）的文件夹，以及用于说明数据集内容与结构的元数据文件0-READ_ME_metadata_dataset.xlsx。 "before-3-Autocorrelation.zip"为子R项目，用于在必要时校正BRT模型中的空间自相关性，需在运行"3-BRT.qmd"之前执行该项目。