Supporting data for "Honey bee (<i>Apis mellifera</i>) wing images: a tool for identification and conservation"

The honey bee (<i>Apis mellifera</i>) is an ecologically and economically important species that provides pollination services to natural and agricultural systems. The biodiversity of the honey bee in parts of its native range is endangered by migratory beekeeping and commercial breeding. In consequence, some honey bee populations that are well adapted to the local environment are threatened with extinction. A crucial step for the protection of honey bee biodiversity is reliable differentiation between native and non-native bees. One of the methods that can be used for this is the geometric morphometrics of wings. This method is fast, low-cost, and does not require expensive equipment. Therefore, it can be easily used by both scientists and beekeepers. However, wing geometric morphometrics is challenging due to the lack of reference data that can be reliably used for comparisons between different geographic regions.<br>Here, we provide an unprecedented collection of 26,481 honey bee wing images representing 1,725 samples from 13 European countries. The wing images are accompanied by the coordinates of 19 landmarks and the geographic coordinates of the sampling locations. We present an R script that describes the workflow for analysing the data and identifying an unknown sample. We compared the data with available reference samples for lineage and found general agreement with them.<br>The extensive collection of wing images available on the Zenodo website can be used to identify the geographic origin of unknown samples and therefore assist in the monitoring and conservation of honey bee biodiversity in Europe.西方蜜蜂（Apis mellifera）是兼具生态与经济价值的重要物种，可为自然生态系统与农业生产体系提供授粉服务。其本土分布范围内的部分区域的蜜蜂生物多样性正遭受转地养蜂与商业化育种的威胁，部分高度适应本地环境的蜂群濒临灭绝。保护蜜蜂生物多样性的关键环节之一，是可靠区分本土与外来蜂群；其中一种可行手段便是翅部几何形态测量法（geometric morphometrics）。该方法快速、低成本且无需昂贵设备，科学家与养蜂人均可便捷使用。但由于缺乏可用于不同地理区域间可靠比对的参考数据，翅部几何形态测量法的应用仍存在挑战。 在此项研究中，我们构建了前所未有的数据集：包含来自13个欧洲国家1725个样本的26481张蜜蜂翅部图像，每张图像均附带19个地标点的坐标信息，以及采样地点的地理坐标。我们还提供了一套R语言脚本，用于阐释该数据集的分析流程与未知样本的鉴定方法。我们将本数据集与已公开的谱系参考样本进行比对，结果显示二者总体一致性良好。 该海量翅部图像数据集已上传至Zenodo平台，可用于鉴定未知样本的地理起源，从而助力欧洲蜜蜂生物多样性的监测与保护工作。