Oregon Water Science Center, U.S. Geological Survey, Bend, Oregon, United States of America.
Fort Collins Science Center, U.S. Geological Survey, Fort Collins, Colorado, United States of America.
PLoS One. 2024 Apr 2;19(4):e0301474. doi: 10.1371/journal.pone.0301474. eCollection 2024.
With the decline of bee populations worldwide, studies determining current wild bee distributions and diversity are increasingly important. Wild bee identification is often completed by experienced taxonomists or by genetic analysis. The current study was designed to compare two methods of identification including: (1) morphological identification by experienced taxonomists using images of field-collected wild bees and (2) genetic analysis of composite bee legs (multiple taxa) using metabarcoding. Bees were collected from conservation grasslands in eastern Iowa in summer 2019 and identified to the lowest taxonomic unit using both methods. Sanger sequencing of individual wild bee legs was used as a positive control for metabarcoding. Morphological identification of bees using images resulted in 36 unique taxa among 22 genera, and >80% of Bombus specimens were identified to species. Metabarcoding was limited to genus-level assignments among 18 genera but resolved some morphologically similar genera. Metabarcoding did not consistently detect all genera in the composite samples, including kleptoparasitic bees. Sanger sequencing showed similar presence or absence detection results as metabarcoding but provided species-level identifications for cryptic species (i.e., Lasioglossum). Genus-specific detections were more frequent with morphological identification than metabarcoding, but certain genera such as Ceratina and Halictus were identified equally well with metabarcoding and morphology. Genera with proportionately less tissue in a composite sample were less likely to be detected using metabarcoding. Image-based methods were limited by image quality and visible morphological features, while genetic methods were limited by databases, primers, and amplification at target loci. This study shows how an image-based identification method compares with genetic techniques, and how in combination, the methods provide valuable genus- and species-level information for wild bees while preserving tissue for other analyses. These methods could be improved and transferred to a field setting to advance our understanding of wild bee distributions and to expedite conservation research.
随着全球蜜蜂数量的减少，确定当前野生蜜蜂分布和多样性的研究变得越来越重要。野生蜜蜂的鉴定通常由经验丰富的分类学家或通过遗传分析来完成。本研究旨在比较两种鉴定方法，包括：（1）使用野外采集的野生蜜蜂图像由经验丰富的分类学家进行形态鉴定，（2）使用 metabarcoding 对复合蜜蜂腿（多个分类群）进行遗传分析。2019 年夏季，在爱荷华州东部的自然保护区草地采集蜜蜂，并使用这两种方法对其进行分类学上的最低分类单元鉴定。对野生蜜蜂腿的个体 Sanger 测序被用作 metabarcoding 的阳性对照。使用图像对蜜蜂进行形态鉴定可鉴定出 22 个属中的 36 个独特分类群，>80%的熊蜂标本鉴定到种。metabarcoding 只能在 18 个属中进行属级分配，但解决了一些形态相似的属。metabarcoding 不能始终检测到复合样本中的所有属，包括盗寄生蜂。Sanger 测序显示与 metabarcoding 相似的存在或不存在检测结果，但为隐种（即 Lasioglossum）提供了种级鉴定。形态鉴定的属特异性检测比 metabarcoding 更频繁，但某些属，如 Ceratina 和 Halictus，用 metabarcoding 和形态鉴定都能很好地鉴定。在复合样本中组织比例较低的属使用 metabarcoding 检测的可能性较小。基于图像的方法受到图像质量和可见形态特征的限制，而遗传方法受到数据库、引物和目标基因座扩增的限制。本研究展示了基于图像的鉴定方法与遗传技术的比较，以及如何结合使用这些方法，为野生蜜蜂提供有价值的属和种级信息，同时为其他分析保留组织。这些方法可以得到改进并应用于实地，以促进我们对野生蜜蜂分布的理解，并加快保护研究。
