蜜蜂(Apis mellifera)翅膀图像:一种识别和保护工具。

IF 11.8 2区 生物学 Q1 MULTIDISCIPLINARY SCIENCES
GigaScience Pub Date : 2023-03-20 Epub Date: 2023-03-27 DOI:10.1093/gigascience/giad019
Andrzej Oleksa, Eliza Căuia, Adrian Siceanu, Zlatko Puškadija, Marin Kovačić, M Alice Pinto, Pedro João Rodrigues, Fani Hatjina, Leonidas Charistos, Maria Bouga, Janez Prešern, İrfan Kandemir, Slađan Rašić, Szilvia Kusza, Adam Tofilski
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引用次数: 0

摘要

背景:蜜蜂(Apis mellifera)是一种具有重要生态和经济价值的物种,为自然和农业系统提供授粉服务。蜜蜂在其原生地的部分地区的生物多样性因养蜂业的迁徙和商业繁殖而受到威胁。因此,一些适应当地环境的蜜蜂种群正面临灭绝的威胁。保护蜜蜂生物多样性的一个关键步骤是可靠地区分本地蜜蜂和非本地蜜蜂。翅膀几何形态计量学是其中一种可用的方法。这种方法速度快、成本低,而且不需要昂贵的设备。因此,科学家和养蜂人都可以轻松使用。然而,由于缺乏可用于不同地理区域比较的可靠参考数据,翅膀几何形态计量学具有挑战性:在此,我们前所未有地收集了 26,481 张蜜蜂翅膀图像,代表了来自 13 个欧洲国家的 1,725 个样本。这些翅膀图像附有 19 个地标的坐标和采样地点的地理坐标。我们介绍了一个 R 脚本,其中描述了分析数据和识别未知样本的工作流程。我们将数据与现有的参考样本进行了比较,发现两者基本一致:Zenodo网站上广泛收集的翅膀图像可用来识别未知样本的地理来源,从而帮助监测和保护欧洲的蜜蜂生物多样性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Honey bee (Apis mellifera) wing images: a tool for identification and conservation.

Honey bee (Apis mellifera) wing images: a tool for identification and conservation.

Honey bee (Apis mellifera) wing images: a tool for identification and conservation.

Honey bee (Apis mellifera) wing images: a tool for identification and conservation.

Background: The honey bee (Apis mellifera) 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 nonnative bees. One of the methods that can be used for this is the geometric morphometrics of wings. This method is fast, is 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.

Findings: 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 analyzing the data and identifying an unknown sample. We compared the data with available reference samples for lineage and found general agreement with them.

Conclusions: 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.

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来源期刊
GigaScience
GigaScience MULTIDISCIPLINARY SCIENCES-
CiteScore
15.50
自引率
1.10%
发文量
119
审稿时长
1 weeks
期刊介绍: GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.
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