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生物多样性数据中的分类学偏差与社会偏好。

Taxonomic bias in biodiversity data and societal preferences.

机构信息

Institut de Systématique, Evolution, Biodiversité, ISYEB - UMR 7205 MNHN CNRS UPMC EPHE, Sorbonne Universités, 45 rue Buffon, 75005, Paris, France.

Outils et Méthodes de la Systématique Intégrative, OMSI - UMS 2700 CNRS MNHN, Muséum national d'Histoire naturelle, CP26, 57 rue Cuvier, 75231, Paris Cedex 05, France.

出版信息

Sci Rep. 2017 Aug 22;7(1):9132. doi: 10.1038/s41598-017-09084-6.

Abstract

Studying and protecting each and every living species on Earth is a major challenge of the 21 century. Yet, most species remain unknown or unstudied, while others attract most of the public, scientific and government attention. Although known to be detrimental, this taxonomic bias continues to be pervasive in the scientific literature, but is still poorly studied and understood. Here, we used 626 million occurrences from the Global Biodiversity Information Facility (GBIF), the biggest biodiversity data portal, to characterize the taxonomic bias in biodiversity data. We also investigated how societal preferences and taxonomic research relate to biodiversity data gathering. For each species belonging to 24 taxonomic classes, we used the number of publications from Web of Science and the number of web pages from Bing searches to approximate research activity and societal preferences. Our results show that societal preferences, rather than research activity, strongly correlate with taxonomic bias, which lead us to assert that scientists should advertise less charismatic species and develop societal initiatives (e.g. citizen science) that specifically target neglected organisms. Ensuring that biodiversity is representatively sampled while this is still possible is an urgent prerequisite for achieving efficient conservation plans and a global understanding of our surrounding environment.

摘要

研究和保护地球上的每一个生物物种是 21 世纪的主要挑战。然而,大多数物种仍然不为人知或未被研究过,而其他物种则吸引了公众、科学界和政府的大部分注意力。尽管这种分类偏见已知是有害的,但它在科学文献中仍然普遍存在,而且仍然研究和理解得很差。在这里,我们使用了全球生物多样性信息设施(GBIF)的 6.26 亿个物种发生数据,这是最大的生物多样性数据门户,来描述生物多样性数据中的分类偏见。我们还研究了社会偏好和分类学研究如何与生物多样性数据收集相关。对于属于 24 个分类类别的每一个物种,我们使用来自 Web of Science 的出版物数量和 Bing 搜索的网页数量来近似研究活动和社会偏好。我们的结果表明,社会偏好而不是研究活动与分类偏见强烈相关,这使我们断言科学家应该宣传不太有魅力的物种,并制定专门针对被忽视生物的社会倡议(例如公民科学)。在仍然有可能的情况下,确保生物多样性得到有代表性的抽样是实现有效保护计划和对我们周围环境有全球了解的紧迫前提。

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