Taxonomic bias in biodiversity data and societal preferences

Abstract : Studying and protecting each and every living species on Earth is a major challenge of the 21st 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.
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Scientific Reports, Nature Publishing Group, 2017, 7, pp.9132. 〈10.1038/s41598-017-09084-6〉
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Julien Troudet, Philippe Grandcolas, Amandine Blin, Régine Vignes-Lebbe, Frédéric Legendre. Taxonomic bias in biodiversity data and societal preferences. Scientific Reports, Nature Publishing Group, 2017, 7, pp.9132. 〈10.1038/s41598-017-09084-6〉. 〈hal-01585590〉

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