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Taxonomic bias in biodiversity data and societal preferences

Studying and protecting each and every living species on Earth is a major challenge of the 21(st) 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 b...

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Autores principales: Troudet, Julien, Grandcolas, Philippe, Blin, Amandine, Vignes-Lebbe, Régine, Legendre, Frédéric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5567328/
https://www.ncbi.nlm.nih.gov/pubmed/28831097
http://dx.doi.org/10.1038/s41598-017-09084-6
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author Troudet, Julien
Grandcolas, Philippe
Blin, Amandine
Vignes-Lebbe, Régine
Legendre, Frédéric
author_facet Troudet, Julien
Grandcolas, Philippe
Blin, Amandine
Vignes-Lebbe, Régine
Legendre, Frédéric
author_sort Troudet, Julien
collection PubMed
description Studying and protecting each and every living species on Earth is a major challenge of the 21(st) 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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spelling pubmed-55673282017-09-01 Taxonomic bias in biodiversity data and societal preferences Troudet, Julien Grandcolas, Philippe Blin, Amandine Vignes-Lebbe, Régine Legendre, Frédéric Sci Rep Article Studying and protecting each and every living species on Earth is a major challenge of the 21(st) 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. Nature Publishing Group UK 2017-08-22 /pmc/articles/PMC5567328/ /pubmed/28831097 http://dx.doi.org/10.1038/s41598-017-09084-6 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Troudet, Julien
Grandcolas, Philippe
Blin, Amandine
Vignes-Lebbe, Régine
Legendre, Frédéric
Taxonomic bias in biodiversity data and societal preferences
title Taxonomic bias in biodiversity data and societal preferences
title_full Taxonomic bias in biodiversity data and societal preferences
title_fullStr Taxonomic bias in biodiversity data and societal preferences
title_full_unstemmed Taxonomic bias in biodiversity data and societal preferences
title_short Taxonomic bias in biodiversity data and societal preferences
title_sort taxonomic bias in biodiversity data and societal preferences
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5567328/
https://www.ncbi.nlm.nih.gov/pubmed/28831097
http://dx.doi.org/10.1038/s41598-017-09084-6
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