Semantic Scholar Open Access 2017 380 sitasi

Taxonomic bias in biodiversity data and societal preferences

Julien Troudet P. Grandcolas A. Blin Régine Vignes-Lebbe F. Legendre

Abstrak

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.

Topik & Kata Kunci

Penulis (5)

J

Julien Troudet

P

P. Grandcolas

A

A. Blin

R

Régine Vignes-Lebbe

F

F. Legendre

Format Sitasi

Troudet, J., Grandcolas, P., Blin, A., Vignes-Lebbe, R., Legendre, F. (2017). Taxonomic bias in biodiversity data and societal preferences. https://doi.org/10.1038/s41598-017-09084-6

Akses Cepat

Lihat di Sumber doi.org/10.1038/s41598-017-09084-6
Informasi Jurnal
Tahun Terbit
2017
Bahasa
en
Total Sitasi
380×
Sumber Database
Semantic Scholar
DOI
10.1038/s41598-017-09084-6
Akses
Open Access ✓