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Sampling biases shape our view of the natural world

Alice C. HughesCenter for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences Menglun ChinaMichael C. OrrKey Laboratory of Zoological Systematics, Inst. of Zoology, Chinese Academy of Sciences Beijing ChinaKeping MaInst. of Botany, Chinese Academy of Sciences Beijing ChinaMark J. CostelloSchool of Environment, Univ. of Auckland Auckland New ZealandJohn WallerGBIF, Global Biodiversity Information Facility Copenhagen DenmarkPieter ProvoostOBIS, Intergovernmental Oceanographic Commission (IOC) of UNESCO Paris FranceQinmin YangState Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang Univ. ChinaChao‐Dong ZhuKey Laboratory of Zoological Systematics, Inst. of Zoology, Chinese Academy of Sciences Beijing ChinaHuijie QiaoKey Laboratory of Zoological Systematics, Inst. of Zoology, Chinese Academy of Sciences Beijing China
2021en
ABI

Аннотация

Spatial patterns of biodiversity are inextricably linked to their collection methods, yet no synthesis of bias patterns or their consequences exists. As such, views of organismal distribution and the ecosystems they make up may be incorrect, undermining countless ecological and evolutionary studies. Using 742 million records of 374 900 species, we explore the global patterns and impacts of biases related to taxonomy, accessibility, ecotype and data type across terrestrial and marine systems. Pervasive sampling and observation biases exist across animals, with only 6.74% of the globe sampled, and disproportionately poor tropical sampling. High elevations and deep seas are particularly unknown. Over 50% of records in most groups account for under 2% of species and citizen‐science only exacerbates biases. Additional data will be needed to overcome many of these biases, but we must increasingly value data publication to bridge this gap and better represent species' distributions from more distant and inaccessible areas, and provide the necessary basis for conservation and management.

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