Published July 21, 2021 | Version v1
Dataset Open

Sampling biases shape our view of the natural world

  • 1. Xishuangbanna Tropical Botanical Garden
  • 2. Chinese Academy of Sciences
  • 3. University of Auckland
  • 4. Global Biodiversity Information Facility
  • 5. Intergovernmental Oceanographic Commission of UNESCO
  • 6. Zhejiang University

Description

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.

Notes

Uploaded files include species and samples per cell for each group for the land and ocean. See readme for specifics. Five excel files of supplemental data are also included. 

Files

Data_S3.csv

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