The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Sampling biases shape our view of the natural world
Open accessAbstract
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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Citations
Cites
The global diversity of birds in space and time
Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K., & Mooers, A. O. (2012) · Nature · doi:10.1038/nature11631 · Cited by 3,934
Global patterns and predictors of marine biodiversity across taxa
Tittensor, D. P., Mora, C., Jetz, W., Lotze, H. K., Ricard, D., Berghe, E. V., & Worm, B. (2010) · Nature · doi:10.1038/nature09329 · Cited by 1,524
Distorted Views of Biodiversity: Spatial and Temporal Bias in Species Occurrence Data
Boakes, E. H., McGowan, P. J. K., Fuller, R. A., Chang-qing, D., Clark, N. E., O'Connor, K., & Mace, G. M. (2010) · PLoS Biology · doi:10.1371/journal.pbio.1000385 · Cited by 824
Species richness, hotspots, and the scale dependence of range maps in ecology and conservation
Hurlbert, A. H., & Jetz, W. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0704469104 · Cited by 710
How Global Is the Global Biodiversity Information Facility?
Yesson, C., Brewer, P. W., Sutton, T., Caithness, N., Pahwa, J. S., Burgess, M., Gray, W. A., White, R. J., Jones, A. C., Bisby, F. A., et al. (2007) · PLoS ONE · doi:10.1371/journal.pone.0001124 · Cited by 369
Cited by
Hoban, S., Archer, F. I., Bertola, L. D., Bragg, J. G., Breed, M. F., Bruford, M. W., Coleman, M. A., Ekblom, R., Funk, W. C., Grueber, C. E., et al. (2022) · Biological Reviews · doi:10.1111/brv.12852 · Cited by 282
Colonial history and global economics distort our understanding of deep-time biodiversity
Raja, N. B., Dunne, E. M., Matiwane, A., Khan, T. M., Nätscher, P. S., Ghilardi, A. M., & Chattopadhyay, D. (2021) · Nature Ecology & Evolution · doi:10.1038/s41559-021-01608-8 · Cited by 259
How taxonomic change influences forecasts of the Linnean shortfall (and what we can do about it)?
Lessa, T., Stropp, J., Hortal, J., & Ladle, R. J. (2024) · Journal of Biogeography · doi:10.1111/jbi.14829 · Cited by 29
Exploring gaps, biases, and research priorities in the evidence for reptile conservation actions
Speight, O., Morgan, W. H., White, T. B., Sainsbury, K. A., Bouskila, A., Rotem, G., Smith, R. K., Sutherland, W. J., Watson, M. J., & Christie, A. P. (2025) · Conservation Biology · doi:10.1111/cobi.70073 · Cited by 11
Faxon, H., & Chapman, M. (2025) · Environmental Research Letters · doi:10.1088/1748-9326/add6b6 · Cited by 10
Metadata
- Authors
- Hughes, A. C., Orr, M. C., Ma, K., Costello, M. J., Waller, J., Provoost, P., Yang, Q., Zhu, C., & Qiao, H.
- Venue
- Ecography
- Publisher
- Wiley
- Published
- 2021-06-21
- Volume
- 44
- Issue
- 9
- Pages
- 1259-1269
- ISSN
- 0906-7590 (ISSN-L)
- 1600-0587
- OpenAlex
- W3175139132
- Cited by
- 634
- References
- 5
- FWCI
- 337.84
- Type
- journal article
- Language
- en
- Open access
- gold
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- Hughes, A. C., Orr, M. C., Ma, K., Costello, M. J., Waller, J., Provoost, P., Yang, Q., Zhu, C., & Qiao, H. (2021). Sampling biases shape our view of the natural world. Ecography. https://doi.org/10.1111/ecog.05926
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
