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Cited by 158

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Predicting unknown species numbers using discovery curves

Open access
Bebber, Daniel P, Marriott, Francis H.C, Gaston, Kevin J, Harris, Stephen A, Scotland, Robert W·2007·Proceedings of the Royal Society B: Biological Sciences

Abstract

A common approach to estimating the total number of extant species in a taxonomic group is to extrapolate from the temporal pattern of known species descriptions. A formal statistical approach to this problem is provided. The approach is applied to a number of global datasets for birds, ants, mosses, lycophytes, monilophytes (ferns and horsetails), gymnosperms and also to New World grasses and UK flowering plants. Overall, our results suggest that unless the inventory of a group is nearly complete, estimating the total number of species is associated with very large margins of error. The strong influence of unpredictable variations in the discovery process on species accumulation curves makes these data unreliable in estimating total species numbers.

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Metadata

Authors
Bebber, D. P., Marriott, F. H. C., Gaston, K. J., Harris, S. A., & Scotland, R. W.
Venue
Proceedings of the Royal Society B: Biological Sciences
Published
2007-04-24
Volume
274
Issue
1618
Pages
1651-1658
ISSN
  • 0080-4649 (ISSN-L)
  • 0962-8452
  • 1471-2954
OpenAlex
W2151173963
Cited by
158
References
0
FWCI
4.84
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Predicting unknown species numbers using discovery curves. https://app.cochat.ai/papers/10.1098/rspb.2007.0464
The paper
Bebber, D. P., Marriott, F. H. C., Gaston, K. J., Harris, S. A., & Scotland, R. W. (2007). Predicting unknown species numbers using discovery curves. Proceedings of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rspb.2007.0464

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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.