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Cited by 401

The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.

Extinction risk is most acute for the world’s largest and smallest vertebrates

Open access
Ripple, William J., Wolf, Christopher, Newsome, Thomas M., Hoffmann, Michael, Wirsing, Aaron J., McCauley, Douglas J.·2017·Proceedings of the National Academy of Sciences

Abstract

Significance: Determining the drivers of extinction risk has been a key pursuit of conservation biology. Considering that body mass could be a strong predictor of extinction risk, we constructed a global database of body masses for 27,647 vertebrate species. Results show that the smallest- and largest-bodied vertebrates have elevated extinction risk. The largest vertebrates are mostly threatened by direct killing by humans, whereas the smallest species are more likely to have restricted geographic ranges—an important predictor of extinction risk—and be threatened by habitat degradation. Declines of large and small vertebrate species will truncate the size distributions characterizing these taxa, jeopardizing ecosystem services to humans, and generating cascading ecological and evolutionary effects on other species and processes.

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Crossref · 10.1073/pnas.1702078114

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Metadata

Authors
Ripple, W. J., Wolf, C., Newsome, T. M., Hoffmann, M., Wirsing, A. J., & McCauley, D. J.
Venue
Proceedings of the National Academy of Sciences
Published
2017-09-18
Volume
114
Issue
40
Pages
10678-10683
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2754584182
Cited by
401
References
51
FWCI
22.13
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Extinction risk is most acute for the world’s largest and smallest vertebrates. https://app.cochat.ai/papers/10.1073/pnas.1702078114
The paper
Ripple, W. J., Wolf, C., Newsome, T. M., Hoffmann, M., Wirsing, A. J., & McCauley, D. J. (2017). Extinction risk is most acute for the world’s largest and smallest vertebrates. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1702078114

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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.