The DOI matches its Crossref record; 80 of the 80 references it cites were found in a registry or an index.
A review of the relation between species traits and extinction risk
Open accessAbstract
Biodiversity is shrinking rapidly, and despite our efforts only a small part of it has been assessed for extinction risk. Identifying the traits that make species vulnerable might help us to predict the status for those less known. We gathered information on the relationships between traits and extinction risk from 173 publications, across all taxa, spatial scales and biogeographical regions, in what we think it is the most comprehensive compilation to date. We aimed to identify (1) taxonomical and spatial biases, and (2) statistically robust and generalizable predictors of extinction risk through the use of meta-analyses. Vertebrates and the Palaearctic are the most studied taxon and region because of higher accumulation of data in these groups. Among the many traits that have been suggested to be predictors, only three had enough data for meta-analyses. Two of them are potentially useful in assessing risk for the lesser-known species: regardless of the taxon, species with small range and narrow habitat breadth are more vulnerable to extinction. Contrastingly, body size (the most studied trait) did not present a consistently positive or negative response. We hypothesize that the relationship between body size and extinction risk is shaped by different aspects, namely the phenomena represented by body size depending on the taxonomic group. To increase our understanding of the drivers of extinction, further studies should focus on understudied groups such as invertebrates and fungi and regions such as the tropics and expand the number of traits in comparative analyses that should avoid current biases.
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Cites
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Self-citation
Cited by
Bromham, L. (2023) · Cambridge Prisms: Extinction · doi:10.1017/ext.2022.3 · Cited by 18
Metadata
- Authors
- Chichorro, F., Juslén, A., & Cardoso, P.
- Venue
- Biological Conservation
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 237
- Pages
- 220-229
- ISSN
- 0006-3207 (ISSN-L)
- OpenAlex
- W2957909811
- Cited by
- 396
- References
- 80
- FWCI
- 26.17
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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