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Extinction risk and threats to plants and fungi
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Societal Impact Statement: There is increasing awareness that plants and fungi, as natural solutions, can play an important role in tackling ongoing global environmental challenges. We illustrate how understanding current and projected threats to plants and fungi is necessary to manage and mitigate risks, while building awareness of gaps and bias in current assessment coverage is essential to adequately prioritize conservation efforts. We highlight the state of the art in conservation science and point to current methods of assessment and future studies needed to mitigate species extinction. Summary: Plant and fungal biodiversity underpin life on earth and merit careful stewardship in an increasingly uncertain environment. However, gaps and biases in documented extinction risks to plant and fungal species impede effective management. Formal extinction risk assessments help avoid extinctions, through engagement, financial, or legal mechanisms, but most plant and fungal species lack assessments. Available global assessments cover c. 30% of plant species (ThreatSearch). Red List coverage overrepresents woody perennials and useful plants, but underrepresents single‐country endemics. Fungal assessments overrepresent well‐known species and are too few to infer global status or trends. Proportions of assessed vascular plant species considered threatened vary between global assessment datasets: 37% (ThreatSearch), and 44% (International Union for Conservation of Nature Red List of Threatened Species). Our predictions, correcting for several quantifiable biases, suggest that 39% of all vascular plant species are threatened with extinction. However, other biases remain unquantified, and may affect our estimate. Preliminary trend data show plants moving toward extinction. Quantitative estimates based on plant extinction risk assessments may understate likely biodiversity loss: they do not fully capture the impacts of climate change, slow‐acting threats, or clustering of extinction risk, which could amplify loss of evolutionary potential. The importance of extinction risk estimation to support existing and emerging conservation initiatives is likely to grow as threats to biodiversity intensify. This necessitates urgent and strategic expansion of efforts toward comprehensive and ongoing assessment of plant and fungal extinction risk.
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Metadata
- Authors
- Nic Lughadha, E., Bachman, S. P., Leão, T. C. C., Forest, F., Halley, J. M., Moat, J., Acedo, C., Bacon, K. L., Brewer, R. F. A., Gâteblé, G., Gonçalves, S. C., Govaerts, R., Hollingsworth, P. M., Krisai‐Greilhuber, I., de Lirio, E. J., Moore, P. G. P., Negrão, R., Onana, J. M., Rajaovelona, L. R., Razanajatovo, H., Reich, P. B., Richards, S. L., Rivers, M. C., Cooper, A., Iganci, J., Lewis, G. P., Smidt, E. C., Antonelli, A., Mueller, G. M., & Walker, B. E.
- Venue
- PLANTS, PEOPLE, PLANET
- Publisher
- Wiley
- Published
- 2020-09
- Volume
- 2
- Issue
- 5
- Pages
- 389-408
- ISSN
- 2572-2611 (ISSN-L)
- OpenAlex
- W3089890018
- Cited by
- 451
- References
- 146
- FWCI
- 33.01
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
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.