ArticleProceedings of the National Academy of Sciences of the United States of America2018
Predicting plant conservation priorities on a global scale.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 131 citations in OpenAlex.
- Critical thresholds for co-benefits of carbon accumulation and biodiversity conservation under global nitrogen enrichment.Nature communications · 2026Pooled it
- Harnessing the benefits of herbarium specimen digitisation for inferring recent and ongoing plant extinctions.The New phytologist · 2026Review
- Using comparative extinction risk analysis to prioritize the IUCN Red List reassessments of amphibians.Conservation biology : the journal of the Society for Conservation Biology · 2024Article
- Effectiveness of South Africa's network of protected areas: Unassessed vascular plants predicted to be threatened using deep neural networks are all located in protected areas.Ecology and evolution · 2024Article
- Predicting undetected native vascular plant diversity at a global scale.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- More than 17,000 tree species are at risk from rapid global change.Nature communications · 2024Article
- Predicting genetic biodiversity in salamanders using geographic, climatic, and life history traits.PloS one · 2024Article
- Mass production of unvouchered records fails to represent global biodiversity patterns.Nature ecology & evolution · 2023Article
- WASP: the World Archives of Species Perception.Database : the journal of biological databases and curation · 2023Article
- Evidence-based guidelines for automated conservation assessments of plant species.Conservation biology : the journal of the Society for Conservation Biology · 2023Article
- Implications for conservation assessment from flux in the botanical record over 20 years in southwest Ghana.Ecology and evolution · 2023Article
- A comprehensive database of squirrel distribution and occurrence in South Asia.Biodiversity data journal · 2023Article
- phylogatR: Phylogeographic data aggregation and repurposing.Molecular ecology resources · 2022Article
- The likely extinction of hundreds of palm species threatens their contributions to people and ecosystems.Nature ecology & evolution · 2022Article
- Automated assessment reveals that the extinction risk of reptiles is widely underestimated across space and phylogeny.PLoS biology · 2022Article
- Analysis of biodiversity data suggests that mammal species are hidden in predictable places.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Global Estimation and Mapping of the Conservation Status of Tree Species Using Artificial Intelligence.Frontiers in plant science · 2022Article
- Widespread homogenization of plant communities in the Anthropocene.Nature communications · 2021Article
- Prioritizing actions: spatial action maps for conservation.Annals of the New York Academy of Sciences · 2021Article
- Applying conservation reserve design strategies to define ecosystem monitoring priorities.Ecology and evolution · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 1 country.
Funding
Abstract
The conservation status of most plant species is currently unknown, despite the fundamental role of plants in ecosystem health. To facilitate the costly process of conservation assessment, we developed a predictive protocol using a machine-learning approach to predict conservation status of over 150,000 land plant species. Our study uses open-source geographic, environmental, and morphological trait data, making this the largest assessment of conservation risk to date and the only global assessment for plants. Our results indicate that a large number of unassessed species are likely at risk and identify several geographic regions with the highest need of conservation efforts, many of which are not currently recognized as regions of global concern. By providing conservation-relevant predictions at multiple spatial and taxonomic scales, predictive frameworks such as the one developed here fill a pressing need for biodiversity science.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.