ArticleConservation biology : the journal of the Society for Conservation Biology2015
Predicting the conservation status of data-deficient species.
Article in Conservation biology : the journal of the Society for Conservation Biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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Who cites it
65 citing papers in PubMed.
- A synthesis of recorded fine-scale threats to imperiled species in the United States.iScience · 2026Article
- Identifying hotspots of faunal data deficiency to direct urgent research and monitoring.Conservation biology : the journal of the Society for Conservation Biology · 2026Article
- Environmental and Evolutionary Correlates of Extinction Risk in a Global Biodiversity Hotspot.Ecology and evolution · 2026Article
- The entanglement between the IUCN Red List and international biodiversity law.Conservation biology : the journal of the Society for Conservation Biology · 2026Article
- Red listing the flora of the Green Islands reveals high extinction risk in the Azores.Scientific reports · 2026Article
- The City Nature Challenge as an urban BioBlitz: evaluating Citizen Science contributions to biodiversity monitoring in Berlin.BMC ecology and evolution · 2026Article
- Phenotypic and Ecological Correlates of Population Decline in the World's Anurans.Ecology and evolution · 2026Article
- Unveiling Emerging Trends and Gaps in Scientific Research on Vertebrate Biodiversity in Tropical Savannahs.Ecology and evolution · 2026Review
- Gaps in trait data and conservation impediments from the Raunkiæran shortfall in a megadiverse nation.iScience · 2025Article
- Can Macroevolution Inform Contemporary Extinction Risk?Ecology letters · 2025Review
- 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
- Effective Survey Methods for the Elusive Data Deficient Black Flying Squirrel (Animals : an open access journal from MDPI · 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
- Inferring the extinction risk of marine fish to inform global conservation priorities.PLoS biology · 2024Article
- Past, present, and future of the Living Planet Index.npj biodiversity · 2023Review
- The contribution of historical processes to contemporary extinction risk in placental mammals.Science (New York, N.Y.) · 2023Article
- The EDGE2 protocol: Advancing the prioritisation of Evolutionarily Distinct and Globally Endangered species for practical conservation action.PLoS biology · 2023Article
- The likely extinction of hundreds of palm species threatens their contributions to people and ecosystems.Nature ecology & evolution · 2022Article
- Global and regional erosion of mammalian functional diversity across the diel cycle.Science advances · 2022Article
- More than half of data deficient species predicted to be threatened by extinction.Communications biology · 2022Article
5 more citing papers are in PubMed but not listed here.
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4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is little appreciation of the level of extinction risk faced by one-sixth of the over 65,000 species assessed by the International Union for Conservation of Nature. Determining the status of these data-deficient (DD) species is essential to developing an accurate picture of global biodiversity and identifying potentially threatened DD species. To address this knowledge gap, we used predictive models incorporating species' life history, geography, and threat information to predict the conservation status of DD terrestrial mammals. We constructed the models with 7 machine learning (ML) tools trained on species of known status. The resultant models showed very high species classification accuracy (up to 92%) and ability to correctly identify centers of threatened species richness. Applying the best model to DD species, we predicted 313 of 493 DD species (64%) to be at risk of extinction, which increases the estimated proportion of threatened terrestrial mammals from 22% to 27%. Regions predicted to contain large numbers of threatened DD species are already conservation priorities, but species in these areas show considerably higher levels of risk than previously recognized. We conclude that unless directly targeted for monitoring, species classified as DD are likely to go extinct without notice. Taking into account information on DD species may therefore help alleviate data gaps in biodiversity indicators and conserve poorly known biodiversity.
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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.