ArticleScientific data2022
Native range estimates for red-listed vascular plants.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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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.
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Who cites it
7 citing papers in PubMed.
- Revealing Hidden Biodiversity Footprints Embedded in Global Mining Supply Chains.Environmental science & technology · 2026Article
- Validating a rapid algorithmic weed hazard ranking method.Pest management science · 2026Article
- What Is the Impact of Accidentally Transporting Terrestrial Alien Species? A New Life Cycle Impact Assessment Model.Environmental science & technology · 2024Article
- Biodiversity Impact Assessment Considering Land Use Intensities and Fragmentation.Environmental science & technology · 2023Article
- Ecological niche model transferability of the white star apple (Chrysophyllum albidum G. Don) in the context of climate and global changes.Scientific reports · 2023Article
- Increased Invasion Risk ofPlants (Basel, Switzerland) · 2022Article
- Native range estimates for red-listed vascular plants.Scientific data · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Besides being central for understanding both global biodiversity patterns and associated anthropogenic impacts, species range maps are currently only available for a small subset of global biodiversity. Here, we provide a set of assembled spatial data for terrestrial vascular plants listed at the global IUCN red list. The dataset consists of pre-defined native regions for 47,675 species, density of available native occurrence records for 30,906 species, and standardized, large-scale Maxent predictions for 27,208 species, highlighting environmentally suitable areas within species' native regions. The data was generated in an automated approach consisting of data scraping and filtering, variable selection, model calibration and model selection. Generated Maxent predictions were validated by comparing a subset to available expert-drawn range maps from IUCN (n = 4,257), as well as by qualitatively inspecting predictions for randomly selected species. We expect this data to serve as a substitute whenever expert-drawn species range maps are not available for conducting large-scale analyses on biodiversity patterns and associated anthropogenic impacts.
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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.