ReviewCambridge prisms. Extinction2023
Predicting extinctions with species distribution models.
Review in Cambridge prisms. Extinction, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
12 citing papers in PubMed.
- Providing regular and frequent maps of losses and gains of farmland birds based on European monitoring data.Conservation biology : the journal of the Society for Conservation Biology · 2026Article
- Review
- Models used for Red List assessments underestimate climate-related extinction risk of range-shifting species.Nature ecology & evolution · 2026Article
- Social and structural traits influence species gains while resources influence species losses in a native grassland.Ecology · 2026Article
- Article
- VegVault dataset: linking global paleo-, and neo-vegetation data with functional traits and abiotic drivers.Scientific data · 2025Article
- Late 21st-Century Climate and Land Use Driven Loss of Plant Diversity in African Mountains.Global change biology · 2025Article
- Incorporating Genetic Diversity to Optimize the Plant Conservation Network in the Third Pole.Global change biology · 2025Article
- Marine species and assemblage change foreshadowed by their thermal bias over Early Jurassic warming.Nature communications · 2025Article
- Chronicle of a death foretold:PhytoKeys · 2025Article
- Data fusion and integrated species distribution models for three endangered ferns (Frontiers in plant science · 2025Article
- With super SDMs (machine learning, open access big data, and the cloud) towards more holistic global squirrel hotspots and coldspots.Scientific reports · 2024Article
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
Predictions of species-level extinction risk from climate change are mostly based on species distribution models (SDMs). Reviewing the literature, we summarise why the translation of SDM results to extinction risk is conceptually and methodologically challenged and why critical SDM assumptions are unlikely to be met under climate change. Published SDM-derived extinction estimates are based on a positive relationship between range size decline and extinction risk, which empirically is not well understood. Importantly, the classification criteria used by the IUCN Red List of Threatened Species were not meant for this purpose and are often misused. Future predictive studies would profit considerably from a better understanding of the extinction risk-range decline relationship, particularly regarding the persistence and non-random distribution of the few last individuals in dwindling populations. Nevertheless, in the face of the ongoing climate and biodiversity crises, there is a high demand for predictions of future extinction risks. Despite prevailing challenges, we agree that SDMs currently provide the most accessible method to assess climate-related extinction risk across multiple species. We summarise current good practice in how SDMs can serve to classify species into IUCN extinction risk categories and predict whether a species is likely to become threatened under future climate. However, the uncertainties associated with translating predicted range declines into quantitative extinction risk need to be adequately communicated and extinction predictions should only be attempted with carefully conducted SDMs that openly communicate the limitations and uncertainty.
Indexed as
Identifiers
What OpenQuestion holds
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.