ArticlePeerJ2023
Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation.
Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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.
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.
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Who cites it
11 citing papers in PubMed.
- The Effects of Biome Stability During the Quaternary on Plant Diversity.Ecology and evolution · 2026Article
- Article
- Exploring Bioactive Polysaccharides in Edible Fruits: A Cross-Biome Perspective.Plants (Basel, Switzerland) · 2025Review
- Climate vulnerability of Earth's terrestrial biomes.Scientific reports · 2025Article
- Global 30-m annual median vegetation height maps (2000-2022) based on ICESat-2 data and Machine Learning.Scientific data · 2025Article
- The distribution of self-incompatibility systems in angiosperms: the relationship between mating system diversity, life span, growth habit and latitude in a changing global environment.Annals of botany · 2025Article
- Modelling the seasonal dynamics of Aedes albopictus populations using a spatio-temporal stacked machine learning model.Scientific reports · 2025Article
- Multiple influences on cyanobacterial abundance and diversity in the Beijing-Tianjin-Hebei Economic Circle and nearby areas of China.Current research in microbial sciences · 2025Article
- Microbial co-occurrence network demonstrates spatial and climatic trends for global soil diversity.Scientific data · 2024Article
- Accounting for albedo change to identify climate-positive tree cover restoration.Nature communications · 2024Article
- Article
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
The global potential distribution of biomes (natural vegetation) was modelled using 8,959 training points from the BIOME 6000 dataset and a stack of 72 environmental covariates representing terrain and the current climatic conditions based on historical long term averages (1979-2013). An ensemble machine learning model based on stacked regularization was used, with multinomial logistic regression as the meta-learner and spatial blocking (100 km) to deal with spatial autocorrelation of the training points. Results of spatial cross-validation for the BIOME 6000 classes show an overall accuracy of 0.67 and R
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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.