Climate and soil attributes determine plant species turnover in global drylands
Bibliographic record
Abstract
Abstract Aim Geographical, climatic and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. The aim of this study was to: (1) characterize patterns of beta diversity in global drylands; (2) detect common environmental drivers of beta diversity; and (3) test for thresholds in environmental conditions driving potential shifts in plant species composition. Location Global. Methods Beta diversity was quantified in 224 dryland plant communities from 22 geographical regions on all continents except Antarctica using four complementary measures: the percentage of singletons (species occurring at only one site); Whittaker's beta diversity, β(W); a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites, β( R 2 ); and a multivariate abundance‐based metric, β( MV ). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographical, climatic and soil variables. Results Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity [percentage of singletons and β(W)] were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance [(β( R 2 ) and β( MV )] were more associated with climate variability. Interactions among soil variables, climatic factors and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Main conclusions Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving c . 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".