Dryness is accelerating degradation of vulnerable shrublands in semiarid Mediterranean environments
Bibliographic record
Abstract
Semiarid Mediterranean regions are highly susceptible to desertification processes. This study investigated the influence of increasing climate aridity in explaining the decline in vegetation cover in highly vulnerable gypsum semiarid shrublands of the Mediterranean region. For this purpose, we have used time series of percent cover of vegetation obtained from remote sensing imagery (Landsat satellites). We found a dominant trend toward decreased vegetation cover, mainly in summer and in areas affected by the most severe water stress conditions (low precipitation, higher evapotranspiration rates, and sun‐exposed slopes). We show that past human management and current climate trends interact with local environmental conditions to determine the occurrence of vegetation degradation processes. The results suggest that degradation could be a consequence of the past overexploitation that has characterized this area (and many others in the Mediterranean region), but increased aridity, mainly related to global warming, may be triggering and/or accelerating the degradation processes. The observed pattern may be an early warning of processes potentially affecting more areas of the Mediterranean, according to the most up‐to‐date climate change models for the 21st century.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".