Yield Response of Mediterranean Rangelands under a Changing Climate
Bibliographic record
Abstract
Abstract Understanding the Mediterranean rangelands degradation trends is a key element of mitigating their vulnerability and enhancing their resilience. Climate change and its inherent effects on mean temperature and the precipitation variability can regulate the magnitude, frequency and duration of droughts and aridity with a profound effect on ecosystem productivity. Here we investigate the effects of climate change to project the development of vegetation in the Mediterranean rangelands by (i) estimating the relative Standardized Precipitation Index and a modification of the United Nations Environment Programme Aridity Index to classify climate variability, and (ii) modelling vegetation response to climate using the Food and Agriculture Organisation crop–water production function. Climate model data are obtained from nine general circulation models under Relative Concentration Pathways 2.6 and 8.5 of the fifth phase of the Coupled Model Intercomparison Project. After correcting climate model data for biases, results for two 40‐year future study periods are compared with the baseline period 1961–2000 within a domain that includes the European Mediterranean. We show that a gradual but robust increase of aridity and drought frequency is estimated for most of the Mediterranean region, impacting rangeland vegetation yields. Projected drought and aridity disturbances may well represent permanent shifts to a warmer and more frequently dry status. This alternative stability of climatic pressure lies outside the limits of ecosystem resilience and may indicate that in some cases vegetation will either adapt to the new conditions or be succeeded by more water‐stress tolerant species. Results raise concerns about the fate of the Mediterranean rangelands and the effectiveness of mitigation measures. Copyright © 2017 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".