The Greening of the Sahara: Past Changes and Future Implications
Bibliographic record
Abstract
In the future, the Sahara and Sahelian regions could experience more rainfall than today as a result of climate change. Wetter periods, termed African humid periods, occurred in the past and witnessed a mesic landscape in place of today's hyperarid and semiarid environment. Such large past changes raise the question of whether the near future might hold in store similar environmental transformations, particularly in view of the growing human-induced climate, land-use, and land-cover changes. In the last decades, geoengineering initiatives (in the form of active re-greening projects of the Sahara and Sahel) have been proposed and could have significant effects on the climate of the region. Here, we synthesize the literature on past and projected changes in the hydroclimate of the Sahelian-Saharan region and the associated feedbacks. We further address the current state of knowledge concerning Saharan and Sahelian afforestation projects and their consequences. Our review underscores the importance of vegetation in land-atmosphere-ocean feedback processes and the far-field impacts of northern African ecosystem changes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".