Chinese Grain for Green Program led to highly increased soil organic carbon levels: A meta-analysis
Bibliographic record
Abstract
The Grain for Green Program (GGP), initiated in 1999, is the largest ecological restoration project in central and western China. Here, for the first time, we performed a meta-analysis and found that the GGP largely increased the soil organic carbon (SOC). The SOC was increased by 48.1%, 25.4%, and 25.5% at soil depths of 0-20 cm, 20-40 cm, and 40-60 cm, respectively. Moreover, this carbon accumulation has significantly increased over time since GGP implementation. The carbon accumulation showed a significantly more active response to the GGP in the top 20 cm of soil than in the deeper soil layers. Conversion of cropland to forest could lead to significantly greater SOC accumulation than would the conversion of cropland to grassland. Conversion from cropland to woodland could lead to greater SOC accumulation than would the conversion to either shrubland or orchard. Our results suggest that the GGP implementation caused SOC to accumulate and that there remains a large potential for further accumulation of carbon in the soil, which will help to mitigate climate change in the near future.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".