Effects of regional afforestation on global climate
Bibliographic record
Abstract
Carbon (C) sequestration following afforestation is regarded as economically, politically, and technically feasible for fighting global warming, whereas the afforested area which will contribute more efficiently as sinks for CO2 is still uncertain. To compare the benefits for C sequestration combined with its biogeochemical effects, an earth system model of intermediate complexity, the McGill Paleoclimate Model-2 (MPM-2) is used to identify the biogeophysical effects of regional afforestation on shaping global climate. An increase in forest in China has led to a prominent global warming during summer around 45° N. Conversely, the forest expansion in the USA causes a noticeable increase in global mean annual temperature during winter. Afforestation in the USA and China brings about a decrease in annual mean meridional oceanic heat transport, while the afforestation in low latitudes of the southern hemisphere causes an increase. These local and global impacts suggest that regional tree plantations may produce a differential effect on the Earth's climate, and even exert an opposite effect on the annual mean meridional oceanic heat transport; they imply that its spatial variation of biogeophysical feedbacks needs to be considered when evaluating the benefits of afforestation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".