Climate Offsets CO <sub>2</sub> Increase as the Main Driver of Tree Growth in Arid and Semi‐Arid Northern China
Bibliographic record
Abstract
Abstract The combined contribution of CO 2 fertilization and climate variability to arid and semi‐arid forest growth remains unclear. To disentangle these multiple influences, we used a preexisting process‐based ecophysiological model (MAIDENiso) to simulate tree growth changes during 1956–2010 in arid and semi‐arid regions of China. Results revealed that simulated tree growth was more dependent on climate trends than on atmospheric CO 2 concentration. Mechanistic analysis showed that the regulation of stomatal conductance under water stress positively affected tree growth in the arid region, but had an opposite pattern in the semi‐arid region. Intrinsic water‐use efficiency (iWUE, measured from tree‐ring δ 13 C) has increased by 29% and 44% since 1900 CE in the arid and semi‐arid regions, respectively, but did not stimulate radial tree growth. This suggests that there will possibly be a continued increase (decrease) of radial forest growth in arid (semi‐arid) areas of northern China if the current climate trends remain in the next decades.
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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 | 0.000 | 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".