Spatial variability of tree growth along a latitudinal transect in the Qilian Mountains, northeastern Tibetan Plateau
Bibliographic record
Abstract
Little is known about the spatial variability in tree growth and its responses to climate on the Tibetan Plateau; however, such information is essential for improving predictions of forest ecosystem response to climatic change. A network of 16 ring width chronologies was developed along a latitudinal transect in the Qilian Mountains, northeastern Tibetan Plateau. A principal components analysis revealed that the residual chronologies had a positive loading on the first unrotated principal component (PC1). After rotation, PC1 yielded the highest loadings on the driest sites in the northwest and decreased to the south and to the east. PC2 was negatively correlated with altitude. Moisture availability was a dominant limiting factor for tree growth, and this dominance increased northwards and westwards along the precipitation gradient. Loadings of the first two rotated principal components separated the 16 forest sites into three major groups corresponding to the three regions affected by the East Asian Monsoon, Westerlies, and their interaction. Thus, spatial variability in tree growth is an excellent bioindicator of regional climate.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".