The Effect of Stand Age and Climate on Aboveground Biomass Accumulation of <i>Pinus tabulaeformis</i> Forests
Bibliographic record
Abstract
In order to investigate the effect of stand age and climate hydrothermic factors on aboveground biomass accumulation (ABA), data from 65 typical Pinus tabulaeformis forest stands were compiled from published literatures. By means of stepwise multiple regression, the variations in ABA were examined across the range of stand age and gradients of mean annual precipitation (MAP) and mean annual temperature (MAT). For comparison, stand age was also used as explaining variable alone. The results show that, stand age and MAP could explain 85.1% of variation in ABA, the predictive power is much better than stand age alone. The explanatory power of stand age and MAP were 70.7% and 15.3% respectively. In comparison with stand age, MAP has a relatively poor but significant effect. ABA is not significantly related to MAT, which implies that water availability is more important than thermal condition for ABA of Pinus tabulaeformis forests.
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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 | 0.002 | 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 | 0.001 |
| 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 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".