Leaf/sapwood area ratios in Scots pine show acclimation across Europe
Bibliographic record
Abstract
We tested the hypothesis that leaf/sapwood area ratios (S) in Scots pine (Pinus sylvestris L.) differ across Europe. Data from published records were collected and critically reviewed, and five new sites were studied to increase the overall sample size available for analyses. For seven studies for which data were available, we also determined the magnitude of the errors resulting from the use of ratio and regression-type estimators during subsampling for leaf areas of individual trees. These subsampling errors were then compared with those resulting from least square regressions of leaf area against sapwood area, and the total error was determined. Finally, correlation analysis was used to test for significant relationships between S and site-specific and stand-specific variables. Subsampling for leaf area resulted in errors, the magnitude of which was site specific and depended on sampling sizes and protocols. In general, despite larger total errors resulting from accounting for subsampling, significant differences were found among S, both at breast height and at the base of the living crown, at least for the most extreme cases. Significant negative relationships were found between S and summer vapour pressure deficit and maximum summer temperature. Although preliminary, our results confirm previous suggestions about climatic effects on Scots pine leaf/sapwood area ratios by enlarging the analysis to a wider range of European sites and by including genetic variability across stands.
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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".