Hydraulic limitations and water-use efficiency in <i>Pinus pinaster</i> along a chronosequence
Bibliographic record
Abstract
Hydraulic constraints to water transport and water-use efficiency were studied in a Pinus pinaster Ait. chronosequence in Italy, consisting of four even-aged stands ranging from young (10 years old) to mature (75 years old), to explore the mechanisms involved in the decline of stand productivity as tree grow taller. Leaf-specific transpiration was estimated from sapflow rates measured by the heat dissipation technique, leaf-specific hydraulic conductance was computed from the slope of the relationship between transpiration and leaf water potential, long-term water-use efficiency was estimated from carbon isotope discrimination (Δ13C) in xylem cores, and photosynthetic capacity was assessed from CO2 assimilation/CO2 intercellular concentration curves. Leaf-specific transpiration decreased with stand development, suggesting a reduction in stomatal conductance, and a negative relationship was found between leaf-specific hydraulic conductance and tree height, suggesting a role of hydraulic constraints in the decline of current annual increment. Minimum daily leaf water potential did not change with stand height, suggesting that homeostasis in leaf water potential is achieved through a reduction in leaf transpiration. The Δ13C values increased with stand development, indicating a decline of water-use efficiency. Leaf level stomatal conductance was higher in the younger stand; no significant difference in maximum carboxylation rate was found among 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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".