The canopy conductance of a boreal aspen forest, Prince Albert National Park, Canada
Bibliographic record
Abstract
Abstract Annual fluxes of canopy‐level heat, water vapour and carbon dioxide were measured using eddy covariance both above the aspen overstory (Populus tremuloides Michx.) and hazelnut understory (Corylus cornuta Marsh.) of a boreal aspen forest (53·629 °N 106·200 °W). Partitioning of the fluxes between overstory and understory components allowed the calculation of canopy conductance to water vapour for both species. On a seasonal basis, the canopy conductance of the aspen accounted for 70% of the surface conductance, with the latter a strong function of the forest's leaf area index. On a half‐hour basis, the canopy conductance of both species decreased non‐linearly as the leaf‐surface saturation deficits increased, and was best parameterized and showed similar sensitivities to a modified form of the Ball–Berry–Woodrow index, where relative humidity was replaced with the reciprocal of the saturation deficit. The negative feedback between the forest evaporation and the saturation deficit in the convective boundary layer varied from weak when the forest was at full leaf to strong when the forest was developing or loosing leaves. The coupling between the air at the leaf surface and the convective boundary layer also varied seasonally, with coupling decreasing with increasing leaf area. Compared with coniferous boreal forests, the seasonal changes in leaf area had a unique impact on vegetation–atmosphere interactions. Copyright © 2004 John Wiley & Sons, Ltd.
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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 | 0.001 | 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".