Crown allometry and application of the pipe model theory to white spruce (<i>Picea glauca</i> (Moench) Voss) and aspen (<i>Populus tremuloides</i> Michx.) in the western boreal forest of Canada
Bibliographic record
Abstract
White spruce (Picea glauca (Moench) Voss) and aspen (Populus tremuloides Michx.) from unmanaged stands in the boreal forest of Alberta, Canada, were examined for two of the main structural assumptions in the process-based model CROBAS: (i) a constant allometric relationship between foliage mass and crown length and (ii) a constant relationship between foliage mass and sapwood area. We evaluated these relationships at both at the whole-crown and within-crown levels. Results indicated that for both species, a constant allometric relationship between foliage mass and crown length was maintained at the whole-crown level over a period exceeding the peak mean annual increment of each species. Within the crowns of spruce, foliage mass accumulated faster near the tree apex as total crown length increased. For aspen, the increase in foliage mass per unit crown length for any section within the crown showed greater similarity to the relationship observed at the whole-crown level. The assumption of a constant relationship between foliage mass and sapwood area at the crown base generally held for spruce but showed considerable variation for any given diameter class. For aspen, this assumption did not appear to be appropriate. For both species, there was more foliage mass per unit sapwood area with increasing height from the ground for nearly all tree size classes. This latter finding was in conflict with the pipe model theory but could not be explained by the hydraulic theory of crown architecture, which predicts a decrease in the ratio of foliage mass to sapwood area with increasing path length.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".