Bibliographic record
Abstract
The hypothesis was tested that upper limits to height growth in trees are the result of the increasing bending moment of trees as they grow in height. The increasing bending moment of tall trees demands increased radial growth at the expense of height growth to maintain mechanical stability. In this study, the bending moment of large lodgepole pine (Pinus contorta Dougl. Ex Loud. var. latifolia Engelm.) was reduced by tethering trees at 10 m height to counter the wind load. Average bending moment of tethered trees was reduced to 38% of control trees. Six years of tethering resulted in a 40% increase in height growth relative to the period before tethering. By contrast, control trees showed decreased height growth in the period after tethering treatment. Average radial growth along the bole, relative to height growth, was reduced in tethered trees. This strongly suggests that mechanical constraints play a crucial role in limiting the height growth of tall trees. Analysis of bending moment and basal area increment at both 10 m and 1.3 m showed that the amount of wood added to the stem was closely related to the bending moment produced at these heights, in both control and tethered trees. The tethering treatment also resulted in an increase in the proportion of latewood at the tethering height, relative to 1.3 m height. For untethered control trees, the ratio of bending stresses at 10 m versus 1.3 m height was close to 1 in both 1998 and 2003, suggesting a uniform stress distribution along the outer surface of the bole.
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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 | 0.000 | 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".