Stand structure governs the crown collisions of lodgepole pine
Bibliographic record
Abstract
We investigated tree sway and crown collision behavior of even-aged lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) stands of different structure in Alberta, Canada, to examine how these factors might affect loss of leaf area as stands mature. The Two Creeks stand (TC) had high density and slender trees, while the Chickadee stand (CH) had stout trees. The TC stand was then thinned (TCT) to reduce the stand density. For each stand, simultaneous tree sways of a group of 10 trees were monitored with biaxial clinometers during wind speed of 5 m/s (canopy top). Crown collisions were reconstructed by combining sway displacement of individual trees with their respective crown dimensions. Comparing the sway statistics between stands with contrasting mean bole slenderness (TC and CH) indicated that more slender trees have greater sway displacements, faster sway speeds, and a greater depth of collision. Disturbance by thinning increased sway displacements, sway speeds, and depth of collisions at TCT. Tree sway patterns were circular in shape and not aligned with wind direction, but patterns were elongated after thinning. This demonstrates the high frequency of crown collision experienced by stands with slender trees and supports the notion that crown collisions result in empty space between crowns of trees.
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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 | 0.001 |
| 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".