Trembling Aspen Removal Effects on Lodgepole Pine in Southern Interior British Columbia: Ten-Year Results
Bibliographic record
Abstract
Abstract Manual cutting treatments are routinely applied to release lodgepole pine (Pinus contorta var. latifolia Engelm.) from trembling aspen (Populus tremuloides Michx.) competition in southern interior British Columbia. We studied the effects of this treatment on pine and an aspen-dominated community on three sites in the Interior Douglas-Fir and Montane Spruce biogeoclimatic zones. After 10 years, when stands were 17–20 years old, treated aspen was significantly shorter than control aspen, and treated pine had significantly (21%) larger diameter than control pine. There were few other differences between brushed and unbrushed pine, and survival was excellent (≥97%), regardless of treatment. Brushing nearly doubled the average density of conifer stems that were free-growing according to legislated standards, but results were variable, and the free-growing status of the stand was changed on only one site. Regression analysis was used to examine the correlation between aspen abundance and pine size. The density of aspen at least as tall as the pine (tall aspen) predicted 36.2% of the variation in pine diameter, and total aspen density predicted 35.9% of the variation in pine height. An average density threshold of 1,867 tall aspen stems/ha, above which pine stem diameter declined, was identified in the three 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".