Conifer response to three silvicultural treatments in the Oregon Coast Range foothills
Bibliographic record
Abstract
This study assessed growth, condition, and mortality of residual trees one decade after harvest across three silvicultural treatments in thirty 85- to 125-year-old Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) stands in the Oregon Coast Range foothills. Group-selection cuts had 33% of the entire stand volume extracted as patches approximately 0.20.8 ha in size; two-story regeneration harvests had 75% of the volume extracted, and 2030 residual trees/ha were left; clearcuts had all trees removed, except for 1.2 trees/ha. One decade after harvest, tree basal area, diameter, and height growth, and crown width and fullness did not differ between silvicultural treatments. In contrast, live crown ratio was largest in clearcuts (0.74), and the proportion of trees with epicormic branching was highest in two-story stands (35%). Overall, 45% of trees had more basal area growth in the decade after harvest than in the previous decade. Residual green trees in clearcuts and group-selection stands experienced the highest and lowest percentage mortality, respectively (30.6% vs. 0.2%). Our results reflect little differentiation in the characteristics of trees growing under three silvicultural conditions one decade after harvest. However, percent residual green tree mortality increased with increasing harvest intensity.
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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".