A partial deciduous canopy, coupled with site preparation, produces excellent growth of planted white spruce
Bibliographic record
Abstract
Survival and growth of planted white spruce (Picea glauca (Moench) Voss) were assessed at year 15 in boreal mixedwood stands of northern Alberta, Canada, in stands that were deciduous-dominated prior to logging or were conifer-dominated. Three overstory retention levels (0%, 50%, and 75% retention) and four site preparation treatments (mound, high speed mix, scalp, and no treatment) were evaluated. In deciduous-dominated stands, planted spruce performed best in the 50% retention; here, stem volume was at least double that of any other retention treatment after 15 years. In contrast, spruce had reduced growth in coniferous-dominated stands in both 50% and 75% retention treatments compared with the 0% retention. Survival of planted spruce was unaffected by level of retention, but survival was lower in coniferous-dominated stands than in deciduous-dominated stands; in the coniferous-dominated stands, survival was better with mounding and mixing and lowest with scalp treatments. All height variables tended to be greater in the mix and mound site preparation treatments. Finally, the best estimates of future total growth (regenerated spruce and deciduous combined) in the coniferous-dominated stands were in the clearcut treatment. In terms of regenerated spruce growth, the best estimates occurred in the deciduous-dominated – 50% retention stand planted with soil mixing–mounding treatments, where projected growth of spruce was comparable with that of open-grown and tended stands in Alberta’s boreal forests.
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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 | 0.001 | 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".