The role of advanced regeneration at time of partial harvest on tolerant hardwood stands development
Bibliographic record
Abstract
In tolerant hardwood forests of eastern North America, multiple-aged silvicultural systems rely on advanced regeneration to restock the forests. Evaluation of the long-term influence of advanced regeneration on the mature stand is critical for improving management practices. We used a retrospective approach to evaluate the influence of advanced regeneration present at the time of harvest on the current (2012) stand structure and the quality of the growing stock. The study was carried out in partially harvested stands in northwestern New Brunswick, Canada. Trees were sampled from stands with varying degrees of harvest intensities, times since harvest, and site characteristics. Pre-existing advanced regeneration contributed the bulk of trees in the 10–19 cm diameter class across the stands. In stands with low-intensity harvest, the overstory was dominated by sugar maple (Acer saccharum Marsh.) that originated as advanced regeneration. In stands with high-intensity harvest, however, yellow birch (Betula alleghaniensis Britt.) pre-existing advanced regeneration dominated the overstory. The probability of sugar maple and yellow birch being acceptable growing stock peaked at a diameter at breast height (DBH) of about 30–40 cm, while other species combined peaked at a DBH of around 20–25 cm. Our results suggest that harvest intensities based on the dominant advanced regeneration composition and harvesting systems that minimize the risk of physical damage to advanced regeneration are required to achieve partial harvesting objectives.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".