Resilience of uneven-aged mixedwood stands altered by diameter-limit cutting and opportunities for their rehabilitation
Bibliographic record
Abstract
Repeated diameter-limit cutting in mixedwood forests often leads to altered stand composition, quality, and regeneration, hence decreasing productivity and value over time. We studied the evolution of stand characteristics after diameter-limit cutting on a 15-year period, beginning from 11 to 43 years after cutting. We used 415 sample plots (200 m 2 ) and three criteria: (i) ≥9.0 m 2 /ha overstory (trees ≥9.1 cm dbh [diameter at breast height, 1.3 m above ground]) acceptable growing stock (AGS, i.e. basal area of vigorous trees with sawlog potential), (ii) ≥3.0 m 2 /ha pole timber AGS (9.1 cm-23.0 cm dbh) and (iii) ≥60% sapling (dbh 1.1-9.0 cm) stocking of desired species. Stand initial quality was determined in function of overstory AGS at the beginning of the monitoring period: good quality (AGS≥9.0 m 2 /ha), impoverished (7.0≤AGS< 9.0 m 2 /ha), degraded (AGS <7.0 m 2 /ha). After 15 years, 47% of stands satisfied at least two criteria, but most stands (65%) had insufficient sapling regeneration. Stands in good quality and impoverished categories had sufficient basal area and AGS to support a new partial cutting cycle, contrary to stands in the degraded category. A conceptual model based on these three criteria is presented to guide silvicultural rehabilitation of uneven-aged mixedwood stands altered by past cutting practices.
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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 | 0.001 |
| 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".