Effect of cutting intensity on microenvironmental conditions and regeneration dynamics in yellow birch – conifer stands
Bibliographic record
Abstract
This paper presents the 5 year results of different cutting intensities (removal of 0%, 40%, 50%, 60%, and 100% of the basal area) applied in two mixed yellow birch ( Betula alleghaniensis Britt.) – conifer stands of eastern Quebec, Canada. Two sites 90 km apart were used: Armagh and Duchesnay. Each site had four replicates of the treatments in a randomized block design. The effect on light availability was similar in the two sites: the 0%, 40%, 50%, 60%, and 100% cuts transmitting a mean of 5%, 21%, 26%, 30%, and 94% of full light, respectively, during the first summer. Soil temperature increased only in the 100% cut (4−5 °C, maximum daily temperature). Soil disturbance during harvest was higher at Duchesnay than at Armagh, which clearly improved seedbed receptivity, particularly to yellow birch. After 5 years, treated areas contained 21 000 to 48 300 seedlings/ha at Duchesnay compared with 5500 – 10 500 seedlings/ha at Armagh. Significant losses of coniferous advance growth were observed at both sites, but a subsequent seedling recruitment occurred only at Duchesnay. Red spruce ( Picea rubens Sarg.) showed superior establishment in the 60% cut (4400 seedlings/ha) than under other cutting intensities (1600–2100 seedlings/ha), whereas balsam fir ( Abies balsamea (L.) Mill.) responded well to all partial cutting treatments. At both sites, pin cherry ( Prunus pensylvanica L.f.) was the main competing species in the 100% cut, whereas densities of the preestablished mountain maple ( Acer spicatum Lamb.) and striped maple ( Acer pensylvanicum L.) either remained the same or increased in the partial cuts.
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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 | 0.000 |
| 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".