Managing succession in conifer plantations: converting young red pine (<i>Pinus resinosa</i> Ait.) plantations to native forest types by thinning and underplanting
Bibliographic record
Abstract
The effects of thinning on growth and survival of white pine (Pinus strobus L.), white ash (Fraxinus americana L.), and red oak (Quercus rubra L.), and understory plant diversity were examined in a young red pine (Pinus resinosa Ait.) plantation. Five years after thinning, seedling diameter, height, and stem volume were positively correlated with thinning intensity and the size of canopy openings. Percent survival did not differ among thinning treatments, but was significantly higher in white ash and white pine than red oak. Understory vegetation included 113 species, with species richness increasing with thinning intensity and proximity to neighbouring plant communities. Thinning to create relatively large canopy openings in combination with underplanting can promote the natural succession of young pine plantations to native forest species. Keywords: direct seeding, plant diversity, natural regeneration, red oak, restoration, white ash, white pine
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".