Artificial Regeneration of Hardwoods in Early Successional Shrub Communities Using Two Clearing Intensities and Herbicide Application
Bibliographic record
Abstract
Abstract In southern Quebec, returning abandoned farmland to forest production presents a management opportunity. The shrub communities, which naturally colonize abandoned agricultural land, could be enriched by planting hardwood species that occurred in the precolonial forests. This study examines the growth of four hardwood species (Acer saccharum, Fraxinus americana, Prunus serotina, and Juglans nigra) planted on former pastures now covered by shrubby vegetation. Retaining part of this shrubby vegetation may produce improved growth in the planted trees. The experimental plantations were established in 1998 in two sites with different soil conditions and consisted of various treatments to control competition. Analyses seek to determine the effect of these treatments on (i) the light conditions, (ii) the cover of competing vegetation, and (iii) the growth and vigor of planted trees. Results show that increasing shrub clearing intensity has reduced the cover of tall competing vegetation after 5 years. However, light conditions and the cover of low competing vegetation around planted trees no longer vary significantly among treatments after 5 years. Strip clearing (SC) improved the growth of white ash and total clearing improved the growth of black walnut, with respect to site considered. Herbicide use was beneficial for the majority of species. SC presents a useful alternative for hardwood plantations. However, low competing vegetation control remains an important factor for increasing planted tree productivity in these managed shrub communities.
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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".