Regeneration response of tolerant hardwoods to beech bark disease vegetation management
Bibliographic record
Abstract
Beech bark disease (BBD) is the most significant natural disturbance affecting the Bancroft Minden Forest (BMF) and other forests across central Ontario. As a response to mortality from BBD or root injuries from harvesting, beech trees regenerate at a quicker rate than other species as they are very shade tolerant and can reproduce asexually from root or stump sprouts or sexually from a parent tree. The dominant regeneration of beech will affect the future composition of the forest as it makes it difficult for more valuable species to regenerate. Several vegetation management treatments are available to remove understory regeneration and mitigate root sprouts, such as mechanical treatments and chemical treatments. This study aims to determine which vegetation management treatment, between a mechanical brush saw treatment and a basal bark application of the herbicide triclopyr, is more effective six years after treatments were applied. Our results show that six years after treatments were applied, there is no significant difference between the two treatments amongst the large beech regeneration. However, the basal bark application of triclopyr may be a more effective long term treatment than the brush saw when looking at the small and medium regeneration size classes likely due to the increased sprouting response after mechanical treatments. We also aim to determine if these treatments had an effect on the regeneration of more desirable species such as sugar maple. We found no evidence that the treatments had any effect on sugar maple regeneration.
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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 | 0.000 | 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) | 0.001 | 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".