The effects of various site preparation treatments on the control of Alnus incana and forest regeneration in boreal forests of Western Quebec, Canada
Bibliographic record
Abstract
Our study, conducted in the mixed boreal forest of western Quebec, Canada, assessed the effectiveness of various site preparation treatments to promote black spruce ( Picea mariana (Mill.) BSP) regeneration on wet sites invaded by speckled alder ( Alnus incana subsp. rugosa (du roi) R.T. Clausen) following harvest. In 2019, four treatments were established: scalping, mulching, soil inversion, and an untreated control. Black spruce seedlings were planted in 2020. Measurements taken in 2021, at the end of the second growing season, revealed that the treatments doubled the growth and size of seedlings compared to the control group. While differences were small, seedlings in mulched plots showed significantly greater height growth and annual shoot elongation compared to those in inverted plots. The treatments also reduced competing species cover, while promoting the presence of grasses. Environmental conditions and soil properties did not vary significantly between treatments and the control group, except for pH and potassium in some cases. These results suggest that all three site preparation treatments tested are effective in establishing black spruce regeneration on wet sites invaded by speckled alder. Long-term monitoring is needed to assess the economic impact of treatments and better understand the role of alder in nitrogen availability on treated sites.
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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".