Contrasting effects of season and method of harvest on soil properties and the growth of black spruce regeneration in the boreal forested peatlands of eastern Canada
Bibliographic record
Abstract
It has been suggested that without sufficient soil disturbance, harvest in boreal forested peatlands may accelerate paludification and reduce forest productivity. The objectives of this study were to compare the effects of harvest methods (clearcutting vs. careful logging) and season (summer vs. winter harvest) on black spruce regeneration and growth in boreal forested peatlands of eastern Canada, and to identify the soil variables that favour tree growth following harvest. Moreover, we sought to determine how stand growth following harvest compared with that observed following fire. The average tree height of summer clearcuts was greater than that of summer carefully logged stands and that of all winter harvested sites. Summer clearcutting also resulted in a higher density of trees > 3 m and > 4 m tall and in a 50% reduction in Rhododendron groenlandicum cover, a species associated with reduced black spruce growth. Height growth of sample trees was related to foliar N and P concentrations, and to soil total N, pH and available Ca and Mg but not to harvest method or season. Our results also indicate that summer clearcutting could produce stand productivity levels comparable to those observed after high-severity soil burns. These results suggest that summer clearcutting could be used to restore forest productivity following harvest in forested peatlands, and offer further support to the idea that sufficient levels of soil disturbance may be required to restore productivity in ecosystems undergoing paludification.
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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".