Sprucing up the mixedwoods: growth response of white spruce (<i>Picea glauca</i>) to partial cutting in the eastern Canadian boreal forest
Bibliographic record
Abstract
Mixed-species stands present a number of opportunities for and challenges to forest managers. Boreal mixedwood stands in eastern Canada are often characterized by a dominant canopy of shade-intolerant aspen (Populus tremuloides Michx.) with more shade-tolerant conifers in the mid- to sub-canopy layers. Because the aspen and conifer components often attain optimal merchantable sizes at different moments in stand development, there is an interest in developing silvicultural practices that allow partial or total removal of aspen and favour accelerated growth of residual conifers. We tested four partial harvesting treatments in mixed aspen – white spruce (Picea glauca (Moench.) Voss) stands in which different proportions of aspen (0%, 50%, 65%, and 100% basal area) were removed. Ten years after treatments, 72 spruce stems representing dominant, co-dominant, and suppressed social classes were destructively sampled for stem analysis. Using linear mixed effect models, we analyzed growth as a function of treatment intensity, time since treatment, social status, pretreatment growth rate, and neighbourhood competition. Relative to control stands, radial and volume growth responses were detected only in the extreme treatment of 100% aspen removal. In relative terms, suppressed trees showed the greatest magnitude of cumulative growth increase. Compared with control trees, average annual radial and volume increments were, respectively, 23.5% and 7.1% higher for dominant trees, 67.7% and 24.1% higher for co-dominant trees, and 115.8% and 65.6% higher for suppressed trees over the 10 years after treatment. Growth response was proportional to pretreatment growth rate, and among neighbouring trees, only coniferous neighbours had a negative effect on white spruce growth. Our results suggest that in similar mixed-stand conditions, relatively heavy removal of overstory aspen accompanied by thinning of crowded conifers would result in greatest growth response of residual spruce stems.
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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) | 0.000 | 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 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".