Radial growth response of black spruce roots and stems to commercial thinning in the boreal forest
Bibliographic record
Abstract
Black spruce is one of the most important boreal tree species in Canada. In the current ecosystem-based management context, commercial thinning (CT) could be a sound choice for attaining sustainable forest management while still achieving maximum returns on competitive timber markets. Through stand density regulation, CT aims to increase tree growth and enhances stand productivity, but the pattern and level of treatment responses are still unknown. This study examined the radial growth response of roots and stems to CT in 10 thinned stands and their controls. A split-plot unbalanced model was developed to describe growth variations over time. The study shows that CT leads to an increase in the radial growth of stems and roots for at least 10 years after the treatment. The 10-year post-treatment radial growth increment of stems is from 20 to 100 per cent higher than the pre-treatment 10-year mean growth. Response depends upon tree diameter and competition, with the biggest trees exhibiting the lowest response to the treatment. Nevertheless, these variables only explain a fraction of the response (R2 = 0.0511), suggesting that much of the observed variation may be due to variability between the stands and between trees within a stand. Moreover, stem growth response is correlated with, but lags behind root growth response. This study suggests that CT results may be enhanced by the selection of retained trees based on initial diameter at breast height.
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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 | 0.005 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".