Maximum Branch Diameter in Black Spruce Following Partial Cutting and Clearcutting
Bibliographic record
Abstract
Branch diameter is an important aspect of wood quality, as lumber grades can be determined based on the maximum diameter of branches. Crown and branch development can be influenced by the environment surrounding the trees, and silvicultural interventions, which reduce stand density and increase the growth of residual trees, could therefore alter branch properties. We evaluated maximum branch diameter within the crown of residual black spruce (Picea mariana (Mill.) B.S.P.) subjected to five types of silvicultural intervention—three partial-cutting and two clearcutting treatments—as well as trees within unmanaged control stands. We sampled a total of 41 stands and 223 trees. We collected 15 whorls from the live crown of each tree and measured the diameters of the largest branches. For all treatments, we observed a curvilinear relationship between maximum branch diameter and distance from the stem apex, and the largest branches were located in the lower third of the live crown. DBH before treatment and treatment were the variables that best explained maximum branch diameter in the lowest portion of the crown. A generalized additive model showed that maximum branch diameter in black spruce following silvicultural treatment will not differ significantly from trees of unmanaged control stands. Therefore, the studied partial cutting and clearcutting treatments do not have adverse effects on maximum branch diameter when compared to unmanaged control stands. However, DBH prior to treatment must be considered before any treatment is applied in forest management operations if maximum branch diameter is an important wood quality factor at the time of the final harvest of the stands.
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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) | 0.001 | 0.001 |
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".