Effects of precommercial thinning on the forest value chain in northwestern New Brunswick: Part 3 – Incidence of root and butt decay
Bibliographic record
Abstract
The Green River precommercial thinning (PCT) trials were established between 1959 and 1961 in naturally regenerating balsam fir (Abies balsamea [L.] Mill.)-dominated stands an average of eight years after overstory removal. Three nominal spacings of 4 ft (1.2 m), 6 ft (1.8 m) and 8 ft (2.4 m) were compared to an unthinned control in six replicate blocks. In the fall of 2008, following completion of the ninth sequential evaluation of the study’s 48 permanent sample plots, three of the six replicates were clearcut harvested; butt rot data were collected immediately afterwards. To date, forest management research and goals have focused on the benefits of PCT, such as increased tree size and merchantable volume, shorter rotation ages, and better stem form and uniformity. Comparatively little attention has been placed on negative aspects of PCT, such as the incidence and development of root and butt rots, and their impact on fibre yields and wood product values. Results from the Green River study provide evidence that PCT may increase the incidence of butt rot in balsam fir, with incidence proportional to thinning intensity (p < 0.01). We also observed incidence and volume of butt rot to increase with stem diameter (p ≤ 0.05). The experiment suggests that factors such as stand age at time of thinning, and age at the time of harvest are important considerations when it comes to mitigating the impacts of butt rot through forest management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".