Precommercial thinning of trembling aspen in northern Ontario: Part 2 – Interactions with Hypoxylon canker
Bibliographic record
Abstract
Hypoxylon canker [Entoleuca mammata (Wahlenberg:Fr) J.D. Rogers and Y.-M. Ju] incidence and mortality were monitored in six northern Ontario trembling aspen (Populus tremuloides Michx.) stands following precommercial thinning. At each of the six sites, a randomized complete block design experiment was established with four replicates of five thinning levels (none, 2-, 3-, 4-, and 5-m spacing). At the time of thinning, three stands were five years old; the remaining were ages 10, 15, and 22. Over the 15- to 17-year observation period, Hypoxylon-related mortality increased to 6–9% by the end of the period, regardless of thinning age or density. Hypoxylon infection incidence (excluding mortality) also increased, to 2–6% in unthinned stands and 8–11% in thinned stands by year 15. No differences among the thinning levels were observed. Prevalence, infection expressed as a percentage of surviving trees, did not differ among thinned and unthinned stands. Mortality attributed to factors other than Hypoxylon was 31–44% in unthinned stands and 7–23% in thinned stands, with no significant differences among thinning levels. Trees dying of other causes were typically small in diameter and of more subordinate crown classes than survivors. In contrast, Hypoxylon-caused mortality was independent of tree size and canopy position. Results suggest that log size and stand yield may be manipulated through density regulation, without concern for interacting impacts associated with Hypoxylon canker. Models are provided for estimating disease losses; predictions can then be factored into the crop-planning process. Key words: trembling aspen, precommercial thinning, Hypoxylon canker, growth and yield, crop planning
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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 | 0.001 | 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".