Timing of growth reductions in black spruce stem and branches during the 1970s spruce budworm outbreak<sup>1</sup>This article is one of a selection of papers from the 7th International Conference on Disturbance Dynamics in Boreal Forests.
Bibliographic record
Abstract
Spruce budworm ( Choristoneura fumiferana (Clemens)) defoliation is known to regularly produce radial growth decrease in black spruce ( Picea mariana (Mill.) Britton, Sterns & Poggenb.) in the boreal forest of Quebec. Some studies have already shown that the first year of defoliation does not induce growth losses in the stem but could occur in other tree parts. We therefore examined the timing and duration of the growth reduction caused by the last outbreak in black spruce by also considering the branches. More than 79% of branches and 65% of stems exhibited a >40% growth decrease.The reduction was first registered in the upper part of the stem before being detected lower in the stem in 87% of the trees. Probabilities of growth reduction in the upper part of the stem were highest in 1976 and 1977. In the lower stem, the probabilities were highest in 1978. An interesting finding was that in 69% of the studied stands, the probability of growth reduction started earlier (1–2 years) in the branches than in the stem at 1.3 m. Branch analysis should be considered whenever questions arise in regard to the evolution of spruce budworm defoliation as well as the timing of observed growth reduction in black spruce.
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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 | 0.001 | 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 | 0.000 |
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".