Does a Spruce Budworm Outbreak Affect the Growth Response of Black Spruce to a Subsequent Thinning?
Bibliographic record
Abstract
In Canada, new forestry practices are proposed for integrating forest management with the natural dynamics of tree growth and regeneration. In particular, the current spruce budworm (Choristoneura fumiferana (Clemens) outbreak in northeastern North America is forcing natural resource managers to clarify the potential interactions between natural disturbances and commercial thinning. The aim of this study was to investigate if and how the spruce budworm outbreak of the 1970s affected the responses of black spruce [Picea mariana (Mill.) B.S.P.] to a subsequent thinning. Stem growth was reconstructed by measuring and cross-dating chronologies of tree-ring width of 1290 adult trees from 34 control and thinned stands within an area of 11,000 km2 in the boreal forest of the Saguenay-Lac-Saint-Jean region (QC, Canada). The treatment consisted of a low thinning performed during 1995-1999 that removed 25-35% of the basal area. Segmented models were applied to the tree-ring chronologies to define the growth pattern during the outbreak and thinning periods within a time window of eight years. Trees showed abrupt growth decreases during the outbreak, with the tree-ring index showing minimum values in 1977-1979. The tree-ring index had a flat trend before thinning, while it increased for 6-10 years after thinning. The growth pattern during the outbreak period was characterized by a reduction, mainly in trees with larger tree rings, while slow-growing trees showed less sensitivity to the disturbance. Thinning produced a significant increase in tree growth. No relationship was found between the effects of spruce budworm outbreaks in trees and the changes in growth pattern after thinning. If the timespan between the two disturbances exceeds 7 years, partial cutting can be applied independently of the growth reductions that had occurred during the outbreak. When applied in black spruce stands with high annual radial growth, thinning is expected to optimize the volume growth of the residual trees.
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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 | 0.001 |
| 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 | 0.000 |
| 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".