Long-term effects of spruce budworm outbreak and insecticide protection on forest recovery and structure in Eastern Quebec
Bibliographic record
Abstract
Insect outbreaks can significantly alter forest structure through tree mortality. While surviving trees often exhibit growth release, overall productivity may still decline. Aerial insecticide applications have been widely used in Canada to mitigate spruce budworm ( Choristoneura fumiferana) impacts, though their long-term effects remain poorly understood. This study assessed the long-term impacts of the 1967–1992 outbreak, 12 years after its collapse, in protected and unprotected mixed forests in Eastern Quebec. We evaluated growth release at tree- and stand-levels, stand recovery duration, structural changes, and the influence of spraying. We remeasured 78 permanent 500 m 2 plots, recording DBH for all commercial species ≥10 cm and classifying stems as alive or dead. Growth losses were assessed via stem analysis. Balsam fir ( Abies balsamea) mortality was significantly higher in poorly protected plots (45.33%–57.11%) compared to well-protected ones (<25%). Surviving trees showed growth release across treatments, but only average- or well-protected plots had improved productivity and faster recovery. Poorly protected plots showed higher mortality, limited recovery, and more pronounced thinning effects compared to well-protected plots, with smaller trees most affected. The outbreak caused growth losses equal to 16 years for balsam fir, highlighting the need to prioritize this species in protection programs.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".