Efficacy of insecticide aerial spraying programs to reduce tree mortality during a spruce budworm outbreak (1967–1992) in the province of Quebec
Bibliographic record
Abstract
Abstract Spruce budworm ( Choristoneura fumiferana ) is the most important pest of conifer forests in eastern North America. The main approach for protecting forests against this defoliator is aerial spraying of insecticides. Despite the crucial role of aerial insecticide applications in the global forest protection strategy, little is known about its real effects on tree mortality or the stand characteristics that may affect its long‐term efficacy. We evaluated the efficacy of the protection program that was implemented during the 1967–1992 outbreak in Quebec (Canada) in tree mortality reduction. We established 422 plots in eastern Quebec based upon the following parameters: insecticide application; stand composition; drainage quality; and stand age. Unprotected plots exhibited 18 to 44% greater tree mortality than protected plots. Insecticide efficacy was affected by drainage condition. Protected plots that established on sites with poor quality drainage exhibited 67.53% lower balsam fir ( Abies balsamea ) mortality than did unprotected plots. Stand age did not affect tree mortality. Insecticide application had no substantial effect on spruce mortality. Our study also found that the return on protection investment in terms of mortality reduction may decline after 7 years of aerial spraying, and that it is not necessary to achieve the target protection goal (50% foliage protection) every year to reduce host tree mortality. Our results may be useful for decision‐makers to decide where and when to apply insecticides during a spruce budworm outbreak and may help to determine the appropriateness of treating the forest on an annual basis depending upon the protection goals.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".