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 to protect Quebec forests against this defoliator is aerial spraying of insecticides. Despite the crucial role of aerial spraying of insecticides in the global forest protection strategy, little is known about its real impact on tree mortality reduction or the stand characteristics that may affect its long-term efficacy. We evaluate the efficacy of the protection program implemented between 1967 and 1992 in reducing tree mortality during the previous outbreak in Quebec and how its efficacy is affected by stand characteristics such as drainage quality and stand age. We established 422 plots in Eastern Quebec based on the following parameters: insecticide application (0-13 years), stand composition, drainage quality, and stand age at the beginning of the previous outbreak. Our results show that unprotected plots exhibited in average between 18 and 32.6% higher mortality than protected plots. Insecticide efficacy was affected by drainage quality. For example, protected plots established on sites with bad drainage quality exhibited 49% less balsam fir mortality than unprotected plots. Furthermore, immature and mature protected stands exhibited a similar reduction in balsam fir mortality (32.2 and 32.1% less mortality respectively) compare to unprotected stands. Our results may be useful for decision-makers not only to decide where and when apply insecticides during a spruce budworm outbreak but also, they may help to determine the pertinence of continuous protection during longer than usual outbreaks depending on protection goal.
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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".