Influence of Partial Cutting on Parasitism of Endemic Spruce Budworm (Lepidoptera: Tortricidae) Populations
Bibliographic record
Abstract
Silvicultural treatments such as thinning have been suggested as management tools against the spruce budworm, Choristoneura fumiferana (Clemens) (Lepidoptera: Tortricidae). Among other things, parasitoids are also proposed to be influenced by silvicultural procedures, but the effect of thinning on spruce budworm's natural enemies has not been tested yet. In this study, the influence of partial cutting on parasitism of endemic spruce budworm populations has been investigated in mature balsam fir-white birch forests. Two intensities of partial cutting (25 and 40% stand basal area reduced) were conducted in 2009 and parasitism of introduced spruce budworm larvae and pupae was determined during the 3 yr after these treatments. Pupal parasitism was too low for comparison between treatments. However, 2 yr after treatments, parasitism of the fourth- and fifth-instar larvae was significantly reduced in plots with both intensities of partial cutting, which was attributed to the parasitoid Tranosema rostrale (Brischke). Three years after treatments, no significant influence of partial cutting on parasitism of spruce budworm larvae was found. This study suggests that the influence of partial cutting on parasitism of endemic spruce budworm populations is not consistent, but that under certain circumstances parasitism is reduced by partial cutting.
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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 | 0.000 | 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".