Top-down trophic interactions related to forest tent caterpillar outbreaks in temperate hardwood and boreal mixed-wood forests in Quebec
Bibliographic record
Abstract
This thesis aims to investigate different trophic interactions related to the outbreaking cycles of the forest tent caterpillar (Malacosoma disstria Hübner, Lepidopter:Lasiocampidae), both top-down and bottom-up, in the two types of forests, the boreal and the temperate. Throughout field studies, we determined that forest tent caterpillar early-instar larvae were more susceptible to mortality due to pathogens and maternal effects in years after the outbreak than to predators. These results suggest delayed density dependence and contribute to low endemic levels between outbreak peaks. We also investigated the overwintering mortality of forest tent caterpillars at the egg stage. While larger egg masses tended to promote survival, this factor was not the only significant predictor. Mortality was also related to average winter temperature variation and cold spells. With increasingly unpredictable \nclimate patterns, both factors could cause high mortality levels during the winter. Finally, with the high amount of organic material released during the outbreaks, we investigated the impact on potential predators, such as ants. We observed a shift in ant communities in the boreal forest but not in temperate forests, suggesting that disturbances caused by the forest tent caterpillar can alter less ecologically complex and redundant ecosystems. Forest tent caterpillars are important disturbance agents and participate in multiple trophic interactions during outbreaks, cementing the importance of a better understanding of their population dynamics.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".