Effects of a forest tent caterpillar outbreak on the dynamics of mixedwood boreal forests of eastern Canada
Bibliographic record
Abstract
In boreal mixedwood stands dominated by trembling aspen (Populus tremuloides), forest tent caterpillar (Malacosoma disstria, FTC) outbreaks are recurrent events whose effects on stand dynamics are poorly documented. To describe and characterize the effects of FTC outbreaks, we assessed canopy opening, gap size, and understory tree recruitment in 12 stands dominated by trembling aspen that had experienced different levels of defoliation (in terms of severity and duration) during the last outbreak in northwestern Quebec (1999–2002). The study showed a significant increase in canopy opening and gap size with defoliation intensity. Furthermore, the proportion of large gaps and aspen mortality increased with defoliation intensity. Balsam fir (Abies balsamea) regeneration benefited from changes in canopy structure caused by the FTC, while aspen did not. Forest succession in mixedwood stands that had been defoliated for 1 y was not profoundly affected, while multiple years of defoliation likely caused more rapid canopy transition from aspen to fir. By creating a variety of gaps, FTC outbreaks modify stand structure in ways that differ from succession to coniferous dominance controlled by single-stem exclusion.
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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 | 0.001 | 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".