Forest tent caterpillar (Lepidoptera: Lasiocampidae) across Canada, 1938–2001: I. Periodic outbreaks; episodic impacts
Bibliographic record
Abstract
Abstract I review the history of forest tent caterpillar, Malacosoma disstria (Hübner) (Lepidoptera: Lasiocampidae), occurrence from 1938 to 2001 throughout Canada, with emphasis on the insect’s impact on tree mortality. I show that forest tent caterpillar routinely kills a portion of its host tree population during outbreaks. Although the proportion killed is typically small, there are some unusual conditions during which the foliage grazer can precipitate large-scale host forest declines. These decline episodes are the result of a spatially complex pattern of outbreak spread whereby successive cycles occur asynchronously enough that there is a zone of overlap where the two cycles occur in rapid succession, leading to three to six years of defoliation, triggering a nonlinear mortality response that endures through time. One of these “cycles” is typically amplified locally to an intensity that is anomalously high and nonrecurring. Defoliation events that are periodic in aggregate may thus give rise to patterns of insect-caused forest decline that are episodic. These decline events have been shifting northwards over time and have been growing in extent. The dynamics of outbreak occurrence appears to be a complex result of interacting top–down and bottom–up forces, making it challenging to predict in advance whether or not any given outbreak will exceed the threshold required to precipitate large-scale mortality.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| 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".