Forest tent caterpillar (Lepidoptera: Lasiocampidae) across Canada, 1938–2001: II. Emergent periodicity from asynchronous eruptive anomalies
Bibliographic record
Abstract
Abstract Using aerial sketch map data spanning more than 1 000 000 km2 across Canada, I use cluster analysis to show that outbreaks of forest tent caterpillar, Malacosoma disstria Hübner (Lepidoptera: Lasiocampidae), through the 20th century have occurred regularly every decade or so; however, there are two distinct aspects to the patterning of outbreaks. The dominant mode of variability is a nonrecurring pattern of singular spike anomalies, lasting just a few years, that are regional in extent but are not synchronised across the country. The regional time series derived from cluster analysis that are dominated by these singular spike eruptions exhibit extreme skewness and kurtosis, are not stationary in mean or variance, and are not amenable to classical time-series analysis. Although these regional-scale eruptive anomalies tend to occur periodically in aggregate, their central location always varies in an unpredictable manner, resulting in aperiodic local behaviour. Range-wide periodicity is thus an emergent property from asynchronous, aperiodic eruptions aggregated across regions. The second mode of variability is a low-amplitude fluctuation of weak periodicity that is weakly synchronised across the country. These observations support a hybrid cyclic–eruptive theory of outbreak occurrence that is not consistent with the simpler idea of spatially synchronised cycling.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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".