Population Dynamics of the Western Tent Caterpillar: The Roles of Fecundity, Disease and Temperature
Bibliographic record
Abstract
Many populations of forest Lepidoptera exhibit regular periodic cycles in abundance. Explicit mechanisms for such dynamics however, remain a subject of debate in Ecology. I used annual field data (1977-2015) from a cyclical species of forest Lepidoptera native to southwestern B.C., the western tent caterpillar (Malacosoma californicum pluviale), to elucidate how fecundity, viral disease and temperature contribute to its dynamics. Using time-series analysis and relationships between lagged population density, disease prevalence and annual population growth rate, I demonstrated that cyclical dynamics can be generated. I then used AIC model selection to show that fecundity and lagged population density had the greatest contributions to annual population rate of increase, followed by disease prevalence and warmer spring temperatures during larval development. Using these factors, I constructed a population model capable of generating population cycles similar to those observed in the field. These results indicate that fecundity, density-dependent disease prevalence and temperature contribute significantly to the cyclical dynamics of these populations.
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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 | 0.000 | 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) | 0.000 | 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".