Modeling Migratory Flight in the Spruce Budworm: Temperature Constraints
Bibliographic record
Abstract
We describe an individual-based model of spruce budworm moth migration founded on the premise that flight liftoff, altitude, and duration are constrained by the relationships between wing size, body weight, wingbeat frequency, and air temperature. We parameterized this model with observations from moths captured in traps or observed migrating under field conditions. We further documented the effects of prior defoliation on the size and weight (including fecundity) of migrating moths. Our simulations under idealized nocturnal conditions with a stable atmospheric boundary layer suggest that the ability of gravid female moths to migrate is conditional on the progression of egg-laying. The model also predicts that the altitude at which moths migrate varies with the temperature profile in the boundary layer and with time during the evening and night. Model results have implications for the degree to which long-distance dispersal by spruce budworm might influence population dynamics in locations distant from outbreak sources, including how atmospheric phenomena such as wind convergence might influence these processes. To simulate actual migration flights en masse, the proposed model will need to be linked to regional maps of insect populations, a phenology model, and weather model outputs of both large- and small-scale atmospheric conditions.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".