Strouhal and Reynolds number scaling of force production in the Mountain Pine Beetle
Bibliographic record
Abstract
The Mountain Pine Beetle, Dendroctonus ponderosae Hopkins (Coleoptera: Curculionidae: Scolytinae), a destructive pest found in the pine forests of Western North America, has exhibited range expansion and unprecedented population growth due to climate change. As this insect disperses by flight, understanding its flight mechanics may help to model and predict its rate of spread through the environment. In this work, aerodynamic scaling relationships—previously identified in idealized, predominantly two-dimensional and numerical cases—are applied to the case of live flight. In particular, this aims to improve the statistical confidence in predicting sex and age differences in flight performance, which have historically been analyzed in ecology using dimensional quantities. Thrust coefficient is found to scale with the square of Strouhal number, as has been found in prior studies. However, with respect to Reynolds number, scaling was with the inverse of Reynolds number, rather than the inverse of the square root. We demonstrate here that the established Strouhal number and Reynolds number scaling of force coefficient can be successfully extended not just to highly three-dimensional flows, and lower Reynolds number flows, but remains robust even across distinct individuals within a population of beetles. Using this scaling, we observe that males fly with a greater mean thrust coefficient and Strouhal number compared to females (p < 0.001), which is a significant improvement in statistical confidence over prior studies, which could not identify a major difference between sexes (p > 0.05). Meanwhile, there is also a significant difference in thrust coefficient between different age cohorts, with younger beetles exhibiting a lower magnitude than other age groups (p < 0.05).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".