Variation in Forewing Size Linked to Migratory Status in Monarch Butterflies
Bibliographic record
Abstract
Abstract Long-distance migration can be seen throughout the animal kingdom and can have large impacts on population dynamics and species distributions. The act of migration itself also affects the evolution of a species, as evolutionary forces select for certain characteristics in animals conducting long-distance migration. Monarch butterflies are best known for their annual migration from Canada and the northern United States to central Mexico, but some populations of monarchs have lost the ability to migrate. Previous research found that migratory monarchs had larger, more elongated wings than their non-migratory counterparts and it was hypothesized that these traits were beneficial for migration. However, Bergmann’s rule - which predicts larger body sizes with increasing latitude - could also explain this pattern as migratory populations are found at higher latitudes. To understand the role of wing dimensions in migration, we examined forewing size and shape of migratory and non-migratory monarchs from seven worldwide populations varying in latitude. Results showed that larger forewing size was indeed correlated with migratory status rather than latitude. However, migratory monarchs did not have more elongated forewing shape than non-migratory monarchs across the globe. Our study indicates that size may play a larger role than shape in long-distance migratory capability.
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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 | 0.001 | 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) | 0.001 | 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".