Got milkweed? Genetic assimilation as potential source for the evolution of nonmigratory monarch butterfly wing shape
Bibliographic record
Abstract
Monarch butterflies (Danaus plexippus) are well studied for their annual long-distance migration from as far north as Canada to their overwintering grounds in Central Mexico. At the end of the cold season, monarchs start to repopulate North America through short-distance migration over the course of multiple generations. Interestingly, some populations in various tropical and subtropical islands do not migrate and exhibit heritable differences in wing shape and size, most likely an adaptation to island life. Less is known about forewing differences between long- and short-distance migrants in relation to island populations. Given their different migratory behaviors, we hypothesized that these differences would be reflected in wing morphology. To test this, we analyzed forewing shape and size of three different groups: nonmigratory, lesser migratory (migrate short-distances), and migratory (migrate long-distances) individuals. Significant differences in shape appear in all groups using geometric morphometrics. As variation found between migratory and lesser migrants has been shown to be caused by phenotypic plasticity, and lesser migrants develop intermediate forewing shapes between migratory and nonmigratory individuals, we suggest that genetic assimilation might be an important mechanism to explain the heritable variation found between migratory and nonmigratory populations. Additionally, our research confirms previous studies which show that forewing size is significantly smaller in nonmigratory populations when compared to both migratory phenotypes. Finally, we found sexual dimorphism in forewing shape in all three groups, but for size in nonmigratory populations only. This might have been caused by reduced constraints on forewing size in nonmigratory 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".