Migratory life histories explain the extreme egg-size dimorphism of<i>Eudyptes</i>penguins
Bibliographic record
Abstract
When successive stages in the life history of an animal directly overlap, physiological conflicts can arise resulting in carryover effects from one stage to another. The extreme egg-size dimorphism (ESD) of Eudyptes penguins, where the first-laid A-egg is approximately 18-57% smaller than the second-laid B-egg, has interested researchers for decades. Recent studies have linked variation in this trait to a carryover effect of migration that limits the physiology of yolk production and egg sizes. We assembled data on ESD and estimates of migration-reproduction overlap in penguin species and use phylogenetic methods to test the idea that migration-reproduction overlap explains variation in ESD. We show that migration overlap is generally restricted to Eudyptes relative to non-Eudyptes penguins, and that this overlap (defined as the amount of time that egg production occurs on land versus at sea during homeward migration) is significantly and positively correlated with the degree of ESD in Eudyptes In the non-Eudyptes species, however, ESD was unrelated to migration overlap as these species mostly produce their clutches on land. Our results support the recent hypothesis that extreme ESD of Eudyptes penguins evolved, in part, as a response to selection for a pelagic overwinter migration behaviour. This resulted in a temporal overlap with, and thus a constraint on, the physiology of follicle development, leading to smaller A-egg size and greater ESD.
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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 | 0.001 |
| 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".