Sexual size dimorphism and timing of spring migration in birds
Bibliographic record
Abstract
Sexually selected traits are limited by selection against those traits in other fitness components, such as survival. Thus, sexual selection favouring large size in males should be balanced by higher mortality of larger males. However, evidence from red-winged blackbirds (Agelaius phoeniceus) indicates that large males survive better than small males. A survival advantage to large size could result from males migrating north in early spring, when harsh weather favours large size for energetic reasons. From this hypothesis we predicted that, among species, sex differences in body size should be correlated with sex differences in timing of spring migration. The earlier males migrate relative to females, the larger they should be relative to females. We tested this prediction using a comparative analysis of data collected from 30 species of passerine birds captured on migration. After controlling for social mating system, we found that sexual size dimorphism and difference in arrival dates of males and females were significantly positively correlated. This result is consistent with the hypothesis that selection for survival ability promotes sexual size dimorphism (SSD), rather than opposes SSD as is the conventional view. If both natural selection and sexual selection favour large adult males, then limits to male size must be imposed before males become adults.
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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 | 0.002 |
| 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".