Can sexual selection drive female life histories? A comparative study on Galliform birds
Bibliographic record
Abstract
Sexual selection has been identified as a major evolutionary force shaping male life history traits but its impact on female life history evolution is less clear. Here we examine the impact of sexual selection on three key female traits (body size, egg size and clutch size) in Galliform birds. Using comparative independent contrast analyses and directional discrete analyses, based on published data and a new genera-level supertree phylogeny of Galliform birds, we investigated how sexual selection [quantified as sexual size dimorphism (SSD) and social mating system (MS)] affects these three important female traits. We found that female body mass was strongly and positively correlated with egg size but not with clutch size, and that clutch size decreased as egg size increased. We established that SSD was related to MS, and then used SSD as a proxy of the strength of sexual selection. We found both a positive relationship between SSD and female body mass and egg size and that increases in female body mass and egg size tend to occur following increases in SSD in this bird order. This pattern of female body mass increases lagging behind changes in SSD, established using our directional discrete analysis, suggests that female body mass increases as a response to increases in the level of sexual selection and not simply through a strong genetic relationship with male body mass. This suggests that sexual selection is linked to changes in female life history traits in Galliformes and we discuss how this link may shape patterns of life history variation among species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".