EXTRA-PAIR PATERNITY AND THE VARIANCE IN MALE FITNESS IN SONG SPARROWS (<i>MELOSPIZA MELODIA</i>)
Bibliographic record
Abstract
The variance in fitness across population members can influence major evolutionary processes. In socially monogamous but genetically polygynandrous species, extra-pair paternity (EPP) is widely hypothesized to increase the variance in male fitness compared to that arising given the socially monogamous mating system. This hypothesis has not been definitively tested because comprehensive data describing males' apparent (social) and realized (genetic) fitness have been lacking. We used 16 years of comprehensive social and genetic paternity data for an entire free-living song sparrow (Melospiza melodia) population to quantify and compare variances in male apparent and realized fitness, and to quantify the contribution of the variances in within-pair reproductive success (WPRS) and extra-pair reproductive success (EPRS) and their covariance to the variance in realized fitness. Overall, EPP increased the variance in male fitness by only 0-27% across different fitness and variance measures. This relatively small effect reflected the presence of socially unpaired males with zero apparent and low realized fitness, small covariance between WPRS and EPRS, and large variance in WPRS that was relatively unaffected by EPP. Therefore, although EPP altered individual males' contributions to future generations, its impact on population-level parameters such as the opportunity for selection and effective population size was limited.
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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 | 0.000 | 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) | 0.000 | 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".