Father–offspring phenotypic correlations suggest intralocus sexual conflict for a fitness-linked trait in a wild sexually dimorphic mammal
Bibliographic record
Abstract
In sexually dimorphic and polygynous mammals, sexual selection often favours large males with well-developed weaponry, as these secondary sexual characters confer advantages in intrasexual competition and are often preferred by females. Little is known, however, about the effects of sexually selected paternal traits on offspring phenotype in wild mammals, especially when considering that shared phenotypic traits and selection can also differ greatly between genders. Here, we conducted molecular parentage analyses in a long-term study population of mountain goats (Oreamnos americanus), an ungulate exhibiting high sexual dimorphism in mass, to first assess the determinants of yearly reproductive success (YRS) in males. We then examined the effects of paternal characteristics on offspring mass at 1 year of age. Paternity was highly skewed, with 9 per cent of 57 males siring 51 per cent of 96 offspring assigned over 12 years. Male YRS increased with age until apparent reproductive senescence at 9 years, but mass was a stronger determinant of siring success than age, horn length or social rank. Mass of sons increased with paternal mass, but the mass of daughters was negatively related to that of their father, a finding consistent with recent theory on intralocus sexual conflict. Because early differences in mass persisted to early adulthood, sex-specific effects of paternal mass can have important fitness consequences, as adult mass is positively linked with reproduction in both sexes. Divergent father-offspring phenotypic correlations may partly explain the maintenance of sexual dimorphism in mountain goats and the large variance observed for this homologous trait within each gender in polygynous mammals.
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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 | 0.000 |
| 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) | 0.002 | 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".