Offspring sex ratio increases with male reproductive success in the polygynous southern elephant seals
Bibliographic record
Abstract
In polygynous species, most dominant males sire a disproportionate number of offspring and dominance rank is assumed to be age dependent. Yet, extreme inter-male competition and high early male mortality prevent most males from reaching a social status that could guaranty a high reproductive success. Alternative reproductive tactics may have evolved to maximize male reproductive success despite a low social rank. One of them, offspring sex-ratio adjustment, may allow males to produce more offspring of the sex that will provide a higher fitness. If traits influencing dominance in males are heritable and if the average fitness of subordinate males is lower than the average fitness of females, we predict that the probability of producing a son would increase with a male reproductive success as its sons would be more likely to become dominant. We tested this hypothesis on southern elephant seals breeding on the Kerguelen Archipelago. Using 530 pups sired by 52 males, we found that the probability of siring a son increases with a male reproductive success. Out finding provide new insights on sex ratio variation can be an important tool in managing population dynamics and structure, which has direct implications on wildlife conservation.
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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) | 0.002 | 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".