Paternity in eastern grey kangaroos: moderate skew despite strong sexual dimorphism
Bibliographic record
Abstract
Understanding sexual selection requires adequate measures of reproductive success. In wild mammals, reliable data on variation in male reproductive success are available for very few species. We assessed the distribution of paternities and quantified skew in male reproductive success in 2 populations of a marsupial with strong sexual dimorphism, the eastern grey kangaroos (Macropus giganteus) over 5 years. We assigned fathers to 356 juveniles, or 79% of those with known mother. We found a relatively weak mating skew and the most successful males did not monopolize a large fraction of paternities. Nearly half of the adult males we monitored fathered at least 1 young. The yearly opportunity for sexual selection (Is) for males ranged from 1.80 to 3.98, and Nonacs’ B index of mating skew was significant but low, ranging from 0.01 to 0.07. Considering the strong sexual dimorphism, long breeding season, and strong male dominance hierarchy, our results suggest an unexpectedly low reproductive skew. That is surprising given the wide range in male weights: the smallest fathers weighed 40% less than the heaviest ones. Skew in eastern grey kangaroos is weaker than that estimated for other species with lower sexual size dimorphism. We found substantial year-to-year variability in reproductive skew. Because male mating success varies according to the characteristics of competitors and the distribution of breeding opportunities, multiple years of monitoring are required to obtain reliable estimates. In the absence of data on paternity, strong sexual dimorphism cannot be assumed to imply high polygyny and strong sexual selection.
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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 | 0.001 | 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".