Demographic drivers of age‐dependent sexual selection
Bibliographic record
Abstract
Sexual selection has a critical role in evolution, and it is fundamental to identify what ecological factors drive its variation. Disentangling the ecological correlates of sexual selection over the long term, however, is challenging and has rarely been done in nature. We sought to assess how demographic changes influenced the intensity, direction and form of sexual selection and whether selective pressures varied with age. We tested whether breeder sex ratio, number of competitors and age structure influenced selection differentials on horn length of wild bighorn rams (Ovis canadensis) of different age classes on Ram Mountain, Alberta. We used 21 years of data including a detailed pedigree, demographic parameters and repeated morphological measurements. Sexual selection on horn length of males of all ages was directional and positive. Selection intensity increased with the number of competitors, reflecting male-male encounter rate during the rut, but was independent of breeder sex ratio or age structure. This result can also be linked to changes in population size because the number of competitors was highly correlated to total number of sheep. This demographic effect likely arises from age-dependent mating tactics. Males aged 2-4 years are weakly competitive and experienced stronger sexual selection as they accounted for a greater proportion of all males. Selection experienced by mature males appeared independent of demography. Our study provides a rare description of the demographic determinants of sexual selection in nature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".