Contrasting evolutionary outcomes in a human life history trait which is heritable and under consistent unbiased directional selection
Bibliographic record
Abstract
Abstract Microevolution is well documented in natural populations, yet its persistence as an adaptive process remains debated. Despite widespread directional selection on heritable traits, including life-history traits, evolutionary stasis often prevails, with no detectable microevolutionary response. However, evidence of microevolution in some populations raises a key question: do populations under similar ecological conditions and selective pressures exhibit parallel evolution in the same traits? To address this, we examined age at first reproduction (AFR) in three contemporary human populations considered semi-independent replicates, sharing a genetic, demographic, and historical background, with pedigree data available for ∼7 generations. Across all populations, we found strong directional selection favoring earlier AFR, yet quantitative genetic analyses revealed consistently low heritability ( h 2 ≈ 0.11). Only in the Charlevoix population did AFR show a negative genetic correlation with relative fitness, where more than 50% of the standardized phenotypic selection gradient was explained by the genetic selection gradient. Using the Breeder’s Equation and Robertson’s Secondary Theorem of Selection, we predicted an evolutionary response to selection for AFR, which emerged only in Charlevoix. However, neither phenotypic nor breeding values of AFR showed temporal trends, indicating evolutionary stasis. These findings demonstrate that even under consistent directional selection and moderate additive genetic variation, microevolutionary responses may vary across replicate populations. Our results underscore the prevalence of evolutionary stasis, challenging assumptions about the inevitability of microevolution in response to natural 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 | 0.001 | 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) | 0.001 | 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".