Asymmetric barriers to gene flow can maintain sex role differentiation upon secondary contact
Bibliographic record
Abstract
Acquiring a mate and providing parental care require substantial time and energy. Evolution typically favours allocating more effort to one of these actions at the expense of the other. Differences between the sexes in such allocation are common, with males investing more heavily in mate acquisition and females investing more heavily in parental care in systems with conventional sex roles and the converse pattern in sex-role-reversed systems. If populations diverge in sex roles, pre- or postmating incompatibilities may arise. For example, if different sexes provide parental care in different populations, interpopulation mating combinations may produce broods that receive little to no care, which could lead to low offspring survival. Here, we consider a two-patch model to ask whether variation in sex roles can persist upon secondary contact in populations that have diverged. We find that populations with sexes that are differently specialized in parental care versus sexual selection can, indeed, remain differentiated after secondary contact and, further, that the mechanism maintaining differentiation depends on the direction of dispersal. Importantly, however, whether populations remain diverged depends on both the model of mate acquisition and the resultant population dynamics (density dependence, mating rate, population size). These findings have potential implications for incipient speciation and the evolution of reproductive barriers.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".