Contrasting effects of intralocus sexual conflict on sexually antagonistic coevolution
Bibliographic record
Abstract
Evolutionary conflict between the sexes can induce arms races in which males evolve traits that are detrimental to the fitness of their female partners, and vice versa. This interlocus sexual conflict (IRSC) has been proposed as a cause of perpetual intersexual antagonistic coevolution with wide-ranging evolutionary consequences. However, theory suggests that the scope for perpetual coevolution is limited, if traits involved in IRSC are subject to pleiotropic constraints. Here, we consider a biologically plausible form of pleiotropy that has hitherto been ignored in treatments of IRSC and arrive at drastically different conclusions. Our analysis is based on a quantitative genetic model of sexual conflict, in which genes controlling IRSC traits have side effects in the other sex, due to incompletely sex-limited gene expression. As a result, the genes are exposed to intralocus sexual conflict (IASC), a tug-of-war between opposing male- and female-specific selection pressures. We find that the interaction between the two forms of sexual conflict has contrasting effects on antagonistic coevolution: Pleiotropic constraints stabilize the dynamics of arms races if the mating traits are close to evolutionary equilibrium but can prevent populations from ever reaching such a state. Instead, the sexes are drawn into a continuous cycle of arms races, causing the buildup of IASC, alternated by phases of IASC resolution that trigger the next arms race. These results encourage an integrative perspective on the biology of sexual conflict and generally caution against relying exclusively on equilibrium stability analysis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".