When does sexual selection through mate choice deplete versus exaggerate genetic variation: is there a lek paradox?
Bibliographic record
Abstract
Abstract The evolution of female preferences for male display traits relies on females receiving indirect benefits from their mate. This requires substantial genetic variation in display traits or male quality. Nevertheless, sexual selection through mate choice has been assumed to deplete this genetic variation, ultimately diminishing strong preferences. However, sexual traits often have higher genetic variation than non-sexual traits. This contradiction, and, relatedly, how costly preferences and display traits are maintained, is called the “lek paradox”. Using infinitesimal models, we show that sexual selection through mate choice allows variation in male display traits and female preferences to mutually exaggerate each other, in a process analogous to runaway sexual selection but in terms of genetic variation. Therefore, contrary to prior suppositions, sexual selection may increase equilibrium genetic variance in display traits and preferences over that under random mating, provided that the variance of female preferences relative to male traits during mate choice is not too small and preferences are not too weak. Notably, even if equilibrium preference variation is substantially smaller than trait variation, trait variation can still increase over that under random mating, provided selection on the trait compared to the preference is sufficiently strong. Furthermore, when trait variation does decrease, this reduction is generally slight. It is under situations such as lekking, where females can simultaneously choose from many males so that mate discrimination is effectively strong and fitness costs of choice weak, that sexual selection through mate choice may be most powerful in exaggerating genetic variance in male displays. Significance statement The “lek paradox”—the dissonance between a hypothesized loss of variation in sexual display traits due to mate choice, leading to the subsequent cessation of sexual selection, and evidence of high variation in such traits in nature, accompanied by the long-term persistence of sexual selection—is an enduring mystery of the sexual selection literature. We clarify and quantify multiple pathways by which sexual selection via mate preferences alters genetic variance in both display traits and female preferences. Using mathematical models, we show the lek paradox is built upon a false premise. We find a wide range of conditions under which sexual selection increases or minimally reduces variation in display traits, allowing the maintenance of substantial variance in traits and preferences.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".