INTRALOCUS SEXUAL CONFLICT OVER IMMUNE DEFENSE, GENDER LOAD, AND SEX-SPECIFIC SIGNALING IN A NATURAL LIZARD POPULATION
Bibliographic record
Abstract
In species with separate sexes, antagonistic selection on males and females (intralocus sexual conflict) can result in a gender load that can be resolved through the evolution of sexual dimorphism. We present data on intralocus sexual conflict over immune defense in a natural population of free-ranging lizards (Uta stansburiana) and discuss the resolution of this conflict. Intralocus sexual conflict arises from correlational selection between immune defense and orange throat coloration in these lizards. Males with orange throats and high antibody responses had enhanced survival, but the same trait combination reduced female fitness. This sexual antagonism persisted across the life cycle and was concordant between the juvenile and adult life stages. The opposing selective pressure on males and females is ameliorated by a negative intersexual genetic correlation (r(m,f)=-0.86) for immune defense. Throat coloration was also genetically correlated with immune defense, but the sign of this genetic correlation differed between the sexes. This resulted in sex-specific signaling of immunological condition. We also found evidence for a sex-specific maternal effect on sons with potential to additionally reduce the gender load. These results have implications for signaling evolution, genetic integration between adaptive traits, sex allocation, and mutual mate choice for indirect fitness benefits.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".