Contemporary sexual selection on sexually dimorphic traits in the ambush bug Phymata americana
Bibliographic record
Abstract
Sexual selection is a potent evolutionary force often invoked to explain observed cases of sexual dimorphism. However, evidence of this process operating on existing phenotypic variation is limited. We investigated whether sexual selection could account for sexual dimorphism in size and color pattern in the ambush bug Phymata americana. We considered the alternative hypothesis that dimorphism merely reflects sex differences in habitat use but found no evidence of sex differences in microhabitat during 2 sampling periods in the wild. Although the form of sexual (phenotypic) selection on male lateral color pattern varied between samples, selection consistently favored lateral coloration in males but not size. For females, weight was a consistent predictor of mating status in both the early and the late season. We performed 2 separate laboratory studies to investigate potential proximate mechanisms of sexual selection that might account for the field data. Although we found that male weight predicted male success in direct male--male competition and male courtship intensity predicted success in male--female interactions, we did not detect any role of male color pattern in either laboratory study. These data suggest that visual signaling is unlikely to play a role in the evolution of color pattern dimorphism in this species. Consistent with the field data, our laboratory results also found that female weight predicted the probability of copulation, possibly indicating that female receptivity coincides with female reproductive cycle (i.e., egg maturation). Copyright 2008, Oxford University Press.
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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 | 0.001 |
| 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 | 0.001 |
| 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".