Multivariate sexual selection on male song structure in wild populations of sagebrush crickets, <i>Cyphoderris strepitans</i> (Orthoptera: Haglidae)
Bibliographic record
Abstract
While a number of studies have measured multivariate sexual selection acting on sexual signals in wild populations, few have confirmed these findings with experimental manipulation. Sagebrush crickets are ideally suited to such investigations because mating imposes an unambiguous phenotypic marker on males arising from nuptial feeding by females. We quantified sexual selection operating on male song by recording songs of virgin and mated males captured from three wild populations. To determine the extent to which selection on male song is influenced by female preference, we conducted a companion study in which we synthesized male songs and broadcast them to females in choice trials. Multivariate selection analysis revealed a saddle-shaped fitness surface, the highest peak of which corresponded to longer train and pulse durations, and longer intertrain intervals. Longer trains and pulses likely promote greater mate attraction, but selection for longer intertrain durations suggests that energetic constraints may necessitate "time outs". Playback trials confirmed the selection for longer train and pulse durations, and revealed significant stabilizing selection on dominant frequency, suggesting that the female auditory system is tightly tuned to the species-specific call frequency. Collectively, our results revealed a complex pattern of multivariate nonlinear selection characterized primarily by strong stabilizing and disruptive selection on male song traits.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".