Temporally Variable Multivariate Sexual Selection on Sexually Dimorphic Traits in a Wild Insect Population
Bibliographic record
Abstract
A widely held view is that the strength and form of natural selection varies in time and space in response to varying ecological forces; however, adequate quantitative evaluations of this are relatively scarce. In this study, we measured the strength and form of sexual selection acting on a suite of male morphological traits in a wild ambush bug (Phymata americana) population at 10 sampling dates over 2 years. We tested the prediction that the strength and direction of sexual selection would be associated with one or more important ecological variables. We found that patterns of multivariate selection varied considerably over time, and even within a season. Yet, for this population, a sexually dimorphic color pattern trait was consistently a target of directional selection. The strength of sexual selection on this trait was related to both sex ratio and density, which is consistent with the idea that ecological factors can play an important role in generating patterns of sexual selection. We also demonstrate that the median strength of linear selection obtained from replicated cross-sectional methods was qualitatively similar to the estimates obtained from longitudinal methods, providing multiple lines of evidence that the evolution of sexual color dimorphism in this species is attributable to sexual selection.
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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 | 0.000 | 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) | 0.000 | 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".