Temporal variation in selection on male and female traits in wild tree crickets
Bibliographic record
Abstract
Understanding temporal variation in selection in natural populations is necessary to accurately estimate rates of divergence and macroevolutionary processes. Temporal variation in the strength and direction of selection on sex-specific traits can also explain stasis in male and female phenotype and sexual dimorphism. I investigated changes in strength and form of viability selection (via predation by wasps) in a natural population of male and female tree crickets over 4 years. I found that although the source of viability stayed the same, viability selection affected males and females differently, and the strength, direction and form of selection varied considerably from year to year. In general, males experienced significant linear selection and significant selection differentials more frequently than females, and different male traits experienced significant linear selection each year. This yearly variation resulted in overall weak but significant convex selection on a composite male trait that mostly represented leg size and wing width. Significant selection on female phenotype was uncommon, but when it was detected, it was invariably nonlinear. Significant concave selection on traits representing female body size was observed in some years, as the largest and smallest females were preyed on less (the largest may have been too heavy for flying wasps to carry). Viability selection was significantly different between males and females in 2 of 4 years. Although viability selection via predation has the potential to drive phenotypic change and sexual dimorphism, temporal variation in selection may maintain stasis.
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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 | 0.002 |
| 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".