Data from: Condition dependence and the maintenance of genetic variance in a sexually dimorphic black scavenger fly
Bibliographic record
Abstract
The maintenance of genetic variation in traits under strong sexual selection is a longstanding problem in evolutionary biology. The genic capture model proposes that this problem can be explained by the evolution of condition dependence in exaggerated male traits. We tested the predictions that condition dependence should be more pronounced in male sexual traits and that genetic variance in expression of these traits should increase under stress as among-genotype variation in overall condition is exposed. Genetic variance in female and nonsexual traits should, by contrast, be similar across environments as a result of stabilizing selection on trait expression. The relationship between the degree of sexual dimorphism, condition dependence and additive genetic variance (Va) was assessed for two morphological traits (body size and relative fore femur width) affecting male mating success in the black scavenger fly Sepsis punctum (Diptera: Sepsidae) and for development time (a nonsexual trait often correlated with body size). We compared trait expression between the sexes for two cross-continental populations that differ in degree of sexual dimorphism (Ottawa and Zurich). Condition dependence was indeed most pronounced in males of the strongly dimorphic Zurich population (males larger), and Va was similar for males and females unless the trait was strongly sex specific and condition dependent. Contrary to prediction, however, Va primarily increased under food limitation in both sexes, and genetic variance in fore femur width was low to nil, perhaps depleted by putatively strong sexual selection. Solely for body size of Zurich males, Va increased more in males than females at limited food, in accordance with the predictions of the genic capture model. Overall therefore, quantitative genetic evidence in support of the model was inconsistent and weak at best.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.084 | 0.023 |
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".