Phenotypic extremes or extreme phenotypes? On the use of large and small-bodied “phenocopied” <i>Drosophila melanogaster</i> males in studies of sexual selection and conflict
Bibliographic record
Abstract
Abstract In the fruit fly, Drosophila melanogaster , variation in body size is influenced by a number of different factors and may be strongly associated with individual condition, performance and success in reproductive competitions. Consequently, intra-sexual variation in size in this model species has been frequently explored in order to better understand how sexual selection and sexual conflict may operate and shape evolutionary trajectories. However, measuring individual flies can often be logistically complicated and inefficient, which can result in limited sample sizes. Instead, many experiments use large and/or small body sizes that are created by manipulating the developmental conditions experienced during the larval stages, resulting in “phenocopied” flies whose phenotypes resemble what is seen at the extremes of a population’s size distribution. While this practice is fairly common, there has been remarkedly few direct tests to empirically compare the behaviour or performance of phenocopied flies to similarly-sized individuals that grew up under typical developmental conditions. Contrary to assumptions that phenocopied flies are reasonable approximations, we found that both large and small-bodied phenocopied males frequently differed from their standard development equivalents in their mating frequencies, their lifetime reproductive successes, and in their effects on the fecundity of the females they interacted with. Our results highlight the complicated contributions of environment and genotype to the expression of body size phenotypes and lead us to strongly urge caution in the interpretation of studies solely replying upon phenocopied individuals.
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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 | 0.003 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".