Genetic and environmental canalization are not associated among altitudinally varying populations of <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
Abstract Organisms are exposed to environmental and mutational effects influencing both mean and variance of phenotypes. Potentially deleterious effects arising from this variation can be reduced by the evolution of buffering (canalizing) mechanisms, ultimately reducing phenotypic variability. As such, there has been interest regarding the plausible conditions that enable canalizing mechanisms to evolve. Under some models, the circumstances under which genetic canalization evolves is limited, despite apparent empirical evidence for it. It has been argued that canalizing mechanisms for mutational effects may evolve as a correlated response to environmental canalization (the congruence model). Yet, empirical evidence has not consistently supported the prediction of a correlation between genetic and environmental canalization. In a recent study, a population of Drosophila melanogaster adapted to high altitude showed evidence of genetic decanalization relative to those from low-altitudes. Using strains derived from these populations, we tested if they also varied for environmental canalization, rearing them at different temperatures. Using wing morphology, we quantified size, shape, cell (trichome) density and frequencies of mutational defects. We observed the expected differences in wing size and shape, cell density and mutational defects between the high- and low-altitude populations. However, we observed little evidence for a relationship between a number of measures of environmental canalization with population or with visible defect frequency. Our results do not support the predicted association between genetic and environmental canalization.
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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 | 0.001 |
| 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".