Divergence in genetic (co)variances and the alignment of gmax with phenotypic divergence
Bibliographic record
Abstract
To better understand the sources of biological diversity in nature, we need information on the mechanisms underlying population divergence. Biological systems with patterns of naturally occurring adaptive variation among populations can provide insight into the genetic architecture of diverging traits and the influence of genetic constraints on responses to selection. Using a system of reproductive character displacement in the North American mushroom-feeding fly Drosophila subquinaria, we assessed patterns of genetic (co)variance among a suite of chemical signaling traits and divergence in this pattern among populations. D. subquinaria exhibits stronger reproductive isolation against the closely related Drosophila recens in sympatry, where both female mating preferences and male chemical signalling traits have diverged from the ancestral allopatric populations. We collected three wild populations from each region and, in the lab, characterized the phenotypic divergence in these traits as well as the additive genetic (co)variance structure (G-matrix) with replicate breeding designs. We found divergence between allopatric and sympatric D. subquinaria in the shape and size of the G-matrix, and that the leading axis of genetic variance (gmax) had changed in sympatry to come into alignment with the primary axis of phenotypic divergence between the sympatric and allopatric regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".