Assortative mating but no evidence of genetic divergence in a species characterized by a trophic polymorphism
Bibliographic record
Abstract
Disruptive selection is a process that can result in multiple subgroups within a population, which is referred to as diversification. Foraging-related diversification has been described in many taxa, but many questions remain about the contribution of such diversification to reproductive isolation and potentially sympatric speciation. Here, we use stable isotope analysis of diet and morphological analysis of body shape to examine phenotypic divergence between littoral and pelagic foraging ecomorphs in a population of pumpkinseed sunfish (Lepomis gibbosus). We then examine reproductive isolation between ecomorphs by comparing the isotopic compositions of nesting males to eggs from their nests (a proxy for maternal diet) and use nine microsatellite loci to examine genetic divergence between ecomorphs. Our data support the presence of distinct foraging ecomorphs in this population and indicate that there is significant positive assortative mating based on diet. We did not find evidence of genetic divergence between ecomorphs, however, indicating that isolation is either relatively recent or is not strong enough to result in genetic divergence at the microsatellite loci. Based on our findings, pumpkinseed sunfish represent a system in which to further explore the mechanisms by which natural and sexual selection contribute to diversification, prior to the occurrence of sympatric speciation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".