Divergent selection maintains adaptive differentiation despite high gene flow between sympatric rainbow smelt ecotypes (<i>Osmerus mordax</i>Mitchill)
Bibliographic record
Abstract
In this study, we investigate the relative role of historical factors and evolutionary forces in promoting population differentiation in a new case of sympatric dwarf and normal ecotypes of the rainbow smelt (Osmerus mordax Mitchill) in Lac Saint-Jean (Québec, Canada). Our first objective was to test the hypothesis that the evolution of sympatric smelt ecotypes in Lac Saint-Jean has been contingent upon the secondary contact between two evolutionary lineages in postglacial times. Secondly, the QST method was applied to test the null hypothesis that the extent of phenotypic differences relative to that of neutral marker variation would be similar in comparisons involving populations within and among ecotypes. Thirdly, we applied a quantitative-genetic method as an exploratory assessment as to whether the amount of gene flow observed between populations could affect divergence in adaptive traits under specific conditions. This study revealed a unique situation of dwarf and normal smelt ecotypes that are, respectively, characterized by selmiparous and iteroparous life histories and the occurrence in each of two genetically distinct populations that synchronously use the same spawning habitat in two tributaries. Historical contingency has apparently played little role in the origin of these populations. In contrast, an important role of divergent natural selection in driving their phenotypic divergence was suggested. While divergent selection has apparently been strong enough to maintain phenotypic differentiation in the face of migration, this study suggests that gene flow has been sufficiently important to modulate the extent of adaptive differentiation being achieved between ecotypes, unless the extent of stabilizing selection acting on smelt ecotypes is much more pronounced than usually reported in natural populations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".