Flexible mate choice may contribute to ecotype assortative mating in pumpkinseed sunfish (<i>Lepomis gibbosus</i>)
Bibliographic record
Abstract
Gene flow is expected to limit adaptive divergence, but the ecological and behavioural factors that govern gene flow are still poorly understood, particularly at the earliest stages of population divergence. Reduced gene flow through mate choice (sexual isolation) can evolve even under conditions of subtle population divergence if intermediate phenotypes have reduced fitness. We indirectly tested the hypothesis that mate choice has evolved between coexisting littoral and pelagic ecotypes of polyphenic pumpkinseed sunfish (Lepomis gibbosus) that have diverged in morphology and resource use and where intermediate phenotypes have reduced performance. We assessed the ecotype of nesting males and females using stable isotope estimates of diet and a divergent male morphological trait, oral jaw width. We found positive assortative mating between ecotypes in a common spawning habitat along exposed lake shorelines, but contrary to expectations, assortative mating was variably expressed between two sampling years. Although the factors that influence variable assortative mating remain unclear, our results are consistent with mate choice being expressed by ecotypes. Despite being variably expressed, mate choice will reduce gene flow between ecotypes and could contribute to further adaptive divergence depending on its frequency and strength in the population. Our findings add to a growing body of evidence indicating mate choice behaviour can be a plastic trait, an idea that should be more explicitly considered in empirical studies of mate choice as well as conceptual frameworks of mate choice evolution and adaptive divergence.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".