Consequences of multiple mating‐system shifts for population and range‐wide genetic structure in a coastal dune plant
Bibliographic record
Abstract
Abstract Evolutionary transitions from outcrossing to selfing can strongly affect the genetic diversity and structure of species at multiple spatial scales. We investigated the genetic consequences of mating‐system shifts in the North American, Pacific coast dune endemic plantCamissoniopsis cheiranthifolia(Onagraceae) by assaying variation at 13 nuclear (n) and six chloroplast (cp) microsatellite (SSR) loci for 38 populations across the species range. As predicted from the expected reduction in effective population size (Ne) caused by selfing, small‐flowered, predominantly selfing (SF) populations had much lowernSSRdiversity (but not cpSSR) than large‐flowered, predominantly outcrossing (LF) populations. The reduction innSSRdiversity was greater than expected from the effects of selfing onNealone, but could not be accounted for by indirect effects of selfing on population density. Although selfing should reduce gene flow,SFpopulations were not more genetically differentiated thanLFpopulations. We detected five clusters ofnSSRgenotypes and three groups of cpSSRhaplotypes across the species range consisting of parapatric groups of populations that usually (but not always) differed in mating system, suggesting that selfing may often initiate ecogeographic isolation. However, lineage‐wide genetic variation was not lower for selfing clusters, failing to support the hypothesis that selection for reproductive assurance spurred the evolution of selfing in this species. Within three populations whereLFandSFplants coexist, we detected genetic differentiation among diverged floral phenotypes suggesting that reproductive isolation (probably postzygotic) may help maintain the striking mating‐system differentiation observed across the range of this species.
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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 | 0.000 |
| 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".