Effective Population Size, Gene Flow, and Species Status in a Narrow Endemic Sunflower, Helianthus neglectus, Compared to Its Widespread Sister Species, H. petiolaris
Bibliographic record
Abstract
Species delimitation has long been a difficult and controversial process, and different operational criteria often lead to different results. In particular, investigators using phenotypic vs. molecular data to delineate species may recognize different boundaries, especially if morphologically or ecologically differentiated populations have only recently diverged. Here we examine the genetic relationship between the widespread sunflower species Helianthus petiolaris and its narrowly distributed sand dune endemic sister species H. neglectus using sequence data from nine nuclear loci. The two species were initially described as distinct based on a number of minor morphological differences, somewhat different ecological tolerances, and at least one chromosomal rearrangement distinguishing them; but detailed molecular data has not been available until now. We find that, consistent with previous work, H. petiolaris is exceptionally genetically diverse. Surprisingly, H. neglectus harbors very similar levels of genetic diversity (average diversity across loci is actually slightly higher in H. neglectus). It is extremely unlikely that such a geographically restricted species could maintain these levels of genetic variation in isolation. In addition, the two species show very little evidence of any genetic divergence, and estimates of interspecific gene flow are comparable to gene flow estimates among regions within H. petiolaris. These results indicate that H. petiolaris and H. neglectus likely do not represent two distinct, isolated gene pools; H. neglectus is probably more accurately thought of as a geographically restricted, morphologically and ecologically distinct subspecies of H. petiolaris rather than a separate 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 | 0.001 |
| 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) | 0.000 | 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 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".