Data from: Vicariance, long-distance dispersal, and regional extinction–recolonization dynamics explain the disjunct circumpolar distribution of the arctic-alpine plant Silene acaulis
Bibliographic record
Abstract
PREMISE OF THE STUDY: Many arctic-alpine species have vast geographic ranges, but these may encompass substantial gaps whose origins are poorly understood. Here we address the phylogeographic history of Silene acaulis, a perennial cushion plant with a circumpolar distribution except for a large gap in Siberia. METHODS: We assessed genetic variation in a range-wide sample of 103 populations using plastid DNA (pDNA) sequences and AFLPs (amplified fragment length polymorphisms). We constructed a haplotype network and performed Bayesian phylogenetic analyses based on plastid sequences. We visualized AFLP patterns using principal coordinate analysis, identified genetic groups using the program structure, and estimated genetic diversity and rarity indices by geographic region. KEY RESULTS: The history of the main pDNA lineages was estimated to span several glaciations. AFLP data revealed a distinct division between Beringia/North America and Europe/East Greenland. These two regions shared only one of 17 pDNA haplotypes. Populations on opposite sides of the Siberian range gap (Ural Mountains and Chukotka) were genetically distinct and appear to have resulted from postglacial leading-edge colonizations. We inferred two refugia in North America (Beringia and the southern Rocky Mountains) and two in Europe (central-southern Europe and northern Europe/East Greenland). Patterns in the East Atlantic region suggested transoceanic long-distance dispersal events. CONCLUSIONS: Silene acaulis has a highly dynamic history characterized by vicariance, regional extinction, and recolonization, with persistence in at least four refugia. Long-distance dispersal explains patterns across the Atlantic Ocean, but we found no evidence of dispersal across the Siberian range gap.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".