Migration between continents: geographical structure and long‐distance gene flow in <i>Porpidia flavicunda</i> (lichen‐forming Ascomycota)
Bibliographic record
Abstract
Historical and contemporary geographical distribution ranges with their associated gene flow patterns interact to produce the genetic diversity observed today. Often it is not possible to separate out the impacts of historical events, e.g. past fragmentation, and contemporary gene flow, e.g. long-distance dispersal. Porpidia flavicunda is a lichen-forming ascomycete occurring circumpolar in the boreal to arctic zones for which vegetation history suggests that its distribution pattern has stayed broadly the same over the past millennia. DNA-sequence diversity in P. flavicunda can, thus, be expected to predominantly represent geographical population differentiation and its contemporary migration rates. The population sample consists of 110 specimens collected in Northern Québec, Baffin Island, Western Greenland and Northern Scandinavia. DNA-sequence data sets of three nuclear gene fragments (LSU, RPB2 and beta-tubulin) were analysed for genetic diversity within, and differentiation between, geographical regions. Tests of population subdivision employing analyses of molecular variance and exact tests of haplotype frequency distributions showed significant structure between the geographical regions. However, the lack of fixed nucleotide polymorphisms and the wide sharing of identical haplotypes between geographical regions suggest recurrent long-distance gene flow of propagules. Still, the means by which propagules are dispersed remain to be discovered. Inference of migration rates shows that in many cases a sufficiently high amount of migrants is exchanged between geographical regions to prevent drastic population differentiation through genetic drift. The observed haplotype distributions and migration rates point to a gene flow model of isolation by distance.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".