Biogeographic history of green alder (<i>Alnus alnobetula</i> (Ehrh.) K. Koch s.l.) in Eurasia and North America: evidence from genetic and morphological analyses
Bibliographic record
Abstract
The green alder ( Alnus alnobetula s.l.) is a cold-resistant boreal-arctic shrub species with a complex intraspecific taxonomy and a wide distribution range covering northern Eurasia and North America. In this study, we assess the level and distribution of diversity in five subspecies ( A. alnobetula subsp. fruticosa, kamtschatica, mandschurica, maximowiczii, and sinuata) throughout 34 populations within the native species range by using 7 characters of leaf morphology and 11 nuclear microsatellites (nSSR). The differentiation in both sets of characters that we found has proven to be inconsistent with our previously obtained chloroplast DNA (cpDNA) data. Only three groups were identified using nSSR vs. five cpDNA haplogroups. Both morphological and nSSR analyses support the recognition of A. alnobetula subsp. fruticosa from the western part of the Eurasian distribution range (northwestern Russia, the Urals, and Siberia) and A. alnobetula subsp. maximowiczii from the eastern part (most of Sakhalin Island, the Kuril Islands, and most of Kamchatka). Among other East Asian subspecies such as A. alnobetula subsp. kamtschatica and subsp. mandschurica, as well as in A. subsp. sinuata from North America, considerable genetic and morphological admixture has been recorded. The discordance between the patterns inferred from cpDNA and nSSR data reflects limited gene dispersal via seeds and extensive gene flow via pollen between major glacial refugia.
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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 | 0.001 |
| 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".