Genetic analysis of sympatric char populations in western Alaska: Arctic char (<i>Salvelinus alpinus</i>) and Dolly Varden (<i>Salvelinus malma</i>) are not two sides of the same coin
Bibliographic record
Abstract
The North Pacific Ocean has been of great significance to understanding biogeography and speciation in temperate faunas, including for two species of char (Salmonidae: Salvelinus) whose evolutionary relationship has been controversial. We examined the morphology and genetics (microsatellite and mitochondrial DNA) of Arctic char (Salvelinus alpinus) and Dolly Varden char (Salvelinus malma) in lake systems in western Alaska, the eastern and western Arctic, and south of the Alaskan Peninsula. Morphologically, each lake system contained two forms: one (Arctic char) largely confined to lake habitats and characterized by greater numbers of pyloric caeca, gill rakers, and shallower bodies, and another (Dolly Varden) predominated in adjacent stream habitats and was characterized by fewer pyloric caeca, gill rakers, and deeper bodies. MtDNA partial (550 bp) d-loop sequences of both taxa were interspersed with each other within a single 'Bering' clade and demographic inferences suggested historical gene flow from Dolly Varden to Arctic char had occurred. By contrast, the taxa were strongly differentiated in sympatry across nine microsatellite loci in both lakes. Our data show that the two taxa are highly genetically distinct in sympatry, supporting their status as valid biological species, despite occasional hybridization. The interaction between these species highlights the importance of the North Pacific, and Beringia in particular, as an evolutionary wellspring of biodiversity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".