Low levels of hybridization between sympatric<scp>A</scp>rctic char (<i><scp>S</scp>alvelinus alpinus</i>) and<scp>D</scp>olly<scp>V</scp>arden char (<i><scp>S</scp>alvelinus malma</i>) highlights their genetic distinctiveness and ecological segregation
Bibliographic record
Abstract
Understanding the extent of interspecific hybridization and how ecological segregation may influence hybridization requires comprehensively sampling different habitats over a range of life history stages. Arctic char (Salvelinus alpinus) and Dolly Varden (S. malma) are recently diverged salmonid fishes that come into contact in several areas of the North Pacific where they occasionally hybridize. To better quantify the degree of hybridization and ecological segregation between these taxa, we sampled over 700 fish from multiple lake (littoral and profundal) and stream sites in two large, interconnected southwestern Alaskan lakes. Individuals were genotyped at 12 microsatellite markers, and genetic admixture (Q) values generated through Bayesian-based clustering revealed hybridization levels generally lower than reported in a previous study (<0.6% to 5% of samples classified as late-generation hybrids). Dolly Varden and Arctic char tended to make different use of stream habitats with the latter apparently abandoning streams for lake habitats after 2-3 years of age. Our results support the distinct biological species status of Dolly Varden and Arctic char and suggest that ecological segregation may be an important factor limiting opportunities for hybridization and/or the ecological performance of hybrid char.
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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 | 0.001 | 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) | 0.002 | 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".