The influence of hydrographic structure and seasonal run timing on genetic diversity and isolation-by-distance in chum salmon (Oncorhynchus keta)
Bibliographic record
Abstract
We used 20 microsatellite loci to compare genetic diversity and patterns of isolation-by-distance among three groups of chum salmon ( Oncorhynchus keta ) from two physically distinct watersheds in western Alaska, USA. The results were consistent with the hypothesis that gene flow decreases as the complexity of the hydrographic system increases. Specifically, higher gene flow was inferred among 11 populations from a nonhierarchical collection of short coastal rivers in Norton Sound compared with 29 populations from a complex hierarchical network of inland tributaries of the Yukon River. Within the Yukon River, inferred gene flow was highest among 15 summer-run populations that spawn in the lower drainage, compared with 14 fall-run populations that spawn in the upper drainage. The results suggest that the complexity of the hydrographic system may influence population connectivity and hence the level of genetic diversity of western Alaska chum salmon. Finally, evidence of isolation-by-time, when controlling for geographic distance, supported the hypothesis that genetic divergence in Yukon River chum salmon is influenced by seasonal run timing. However, evidence of isolation-by-distance, when controlling for season run timing, indicated the populations are not sufficiently isolated, spatially or temporally, to prevent gene flow. Dispersal among summer- and fall-run populations may play a role in maintaining genetic diversity.
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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 | 0.000 | 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".