Genetic and Phenotypic Evidence of Reproductive Isolation between Seasonal Runs of Sockeye Salmon in Bear Lake, Alaska
Bibliographic record
Abstract
The effective conservation of salmonids requires the recognition and preservation of populations that are diverse in genetic composition and life history. The management of sockeye salmon Oncorhynchus nerka in Bear Lake, Alaska, is based on the presumption that there are two, genetically isolated seasonal runs that exhibit a bimodal escapement pattern. We investigated the genetic composition and life history of the putative early and late runs in two consecutive years. Significant allele frequency differences at six microsatellite loci demonstrate restricted gene flow between the early and late runs (FST = 0.017). There were also significant, and presumably adaptive, differences between the runs with respect to body weight, somatic weight, ovary weight, and egg size among females after correction to equal body sizes. Further, scale pattern analysis revealed highly significant differences in the growth-at-age patterns of these runs. These results demonstrate that there are significant genetic differences between seasonal runs of sockeye salmon and provide support for the management strategy that has been employed for nearly 20 years to protect the genetic diversity of this species in Bear Lake.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".