Neutral Loci Reveal Population Structure by Geography, not Ecotype, in Kootenay Lake Kokanee
Bibliographic record
Abstract
Abstract Genetic tools are often used to define stocks for fisheries management, however, traditional approaches using neutral markers may be inadequate for detecting fine-scale structure when populations have recently diverged. Kokanee Oncorhynchus nerka is a freshwater form of sockeye salmon that exhibits divergent reproductive ecotypes. We used a combination of expressed sequence tag (EST)-linked and non-EST-linked microsatellites to investigate kokanee stock structure and ecotype differentiation in Kootenay Lake, British Columbia. Despite being highly informative in other lakes in the province, the EST-linked loci used in this study did not exhibit outlier behavior relative to neutral loci for distinguishing shore-spawning and stream-spawning ecotypes. We found conflicting evidence for differentiation between ecotypes and strong evidence for geographical structure corresponding to the North Arm and West Arm of Kootenay Lake. These results are consistent with previous findings that neutral markers are not sufficient for resolving fine-scale ecotype differentiation in kokanee; additional studies are necessary to investigate the degree to which an outlier-based approach to kokanee fisheries management can be applied at a broader level. Received September 29, 2011; accepted December 21, 2011
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".