Population Structure of Sockeye Salmon of the Central Coast of British Columbia: Implications for Recovery Planning
Bibliographic record
Abstract
Abstract The populations of sockeye salmon Oncorhynchus nerka of the south-central coast of British Columbia are in decline. To assist in recovery planning, we determined the population structure of sockeye salmon in the region by assaying the genetic variability of 10 microsatellite DNA loci in samples of sockeye salmon from 22 sites associated with 15 rearing lakes. Samples of sockeye salmon from the watersheds with the largest historical runs in the region were studied. Special emphasis was given to investigating genetic divergence among sockeye salmon spawning in seven rivers of the Owikeno Lake watershed, which once supported the largest sockeye salmon run in south-central British Columbia. Across the region, a mosaic of genetic divergence was evident. Reproductive isolation among watersheds was pronounced in all but one case, making transfer of fish between watersheds inadvisable. Genetic stock identification simulations demonstrated that fish from different watersheds could be accurately distinguished—which will allow for identification of threatened stocks in coastal mixed-stock fishery samples. Within the Owikeno Lake watershed we found little evidence of persistent genetic structure, which precludes the use of genetic stock identification to estimate escapements to its glacially turbid tributaries. Lack of persistent structure supports managing the majority of Owikeno Lake sockeye salmon as a single population.
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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 | 0.000 |
| 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".