Life History and Seasonal Stock‐Specific Ocean Migration of Juvenile Chinook Salmon
Bibliographic record
Abstract
Abstract The ocean feeding grounds of juvenile Pacific salmonOncorhynchusspp. range over several thousand kilometers in which ocean conditions, prey quality and abundance, and predator assemblages vary greatly. Therefore, the fate of individual stocks may depend on where they migrate and how much time they spend in different regions. Juvenile (n= 6,266) and immature (n= 659) Chinook salmonOncorhynchus tshawytschawere collected from coastal Washington to Southeast Alaska in coastal trawl surveys from February to November 1998–2008, which allowed us to reconstruct changes in stock composition for seasons and regions by means of DNA stock identification techniques. Individuals were allocated to 12 regional stocks. The genetic stock assignments were directly validated by showing that 96% of the 339 known‐origin, coded‐wire‐tagged fish were accurately allocated to their region of origin. Overall, the analyses performed in this study support the main findings of previous work based on tagging. However, given that the sample sizes for all stocks were larger and additional stocks were analyzed, we can extend those results; coastal residency of local stocks in their first year at sea with differences between smolt classes for southern stocks. Notably, yearling Chinook salmon moved quickly into waters north of the west coast of Vancouver Island, including Southeast Alaska. Furthermore, subyearling salmon were found over shallower bottom depths than yearling fish. Summer catches in all regions were dominated by Columbia River yearling fish, which suggests a rapid northward migration. In contrast, very few Columbia River subyearling fish were recovered north of Vancouver Island. Columbia River fish were a minor component of the catches in fall and winter, as fish originating from other southern stocks dominated catches off the west coast of Vancouver Island while northern British Columbia and Southeast Alaska stocks dominated northern regions during these time periods. In addition, we found no effect of hatchery origin on the distribution of fish.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".