Species and Life History Affect the Utility of Otolith Chemical Composition for Determining Natal Stream of Origin for Pacific Salmon
Bibliographic record
Abstract
Abstract To test the utility of otolith chemical composition as a tool for determining the natal stream of origin for salmon, we examined water chemistry and otoliths of juvenile and adult Chum Salmon Oncorhynchus keta and Coho Salmon O. kisutch from three watersheds (five rivers) in the Norton Sound region of Alaska. The two species are characterized by different life histories: Coho Salmon rear in freshwater for up to 3 years, whereas Chum Salmon emigrate from freshwater shortly after emergence. We used laser ablation (LA) inductively coupled plasma (ICP) mass spectrometry (MS) to quantify element: Ca ratios for Mg, Mn, Zn, Sr, and Ba, and we used multicollector LA‐ICP‐MS to determine 87Sr:86Sr ratios in otolith regions corresponding to the period of freshwater residence. Significant differences existed in both water and otolith elemental composition, suggesting that otolith composition could be used to discriminate the natal origin of Coho Salmon and Chum Salmon but only when 87Sr:86Sr ratios were included in the discriminant function analyses. The best discriminant model included 87Sr:86Sr ratios, and without 87Sr:86Sr ratios it was difficult to discriminate among watersheds and rivers. Classification accuracy was 80% for Coho Salmon and 68% for Chum Salmon, indicating that this method does not provide sufficient sensitivity to estimate straying rates of Pacific salmon at the scale we studied.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".