Using natural strontium isotopic signatures as fish markers: methodology and application
Bibliographic record
Abstract
To distinguish Atlantic salmon (Salmo salar) populations in tributaries of the Connecticut River, we studied the incorporation and stability of Sr isotopes in juvenile salmon. We established the geologic basis for unique isotopic signatures in 29 salmon sites. Stream-specific Sr isotopic ratios ( 87 Sr/ 86 Sr) were found in calcified tissues of salmon parr within 3 months of stocking. We found little seasonal variation in the Sr signatures of stream water or fish tissue. There were no significant differences among the Sr signatures of otoliths, scales, and vertebrae. For mature salmon raised under constant conditions, 70% of the Sr isotopic signature in calcified tissues was derived from food sources. We developed a criterion for identifying moving fish based upon the isotopic variability of genetically marked fish. Applying this criterion to our streams, 7% of the fish in our study had incorporated Sr from multiple streams. Strontium isotopes distinguished all 8 regions in the White River basin and 7 of the 10 regions in the West River basin. When watersheds are considered together, Sr isotopes differentiated 11 unique signatures from 18 regions. We conclude that Sr isotopes are an effective marking tool and discuss ways in which they can be combined with other marking techniques over larger spatial scales.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".