Distinguishing Wild from Hatchery-Produced Juvenile Red Snapper with Otolith Chemical Signatures
Bibliographic record
Abstract
Abstract Otolith chemical signatures were evaluated as natural tags to distinguish wild from hatchery-produced juvenile red snapper Lutjanus campechanus. Otoliths were sampled from 59 hatchery-reared fish and 146 wild fish collected over the continental shelf from northwest Florida to Texas. One sagitta from each fish was cleaned, dissolved in ultrapure nitric acid, and analyzed with sector field inductively coupled plasma mass spectrometry to test for differences in otolith element:Ca ratios (Ba:Ca, Li:Ca, Mg:Ca, Mn:Ca, and Sr:Ca) between wild and hatchery fish. The second sagitta was cleaned, ground to a fine powder, and analyzed with stable isotope ratio mass spectrometry to test for differences in delta (δ) values of the stable isotopes 13C and 18O. Significant differences existed in otolith chemical signatures between hatchery and wild juveniles (multivariate analysis of variance, Pillai's trace: P < 0.001). Jackknifed classification accuracies from linear discriminant function analysis indicated that hatchery fish could be distinguished from wild fish with 100% accuracy based on otolith chemical signatures. The most important otolith chemistry feature in distinguishing hatchery from wild fish was δ13C, with the mean difference in δ13C between hatchery and wild fish (−2.6‰) being similar to the mean difference in δ13C between hatchery feeds and the predominant food of wild juveniles (−2.8‰). Overall, results suggest that otolith chemical signatures may be employed as effective natural tags for mass marking of future stockings of red snapper or other marine fishes to estimate the hatchery contribution to wild populations.
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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 | 0.000 | 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".