Natural tracers reveal population structure of albacore (Thunnus alalunga) in the eastern North Pacific
Bibliographic record
Abstract
Abstract Chemical signatures in otoliths and muscle tissue of albacore (Thunnus alalunga) from two regions of the North Pacific were characterized to examine population structure. Regions included northern (offshore northwest United States and Canada, >40°N) and southern (offshore southwest United States and Mexico, <40°N) areas where albacore have demonstrated region-specific differences in movement and size at age. Juvenile (ages 1–4 years) albacore were collected from each region through recreational and commercial fisheries over a 5-year period (2009–2013). Three different otolith chemistry assays were performed, including whole otoliths (proxy for lifetime signature), otolith edge (recent signature), and otolith core (nursery signature). Whole otolith δ13C and δ18O showed similar δ13C and enriched δ18O (∼0.5‰) values for juvenile albacore collected in the southern region; classification success to the two regions ranged from 78 to 91% during each year (similar age classes). Otolith edge δ13C and δ18O showed similar results as whole otoliths, but no regional differences were found for otolith core chemistry. Incorporation of trace element concentrations from whole otoliths improved discrimination between regions to 90–100% classification success during each year of the study, with significantly higher Ba:Ca, Mg:Ca, and Mn:Ca in albacore otoliths from the northern region. Albacore from the southern region also displayed enriched muscle δ13C (∼1.21‰) and δ15N (∼0.85‰) values relative to fish of the same size range from the northern region. Discrimination success between the two regions across all years using muscle δ13C and δ15N was 91%. Ultimately, results from this study suggest regional separation of albacore in the eastern North Pacific warranting region-specific vital rates in future modelling efforts.
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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 | 0.001 | 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) | 0.000 | 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".