Influence of life-history-dependent migration strategies on Atlantic salmon diets
Bibliographic record
Abstract
Abstract Migratory behaviour may vary according to the life history and demographic attributes of fish and lead to the spatial segregation of distinct population segments during the non-breeding season. In adult Atlantic salmon, spawning history differences are associated with intra-population variation in marine movements, but the degree of connectivity in spatial resource use among and within maiden and repeat spawning salmon is not well understood. We analysed muscle fatty acids (FAs), δ13C and δ15N of Atlantic salmon returning to spawn, and found significant differences among spawning histories. Maiden and alternate repeat spawning Atlantic salmon were differentiated from consecutive repeat spawners by fatty acid biomarkers associated with distinct biogeographic regions of the Labrador Sea, consistent with differential migration and divergent feeding locations. The presence and pattern of feeding contrasts among spawning history groups were further supported by dorsal muscle δ15N, which covaried with FA compositional values and distinguished consecutive repeat spawners from the two other groups. Because the degree of connectivity among population segments affects the ecological factors faced by such groups, an improved understanding of differential migration is necessary to better predict potential population responses to environmental change.
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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".