Evidence for spatial coherence in time trends of marine life history traits of Atlantic salmon in the North Atlantic
Bibliographic record
Abstract
Abstract A hierarchical Bayesian life cycle model is presented that considers spatial covariation of marine life history traits of Atlantic salmon ( Salmo salar ) populations in the North Atlantic. The model is based on a collective analysis of the dynamics of 13 stock units ( SU s) from two continental stock groups ( CSG s) in North America and Southern Europe in a single hierarchical model over the period 1971–2014. The model sets up a new assessment framework for Atlantic salmon stocks. It also provides a framework to investigate the drivers of changes in Atlantic salmon population dynamics including disentangling the effects of fisheries from those of environmental factors in a hierarchy of spatial scales. It is used to test the hypothesis of a strong spatial synchrony in marine life history dynamics of Atlantic salmon populations. The trends in two key parameters associated with the early marine phase of the life cycle are estimated: (i) the marine survival during the first summer–autumn spent at sea and (ii) the proportion of fish maturing after the first winter at sea. The results provide evidence of a decline in the marine survival together with an increase in the proportion of fish that mature after the first winter at sea, common to all SU s. Our results show an increased coherence in the covariations of trends in these two marine life history traits related to geographic proximity of SU s which support the hypothesis of a coherent response of geographically proximate Atlantic salmon populations that likely share similar migration routes.
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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 | 0.000 | 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) | 0.005 | 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".