Unravelling the stock structure of blue whiting in the Northeast Atlantic: navigating contradictions towards resolution
Bibliographic record
Abstract
Abstract Understanding population structure is fundamental to the sustainable management of marine fish. Blue whiting (Micromesistius poutassou) plays a key ecological role in the Northeast Atlantic as a mid-trophic species linking zooplankton to top predators, while also supporting major commercial fisheries. This review synthesises available evidence on its population structure, revealing a complex metapopulation composed of resident and migratory subpopulations. Although currently assessed as a single stock, this management unit does not account for underlying biological structure, potentially limiting the effectiveness of assessment and management strategies. Our synthesis supports the presence of partial migration, with both migratory and resident contingents contributing to spatial complexity in population structure. Genetic, otolith, parasite, and life-history data indicate the existence of relatively discrete northern and southern subpopulations, mixing zones, and resident groups. We highlight the importance of adaptive, spatially explicit management approaches that account for temporal variability, support stakeholder engagement, and foster regional cooperation. Key knowledge gaps remain in fine-scale population structuring, life-history stage characterisation, and connectivity mechanisms. Addressing these will require integrative approaches using genomics, otolith chemistry, and biophysical modelling. While current stock boundaries encompass the species' range, integrating internal biological structure into assessments and management strategies will enhance their effectiveness and contribute to sustainable exploitation. Graphical abstract
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".