Multi-decadal trends in contingent mixing of Atlantic mackerel (Scomber scombrus) in the Northwest Atlantic from otolith stable isotopes
Bibliographic record
Abstract
Abstract The Atlantic mackerel (Scomber scombrus) in the Northwest Atlantic is comprised of northern and southern components that have distinct spawning sites off Canada (northern contingent) and the US (southern contingent), and seasonally overlap in US fished regions. Thus, assessment and management of this population can be sensitive to levels of mixing between contingents, which remain unknown. Multi-decadal trends in contingent mixing levels within the US fisheries region were assessed, and the contingent composition across seasons, locations, ages, and size classes were characterized using archived otoliths and developing a classification baseline based on juvenile otolith carbon and oxygen stable isotopes (δ13C/δ18O values). Classification of age ≥ 2 adults demonstrated that northern contingent mixing was prevalent within the US continental shelf waters during the past 2 decades (2000–2019), providing an important seasonal subsidy to the US winter fishery despite substantial depletion in spawning stock biomass of the dominant northern contingent. While the majority of older fish were of the northern contingent during the early 2000s, the southern contingent contribution increased with age/size class during the recent period (2013–2019). Spatial mixing was most prevalent during February and March when the northern contingent occurred as far south as the Delmarva Peninsula, but were mostly absent from US waters in May. A positive relationship (albeit not significant; r = 0.60, p = 0.07) occurred between northern contingent mixing and US fisheries landings, which could imply that higher contingent mixing levels might be associated with greater landings for the US winter mackerel fishery. The yield of the Northwest Atlantic mackerel depends upon the status of the northern contingent, with the southern contingent possibly more prone to depletion. Spatially explicit stock assessment models are recommended to conserve both productivity and stability in this two-component population.
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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 | 0.001 | 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) | 0.001 | 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".