Modelling Atlantic mackerel spawning habitat suitability and its future distribution in the north‐west Atlantic
Bibliographic record
Abstract
Abstract We investigated the effect of environmental conditions on Atlantic mackerel spawning habitat in the southern Gulf of St. Lawrence (sGSL). Based on generalized additive models, we (i) modelled the optimal spawning habitat of mackerel in the sGSL using daily egg production (DEP) in June, (ii) predicted known and new potential present spawning habitats in the GSL and the north‐west Atlantic, and (iii) assessed how they respond to future climate change. Our findings showed that both mackerel presence–absence and given‐presence DEP were associated with sea surface temperature (10–16.5°C), salinity above 31 and depth < 120 m. Adding zooplankton showed a marked effect on the DEP given‐presence compared to the presence–absence. Predictions of spawning habitats under present (1999–2012) and future scenario (2066–2085) conditions were estimated from the presence–absence model without zooplankton, using physical conditions of the BNAM. Under present conditions, our model predicted well the main spawning habitat in the sGSL and other known secondary spawning habitats in the northern GSL (nGSL), the western and southern Newfoundland, and the north‐west Atlantic coast. Under future conditions, our study suggests that spawning habitats in the sGSL and the nGSL would expand. Our results, therefore, suggest that mackerel could benefit from a warmer GSL, minimizing the potential for a northward migration of the stock due to decreasing suitability of the sGSL as its main spawning ground, and a new but spatially limited potential habitat in Newfoundland coasts. These results can be used to inform stock management and develop adaptive management plans in the context of climate change.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".