Potential impact of climate change on northern shrimp habitats and connectivity on the Newfoundland and Labrador continental shelves
Bibliographic record
Abstract
Abstract The effect of climate change on ocean circulation and environmental conditions will likely impact important fisheries species which have a limited habitat range and a prolonged larval dispersal phase. Based on projections from a regional scale ice‐ocean model (RCP 8.5 scenario), we investigated the spatial distribution variability of the bentho‐pelagic northern shrimp (Pandalus borealis) preferred depth and thermal habitat and larval settlement patterns in the Newfoundland and Labrador waters for the next 70 years. Our projections of ocean temperature revealed the persistence of major shelf‐scale temperature features, but a gradual increase of bottom water temperatures by more than 4°C by 2090. Such warming led to an expansion of the potentially suitable habitat for northern shrimp from 2010 to 2050 prior to a decline and shift towards more coastal and southern areas from 2060 to 2090. The modification of the northern shrimp suitable habitat distribution, associated with changes in the ocean circulation features, affected the settlement patterns from larval dispersal simulations and the temperatures encountered by larvae. During the projection period, historically important areas were mostly negatively impacted in terms of suitable habitat and settlement potential, whereas areas that had been less important in the past (e.g., the north and the shallow area to the south) were projected to receive more settlers in comparison with the historical period. Our study demonstrated the important role of shelf‐scale processes in determining larval connectivity and suggests that regional scale ocean models are needed to assess potential impacts of climate change on fisheries and ecosystems.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".