Assessing ecosystem-scale synchrony in Atlantic cod body condition
Bibliographic record
Abstract
During the 1990s, the marine ecosystem around Newfoundland and Labrador experienced a regime shift following significant fluctuations in bottom-water temperatures and heightened fishing pressure. This study investigates the relationship between bottom-up processes and stock productivity as indicated by body condition of Atlantic cod ( Gadus morhua) across Northwest Atlantic Fisheries Organization Divisions 2J, 3K, 3L, 3N, 3O, and 3Ps from 1977 to 2021. We use generalized linear mixed-effects models applied to body weight measurements from bottom-trawl research surveys, to analyze variation in body condition across space, time, and size categories. Quantifying changes in condition across multiple cod populations can help identify broader trends in condition attributed to environmental change. We found regional stock synchronicity, suggesting that broad factors such as environmental temperature variations and capelin abundance greatly influenced the 1990s and mid-2010s biomass declines. Condition in April, May, and June showed large declines following the 1990s, possibly due to changing spatiotemporal overlap with prey. The smallest cod (15–30 cm) had lower condition compared to larger cod. Condition research across stocks enhances our understanding of the environmental mechanisms contributing to survival, ecosystem productivity, and drivers of stock resilience.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".