The population dynamics of Northeast Arctic cod (<i>Gadus morhua</i>) through two decades: an analysis based on survey data
Bibliographic record
Abstract
We analyse the population dynamics of Northeast Arctic cod (Gadus morhua) by applying statistical population models to 22 years of research survey data on abundance, length, and maturation. The models for abundance and individual length are selected using Akaike's information criterion (AICC). Survival of 2- to 4-year-old cod was found to be negatively related to the abundance of cod relative to its preferred prey, capelin (Mallotus villosus), likely the result of increased cannibalism from older cod when there is a lack of capelin. Growth up to age 4 decreases with abundance and increases with sea temperature and the North Atlantic Oscillation index, whereas growth from age 4 to age 8 decreases with increasing cod–capelin ratio. The statistical models were combined in a dynamic age-structured model, coupling the dynamics of abundance and body length (reproduction depends on body length, and length growth is influenced by abundance). Simulations using this model are able to recreate the main abundance patterns of each age group for 1982–2002. The model's ability to predict changes in the abundance of spawners appeared to be most limited by our ability to predict survival of 3- to 6-year-old immature cod.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".