Pronounced long-term juvenation in the spawning stock of Arcto-Norwegian cod (<i>Gadus morhua</i>) and possible consequences for recruitment
Bibliographic record
Abstract
The oldest and largest individuals are disappearing from many fish stocks worldwide as a result of overexploitation. This has been suggested to impair recruitment through decreasing the reproductive capacity of the spawners and increasing the mortality rate of the offspring. By using a time series on spawners biomass by age class for Arcto-Norwegian cod (Gadus morhua) from 1913–2004, I have documented pronounced changes in the spawning stock, including a trend towards younger fish, a less diverse distribution across ages, and a declining proportion of repeat spawners. Despite the total spawning stock biomass (SSB) being at similar levels now as in 1933, the mean age in the SSB has declined from 10–12.5 years to 7–8 years during the study period, and the percentage of fish of age 10 or above in the SSB has decreased from ~97% to ~10%. Contrary to earlier theoretical and experimental studies, no clear link between age structure and recruitment was found here. Recruitment to the Arcto-Norwegian cod stock may thus be more robust towards spawner juvenation than expected, possibly because of strong recruitment compensation.
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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 | 0.000 |
| 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".