Bibliographic record
Abstract
Johan Hjort’s so-called second recruitment hypothesis addressed the fate of offspring that drift out of areas suitable for their survival. This hypothesis has forged the concept of a population as a closed life cycle, making countercurrent adult spawning migration a necessary mechanism in balancing larval drift. The Norwegian spring-spawning (NSS) herring stock (Clupea harengus), the object of much of Hjort’s work, is spread over large areas in the Northeast Atlantic, with spawning along the Norwegian coast, nursery areas in the Barents Sea, feeding areas in the Norwegian Sea, and overwintering areas outside northern Norway. Understanding the spatial dynamics of highly migratory fish stocks such as the NSS herring, therefore, is critical to understanding their population dynamics. Here I review hypotheses on the spatial dynamics of fish focusing on NSS herring and discuss consequences for population dynamics and interactions with other ecosystem components. The results illustrate the key role that strong herring cohorts play both as predators in the Barents and Norwegian seas and as prey on the overwintering and spawning grounds along the Norwegian coast. It is advocated that spatial full life cycle models should be developed for key fish stocks as a meeting place for model assumptions and observations and as a test bed for a multiple hypothesis testing approach.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".