Decadal changes in the North Sea food web between 1981 and 1991 — implications for fish stock assessment
Bibliographic record
Abstract
The North Sea ecosystem of the early 1980s differed substantially from that of the early 1990s. The current North Sea multispecies fisheries assessment models are parameterized by fish diet data sets that reflect both ecosystem states, as the stomachs were sampled in 1981 and 1991. In this study, multispecies virtual population analysis (MSVPA) was parameterized with either diet data set, leading to different model food webs, each representing the predator's diet selection behavior and spatiotemporal overlap with their prey in the two respective ecosystem states. The impact of these changes in predator preferences and spatiotemporal overlap on recruitment success and on stock developments could be demonstrated by using either stomach data set to estimate historic and future spawning stock biomass and recruitment trajectories. The observed changes in the food web mainly impacted the hindcasted recruitment trajectories, whereas spawning stock biomass estimates were quite robust. In the prediction runs, the differences in the survival rate of the recruits decided whether fish stocks of commercially important species (e.g., Gadus morhua, Merlangius merlangus) would recover or collapse in the near future.
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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 | 0.001 |
| 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".