Marine mammal and seabird population changes have contrasting but limited impacts on fisheries catches in the North Sea
Bibliographic record
Abstract
Marine mammals and seabirds are high trophic level consumers that impact community dynamics. In the southern North Sea and eastern English Channel, the abundance of marine mammal species has markedly increased since 1990, while seabird abundance has remained stable since the early 2000s. To evaluate the interaction between top predators and fisheries, we developed an ecosystem model (1990–2014) that incorporated changes in predator abundances, fishing mortalities, and fishing effort. As marine mammal populations increased, predation mortality on commercial fish species increased. However, reductions in fishing mortality were the dominant driver of the overall change in total mortality for most commercial stocks. Seabirds had minimal impacts on commercial species, regardless of population trends. Resource overlap was higher among fishing fleets than between fisheries and top predators, suggesting inter-fleet competition, rather than predator foraging, drives competition. Although marine mammal impacts on fish stocks were evident, the overall effects of top predator increases on fisheries were limited, indicating that the restoration of marine mammal populations is not incompatible with optimized fisheries yields when viewed at the ecosystem scale.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".