Using trophic models to assess the impact of fishing in the Bay of Biscay and the Celtic Sea
Why this work is in the frame
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Bibliographic record
Abstract
Using the Bay of Biscay and Celtic Sea area as a case study, we showed how stock-assessments and trophic models can be useful and complementary tools to quantify the fishing impacts on the whole food web and to draw related diagnoses at the scale of marine ecosystems. First, an integrated synthesis of the status and trends in fish stocks, derived from ICES assessments, was consolidated at the ecosystem level. Then, using the well-known Ecopath and Ecosim and the more recently developed EcoTroph approach, we built advice-oriented ecosystem models structured around the stocks assessed by ICES. We especially analysed trends over the last three decades and investigated the potential ecosystem effects of the recent decrease observed in the overall fishing pressure. The Celtic/Biscay ecosystem appeared heavily fished during the 1980–2015 period. Some stocks would have started to recover recently, but changes in species composition seem to lead to more rapid and less efficient transfers within the food web. This could explain why the biomass of intermediate and high trophic levels increased at lower rates than anticipated from the decrease in the fishing pressure. We conclude that, in the frame of the Ecosystem approach to fisheries management, trophic models are key tools to expand stock assessment results at the scale of the whole ecosystem, and to reveal changes occurring in the global parameters of the trophic functioning of ecosystems.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it