Farmed bivalve loss due to seabream predation in the French Mediterranean Prevost Lagoon
Why this work is in the frame
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Bibliographic record
Abstract
Bivalve predation by seabream has been observed worldwide and is a major concern for bivalve farmers. Farmed bivalve-seabream interactions must be better understood to ensure the sustainability of bivalve aquaculture. The objectives of this study were to characterize gilthead seabream Sparus aurata presence in a bivalve farm in Prevost Lagoon (Mediterranean Sea) using acoustic telemetry and to evaluate monthly losses of mussels Mytilus galloprovincialis and oysters Crassostrea gigas due to seabream predation over an 18 mo period inside the farm and at an unprotected experimental platform. Large (281 to 499 mm TL) seabream were more commonly detected in the bivalve farm than were small (200 to 280 mm TL) seabream. In contrast to small seabream, 90% of large seabream returned to and spent extended periods in the study area the following year, suggesting inter-annual site fidelity for large fish that used the bivalve farm as a feeding site. Signs of predation were observed on mussels and oysters throughout the year at the unprotected experimental platform. Farmers noted losses in the farm from April to September. Maximal losses (90 to 100%) were observed post-oyster ‘sticking’ and mussel socking. Despite the deployment of nets as mechanical protection to reduce predation, oyster losses represented 28% of the annual value of oysters sold while mussel losses were estimated at ca. 1%. These results suggest that bivalves must be protected by nets throughout the year to avoid predation, particularly post-handling. A collaboration between shellfish farmers and fishermen could be a sustainable solution for bivalve farming, by regularly fishing for seabream in farms, between tables and inside protective nets.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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