Prey preferences of adult sea bass Dicentrarchus labrax in the northeastern Atlantic: implications for bycatch of common dolphin Delphinus delphis
Bibliographic record
Abstract
Abstract Spitz, J., Chouvelon, T., Cardinaud, M., Kostecki, C., and Lorance, P. 2013. Prey preferences of adult sea bass Dicentrarchus labrax in the northeastern Atlantic: implications for bycatch of common dolphin Delphinus delphis – ICES Journal of Marine Science, 70: 452–461. In the northeastern Atlantic, adult sea bass (Dicentrarchus labrax) is one of largest fish living on the shelf, and this species has important commercial value. However, pelagic trawl fisheries that target sea bass have negative operational interactions with common dolphins (Delphinus delphis). Our goal was to determine the diet of adult sea bass in the Bay of Biscay from stomach-content and stable-isotope analyses, and explore the dietary overlap between sea bass and common dolphins. We found that sea bass primarily target small pelagic fish, most notably mackerel (Scomber scombrus), scads (Trachurus spp.), anchovy (Engraulis encrasicolus), and sardine (Sardina pilchardus). These four species also dominated the diets of common dolphins. This overlap in feeding preferences could increase the risk of dolphins being caught by trawl fisheries while feeding among sea bass, and may be an underlying mechanism to explain the high rate of common dolphin bycatch observed in the pelagic trawl fishery for sea bass in the Bay of Biscay. Understanding the foraging ecology and trophic interactions of predator species is an essential step for identifying and resolving management issues in the northeastern Atlantic and other marine ecosystems.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".