Inter‐ and intra‐specific interactions affecting crustacean trap fisheries—Implications for management
Bibliographic record
Abstract
Abstract The UK coastal trap fisheries target two key species, European lobster Homarus gammarus (L.) and brown crab Cancer pagurus L. Their stock status is assessed periodically using size‐based, yield‐per‐recruit analysis. Fishery trends are described using landings and, where available, effort data to estimate catch per unit of effort (CPUE), nominally proportional to abundance. Despite being caught together, assessments assume that concurrent capture of these species does not distort their individual CPUE estimates. Here, an in situ experiment tested impacts of inter‐specific and intra‐specific interactions by pre‐loading baited traps with different species and observing subsequent catches. Pre‐loaded European lobster significantly reduced brown crab catches, whereas, other species produced no such effects. The findings highlight the likely inconsistency of using CPUE as an index of abundance if landings data originate from a mixed‐species fishery in which species interactions and targeting behaviour of fishers are unknown or un‐quantified.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".