Pulse fishing and its effects on the marine ecosystem fisheries : an update of the scientific knowledge
Bibliographic record
Abstract
This report summarises the knowledge on the effects of pulse trawls used in the North Sea fishery for flatfish and brown shrimp.The report describes the electrical characteristics of the pulse trawl systems currently used (potential difference over electrode pairs, pulse frequency, pulse width, duty cycle and dimensions of the gear).The shrimp pulse applies a low frequency pulse that invokes a startle response (tailflip) in shrimps.The sole pulse applies a higher frequency that invokes a cramp response that immobilise the fish species facilitating the catching process.Electrical stimulation changes the species selectivity of the trawl.The catch efficiency of the pulse trawl for sole is higher, and the catch efficiency for plaice and other fish species is lower, when expressed in terms of the catch rate per swept area.It is uncertain whether the pulse trawl has a better size selectivity (reduced bycatch of undersized fish), but all experiments show that the bycatch of benthic invertebrates is substantially reduced.Applying electrical stimulation in the fishery for brown shrimp, offers a promising innovation to reduce the bycatch of fish and benthic invertebrates, while maintaining the catch rate of marketable sized shrimps.The reduction in bycatch depends on the design of the net, in particular the specifics of the groundrope.In ecological terms, the replacement of the tickler chains with electrodes and a lower trawl footprint constitute a highly positive contribution to diminishing the impact of trawling on the North Sea benthic ecosystem.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".