Analysis of the Flemish Cap cod fishery: monitoring of the consequences of the management decisions
Bibliographic record
Abstract
The objective of this document is to present the necessary information to the SC to monitor the consequences of \nthe implementation in January 1st 2021 by the Commission of the technical measures in fisheries targeting cod in \nDiv. 3M. The technical measures implemented were the closure of the cod directed fishery in Div. 3M in the first \nquarter of the year and the use of sorting grids in the cod directed trawl fishery. Data from the haul by haul \ndatabase in the period 2016-2022 provided by the NAFO Secretariat have been used to study the situation before \n(2016-2020) and after (2021-2022) the measures were in place in the cod directed fisheries and in the fisheries \nwith bycatch of cod. Also, the length and age distributions used in the assessment of this stock have been analysed. \nIt should be noted that, apart from the technical measures implemented since 2021, in the 2021-2022 period the \nTAC of 3M cod suffered a large reduction due to the stock situation. This large reduction in the TAC may make it \ndifficult to interpret the changes observed in the fisheries after 2021, interfering in the interpretation of this \nanalysis. In order to have a clear idea and describe appropriately the consequences of the implementation of \ntechnical measures, a longer series of data after implementation needs to be analysed. \nPrior to 2021, most of the cod catches from the directed fisheries were taken in the first quarter and in the east \nand southwest of the bank for the longliners and in the southwest for the trawlers. Since 2021 catches are mainly \ntaken in the second quarter and they are concentrated in the central part of Flemish Cap bank for the longliners \nand in the southwest of Flemish Cap for the trawlers. Almost 100% of the cod catches made with longline gear \nhave been made in hauls targeting cod both before and after the technical measures were implemented. In the \ncase of cod catches made in trawl hauls targeting cod that percentage dropped from over 96% in the 2016-2020 \nperiod to 85-88% in the 2021-2022 period. No significant change has been observed after the implementation of \nthe technical measures in the catch composition and bycatch levels of the hauls directed to cod neither by longline \nnor trawl gears. In both directed fisheries, longliners and trawlers, the percentage of catches and effort inside the \nVME polygons in 2021-2022 is much lower than in 2016-2020. \nThe bycatch of cod in the longline hauls targeting other species is negligible in the whole period 2016-2022. Cod \nbycatch in trawl hauls targeting other species increased significantly after the technical measures were \nimplemented, mainly in 2022. No major change has been observed in the spatial-temporal pattern of sets catching \ncod as bycatch before and after the implementation of the technical measures. The impact on vulnerable marine \necosystems of longline sets catching cod as bycatch is minimal in both periods. Regarding the trawl hauls catching cod as bycatch, it should be noted the increase in effort carried out within the VME polygons of sponges and large \ngorgonians in the southwestern part of the Flemish Cap in 2022. \nFrom the analysis of the total length and age distribution of the cod catches, it can be concluded that, after the \nimplementation of the technical measures, in the longline the proportion of intermediate lengths (42-54 cm) and \nages (4-5 years) has increased in the period of implementation of the technical measures, while the proportion \nof larger individuals (>99 cm) decreased. In trawling fishery, the proportions of smaller lengths (<45 cm) and the \nyounger ages (1-3) have decreased after the implementation of the technical measures.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".