Implementing the landing obligation - what costs are involved for the shrimp fisheries sector? : a brief overview
Bibliographic record
Abstract
Because the current period of the de minimis exemption under the European landing obligation expires, this exemption must be reapplied for in the submission of the Joint Recommendation (JR) in May 2023. For this purpose, it was agreed that the costs involved in the introduction of the landing obligation for the shrimp fishery will be investigated and substantiated. The Ministry of LNV has therefore commissioned Wageningen Marine Research (WMR) and Wageningen Economic Research (WEcR) to investigate and report on the additional costs associated with the implementation of the landing obligation in the shrimp fishery sector. This study is a semi-quantitative study that provides an overview of the difficulties and constraints in implementing the landing obligation in the shrimp fishery and, where possible, an indication of the costs of implementation. An expert session and interviews with fishers and trained observers identified the critical factors that determine the cost of implementing the landing obligation. In addition, from two observer trips estimations of the extra costs and duration of the sorting process were made. The results show that, taking into account all aspects concerning duration of the process, extra costs of material, time and personnel, safety aspects and practical implementation, implementing the landing obligation for Dutch shrimp fisheries seems for most vessels very difficult or even not possible. Many issues were identified and the results show that even for the part of the fleet where sorting is possible (due to the presence of a sorting belt), it will either lead to considerable extra costs due to significant changes to vessels and crew or will on the other hand lead to loss of income. For all other vessels without a sorting belt implementing the landing obligation is not possible. Extra costs and time are also directly related to the amount and composition of bycatch, which is different over the seasons and locations. Significant amounts of different fractions of bycatches are obtained during all quarters, and total bycatch amounts were in general proportionally larger in quarters where the fishing effort and shrimp landings were higher. An exception is benthos which was proportionally highest in quarter 3. Large amounts of other bycatch than TAC species, such as high proportions of benthos, influences time and effort to sort out TAC species. For shrimp vessels in the fleet section >260 hp vessels with combined fisheries (MFL1) costs for sorting the TAC fish were calculated. If these vessels are obliged to sort undersized catches of TAC species, the total labour time onboard will be more than doubled. For three options based on the options that are available for fishermen to react to this obligation the effects were calculated. 1. If the total share of the revenue for the crew stays the same, the share per crew member halves. Due to the extra sorting time needed for the TAC fish, the crew has to be more than doubled. 2. If the ship owner pays the same share per crew member and hires the extra crew needed, all the extra costs due to the sorting of the undersized TAC fish lead to a negative profit. 3. If the number of crew members and the fishing effort stay the same, the number of hauls per fishing trip will need to be reduced due to the extra sorting time for the undersized TAC fish. The total revenue will be reduced proportionally with the reduction in hauls. This leads to a negative profit and halving the share of per crew member. For the three calculated scenarios, the revenue per crew member either at least halves, the net profit becomes negative, or both. As a result, implementation of the landing obligation in the Dutch shrimp fishery is not economically feasible. Alternatively, there should be room for innovating gears and vessels leading to less bycatch of undersized fish in the future. However, adjustment of the fleet requires time, research and investments.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".