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(Western) Channel Fisheries UK

(Western) Channel Fisheries UK Trevor Hutton, Aaron Hatcher, Finlay Scott, Alyson Little, Charlie Edwards, Tom Carruthers. cemare. Imperial College. Introduction. English Beam trawlers in South West (VIIe) High value fishery (£4.7 million) with regional importance

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(Western) Channel Fisheries UK

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  1. (Western) Channel Fisheries UK Trevor Hutton, Aaron Hatcher, Finlay Scott, Alyson Little, Charlie Edwards, Tom Carruthers cemare Imperial College

  2. Introduction • English Beam trawlers in South West (VIIe) • High value fishery (£4.7 million) with regional importance • Mixed demersal fishery – we focus on sole • Historically, high level of misreporting (landings) • Stock status – CPUE trends down, F above Fpa, Beamer effort increasing

  3. Area of study: boundaries

  4. Effort, F, SSB, LPUE, etc

  5. Long –term maximum yield ~ O.26 Stock recruitment relationship

  6. Management and Enforcement issue • Over quota (evidence of cod, sole) • Declaring Sole (VIIe) as sole landed in VIId()

  7. Sources of Data • SeaFish – economic data • MFA – enforcement data

  8. Technical characteristics UK beam >221kw (<30m)

  9. Economic characteristics e.g. UK beam >221kw (<30m) Added up all variable costs And all fixed costs

  10. Enforcement data – FROM MFA

  11. Enforcement data - Costs

  12. Calculating Social Benefit • Fit enforcement relationships: • Cost of enforcement vs enforcement effort • Cost of enforcement vs probability of detection • Estimate Shadow Value Biomass using bioeconomic model • Estimate enforcement effort that maximises Social Benefit (using WP6 code)

  13. Enforcement relationships

  14. Bioeconomic model • Simple projection model starting from latest WG assessment. • Fitted stock-recruitment relationship • Examined various overfishing scenarios by projecting under a range of constant F values • E.g. No overfishing F = Fpa , harvest = TAC • Scenarios with higher F assumed to have lower enforcement effort • Make a small change in initial biomass level, project forward again. • Estimate profit and Shadow Value Biomass

  15. Catch over time (vary F: TAC + X) Catch (tonnes)

  16. V is social value Shadow value biomass We vary (e) thus x, And compute v and V Euros per tonne Harvest (tonnes)

  17. Maximise Social Benefit • Demo…

  18. Future • Estimate enforcement efforts that maximise Social Benefit • Explore effects of different levels of enforcement efforts • Conduct ‘sensitivity’ analysis – see changes in surface under alternative scenarios (e.g. alternative values of SVB, costs etc.)

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