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(Western) Channel Fisheries UK

Explore the enforcement relationships and economic characteristics in the Western Channel fisheries of UK, focusing on maximizing social benefit. Utilize a bioeconomic model to estimate enforcement efforts for sustainable management.

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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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