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COBECOS Case study on Icelandic cod

COBECOS Case study on Icelandic cod. Overview. Common types of violations Modeling approach Using COBECOS code Using our own code Results Conclusions. Types of violations. Quota and fishing permit violations Landing violations Gear violations, e.g. mesh size Area closure violations

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COBECOS Case study on Icelandic cod

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  1. COBECOSCase study on Icelandic cod

  2. Overview • Common types of violations • Modeling approach • Using COBECOS code • Using our own code • Results • Conclusions

  3. Types of violations • Quota and fishing permit violations • Landing violations • Gear violations, e.g. mesh size • Area closure violations • Utilization factors exaggeration • Ice percentage exaggeration • Discarding

  4. Basic model Private benefits Social benefits

  5. The COBECOS code • Set up for one quantity violation • What violation to include? • Should other violations be transformed into quantity violations? • What about possible interdependence between different types of violations and different types of effort?

  6. Our own model • No limit to the number of management tools or enforcement measures • Current version includes the following types of violations • Landing/quota violations • Mesh size violations • Utilization factor/ice percentage exagg. • Discarding

  7. Private benefits • Pure private benefits • where a is a mesh size index and q is relative discards • and where • mesh size affects costs: • discarding affects price:

  8. Private benefits • Full private benefit function where f is the relative exaggeration of utilization (or ice percentage) and were is the function relating the enforcement effort and the probability of getting fined

  9. Social benefits where

  10. Parameter estimates

  11. Parameter estimates

  12. Optimization • Two-tiered maximization procedure • enforcement agency selects values for enforcement effort • fishermen respond by choosing profit maximizing harvest, mesh size, reported utilization factor and discard rate. • enforcement agency selects new enforcement efforts… • continues iteratively until the optimal enforcement effort has been located. • Uses standard numerical search routine in MATLAB

  13. User interface • Runs in a free runtime environment • Allows changes to key parameters

  14. Results

  15. Private benefits and mgt targets

  16. Social benefits and enf. efforts

  17. Sensitivity analysis

  18. Conclusions • The benefits from enforcement are much larger than the costs • Enforcement effort should be increased to optimize social benefits • specifically for landing and utilization factor • Optimal effort depends on the parameters of the model in complex ways

  19. Conclusions • It is feasible to model a relationship with multiple management measures and types of enforcement • The biggest obstacle to building complex models of fisheries enforcement is the lack of data

  20. Atlantic cod (Gadus morhua)

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