Enforcement of the Icelandic cod fishery – A two management control, two enforcement tool fishery – Ragnar Arnason Preliminary results from the Cobecos.

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Presentation transcript:

Enforcement of the Icelandic cod fishery – A two management control, two enforcement tool fishery – Ragnar Arnason Preliminary results from the Cobecos Project Presented at the Special Workshop for the EU Commission and EU Fisheries Control Administrations Bruxelles, December 3, 2008

Background Icelandic cod fishery –Quite sizable (MSY  m.mt; landed value  m.US$) –Currently depressed (biomass  0.7 m.mt.; OSY biomass  1.2 m.mt) –Capitalistic fishery- fishers are profit maximizers About 700 fishing vessels (some multi-purpose) About 60 landing places –Managed on the basis of ITQs Individual harvest restrictions Also area/time/gear restrictions –Quite profitable (quota rental values 2-3 US$/kg)

Icelandic cod: Sustainble depiction

Enforcement Situation Enforcement agencies –The Fisheries Directorate (the key agency) –Assisted by the Coast Guard Two management tools –The quota constraint ─ the key management control –Fishing area/time/gear restrictions ─ mix of controls Two enforcement tools –Enforcement of harvest or quota –Enforcement of area/time/gear restrictions

Modelling the situation Fishers’ Benefits Social Benefits Harvest Mesh size Biomass Enforcement of harvest Enforcement of mesh size

Functional specifications Fishers’Profit function: Cost coefficient: Biomass growth function:

Functional specifications (cont.) Probability function 1: Probability function 2: Cost of enforcement:

Empirical specifications

Empirical Specifications

Benefits from harvest (  =0.5) Private benefits Social benefits

Mesh-size effect on biomass growth (million metric tonnes)  =1  =0.5

Fishers’ benefits Social benefits Benefits from alpha (Harvest=0.215)

Probability of penalty Enforcement of harvests Enforcement of “mesh-size” Enforcement effort Probability of penalty

Model calculations (to find optimal enforcement mix) Mathlab-code –(Mathlab: Standard general numerical package) Have developed a stand-alone Mathlab-code –To be used on all Windows-based computers

Results (Target: Harvest: m.mt; Mesh size: 1)

Optimizing surfaces

Sensitivity to fines

Sensitivity analysis

Findings 1.Application of enforcement theory to real fisheries enforcement situations is quite feasible –N actions and M enforcement tools –Data is the main constraint 2.Benefits of enforcement may be great compared to the costs –Depends on the fishery and the fisheries management system 3.Optimal enforcement complicated –Few simple rules of thumb

END

Figure 3 Private benefits Social benefits Private benefits Social benefits

Sustainble benefits (  =0.1) Costs Sustainble benefits Sustainble revenues

Private Profit function  =1  =0.5  Fishers would like α=0.5!