DEEPFISHMAN Data and data availability Stakeholder’s meeting Bruxelles 29-30 June 2009 Institute of Economic Studies Gunnar Haraldsson Socio-economic aspects - What are we looking at? • • • • • Sustainability (long-term) Profitability/Social benefits Employment Markets Cost of management The data • • • • • • • Construct a general bio-economic model applicable to each case study for which there exist appropriate data. Data requirements 1. Stocks 2. Harvest 3. Costs 4. Revenue 5. Various macroeconomic data 6. Various microeconomic data Basic characteristics • • • • The model should be 1. Dynamic 2. Stochastic 3. Capable of incorporating various management regimes (which?) What data is ‘easily’ available • Macroeconomic data (economic and social data) – Unemployment rates – Wage developments – ... What data is not so easily available? • Microeconomic data – Cost data (fuel, labor, gear, effort indices) – Prices • Soft data – Institutional setting – Fisheries management measures (official/unofficial) Case studies • • • • • • • • • • • • • • Case study 1 – Directed single species fisheries:Highly vulnerable - orange roughy in Namibian waters – NatMIRC Highly vulnerable - orange roughy in ICES VI &VII – MI Less vulnerable - blue ling (Molva dypterygia) in Vb,VI ,VII – Cefas Case study 2 – Mixed demersal fishery:French trawl fishery for roundnose grenadier (Coryphaenoides rupestris), black scabbardfish, deep-water sharks in Vb, VI and VII – IFREMER Case study 3 – Artisanal fisheries : Vulnerable : -Fisheries for red (blackspot) seabream in the Gibraltar Strait and Bay of Biscay– IEO -Fisheries for red (blackspot) seabream in the eastern Mediterranean– HCMR Less vulnerable : -Portuguese fishery for black scabbardfish in IX –IPIMAR Case study 4 – Data rich stock – NE Atlantic redfish -IMR Case study 5 – Data- rich stock - Greenland halibut stocks in the NAFO area – IEO Case studies • • • • We can do a socio-economic description of each case Bioeconomic modeling for selected cases We rely heavily on receiving data from case study leaders and on collaboration with our colleagues in the scientific community Stakeholder’s participation is very important An example: Comparison between actual and optimal harvest. Actual harvest Static optimal 1-d feedback 2-d feedback 1400 1200 Harvest 1000 800 600 400 200 0 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
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