(western) channel fisheries uk
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(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 - PowerPoint PPT PresentationTRANSCRIPT
(Western) Channel Fisheries UK
Trevor Hutton, Aaron Hatcher, Finlay Scott, Alyson Little, Charlie Edwards, Tom Carruthers
cemare Imperial College
IntroductionIntroduction
• 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
Area of study: boundariesArea of study: boundaries
Effort, F, SSB, LPUE, etcEffort, F, SSB, LPUE, etc
Long –term maximum yieldLong –term maximum yield
~ O.26
Stock recruitment relationshipStock recruitment relationship
Management and Enforcement issueManagement and Enforcement issue• Over quota (evidence of cod, sole)
• Declaring Sole (VIIe) as sole landed in VIId()
1975 1980 1985 1990 1995 2000 2005
05
00
10
00
15
00
Year
La
nd
ing
s
Sources of DataSources of Data
• SeaFish – economic data• MFA – enforcement data
UK beam >221kw (<30m)UK beam >221kw (<30m) Table 4.21.1 Segment characteristics in 2004 and 2005 2004 2005 No. of active vessels 38 36 Total power (kW) 18,801 17,990 Total VCU 14,964 14,384 Total GT 4,965 4,755 Total days at sea 7,535 7,457 Total volume catch (live weight) (T) 6,294 5,831 Value of landings (£m) 13.7 14.4
Technical characteristics
e.g. UK beam >221kw (<30m)e.g. UK beam >221kw (<30m) 2005
Average (£)
% of earnings
Earnings 407,400 100.0% Fishing income 400,700 98.4% Non fishing income 6,700 1.6% Costs Fishing expenses Commission 17,300 4.2% Harbour dues 7,700 1.9% Subscriptions & levies 3,400 0.8% Shore labour 2,000 0.5% Fuel & oil 114,300 28.1% Boxes 0 0.0% Ice 1,900 0.5% Crew travel 4,500 1.1% Food stores 10,000 2.5% Quota leasing 3,700 0.9% Days at sea 0 0.0% Other expenses 10,200 2.5% Crew share 107,900
26.5%
Total fishing expenses1 282,700 69.4% Vessel owner expenses Insurance 29,000 7.1% Repairs 80,900 19.9% Gear 24,700 6.1% Hire and maintenance 5,700 1.4% Other vessel owner expenses 3,600 0.9% Total vessel owner expenses2 140,500 34.5% Total expenses3 422,000 103.6% Net profit4 5 -20,500 -5.0% Depreciation n/a n/a Interest n/a n/a Net profit6 n/a n/a
1 4 5 6 These figures are the average of all vessels and therefore may not be the same as the total of individual items within each of these columns. 5 Net profit before deducting depreciation, interest and taxation 6 Net profit after deducting depreciation and interest, but before taxation
Added up all variable costs And all fixed costs
Economic characteristics
Enforcement data – FROM MFAEnforcement data – FROM MFAPort inspections
0.000
0.050
0.100
0.150
0.200
0.250
1999 2000 2001 2002 2003 2004 2005 2006 2007
year
pro
p i
nsp
ecte
d
Royal Navy inspections at sea
0.000
0.020
0.040
0.060
0.080
0.100
0.120
0.140
0.160
0.180
0.200
1999 2000 2001 2002 2003 2004 2005 2006 2007
year
pro
p in
sp
ecte
d
Enforcement data - CostsEnforcement data - Costs
Calculating Social BenefitCalculating 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)
Enforcement relationshipsEnforcement relationships
Bioeconomic modelBioeconomic 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
Catch over time (vary F: TAC + X)Catch over time (vary F: TAC + X)
Ca
tch
(t
onn
es)
Shadow value biomass Shadow value biomass
Harvest (tonnes)
Euros per tonne
V is social valueWe vary (e) thus x, And compute v and V
Maximise Social BenefitMaximise Social Benefit
• Demo…
FutureFuture
• 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.)