COBECOS mid-term meeting, 2-3 September 2008, San SebastianCOBECOS mid-term meeting, 2-3 September 2008, San Sebastian

Italian case study: GSA 9 bottom trawling fishery

Status of model estimation at September 2008

COBECOSCOBECOSCosts and Benefits of Control Costs and Benefits of Control

StrategiesStrategies

Paolo Accadia (accadia@irepa.org)

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LayoutLayout Brief description of the case studyBrief description of the case study Management and enforcement systemManagement and enforcement system Data available (to be available)Data available (to be available) Penalty probability function Penalty probability function Private cost of violationPrivate cost of violation Enforcement cost functionEnforcement cost function Private benefit functionPrivate benefit function Social benefit functionSocial benefit function

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The case study area: GSA 9 The case study area: GSA 9

GSA 9GSA 9

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Fleet and speciesFleet and species The fishery under analysis is multi-species (>45) and multi-The fishery under analysis is multi-species (>45) and multi-

gear (trawling is predominant but many vessels are gear (trawling is predominant but many vessels are authorised to fish with more than 1 gear). The fleet is authorised to fish with more than 1 gear). The fleet is divided in three fleet segments:divided in three fleet segments:

TrawlsTrawls Small scaleSmall scale PolyvalentPolyvalent

The polyvalent and small scale fleets use a combination of The polyvalent and small scale fleets use a combination of fishing gears. Polyvalent are vessels over 12 m in length, fishing gears. Polyvalent are vessels over 12 m in length, while small scale vessels are under 12 m in length.while small scale vessels are under 12 m in length.

Target species are: hake, mullet, octopus, shrimp and Target species are: hake, mullet, octopus, shrimp and lobster. These are medium migratory species. Hake is a long lobster. These are medium migratory species. Hake is a long live species (up to 20 years) while the others are medium live species (up to 20 years) while the others are medium live species (not >4 years). In the bio-economic model live species (not >4 years). In the bio-economic model simulations are performed for the following species:simulations are performed for the following species:

European hakeEuropean hake Striped mulletStriped mullet ShrimpShrimp Other speciesOther species

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Management systemManagement systemMeasures regulating bottom trawling in GSA 9 are the ones Measures regulating bottom trawling in GSA 9 are the ones applied at national level. In Italy, the trawling activity is applied at national level. In Italy, the trawling activity is managed trough a combination of input control and technical managed trough a combination of input control and technical measures, consisting in:measures, consisting in:

1.1.Input control measures:Input control measures:• fishing activity regulated by a closed license scheme;fishing activity regulated by a closed license scheme;• seasonal withdrawal of the fishing activity during seasonal withdrawal of the fishing activity during

certain period, generally in the summer months. certain period, generally in the summer months. • technical stop of the fishing activity on Saturday and technical stop of the fishing activity on Saturday and

Sunday.Sunday.

2.2.Technical measures:Technical measures:• minimum distance from the coast;minimum distance from the coast;• minimum mesh size;minimum mesh size;• minimum landing size for some target species.minimum landing size for some target species.

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Enforcement systemEnforcement system The main body responsible for the control on the fishery The main body responsible for the control on the fishery

sector is the “Guardia Costiera” .sector is the “Guardia Costiera” . Other military corps (Carabinieri, Guardi di Finanza, Polizia, Other military corps (Carabinieri, Guardi di Finanza, Polizia,

etc..) have a subsidiary responsibility in the fishery control.etc..) have a subsidiary responsibility in the fishery control. Three enforcement tools are considered in this case study: Three enforcement tools are considered in this case study:

Landing inspections;Landing inspections; Inspections at sea;Inspections at sea; Inspections at sea with aircraft support.Inspections at sea with aircraft support.

The inspection reports do not describe in very detail the The inspection reports do not describe in very detail the type of elementary control made. It is assumed that each of type of elementary control made. It is assumed that each of the enforcement tools can investigate on all types of the enforcement tools can investigate on all types of violation.violation.

At the moment, based on the data available, violations are At the moment, based on the data available, violations are classified as follow:classified as follow: Fishing without holding a fishing licenceFishing without holding a fishing licence Using or keeping on board prohibited fishing gearsUsing or keeping on board prohibited fishing gears Unauthorized fishing.Unauthorized fishing.

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Data for the enforcement Data for the enforcement functionsfunctions

Data available:Data available: Infringements and fines by type of behaviour;Infringements and fines by type of behaviour; Inspections and sanctions by enforcement tool (not for Inspections and sanctions by enforcement tool (not for

the entire area GSA9 and not for inspections at sea with the entire area GSA9 and not for inspections at sea with aircraft support).aircraft support).

Data to be available:Data to be available: Inspections by enforcement tool;Inspections by enforcement tool; Infringements, sanctions and fines by type of behaviour Infringements, sanctions and fines by type of behaviour

and enforcement tool;and enforcement tool; Average cost per hour of people employed by Average cost per hour of people employed by

enforcement tool, and number of hours;enforcement tool, and number of hours; Average cost per hour of the aircrafts employed in Average cost per hour of the aircrafts employed in

fishery control, and number of hours;fishery control, and number of hours; Average cost per nautical mile of the ships employed in Average cost per nautical mile of the ships employed in

fishery control, and number of miles.fishery control, and number of miles.

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Penalty Probability Penalty Probability Function (1)Function (1)

Enforcement effort, Enforcement effort, ee, is measured in terms of number of , is measured in terms of number of inspections.inspections.

Under the assumption that a vessel is not inspected twice Under the assumption that a vessel is not inspected twice in a day, the maximum number of inspections in a year in a day, the maximum number of inspections in a year equals the total number of days at sea for a fleet.equals the total number of days at sea for a fleet.

As fishing effort As fishing effort EE is estimated in terms of number of is estimated in terms of number of days at sea:days at sea: max( max(ee) = ) = EE..

Assuming that an inspection of a violating vessel always Assuming that an inspection of a violating vessel always produces a sanction:produces a sanction:

When all units of fishing effort are inspected, the When all units of fishing effort are inspected, the probability to be sanctioned when violating is 1: probability to be sanctioned when violating is 1:

((EE) = 1) = 1

V)| ()| ()(π CpVSpe

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Penalty Probability Penalty Probability Function (2)Function (2)

The penalty probability function can be estimated as the The penalty probability function can be estimated as the ratio between sanctions and violations:ratio between sanctions and violations:

((ee) = p(S|V) = S/V) = p(S|V) = S/V V = ?V = ? Assuming that for an enforcement tool, vessels to be Assuming that for an enforcement tool, vessels to be

inspected (or a sample of them) are randomly selected. By inspected (or a sample of them) are randomly selected. By using the number of inspections and related sanctions, the using the number of inspections and related sanctions, the total number of violations V can be estimated as follow:total number of violations V can be estimated as follow:

Ee

SV

r

r Penalty probability function

0,00

0,20

0,40

0,60

0,80

1,00

1,20

0 5000 10000 15000 20000 25000 30000 35000

e

p(e

)

E

Land

E

e

Ee

SS

V

Se r

r

r

rrr )(

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Penalty Probability Penalty Probability Function (3)Function (3)

When vessels to be inspected are not randomly selected, the When vessels to be inspected are not randomly selected, the penalty probability function can be estimated as follow:penalty probability function can be estimated as follow:

Assuming a quadratic function for the probability of penalty:Assuming a quadratic function for the probability of penalty:

Coefficients can be estimated on the data as follow:Coefficients can be estimated on the data as follow:

yyr

yr

ynrynrynr

yy

Ee

S

See

EE

,

,

,2,,

2 1

Penalty probability function

0,00

0,20

0,40

0,60

0,80

1,00

1,20

0 5000 10000 15000 20000 25000 30000 35000

e

p(e

)

E

Sea

Land

)(

1

,,,

,,,,

2

ynryyynryr

ynryryrynr

y

y

eEEeS

eSeS

E

E

E

e

S

S

V

Se r

r

nrnrnr )(

2)( nrnrnr eee

Ee

SV

r

r

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The private cost of violation for a fleet by The private cost of violation for a fleet by violation violation ii and enforcement tool and enforcement tool jj is estimated is estimated as follow:as follow:

Under the assumption: Under the assumption:

Private cost of violationPrivate cost of violation

j

jiji e )()( e

j

jijiii eVf )(

i jjijii

ii eVf )(

iiii Vf)(e

j

jiji e )()( e

nmee ninmim 0)()(

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Enforcement cost functionEnforcement cost function

As in this case study enforcement is measured in terms of As in this case study enforcement is measured in terms of number of inspections, the enforcement effort can be number of inspections, the enforcement effort can be obtained as a production function where production factors obtained as a production function where production factors are:are: Man-hours employed in landing inspections;Man-hours employed in landing inspections; Man-hours employed in inspections at sea; Man-hours employed in inspections at sea; Flight-hours in activity of fishery control;Flight-hours in activity of fishery control; Nautical miles for activity of fishery control;Nautical miles for activity of fishery control;

The cost of enforcement can be estimated as a linear The cost of enforcement can be estimated as a linear function of the production factors:function of the production factors: Landing inspections;Landing inspections; Inspections at sea;Inspections at sea; Inspections at sea with aircraft support.Inspections at sea with aircraft support.

where where , , ’’, , and and represent the unit costs of the represent the unit costs of the production factors.production factors.

LmanHeC )( 11

shipSman MHeC )( 22

flightshipSman HMHeC )( 33

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Private Benefit FunctionPrivate Benefit Function Short run bio-economic simulation model. Short run bio-economic simulation model. Multi-fleet and multi-species model.Multi-fleet and multi-species model. Full-compliance model

Economic box

State VariationBiological box

t = t+1

Management

Tax

Subsidies

Activity

Capacity

Activity

Capacity

Selectivity

Catch Profit

Activity

Capacity

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Fishing mortalityFishing mortality Population of age Population of age a+1a+1 at time at time t+1t+1 is calculated as follow: is calculated as follow:

The total mortality for the age-class The total mortality for the age-class aa at time at time tt is obtained by the is obtained by the fishing mortality and the natural mortality rates:fishing mortality and the natural mortality rates:

ZZa,ta,t = = FFa,ta,t + + MMa,ta,t . . The fishing mortality for the age-class The fishing mortality for the age-class aa at time at time tt, , FFa,t a,t , is obtained , is obtained

by the fishing mortality rates associated to each fishing gear-by the fishing mortality rates associated to each fishing gear-fleet operating in the area:fleet operating in the area:

FFa,ta,t = = FFa,t,ga,t,g

The fishing mortality for the age-class The fishing mortality for the age-class aa at time at time tt associated to associated to the fishing gear-fleet the fishing gear-fleet gg is a function of selectivity, catchability is a function of selectivity, catchability and effort:and effort:

FFa,t,ga,t,g = = SSa,t,ga,t,g q qt,gt,g E Et,gt,g Catches per fishing gear are estimated by the following equation:Catches per fishing gear are estimated by the following equation:

taZtata eNN ,

,1,1

a gta

gtaZtaagt Z

FeNwC ta

,,

,,,, )1( ,

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Effects of violation on the Effects of violation on the fishing mortalityfishing mortality

Different types of infractions can affect the components of Different types of infractions can affect the components of the fishing mortality: the fishing mortality: Fishing without holding a fishing licence is supposed to Fishing without holding a fishing licence is supposed to

affect fishing effort:affect fishing effort:FFa,t,ga,t,g = = SSa,t,ga,t,g q qt,gt,g (E (Et,gt,g + V + Vt,gt,g))

Using or keeping on board prohibited fishing gears is Using or keeping on board prohibited fishing gears is supposed to affect selectivity:supposed to affect selectivity:FFa,t,ga,t,g = = SSa,t,ga,t,g q qt,gt,g E Et,gt,g + + SS’’a,t,ga,t,g q qt,gt,g V V’’’’t,gt,g

Unauthorized fishing is supposed to affect catchability:Unauthorized fishing is supposed to affect catchability:FFa,t,ga,t,g = = SSa,t,ga,t,g q qt,gt,g E Et,gt,g + + SSa,t,ga,t,g q q’’t,gt,g V V’’’’’’t,gt,g

The same unit of effort can violate more than 1 fishery The same unit of effort can violate more than 1 fishery rule. So, fishing mortality should be estimated as a rule. So, fishing mortality should be estimated as a combination of the above equations.combination of the above equations.

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Social Benefit FunctionSocial Benefit Function

)(),( eqλxq CB

How can the shadow value of biomass be estimated by a simulation bio-economic model?

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Thank you for the Thank you for the attention!attention!

Paolo Accadia (accadia@irepa.org)Paolo Accadia (accadia@irepa.org)