University of Toronto T-Space · Web viewCatchability estimation sub-module3 Fishing mortality module4 Population dynamics module5 Catch, discards and landings module5 Market/price

Supplementary material

Contents

Fleet composition and characteristics by Producer Organization..........................................................2

Variables and equations of the IAM base model....................................................................................2

Notations...........................................................................................................................................2

Modules description...............................................................................................................................3

Fishing mortality and discards survival modules................................................................................3

Fishing mortality allocation sub-module........................................................................................3

Catchability estimation sub-module..............................................................................................3

Fishing mortality module...............................................................................................................4

Population dynamics module.............................................................................................................5

Catch, discards and landings module.................................................................................................5

Market/price module.........................................................................................................................6

Economic module..............................................................................................................................7

Model parameters................................................................................................................................11

Evolution of fleet structure..................................................................................................................13

Indicators related to the ecological dimension....................................................................................15

Indicators related to the economic dimension.....................................................................................17

Decomposition of the Theil index....................................................................................................19

Indicators related to the social dimension...........................................................................................21

Sensitivity analysis................................................................................................................................23

1

Fleet composition and characteristics by Producer Organization

Table S1 – Number of vessels and average characteristics by Producer Organization in the Bay of Biscay sole fishery in 2014 (vessels with landings > 1 metric ton).

Variables and equations of the IAM base model

This section provides detail on the different variables and equations of the IAM base model. It is adapted from the following working paper:

Merzéréaud, M., Macher, C., Bertignac, C., Frésard, M., Le Grand, C., Guyader, O., Daurès, F., and Fifas, S. 2011. Description of the Impact Assessment bio-economic Model for fisheries management (IAM), Amure Electronic Publications, Working Papers Series D-29-2011, 19 pp. Available at: http://www.umr-amure.fr/electro_doc_amure/D_29_2011.pdf.

Note that the equations presented in this on-line supplement correspond to the vessel-based version of the IAM model, whereas Merzéréaud et al. (2011) described an earlier fleet-based version of the model.

Notations

The parameters of the bio-economic model use the following indices:

Table S2 – Definition of indices used in the model description.

Symbols Descriptiont timei vesself fleets speciesm métieras age (depends on species)cs category (depends on species)

Producer Organization

Nb vessels

Share of the total number of vessels

of the PO (%)

Main fleet segments

Sole Landings

(Tons)

Sole dependency

(% GR)

Pêcheurs de Bretagne

145 18.2Mixed bottom trawlersNephrops trawlers

6.1 14.2

OPPAN 25 26.9 Sole netters 18.5 43.1

OP VENDEE 56 40.6Mixed bottom trawlersSole netters

12.9 33.7

FROM SUD-OUEST

23 23.5Sole nettersMixed bottom trawlers

17.1 42.0

OP LA COTINIERE

56 54.9Mixed bottom trawlers

6.7 20.4

Pêcheurs d’Aquitaine

45 37.5 Sole netters 16.5 38.9

Non PO 9 Sole netters 2.0 23.1

2

For ease of notation, subscript s of indices a and c are dropped in the rest of this supplement.

Modules description

Fishing mortality and discards survival modules

This module is divided into two sub-modules. The first sub-module carries out the splitting of total mortality rate per vessel, using their ratio in catch or landings at age. The second sub-module calculates a catchability coefficient which is used in the simulation to relate the control variable “effort” to the fishing mortality applied to the stock.

Fishing mortality allocation sub-module

Initial parameters

Table S3 – Input parameters for the sub-module “Fishing mortality allocation”.

Notation Description

Finis,aInitial fishing mortality coefficient (here, by species and age)

Cs,i,m,aSplitting variable at a given level (here, catch by species, vessel, métier and age)

Ctots,aTotal splitting variable (must be defined at the crossing level of the two previous variables)

Calculated variable

Table S4 – Output parameters for the sub-module “Fishing mortality allocation”.

Notation Type Description Equation

Finis,i,m,a output Instantaneous fishing mortality coefficient Finis , i ,m ,a=

Fini s,a×C s ,i ,m ,a

Ctot s, a

Catchability estimation sub-module

The catchability coefficient is estimated from the initial fishing mortality and corresponding fishing effort. In the simulation, fishing mortality rates are calculated from fishing effort assuming constant

catchability.

Initial parameters

Table S5 – Input parameters for the sub-module “Catchability estimation”.


3

Einii,m Initial effort by vessel and métier

4

Calculated variables

Table S6 – Output parameters for the sub-module “Catchability estimation”.


qs,i,m,a Sortie Catchability (by species, vessel, métier and age)

qs ,i ,m ,a=Finis , i ,m , aEinii ,m

Fishing mortality module

This module uses the two methods described above. It produces fishing mortality partitioned into vessels and métier. The other category stands for residual fishing mortality not accounted for by the vessels or métier considered in the analysis.

Initial parameters

Table S7 – Input parameters of the module “Fishing mortality”.


ds,i,m,aPercentage of total catch discarded in number (by species, vessel, métier and age)

doths,aPercentage of total catch discarded in number by other vessels (by species and age)

srs Survival rate of discards (by species)Ei,m Effort by vessel and metier


Table S8 – Calculated parameters for module “Fishing mortality”


Ks,i,m,a Internal Correcting factor of fishing mortality linked to discards survival

K s, i ,m , a=1−sr s .ds , i ,m ,a

Frs,i,m,a,t OutputFishing mortality (by species, vessel, métier and age, at time t). Input for module Catch et Population dynamics

Frs ,i ,m ,a, t=qs , i ,m , a . Ei ,m , t .K s, i ,m ,a

Fr_oths,a OutputInitial mortality « other fleets, other métier » by species and age. Input for module Catch et Population dynamics

Froths,a

=(Fini s,a−∑i ,m

Finis , i ,m,a ,0 ).(1−sr s .doths, a )

5

Population dynamics module

Initial parameters

Table S9 – Initial parameters for the module “Population dynamics”

Notation DescriptionNs,a,t=0 Total number at age by species at t=0Ns,a=0,t Number of recruitsMs,a Natural mortality rate by age and speciesws,a Mean individual weight at age in the stock by species

Mats,a Proportion of mature individuals at age a by species


Table S10 – Calculated parameters for the module “Population dynamics”


Zs,a,t OutputTotal mortality rate (by species and age at time t). Input to module Catch.

Zs, a , t=M s ,a+∑i ,m

Fr s, i ,m ,a , t+Froths , a

Ns,a,t Output Number at age by species at time t.

N s, a+1, t+1=N s ,a , t .e−Z s ,a , t

, and

N s,a+1, t+1=N s ,a , t .e−Z s , a , t+N s ,a+1 ,t .e

−Zs , a+1 , t

for the ‘+ group’

Bs,t Output Total biomass by species at time t.

Bs , t=∑aN s , a , t .w s, a

SSBs,t Output Spawning stock biomass by species at time t.

SSBs , t=∑aMat s ,a .N s,a , t .w s , a

This module also includes multiple stock-recruitment functions (constant recruitment, Hockey-Stick, Beverton & Holt, Ricker, Shepherd) for determining Ns,a=0,t and allows for addition of a parameterizable noise.

Catch, discards and landings module

Initial parameters

Table S11 – Initial parameters in the module “Catch, discards and landings”


wDs,aAverage weight of discarded individual by species and age

wCs,aAverage weight of individual in the catch by species and age

6


Table S12 – Calculated parameters for the module “Catch, discards and landings”


Cs,i,m,a,t OutputCatch in numbers (by species, vessel, métier and age over period t).

C s ,i ,m , a, t=Frs ,i ,m ,a, tZs, a , t

×N s , a ,t×(1−e−Zs , a ,t )

Cs,a,t OutputCatch in numbers (by species and age over period t)

C s ,a, t=∑i ,m

Frs ,i ,m ,a, t+Froths ,aZ s,a , t

×N s ,a, t×(1−e−Z s ,a , t )

Ys,i,m,a,t OutputCatch in weight (by species, vessel, métier and age over period t).

Y s, i ,m ,a , t=wC s, a×C s , i ,m ,a ,t

Ys,a,t OutputCatch in weight (by species and age over period t).

Y s, a , t=wC s, a×C s , a ,t

Ds,i,m,a,t OutputDiscards in weight (by species, vessel, métier and age over period t).

Ds , i ,m ,a , t=ds , i ,m ,a×wDs , a×C s, i ,m ,a , t

if wD s, a is available,Ds , i ,m , a , t=ds , i ,m ,a×Y s , i ,m ,a ,t otherwise.

Ls,i,m,a,t Output

Landings in weight (by species, vessel, métier and age over period t). Input in module Market.

Ls , i ,m ,a ,t=Y s ,i ,m ,a, t−D s, i ,m ,a , t

Market/price module

The market/price module has two functions. The first function is to aggregate productions by age and species into productions by grade and species according to an age-grade key matrix. The second function is to calculate the price by grade and species that can either be an input parameter or result from a price model function (of the production by grade, the importations, exportations etc.). In the second case parameters of the price model are included in the input file. The following table gives an example of price function that can be implemented in the model.

Initial parameters

Table S13 – Initial Parameters for the “Market/price” module

Notation Descriptionα s , c Constant of the price model specific to each commercial grade c

βs , c Price elasticity of grade c

γs , c Cross elasticity with other grades for grade cicats,a,c Transformation Matrix for age/grade by species: Pe(c/a)

7


Table S14 – Variables calculated for the “Market/price” module


Ls,i,m,c,t Internal Catches in Weight (by species, vessel, metier, grade for t)

Ls , i ,m ,c , t=∑a

(Ls ,i ,m, a, t×icat s,a , c )

Ps,c,t Output Mean price (by species, grade for t) input of the economic module

lnP s, c ,t=α s, c+β s, c×ln(∑i ,m

Ls, i ,m, c ,t )

+γ s, c×ln ( ∑i ,m , cat≠c

Ls ,i ,m ,cat ,t )

Economic module

The economic module produces indicators of performances for consumers, state and producers including indictors for the whole fishery, by fleet, and by vessel.The economic module relies on input data based on data collected within the DCF 1 as well as data from the SACROIS data source which is an algorithm crossing multiple existing data sources (auction halls, logbooks, dealer reports) to provide the best possible estimation of effort and production by vessel at the trip level (source: IFREMER/Fisheries Information System/DPMA). Appendix VI of the European Decision No 199/2008 gives the following list of economic variables to be collected by fleet and member state. Table S15 – Economic and transversal variables collected within the appendix VI (EC) No 199/2008

Variable Group Variable

Income

Gross value of landingsIncome from leasing out quota or other fishing rightsDirect subsidiesOther income

Personnel costs Wages and salaries of crewImputed value of unpaid labour

Energy costs Energy costsRepair and maintenance costs Repair and maintenance costs

Other operational costsVariable costsNon-variable costsLease/rental payments for quota or other fishing rights

Capital costs Annual depreciation

Capital valueValue of physical capital: depreciated replacement valueValue of physical capital: depreciated historical valueValue of quota and other fishing rights

Investments Investments in physical capital

1 COMMISSION DECISION 2008/949/EC of 6 November 2008, adopting a multiannual Community programme pursuant to Council Regulation (EC) No 199/2008 establishing a Community framework for the collection, management and use of data in the fisheries sector and support for scientific advice regarding the common fisheries policy.

8

Financial position Debt/asset ratio

EmploymentEngaged crewFTE NationalFTE harmonised

Fleet

NumberMean LOAMean vessel's tonnageMean vessel's powerMean age

Effort Days at seaEnergy consumption

Number of fishing enterprises/units Number of fishing enterprises/units

Production value per species Value of landings per speciesAverage price per species

The model works with a subset of the economic and transversal indicators (landings data in quantity and value by species by vessel and metier) available from the SACROIS data source. Inputs parameters are listed below. The economic module calculates outputs indicators using economic indicators listed above and outputs from the biological and the market modules.

Input parameters

Table S16 – Input parameters of the economic module


TRANSVERSAL DATA

ndsi Days/ Days at sea

cnbi Employment

GVL i Income_landing/ Gross value of landings

Ls , i Landings by species and vessel, output from Catches module

GVL s,i Income_landing/ Gross value of landings by species

ECONOMIC DATA

Fci Fuelcost/ Energy costs

Fvoli Fuelcons/ Energy consumption

ovci Varcost/ variable costs

repi Repcost/ Repair and maintenance costs

Fixci Fixedcost/ non variable costs

Ccwi Crew costs wages

depi Depreciation

Ki Capital

lci Landing costs (% GR)

9

nbhiNb of hours at sea by yearHarmonized reference 2000 h (250 days at sea* 8 hours/day)

Cshri Crew share (% of the Return to be Shared)

mwh Net Minimum national wage

mwhg Gross Minimum national wage

ici Interest

eeci Crew costs contributionIf data by métier are available

Fci,m Fuelcost/ Energy costs

Fvoli,m Fuelcons/ Energy consumption

ovci,m Varcost/ variable costs


Indicators of type “Ini” are intermediate indicators calculated at the beginning from the input data and used in the model after to calculate the output indicators. For ease of notation, time index is assumed in the following.

Table S17 – Output variables of the economic module


Indicators ini

GVLothsi, Ini GR other species by vessel

GVLothsi=GVLi−∑sGVLs , i

GVLothsuei Ini GR other species by vessel and unit of effort GVLothsuei=

GVLothsiE i

pfi Ini Fuel price euros/L pf i=Fci , iniFvoli , ini

Fvoluei IniFuel consumption by unit of effort (nb of days at sea)

Fvoluei=Fvoli , inindsi , ini

Output indicators

GVLi Output Total gross revenue by vessel

GVLi=∑s, c

(P s, c×Ls ,i , c)+GVLothsue i∗E i

rtbsi Output Return to be shared by vessel

rtbsi=GVLi−pf i. Fvoluei.nds i−ovci

gvai Output Gross Value Added by vessel

gvai=GVLi−pf i .Fvoluei .ndsi−ovc i−repi−Fixci

gcfi Output Gross Cash Flow by vessel

gcf i=GVL i−pf i .Fvoluei .ndsi−ovc i−repi−Fixci−ccw i

ngcfi Output Net Cash Flow by vessel ngcf i=gcf i−depi

10

gpi Output Net Profit by vessel or Owner surplus

gpi=ngcf i−iciIf crew share unavailable

Ccw_ri Ini Crew costs share as a % of the RTBS Ccw¿=

Ccwi Inirtbs i Ini

Ccwi Output Crew costsCcwi=Ccw¿∗rtbsi¿Ccw¿∗(GVLi−pf i .Fvolue i .ndsi−ovc i)

CcwCri Output Crew costs by crew member CcwCri=

Ccwi

cnb iIf crew share available

opersci IniOther crew costs = vacation, employer contribution, premium

opersc i=Ccwi Ini−cshri∗rtbsi Ini¿Ccwi Ini−cshr i¿(GVL i− pf i .Fvoluei .ndsi−ovc i) Ini

Ccwi Output Crew costs Ccwi=cshri∗rtbsi+opersci

CcwCri Output Crew costs by crew member CcwCri =

Ccwi

cnbisshri Output Owner share by vessel

by vessel sshri=rtbsi(1−cshri )

cshrTi Output Crew share by vessel by vessel

cshrT i=cshr i×rtbs i

wagegi OutputGross wage by crew member including crew contributions

wagegi=cshrT i

cnb i

Surplus calculation

oclgi Output Opportunity costs of Labour by vessel

ocl gi=mwhg×cnbi×nbhi

csgi Output Gross Labour surplus by vessel

csgi=cshri−ocl g i

psgi Output Total producer surplus by vessel (gross value)

psgi=csgfi+gpincshri Output Net crew share by vessel ncshr i=cshrT i−ccei

wageni Output Net wage by crew member wageni=

ncshricnb i

ocli Output Net Opportunity costs of Labour by vessel

ocli=nmwh×cnbi×nbhicsi Output Labour surplus by vessel csi=ncshri−oclipsi Output Total producer surplus by

vesselpsi=csi+gpi

If landings costs available

stsi Output State surplus associated to a vessel

stsi=lc i×GVLi

11

Model parameters

Table S18 – Biological parameters.

Age a 2 3 4 5 6 7 8+Sole parameters

Initial abundundance N s , a ,t 0 (×106 25.77 8.86 5.40 7.05 3.46 2.62 1.64

Natural mortality rate M s , a 0.10 0.10 0.10 0.10 0.10 0.10 0.10

Weight at age w s , a (kg) 0.19 0.26 0.30 0.32 0.37 0.41 0.58

% of mature individuals Mat s , a 0.32 0.83 0.97 1.00 1.00 1.00 1.00

Mean recruitment (×106) 25.77

Age a 1 2 3 4 5 6 7 8 9+Nephrops parameters

Initial abundundance N s , a ,t 0(×106) 658.76 529.15 206.38 138.13 65.86 30.06 12.61 4.53 4.26

Natural mortality rate M s , a 0.30 0.30 0.25 0.25 0.25 0.25 0.25 0.25 0.25

Weight at age w s , a (×10−3kg) 3.53 9.17 16.53 26.57 36.37 45.00 56.83 67.57 85.43

% of mature individuals Mat s , a 0 0 0.75 1.00 1.00 1.00 1.00 1.00 1.00

Mean recruitment (×106) 658.76

Source: ICES. 2015. Report of the Working Group for the Bay of Biscay and the Iberian waters Ecoregion (WBGIE), 4–10 May 2015 Copenhagen, Denmark. Ref ICES CM/ACOM:11. 503 pp.

Table S19 – Average revenue and cost structures by sub-fleet and length class in 2014.

Sub-fleet Vessel length (m)

Gross value of landings(k€/trip)

Fuel cost (k€/trip)

Other var. costs (k€/trip)

Crew cost(k€/trip)

Repair cost(k€/trip)

Fixed costs (k€/year)

Specialized Nephrops trawlers

[0-12[ 1.49 0.32 0.18 0.52 0.11 22.14[12-24[ 3.57 0.96 0.45 1.28 0.35 52.08

Non-specialized Nephrops trawlers

[0-12[ 1.59 0.27 0.22 0.60 0.11 26.51[12-18[ 6.29 1.68 0.79 2.25 0.62 54.07[18-24[ 8.30 2.19 1.13 2.69 0.69 61.18

Mixed bottom trawlers

[0-10[ 0.94 0.16 0.13 0.36 0.06 13.58[10-12[ 1.65 0.35 0.20 0.58 0.12 21.15[12-18[ 5.56 1.49 0.70 1.99 0.55 43.54[18-24[ 9.36 2.47 1.28 3.04 0.78 46.14

Pelagic trawlers [0-12[ 2.22 0.27 0.10 0.97 0.12 21.48[12-18[ 4.13 1.04 0.53 1.40 0.38 39.69[18-24[ 9.05 2.40 0.69 1.62 0.70 57.23

Sole netters [0-10[ 1.15 0.09 0.12 0.49 0.06 33.19[10-12[ 2.04 0.17 0.24 0.88 0.15 41.66[12-18[ 5.68 0.45 0.77 2.48 0.35 81.77[18-24[ 16.11 1.62 2.09 6.63 1.25 108.99

Mixed netters [0-12[ 0.68 0.05 0.07 0.29 0.04 14.70[12-18[ 0.87 0.07 0.10 0.38 0.06 16.19

Source: DPMA-Ifremer Information Fisheries System (2015)

12

Table S20 – Premium scale.

Gross tonnage of vessels (GT) Premiuma

Variable part Fixed part[0-5[ 0 €/GT 57,000 €[5-20[ 11,007 €/GT 1,965 €[20-300[ 2,930 €/GT 163,505 €[300-800[ 1,770 €/GT 511,505 €[800-1000[ 850 €/GT 1,247,505 €≥ 1000 0 €/GT 2,097,505 €

a a discount factor function of vessel age is applied: [0-15] years old vessels: no discount factor applied [16-29] years old vessels: discount factor of 1.5 % per year above 15 ≥ 30 years old vessels: discount factor of 22.5 %

Source: reproduced from JORF n°0289 du 12 décembre 2012 (accessible online: https://www.legifrance.gouv.fr/eli/arrete/2012/11/29/DEVM1241341A/jo/texte)

13

Evolution of fleet structure

Table S21 – Contingency table of fleet structure evolution in DS and ITQ: simulated fleet structure in 2025

Status under DS scenario

Status under ITQ scenario

Mixed bottom trawlersNon specialized

Nephrops trawlers

Specialized Nephrops trawlers

Pelagic trawlers Sole nettersMixed netters

Hooks and lines

vessels

Tot

al

[0-1

0[ m

[10-

12[ m

[12-

18[ m

[18-

24[ m

[0-1

2[ m

[12-

18[ m

[18-

24[ m

[0-1

2[ m

[12-

24[ m

[10-

12[ m

[12-

18[ m

[18-

24[ m

[0-1

0[ m

[10-

12[ m

[12-

18[ m

[18-

24[ m

[0-1

0[ m

[10-

18[ m

[0-1

0[ m

[10-

12[ m

Active Active "lease in" 13 49 1 2 1 4 3 10 7 1 1 4 12 20 10 0 11 4 4 1 158

Active Active "lease out" 2 8 6 1 1 2 5 4 24 3 5 4 0 20 27 18 0 1 0 2 133

ActiveInactive "lease out"

0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 0 0 0 0 0 5

ActiveDecommissioned without premium

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Decommissioned with premium

Active "lease in" 3 1 11 2 1 9 0 0 5 0 0 0 2 3 0 0 5 2 0 0 44


Active "lease out" 2 2 3 0 0 2 0 0 4 0 0 0 0 0 0 3 0 0 0 0 16


Inactive "lease out"

0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1


Decommissioned without premium

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0


Active "lease in" 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0


Active "lease out" 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0


Inactive "lease out"

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0



0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

Total 20 60 22 5 3 18 8 14 40 4 6 8 14 47 39 21 16 7 4 3 359

14

Fig. S1 – Evolution of effort per fleet and per metier.

15

Indicators related to the ecological dimension

Fig. S2 – Evolution of the spawning stock biomass (SSB) of (a) sole, (b) Nephrops.

Fig. S3 – Evolution of landings of (a) sole, (b) Nephrops.

16

Fig. S4 – Evolution of sole exploitation patterns per age group.

Fig. S5 – Impact on habitats and carbon footprint: evolution of (a) trawling effort, (b) fuel consumption.

17

Indicators related to the economic dimension

Table S22 – Estimation of subsidies: cost of public-aided decommissioning scheme and fuel tax exemptions.

A based on the premium scale presented in Table A3 (Appendix A)B considering a fuel tax concession rate of 0.63 €/l (Source: JRC estimate for France in 2013 based on OECD data)

Fig. S6 – Evolution of the price of the sole quota.

Public-aided decommissioning

schemeA (million €)

Fuel tax exemptionsB: annual average 2015-2025

(million €)BA scenario - 19.1

DS scenario 15.2 17.5

ITQ scenario - 26.1

18

Fig. S7 – Demand/supply of sole quota by fleet (a) number of vessels, year=2017, (b) tonnes of quota, year=2017, (c) number of vessels, year=2025, (d) tonnes of quota, year=2025.

19

Fig. S8 – Evolution of economic inequality between vessels: Gini index applied to gross value of landings.

Decomposition of the Theil index

For a population of N vessels i, the general formula for the Theil index T T applied to the gross value of landings is:

T T=1N∑

i=1

N (GVLiGVL× ln

GVLiGVL )

where GVL is the average gross value of landings. If the population of vessels is divided into N f fleet segments and sf is the share of the gross value of landings of fleet segment f , the Theil index can be rewritten as:

T T=∑f=1

N f

s f ×T T f+∑f=1

N f

s f ×lnGVLfGVL

where T T f and GVL f are the Theil index and the average gross value of landings of the fleet

segment f , respectively2. The contribution of the fleet segment f to the total inequality is sf ×TT f

. The contribution of the inequality between subgroups to the total inequality is

∑f=1

N f

s f × lnGVLfGVL

.

2 see Bourguignon, F. (1979). Decomposable income inequality measures. Econometrica, 901-920.

20

Fig. S9 – Evolution of inequality between vessels: Theil index applied to gross value of landings (a) BA scenario – decomposition by fleet, (b) BA scenario – decomposition by length class, (c) DS scenario – decomposition by fleet, (d) DS scenario – decomposition by length class, (e) ITQ scenario – decomposition by fleet, (f) ITQ scenario – decomposition by length class.

21

Indicators related to the social dimension

Fig. S10 – Evolution of wage inequality in the fishery: Gini index applied to the yearly wage per crew.

22

Fig. S11 – Evolution of wage inequality in the fishery: Theil index applied to the yearly wage per crew (a) BA scenario – decomposition by fleet, (b) BA scenario – decomposition by length class, (c) DS scenario – decomposition by fleet, (d) DS scenario – decomposition by length class, (e) ITQ scenario – decomposition by fleet, (f) ITQ scenario – decomposition by length class.

23

Sensitivity analysis

Fig. S12 – Sensitivity of (a,b) fishing effort, (c,d) fuel consumption, to effort allocation parameter (profit-tradition weight) and capital malleability parameter (disinvestment dynamics).

24

Fig. S13 – Sensitivity of (a,b) gross operating surplus, (c,d) average hourly wage, to effort allocation parameter (profit-tradition weight) and capital malleability parameter (disinvestment dynamics).

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University of Toronto T-Space · Web viewCatchability estimation sub-module3 Fishing mortality module4 Population dynamics module5 Catch, discards and landings module5 Market/price

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