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Institute for Coastal Marine Environment, TarantoInstitute for Coastal Marine Environment, Taranto

Fernando RUBINO, Laura GIORDANO, Paride BISCI, Carmela CAROPPOFernando RUBINO, Laura GIORDANO, Paride BISCI, Carmela CAROPPO

University of MoliseUniversity of Molise

Nadia PALMIERI, Marina FORLEONadia PALMIERI, Marina FORLEO

University of SalentoUniversity of Salento

Giovanna BELLIO, Anna TRONOGiovanna BELLIO, Anna TRONO

Stazione Zoologica, NaplesStazione Zoologica, Naples

Vincenzo BOTTEVincenzo BOTTE

Thessaloniki Cluster Meeting , 20‐21 October 2009

The

Taranto

marine

area

consists

of

different

basins

with

peculiar

geo‐morphological

and

ecological features.

Human ActivitiesMar Grande and Mar Piccolo are strongly utilised by:•an intensive mussel commercial fishery•the moorage for the regional fishing fleet•the largest Italian Navy base•a major port•a large heavy industry site

Mar

Piccolo

is

a

shallow,

nearly

enclosed

basin,

roughly divided between two basins (Seno I and

Seno

II)

that

have

a

maximum

depth

of

13

and

10 m respectively

The exchange with Mar Grande occurs through a

primary navigation channel and a small inlet

Mar

Grande

is

a

larger

semi‐enclosed

bay

with

a

maximum depth of 33 m and that opens into the

Gulf of Taranto and the Ionian Sea

These

activities

constitute

the

main

employers

at

Taranto,

and

they

all

influence

the environmental quality and the ecosystem

productivity (e.g. the local mussel farms)

The

circulation

is

driven

by

a

positive

water

balance

(runoff

+

precipitation

–

evaporation >0) of ~40 million m3/yr.

The estuarine flushing (~ 2‐3 mos)

due to the exchange through the inlet

is moderate and varies seasonally

depending on the pressure

differences with the Mar Grande.

During summer season a weak

stratification develops that

induces hypoxia in the lower

layer.

Most of the water input derives from 34 submarine freshwater springs (locally called "Citri") and the discharge

from small drainage

ditchs

that carry agricultural chemicals.

In addition, there is the combined discharge of 14 sewage pipes coming from the northern area of Taranto and

from 8 nearby towns. These discharges account for about 18,272 m3 d‐1 (of which 85% at the Second Inlet),

with organic matter equal to 6,767 kg d‐1 of BOD5.

Wind mixing is low due to the limited fetch and tidal‐mixing is low due to the limited tidal range of ~ 30‐40 cm

Taranto has

always

been

one

of

the

most important

mussel

farming area in Italy and Europe. Recently, in 2002‐03 there

were

two

important

policy

actions

that

have

caused

some

modifications:

1930s

2000s

•New

concessions

and

the

enlargement

of

the

old

ones

are

over‐exploiting

the

existing

natural

resources, impacting the ecosystem

trophic

chain

Before 2000 Today Not permitted area

Taranto has

always

been

one

of

the

most important

mussel

farming area in Italy and Europe. Recently, in 2002‐03 there

were

two

important

policy

actions

that

have

caused

some

modifications:

1930s

2000s

•New

concessions

and

the

enlargement

of

the

old

ones

are

over‐exploiting

the

existing

natural

resources, impacting the ecosystem

trophic

chain

•The

closing

of

9

sewage

pipes to improve

the

water

quality and its healthiness

The

combined

effect

was

to

increase

the

harvest

and

decrease the nutrients

This

leads

to

hypothesise

that

these

two

actions

were

causal

to the decline

Our SSA Team met several times with a Participant Group of Policy Makers and Stakeholders:•to identify the main concerns for the SAF implementation•to select the Policy Issues for the SSA

How to include mussel culture in a management plan for the sustainable useof the Mar Piccolo resources

•Regional Environmental Agency of Apulia Region •Province of Taranto (Productive Department )•Province of Taranto (Environmental Department)•Province of Taranto (Tourism Department)•Municipality of Taranto (Ecological and Environmental

Department)•Municipality of Taranto (Productive Activities)•Municipality of Taranto (Culture and Tourism Department)

The stakeholder PG•Health Board in Taranto•Harbour Board in Taranto•Harbour Office•Industrial Handcraft and Agricultural board of trade •Eni Spa•ILVA Spa•“Amm.Michelagnoli”

Foundation ONLUS

Major aimDecision‐making

information on

policy options

Improvement of the

quantity and quality of

mussel culture

•How do different stakeholders perceive water quality?

•What are their demands with respect to water quality?

•Can a “good”

water quality be reached in such impacted basin?

•If no what would be the alternatives?•What are the sustainable policy options for reducing the decline

of the productivity and

quality of the mussels?

•How can this be done to the best long‐term interest of the end‐users and preserve the bio‐

productivity of the Mar Piccolo?

•What trade‐offs and options would minimize such policy decisions?

To outline the approach:

We have identified three categories:

What are the environmental conditions that control or are

causing

the

mussel

decline?

1

2 What would be the costs and benefits derived by enacting the measures needed

for sustainable mussel growth?

3 What

are

the

effects

on

human

health

derived

from

the

exposure

to

hazardous

levels of contaminants or microorganisms?

The VS functionality with regard to the Impact (reduction in mussel size) and the causal

set of environmental conditions driven by its waste discharges

Scarce Information on:

•Geo‐Chem‐Bio‐Physical Variables

•Ecosystem Functioning and Carrying Capacity

•Freshwater Fluxes from Streams, Land Drainage, and Aquifers

•Input Data on Waste Discharge (nutrients, particulate matter, synthetic chemicals)

Lacking Data on:

•Observational Sampling: e.g. Time Series, Depth Profiles, Spatial Coverage

•Process Observations: e.g. Primary Productivity, Sedimentation Rates, Mussel Filtration

Rates and Assimilation

Ecological Data

MARKET DATA•Official prices were not available (maybe inexistent) for the Taranto market•Official harvest figures were also not available (maybe inexistent)•Quantitative estimate of Illegal production was not available

Lacking of Socio‐Economic Data

FINANCIAL BUDGET OF THE MUSSEL FARMS•None of the major operation costs were available yet (!)•Distribution of revenue was not available yet (!)•We are waiting for the data from Chamber of Commerce

HEALTH COSTS•Were not available for the public costs concerning exposure to mercury and PAHs due

to mussel consumption

WILLINGNESS TO PAY•At present we have not completed the analysis of questionnaires

on willingness to pay

and public perceptions

Forcing Data Inputs

Fresh-WaterBalance

Circulation -Exchange

2-layer, 2-basin

VerticalDiffusion

SaltBudget

NitrogenBudget

Phosphate& SilicateBudgets

PrimaryProduction3 size classes

OxygenBudget

Zooplankton ParticulateOrganic MatterLight

Mussel GrowthLarva-Juvenile-Adult

Mussel Harvest

Mar Piccolo Ecological Model by ComponentsGreen arrows are primary mass fluxes , Red arrows are primary feedbacks

Sediment &Regeneration

EconomicComponent

The major components of the Ecological Component model (Extend) for the Mar Piccolo

Only the primary interactions are shown

Fresh Water discharges into Seno II, Mar Piccolo in 2003

0 45.625 91.25 136.875 182.5 228.125 273.75 319.375 3650

11500

23000

34500

46000

57500

69000

80500

92000

Time

Volume flux, m3/dFW sorces for Seno II

The various runoff components freshwater input to Seno II, Mar PiccoloThese were derived from annual means using simple land‐runoff block

Annual MeansAyedda

Channel,

Obs: 6,600 Mod: 6,629

Riso & Cervaro River, Obs: 19,267 Mod: 19,195Le

Copre

Aquifer, Obs: 8640 Mod: 8718 Taranto urban runoff,

Obs: ?? Mod:9491

-0.6218058 45.00319 90.62819 136.2532 181.8782 227.5032 273.1282 318.7532 364.37820

30

60

90

120

150

180

210

240

Time

Fllushing time,daysFlushing of total system

Mean = 78 days

The daily flushing value (outflow/volume) for Seno II

0 45.625 91.25 136.875 182.5 228.125 273.75 319.375 3650

250000

500000

750000

1000000

1250000

1500000

1750000

2000000

Time

Water Flux,m3/dExchange thru Channel and Runoff

Qin_I_II Qout_II_I FWQin_II

The Seno II inflow (blue), outflow (red), freshwater inflow (green) for the test year of 2003. This

model uses the

Thermohaline

Exchange Method to determine the net exchange at its opening to

a

seaward water body. For each, time step calculates the internal salinity and the upper and lower

layer fluxes from the inputs: meteorological, salinity outside, and runoff. (Hopkins, 1999)

0 60.83333 121.6667 182.5 243.3333 304.1667 36532

33

34

35

36

37

38

39

40

Time

SALINITY, pptSurfzce layer salinity, Seno II

The Surface and Bottom layer salinities in Seno II (blue line) compared with vertically integrated

salinities (red x) from a single station approximately in the center of the Seno II. Calibrated through the 3 parameters controlling the salt flux: Channel Restriction, Vertical Diffusion,

and FW flux correction.

0 60.83333 121.6667 182.5 243.3333 304.1667 36532

33

34

35

36

37

38

39

40

Time

SALINITY, pptBottom layer salinity of Seno II

Annual averagesBottom

Obs: 36.46

Mod: 36.46

Surface

Obs: 37.11

Mod: 37.10

0 60.83333 121.6667 182.5 243.3333 304.1667 3652

5.5

9

12.5

16

Time

OXYGEN, mg/lSurface Layer Oxygen, Seno II

0 60.83333 121.6667 182.5 243.3333 304.1667 3652

5.5

9

12.5

16

Time

OXYGEN, mg/lBottom Layer Oxygen, Seno II

The Surface and Bottom layer Oxygen in Seno II (blue line) compared with vertically

integrated oxygen (red x) from a single station approximately in

the center of the Seno II. Fine

tuning of calibration has not been done yet awaiting refinements

in the Nitrogen and

Phytoplankton Components.

The surface and bottom nitrogen in Seno IIThis component is still being refined

0 36 72 108 144 180 216 252 288 324 3600

0.00025

0.0005

0.00075

0.001Nitrogen (kg/m3)

SENO II - Nitrogen

6/1/2003 26/4/2003 14/8/2003 2/12/2003 21/3/2004 9/7/2004 27/10/2004692043.1

1.80190e+07

3.53460e+07

5.26730e+07

7.00000e+07Total Carbon g

Primary Production vs Runoff

258.75

458806.6

917354.5

1375902

1834450Runoff (m3/d)

Diatoms Dinoflages Micros Y2 FWin

getC

RS want

Diatom, g

Diatoms

Eqn

PP_dia

Dia_grow

Dia_grazers

KlLight Dia_inc

Asur

Kr

Eqn

Diatom mort, m2/d

Km_Dia

PP_diaKg

Dia_lossDia_dec

Asur

MU_dia

dia _ass_muss

Example for Diatoms Growth

Natural mortality and ZP grazing Mussels grazing

wrap distance

number of lines

Mussels Farm

8000

0

8000

line length

2

0

2

250

0

247.5

wrap leng

4

2

3.72

Mussels FarmControls

Help

Dimensional parameters:– farming area

– line length (min:max)

– number of lines (min:max)

– wrap distance (min:max)

– wrap length (min:max)

– Initial stock (seeds):1/7 of the final production

These controls will allow

to test the carrying

capacity of mussel

farming for MP

wrap distance

number of lines

Mussels Farm

8000

0

8000

line length

2

0

2

Mussels Growth

250

0

247.5

wrap leng

4

2

3.72

Muss_init

Micro_pom

Diat_pom

Dino_pom

dia _ass_muss

Top POM

Tw

Pom _ass_class2Pom _ass_class1

Muss_bio1

Muss_bio2

dino _ass_muss

micro _ass_muss

Mussels FarmControls

POM_escr_muss

Help Two generational classes considering a 18 months life‐cycle including harvesting phase

Empirical curves used to formulate

three critical processes:

A.

Filtration Rate

B.

Ingestion Rate

C.

Absorption Rate

(depending on POM composition)

from van haren & kooijman'93

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0 1 2 3 4 5 6

L(cm)

Filtr

atio

n ra

te (m

^3/d

ay)

0

0.00001

0.00002

0.00003

0.00004

0.00005

0.00006

0.00007

0.00008

0 0.5 1 1.5 2

POM conc (mg/dm3)In

gest

ion

rate

(mg

POM

/h)

from van haren & kooijman'93L=4,8 cm

L=2,5 cm

A

B

data from Bayne et al. '89

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 0.5 1 1.5 2 2.5

mg POM/h

Abso

rptio

n Ef

ficien

cy

C

Mussels Growth

Micro_pom

Diat_pom

Dino_pom

dia _ass_muss

Top POM

Tw


Muss_bio1

Muss_bio2

dino _ass_muss

micro _ass_muss

POM_escr_muss

Growth parameters according to a

bioenergetic

model by Van

Haren

&

Kooijman, 1993

1/1/2003 24/3/2003 15/6/2003 5/9/2003 27/11/2003 17/2/2004 10/5/2004 31/7/2004 22/10/20040

62500

125000

187500

250000

312500

375000

437500

500000TOP POM (kg of C)

Plotter I/O

0

0.0625

0.125

0.1875

0.25

0.3125

0.375

0.4375

0.5Absorpion efficien

Y2 Eps_POM Top POM Green Black

Three coefficients were used to represent the absorption efficiency due to POM

composition:

A. Diatom Efficiency (45%)B.

Dinoflagellate

Efficiency (30%)C.

Nanoplankton

Efficiency (25%)

1/1/2003 11/2/2003 24/3/2003 4/5/2003 15/6/2003 26/7/2003 5/9/2003 16/10/2003 27/11/2003 7/1/2004 17/2/2004 29/3/2004 10/5/2004 20/6/2004 31/7/2004 10/9/2004 22/10/20040

1250000

2500000

3750000

5000000

6250000

7500000

8750000

1.00000e+07Kg of Carbon

1st & 2nd generation

0

2.50000e+07

5.00000e+07

7.50000e+07

1.00000e+08

1.25000e+08

1.50000e+08

1.75000e+08

2.00000e+08Kg of Carbon

1st generation Y2 2nd generation

1st generation

2nd generation

Mussels Growth depends on

Temperature (Q10), Ingestion rate,

Absorption Eff. and POM

getC

RS want

class 1 Mussels Kg of C

Eqn

growth

Eqn

losses

Eqn

spawning

Muss_bio1

Muss_bio1

Muss_bio1

Muss_init

Oxigen cons

Imax

mortality1

Pom _ass_class1

Muss_Class1

Temp

Top POMEps_POM

RS

C

class 2 Mussels Kg of C

Muss_bio1

class2

spaw

harvesting

Muss_bio1

Con6InCon6In

1st Generation

Con3outCon3out

Con1outCon1out

stock1

muss_numb1

SR

Mussels Growth

Muss_init

Micro_pom

Diat_pom

Dino_pom

dia _ass_muss

Top POM

Tw


Muss_bio1

Muss_bio2

dino _ass_muss

micro _ass_muss

POM_escr_muss

0 175 350 525 7000

0.1125

0.225

0.3375

0.45

Days

Mortality rate 2nd genInput Data

Y Output

0 187.5 375 562.5 7500

0.0875

0.175

0.2625

0.35

Days

Mortality rate 1st genInput Data

Y Output

Biomass loss due to spawning

0 250 500 750 10000

0.15

0.3

0.45

0.6

Days

Harvest rate Input Data

Y Output

Biomass loss due to Harvest

0 175 350 525 7000

0.05

0.1

0.15

0.2

Days

Biomass loss rate Input Data

Y Output

1/1/2003 21/4/2003 9/8/2003 27/11/2003 16/3/2004 4/7/2004 22/10/20040

10

20

30

40

50

60

70

80Shell Length (mm)

Plotter I/O

0

375000

750000

1125000

1500000

1875000

2250000

2625000

3000000

length fit Y2

1/1/2003 0:00

8/3/2003 0:00

13/5/2003 0:00

18/7/2003 0:00

22/9/2003 0:00

27/11/2003 0:00

1/2/2004 0:00

7/4/2004 0:00

12/6/2004 0:00

17/8/2004 0:00

22/10/2004 0:00

0

2500000

5000000

7500000

1.00000e+07

1.25000e+07

1.50000e+07

1.75000e+07

2.00000e+07Mussels (Kg of C)

Plotter I/O

0

250000

500000

750000

1000000

1250000

1500000

1750000

2000000POM (kg of C)

Muss_bio1 Y2 Top POM Y2 Y2

LarvaeGrowth

Spawning Harvesting

POM

The MP mussels life cycle simulation is based on 18 months, including harvesting

Commercial size

•To complete the interface between biomass of mussels and biomass

of harvest

•To connect the two basins of the Mar Piccolo

•To calibrate the phytoplankton biomass

•To estimate the sustainable yield of the system (C:N ratios)

•To simulate various nutrient ratios and loading

•To simulate the Condition Index (CI) [shell weight/meat weight]

The socioeconomic dimension of SSA 14 is Focused on some of the socio‐

economic responses related to the decline of the mussel culture

Mussel Farm Socio‐Economy

Relation with Coastal Zone Socio‐Economy



•In Taranto the mussel farms are mostly managed as Cooperatives (about 80%)

•The mean age of employees has increased progressively because of

failure of

generational turnover, characteristic of traditional family‐run enterprises

•The “illegal”

employment consists of family members of the managers of each

cooperative, who are utilised during the harvest. This is a cultural tradition typical of

farming in southern Italy

•Evidence exists that a Consortium of the Cooperatives would be a

better way to

manage the mussel farming

•As a Consortium there will be advantages in terms of employment benefits and net

revenue

Mussel Farm Socio‐Economy



Relation with Coastal Zone Socio‐Economy

•The need for coordinated waste‐disposal plan (nutrient ratio management and

elimination of toxic substances, etc.)

•The need to evaluate options for improving the ecosystem health and perceived

use value of the Mar Piccolo (shoreline beautification, urban park, fishing,

mussel tourism, etc.)

• Improvement of the water

quality

•Improvement of the mussel

quality and perception

• Increase of the willingness to

invest on building around the

Mar Piccolo of Taranto.

DEPURATION PLANT

• Directly linked to the Benefits

of the park and the depuration

plant:

the increase of value of real

estate market

ECOLOGICAL HEALTH

• Increase of value of real estate

market

• Energy saving (less use of air

conditioning)

• Mitigation of greenhouse effect

(uptake of CO2)

• Decrease of air pollution

(vegetation filters a part of

pollutans).

PARK

Cost_Traditional_Dep

Benefits_Traditional_DepHarvest_tot

Cost_Natural_Dep

Benefit_Natural_Dep

Harvest_tot

Price_1_ time_Consortium

Price_2_ time_ConsortiumPrice_3_ time_Consortium



WTP_Mussel_Quality

WTP_Mussel_Quality

MarketHarvest

Harvest_Tot Harvest_Cooperative

Harvest_tot

Price_1_time_CoopPrice_2_time_CoopPrice_3_time_CoopPrice_1_ time_Consortium


Cost_Ecological_Health

Benefit_Ecological_Health

WTP_Ecological_HealthCost_Park

Benefit_Park



Tot_Rev_Consortium

Harvest_Tot

Harvest_Cooperative

Profit_Coop_Consortium

Price_1_time_CoopPrice_2_time_CoopPrice_3_time_Coop

Harvest_Cooperative

Loss_Coop

Profit_CoopTot_Rev_Cooperative

We have imagined to contribute to the realization of a Consortium

of Mussel Cooperatives

INDIVIDUAL COOPERATIVE

COOPERATIVES OF CONSORTIUM

TotCost

insurance

II Acconto

Interest loan

Maintenance

Daily cost

Interest pas banK

Amortize

Cost equipment

Pay VAT

Saldo e acconto

Dir Cam

INAIL

Inps Coop

LabHarvest_Cooperative_InHarvest_Cooperative_In

Price_1_time_Coop_InPrice_1_time_Coop_In



Tot_Rev_Coop_outTot_Rev_Coop_out

Price_1_time_CoopPrice_2_time_CoopPrice_3_time_Coop

Harvest_Cooperative

Loss_Coop

Profit_CoopTot_Rev_Cooperative

Cooperatives of Consortium

Tot_Rev_Coop1F/do Mutualistico_Coop1

Legal_Reserve_Consortium1

Tot_Rev_Coop2F/do Mutualistico_Coop2


Tot_Rev_Coop3

F/do Mutualistico_Coop3


Price1_Coop_InPrice1_Coop_In



Harvest_Coop_InHarvest_Coop_In

Tot_Rev_Consortium_OutTot_Rev_Consortium_Out

Consortium

Tot_Rev_Coop1

Tot_Rev_Coop2Tot_Rev_Coop3

F/do Mutualistico_Coop

Legal_Reserve_Consortium

Price1_Consortium_InPrice1_Consortium_In



Harvest_tot_InHarvest_tot_In

Mark_Import_InMark_Import_In



Tot_Rev_Consortium

Harvest_Tot

Harvest_Cooperative

Profit_Coop_Consortium

0 182,5 365 547,5 7300

5,00000e+11

1,00000e+12

1,50000e+12

2,00000e+12

Time

ValueProfits Coop Consortium

Prof it_Coop Prof it_Coop_Con… Green Black

0 182,5 365 547,5 7300

2,50000e+11

5,00000e+11

7,50000e+11

1,00000e+12

1,25000e+12

1,50000e+12

1,75000e+12

2,00000e+12

Time

ValueProfits Coop

Prof it_Coop Prof it_Coop_Con… Green Black

Cost_Traditional_Dep

Benefits_Traditional_DepHarvest_tot



WTP_Mussel_Quality

Price1_InPrice1_In

Price2_InPrice2_In

Price3_InPrice3_In

WTP_InWTP_In


Social aspect

Benefit_Trad_dep_outBenefit_Trad_dep_out

Cost_Trad_Dep_OutCost_Trad_Dep_Out

Cost_Natural_Dep

Benefit_Natural_Dep

Harvest_tot



WTP_Mussel_Quality


Price1_InPrice1_In

Price2_InPrice2_In

Price3_InPrice3_In

Social aspect

WTP_InWTP_In

Benefits_Nat_Dep_outBenefits_Nat_Dep_outCost_Nat_Dep_outCost_Nat_Dep_out

0 91,25 182,5 273,75 365 456,25 547,5 638,75 7300

5000000

1,00000e+07

1,50000e+07

2,00000e+07

Time

ValueCost Trad and Natural Dep

0

750000

1500000

2250000

3000000Y2

Y2 Cost_Traditiona… Cost_Natural_Dep

Cost_Ecological_Health

Benefit_Ecological_Health

WTP_Ecological_Health

Social aspect

WTP_Ec_Health_InWTP_Ec_Health_InBenefit_Ecological_Health_outBenefit_Ecological_Health_out

Cost_Ecological_Health_OutCost_Ecological_Health_Out

Water_Quality_Ecological_Health

Sanitary_Benefits_Ecological_Health

WTP_Ecological_HealthCon2InCon2In

Cost_Park

Benefit_Park

Benefit_Park_outBenefit_Park_out

Social aspectCost_Park_OutCost_Park_Out

Total_Costs

Infopoint

Total_Costs_outTotal_Costs_out

Building_Permit 0,1

% VATPrimary_Urban_Planning

Secondary_Urban_Planning

Parking

Costs_Ecomarket

Cinema_in_the_Open

Park_Equipment

Costs_Park

0,1

Design Costsy =f (x) Costs_Design

Other_costs SR

Mitigation_Greenhouse_Effect

Increase_Real_Estate_Market

Decrease_Air_Pollution

Total_Energy_Saving

0 121,6667 243,3333 365 486,6667 608,3333 7300

1,12500e+09

2,25000e+09

3,37500e+09

4,50000e+09

5,62500e+09

6,75000e+09

7,87500e+09

9,00000e+09

Time

ValueCost Benefit Park

0

2500

5000

7500

10000

12500

15000

17500

20000Y2

Y2 Cost_Park Benef it_Park

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