IMAR – Portugal http://www.imar.ptwww.ecowin.org/ecasa

ECASAECASAwww.ecasa.org.uk

ECASA SC group meeting in Rome, 7th – 8th November 2006

A. SequeiraJ.G. Ferreira

Ecosystem Approach for Sustainable AquacultureEcosystem Approach for Sustainable Aquaculture

GISGISLoch Creran division into boxesLoch Creran division into boxes

Physical dataHomogenous physical conditions for

• Morphology • Currents• Vertical stratification 

Water bodies defined for Water Framework Directive (WFD) implementationDue to management requirements for EQS, water body boundaries should fit model box limits Aquaculture sitesWhen possible include aquaculture areas into boxes (rather than across boxes)

EcoWin2000 EcoWin2000 modelmodel

Loch Creran1 Water Body

Model coupling: Spatial Model coupling: Spatial aggregationaggregation

Delft3DDelft3DHydrodynamic modelHydrodynamic model

EcoWin2000EcoWin2000ecological modelecological model

several boxes 20 layers

30 boxes3 layers

Loch Creran Loch Creran Wild species - GIS Wild species - GIS modelmodel Loch Creran total wild species distributionLoch Creran total wild species distribution

Total wild shellfish individuals: 2 585 x 106

Wild speciesWild species - I) Data Processing- I) Data Processing

Loch Creran Loch Creran Wild species modelWild species model

Marine biological interest in Loch Creran:Marine biological interest in Loch Creran:

Tidal rapidsTidal rapids Biogenic reefs ofBiogenic reefs of

– Modiolus modiolusModiolus modiolus– Serpula vermicularisSerpula vermicularis

Habitats Habitats DirectiveDirective

(SAC)(SAC)

Serpula vermicularis reef associated with fauna in Loch Creran from Black et al, 1999

Wild speciesWild species - II) Regulation analysis- II) Regulation analysis

Loch CreranLoch CreranWild species modelWild species model

Total bivalvesTotal bivalves 2 585 x 102 585 x 1066 ind ind

Filtration rateFiltration rate 1.5 – 2.6 L ind1.5 – 2.6 L ind-1-1 h h-1-1

Filtration by wild Filtration by wild populationspopulations

Min: 93.1 x 10Min: 93.1 x 1066 m m33 d d--

11

Max: 98.6 x 10Max: 98.6 x 1066 m m33 dd-1-1

Loch Creran volumeLoch Creran volume 240 x 10240 x 1066 m m33

≈ ≈ 40% of Loch volume is filtered per day40% of Loch volume is filtered per day

≈ ≈ 2.4 – 2.6 days to filter the Loch2.4 – 2.6 days to filter the Loch

Volume filtered per day

Wild speciesWild species - III) Resource partitionig assessment- III) Resource partitionig assessment

Loch CreranLoch Creran Wild species modelWild species model

Filtration by wild Filtration by wild populationspopulations

Min: 93.1 x 10Min: 93.1 x 1066 m m33 d d--

11

Max: 98.6 x 10Max: 98.6 x 1066 m m33 dd-1-1

Loch Creran volumeLoch Creran volume 240 x 10240 x 1066 m m33

Chl Chl a a concentration*concentration* 1 1 µµg Lg L-1-1

Total chl Total chl a a in Loch Creranin Loch Creran 240 kg240 kg

Chl Chl a a cleared by wild speciescleared by wild species 93.1 – 98.6 kg chl 93.1 – 98.6 kg chl a a dd-1-1

Baseline food requirements

* Mean value, from KEYZONES project data - 2005

Wild speciesWild species - III) Resource partitionig assessment- III) Resource partitionig assessment

CClearance rates specific for the species in analysislearance rates specific for the species in analysis– Rates used here were based on the Rates used here were based on the Modiolus modiolusModiolus modiolus filtration. Clearance filtration. Clearance

rates will vary according to species, body size and season.rates will vary according to species, body size and season.

OOther wild speciesther wild species– Consider other filter feeders that are nor shellfish (e.g. red tube worn).Consider other filter feeders that are nor shellfish (e.g. red tube worn).

MMap of sediments and biotopesap of sediments and biotopes– A good map of the type of sediments and biotopes is important to improve A good map of the type of sediments and biotopes is important to improve

the interpolation surfaces.the interpolation surfaces.

IIncrease number of sampling stationsncrease number of sampling stations– Species density is a highy variable parameter. Results shown here are Species density is a highy variable parameter. Results shown here are

useful to give a rough idea of the type of results one can obtain.useful to give a rough idea of the type of results one can obtain.

Wild species - GISWild species - GIS

modelmodel improvementsimprovements::

GEM – Geochemical and Ecological Modelling

http://www.farmscale.org/Address

Eutrophication and Aquaculture in Coastal SystemsApplication of Screening Models for Assessment

Farm-scale screening models

International Symposium on Research and Management of Eutrophication in

Coastal Ecosystems. Nyborg, DenmarkSession 12 – Eutrophication and Aquaculture

http://www.farmscale.org/

20th-23rd June 2006

J.G. Ferreira, S.B. Bricker, A.J.S. Hawkins, R. Pastres, A. Newton

GEM – Geochemical and Ecological Modelling

http://www.farmscale.org/Address

Farm-scale conceptual diagram

Current Current

Farm length

Width

DepthChl a

POM

Chl a

POM

Sections

1 2 3 n-1 n

Shellfish

GEM – Geochemical and Ecological Modelling

http://www.farmscale.org/Address

Farm-scale modellingApplication to shellfish aquaculture

Define farm dimensions Define environmental parameters (e.g Chl a,

POM, TPM, O2) Select species and culture density Transport food across farm segments Calculate food depletion and oxygen

consumption Output cultivation yield Assess eutrophication status

GEM – Geochemical and Ecological Modelling

http://www.farmscale.org/Address

Results – Different culture sitingFarm Dimensions (m) Species Model

300X20X10 C. gigas PMLCultivation period (d) 45 45 45

Food Chl a (g L-1) POM (mg L-1) TPM (mg L-1)10 5 25

Environment Density (ind m-3) T (o C) O2 (mg L-1)Sections 1,2,3 500,500,500 15 8.7

Current speed High Medium Slow(m s-1) 0.5 0.1 0.02

Total seed (X103 ind) 30000 30000 30000Total harvest (TFW) 727.1 692.4 323.9Biomass ratio 485 462 216Final mean Chl a (g L-1) 7.9 4.7 2.1Final min. O2(mg L-1) 8.4 7.7 6.9

Income (k€) 3656 3462 1619

GEM – Geochemical and Ecological Modelling

http://www.farmscale.org/Address

Results – Different culture densitiesFarm Dimensions (m) Species Model

300X20X10 C. gigas PMLCultivation period (d) 180 180 180

Food Chl a (g L-1) POM (mg L-1) TPM (mg L-1)5 5 25

Environment Current (m s-1) T (o C) O2 (mg L-1)0.02 15 8.7

Cultivation scenario Low Medium High

Density (ind m-3) 25 (all) 100 (all) 500 (all)Sections 1,2,3

Total seed (X103 ind) 1500 6000 30000Total harvest (TFW) 34.3 137.3 400.2Biomass ratio 458 458 267Final Chl a (g L-1) 4.3 2.8 0.9

Income (k€) 171.5 686.5 2001

GEM – Geochemical and Ecological Modelling

http://www.farmscale.org/Address

Results – ASSETS modelFarm Dimensions (m) Species Cultivation (d)

300X20X10 Generic 45

Food Chl a (g L-1) POM (mg L-1) TPM (mg L-1)

11 5 25

Environment Current (m s-1) T (o C) O2 (mg L-1)

0.02 15 7.0

Cultivation scenario Low Medium HighDensity (ind m-3) 25 (all) 100 (all) 500 (all)Total seed (X103 ind) 1500 6000 30000Total harvest (TFW) 13.1 36.8 39.1

Final mean Chl a (g L-1) 9.5 6.0 1.3Final min. O2(mg L-1) 5.9 3.8 1.8ASSETS grade Good Moderate Poor

Income (k€) 65.5 184 195

WFD

GEM – Geochemical and Ecological Modelling

http://www.farmscale.org/Address

Synthesis FARM is a screening model directed both at the farmer and the regulator; FARM has three uses: (i) Prospective analysis for siting or distribution;

(ii) Ecological and economic optimisation of existing farms; (iii) Assessment of farm-related eutrophication effects (including mitigation);

The seamless integration of ASSETSTM, allowing eutrophication assessment, means that FARM is effectively a screening model both for shellfish productivity and water quality;

The model’s simple interface hides complex internal processing, including transport equations, shellfish individual growth, population dynamics, dissolved oxygen balance and the calculation of ASSETSTM;

The FARM model will go live in the Fall of 2006, and will include the possibility of adding fish cages and seaweeds to explore polyculture effects. Different combinations of shellfish polyculture will be implemented in 2007;

The FARM model is at the forefront of the latest generation of client-server models, part of the rapidly emerging paradigm of Software as a Service (SaaS).

http://www.farmscale.org

A differential DPSIR approach for coastal ecosystem management

A.M. Nobre, J.G. Ferreira

IMAR – Institute of Marine Researchhttp:// www.ecowin.org/

Research and management of eutrophication in coastal ecosystems

20-23 June 2006, Nyborg Strand,Nyborg, Denmark

ana@salum.net, joao@hoomi.com

Differential DPSIR descriptionObjective

Inform managers about the several problems identified in the coastal zones due to an increase of human pressure, including both ecological and economic components

Questions to answer:

Is it possible to establish a relation between water quality of a coastal ecosystem and its economic value?

If so, how it changes with the pressure from the drainage basin and with other pressures inside the ecosystem?

Eco

logi

cal i

ndic

ator

s

Econom

ic indicators

t t + t t + 2.t t + 3.t

Response implementation periods

Methodology

Assessment of the ecosystem inAssessment of the ecosystem in a given year ( a given year (tt))

DPSIR Drivers Pressures State

Identification of the most relevant issues

Socio-economic activities and land uses

Loads and other forcing functions

Appropriate ecological indicators

Quantification

Ecological

Research - Pressure indicators

State indicators

Manag. - Management Level

State Classification

Economic VDrivers - VEcosystem

Quantification of both environmental and economic variables using the differential DPSIR approach

Year t+tYear t

t

Methodology

Assessment of the impacts in the ecosystem Assessment of the impacts in the ecosystem after a given after a given periodperiod ((tt))

DPSIR Response Drivers Pressure State = Envir. Impact

Identification of the most relevant issues

Management actions and measures

Changes in drivers:

Changes in pressures:

Changes in state = Impacts in the ecosystem:

Quantification

Ecolog.

Res. - - Pressure indicators

State indicators

Man.

- - Management Level (t+t)

State Classification

Economic ResponseCost VDrivers - VImpactEcosyst

Evaluation of changes in t

Year t+tYear t

t

Application to a coastal lagoon

Eutrophication symptoms

• Low pelagic primary production, limited by the fast water turnover

• Benthic eutrophication symptoms as a result of nutrient peaks, large intertidal areas and short water residence times

Urban areasInfrastructureAgricultureAgroforestForestSalt pondsSandRia channels

Bivalve areasLicensed areasHigh productionLow production

Urban areasInfrastructureAgricultureAgroforestForestSalt pondsSandRia channels

Bivalve areasLicensed areasHigh productionLow production

Main economic activities:• Bivalve aquaculture (extensive)• Fisheries (extensive)• Salt production• Tourism• Agriculture and livestock• Industry High ecological value:

• Ramsar Convention (1971) site• Natural park (1978)• Cites Convention (1975)• Birds Directive (1979)• Habitats Directive (1992)• Natura 2000 network

Ria Formosa

Management issues

Period of analysis

The most important issues for management in Ria Formosa:

• Seasonal variation of population

• Water quality in intertidal areas and channel upper reaches

• Excessive macroalgal growth

• Decrease of clam stocks since mid 80’s due e.g. to the appearance of the parasite Perkinsus atlanticus (Azevedo, J.Parasitol.1989)

t , annual average (1980-1985)∆t, period 1985-1995t+∆t, annual average (1995-1999)

0

20000

40000

60000

80000

100000

120000

140000

160000

1970 1975 1980 1985 1990 1995 20000 %

20 %

40 %

60 %

80 %

100 %

120 %

140 %

160 %

Population in Ria Formosa and drainage basin

Visitors per yearR

esid

ent p

opul

atio

n

% of resident

0

20000

40000

60000

80000

100000

120000

140000

160000

1970 1975 1980 1985 1990 1995 20000 %

20 %

40 %

60 %

80 %

100 %

120 %

140 %

160 %

Population in Ria Formosa and drainage basin

Visitors per yearR

esid

ent p

opul

atio

n

% of resident

0

1

2

3

4

1

1980/85

Standard mortality

Standard mortality

Perkinsusinfection

1995/99

Abnormal mortality

Har

vest

Se

edKg . m-2

Mortality situation

1984/1985 Detection of Perkinsus atlanticus

0

1

2

3

4

1

1980/85

Standard mortality

Standard mortality

Perkinsusinfection

1995/99

Abnormal mortality

Har

vest

Se

edKg . m-2

Mortality situation

1984/1985 Detection of Perkinsus atlanticus

DPSIR

Scenarios

Economic and ecological changes in t

0 %

10 %

20 %30 %

40 %

50 %

60 %

0 %

10 %

20 %30 %

40 %

50 %

60 %

Response value

t1 t2 t3

-60%

-40%

-20%

0%

20%

40%

60%

80%

ExternalEnvCost

ResponseCost

Drivers

ExternalEnvCost / Impact value

t1 t2 t3

• Although management actions were taken between 1985 and 1995 the state decrease

• Other measures could have been adopted that might had reduced the lost of the ecosystem economical value

-80 %

-60 %

-40 %

-20 %

0 %

20 %

40 %

Economicalvalue N loads PEQ

Bivalveproduction

rate

Drivers Pressure State

-80 %

-60 %

-40 %

-20 %

0 %

20 %

40 %

Economicalvalue N loads PEQ

Bivalveproduction

rate

Drivers Pressure State