objectives to define the different water bodies in alfacs bay
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Dynamic model to calculate the carrying capacity for bivalve
growth in a coastal embaymentJoana Ibáñez Solé1, Montserrat Ramón2,3 and Margarita Fernández-Tejedor1
1. Institute for Food and Agricultural Research and Technology (IRTA), Sant Carles de la Ràpita, Spain
2. Institut de Ciències del Mar (CSIC), Barcelona, Spain3. Instituto Español de Oceanografía (IEO), Palma, Spain
Symposium on Integrating New Advances in Mediterranean Oceanography and Marine Biology. Barcelona, 25-29 November 2013
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OBJECTIVES
1. To define the different water bodies in Alfacs bay.
2. Modeling the depletion of seston and chlorophyll through a zero-dimensional dynamic model (using the half-saturation coefficient, χk ).
3. Application of the ecophysiological models SFG and DEB.
4. To calculate the carrying capacity of Alfacs bay for bivalve aquaculture.
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ALFACS BAY - Characteristics
• Positive estuarine circulation pattern of the water inside the bay.
• Wide range of temperatures.
• Shallow waters.
• Changes in the characteristics of the bay according to whether the irrigation channels are open or closed.
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Pycnocline identification
Closed channels
Density = 27.10 kg/m3
T (ºC)
Opened channels
Density = 24.71 kg/m3
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SITUATION OF SAMPLING STATIONS INSIDE ALFACS BAY
Main pattern of water circulation inside Alfacs bay. (Camp et al., 1987).
Latitude (º)
Longitude (º)
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Density [kg/m3]
Surface (0.5m)
Bottom(range 2.5 – 6m)
0
5
10
15
20
25
30
Canales abiertosdensidad = 27.10 kg/m3
Canales cerradosdensidad = 24.71 kg/m3
T (ºC)
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Salinity [PSU]
Surface (0.5m)
Bottom(range 2.5 – 6m)
0
5
10
15
20
25
30
Canales abiertosdensidad = 27.10 kg/m3
Canales cerradosdensidad = 24.71 kg/m3
T (ºC)
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Chlorophyll [mg/m3]
Surface (0.5m)
Bottom(range 2.5 – 6m)
0
5
10
15
20
25
30
Canales abiertosdensidad = 27.10 kg/m3
Canales cerradosdensidad = 24.71 kg/m3
T (ºC)
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TRANSECTS SAMPLED IN THE BAY
Latitude (º)
Longitude (º)Entrance transect Dock transect Central transect
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ENTRANCE TRANSECT Density, σt [kg/m3] Salinity [PSU]
Serramar FaroMitad boca
Chlorophyll [mg/m3] Stability, E [rad2/m]
0
5
10
15
20
25
30
Canales abiertosdensidad = 27.10 kg/m3
Canales cerradosdensidad = 24.71 kg/m3
T (ºC)
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DOCK TRANSECTDensity, σt [kg/m3] Salinity [PSU]
Chiringuito Muelle
Chlorophyll [mg/m3] Stability, E [rad2/m]
0
5
10
15
20
25
30
Canales abiertosdensidad = 27.10 kg/m3
Canales cerradosdensidad = 24.71 kg/m3
T (ºC)
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CENTRAL TRANSECTDensity, σt [kg/m3] Salinity [PSU]
Trabucador CentralEmisario
Chlorophyll [mg/m3] Stability, E [rad2/m]
0
5
10
15
20
25
30
Canales abiertosdensidad = 27.10 kg/m3
Canales cerradosdensidad = 24.71 kg/m3
T (ºC)
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ENTRANCE DOCK CENTRAL
Salinity [PSU]
Chlorophyll [mg/m3]
38.5
36.5
34.5
29.0
38.5
36.5
34.5
29.0
38.5
36.5
34.5
29.0
64
26
12
0
64
26
12
0
64
26
12
0
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Modelling depletion at the mussel farm
BeginningPoint A
MiddlePoint B
EndPoint C
Latitude (º)
Longitude (º)
ABC
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Area (m2) = 337038.2
Cultured area (m2) = 81274.2
Nº of nurseries = 42
Nº of ropes = 46200
Weight of the ropes [kg] At seedtime: 3.23·105 At collect: 11.6·105
Water transit time [h] Maximum: 2.03 (Camp et al., 1987) Minimum: 1.47
Area (m2) = 469069.0
Cultured area (m2) =86107.2
Nº of nurseries = 45
Nº of ropes = 49500
Weight of the ropes [kg] At seedtime: 3.47·105 At collect: 12.4·105
Water transit time [h] Maximum: 2.56 (Camp et al., 1987) Minimum: 1.86
Sampling points at the mussel farm
2672.5 m
2123.8m
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Depletion [mg/dm2]
Seston [mg/dm2]
Depletion [mg/dm2]
Seston [mg/dm2]
Seston [mg/dm2]
Depletion [mg/dm2] End rafts (C)
Beginning rafts (A) Middle rafts (B)
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DEPLETION EQUATION: d( ) = 0.7465·
: concentration of available seston
The whole farmDepletion [mg/dm2]
Seston [mg/dm2]
120
150
100
50
0
-50
0 20 40 60 80 100
200
140 160 180 200
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0
2
4
6
8
10
12
14
16
18
Invierno Primavera Verano Otoño
Depletion Rate [mg/m3]
De A a B De B a C Total: De A a C
Winter WinterSpring SpringSummer SummerAutumn Autumn
From A to B
Eastern part
[mg/h]
From B to C
Western part
Total: From A to C
Average
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[µg/L] CR [L/h]
0
0.5
1
1.5
2
2.5
3
3.5
4
Invierno Primavera Verano Otoño
Datos de campo in situ simuladoDatos de campo
Datos in situ simulados(Galimany et al., 2009)
k
Winter WinterSpring SpringSummer SummerAutumn Autumn
Field data
In situ simulated data
(Galimany et al.)
Half-saturation coefficient
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Models DEB and SFG application
• DEB equationsRate of energy ingestion (J/day):
Arrhenius temperature function:
• SFG equations
Ingestion (mg/day):
is the chlorophyll concentration
Standard ingestion function:
k is the half-saturation coefficient
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Models DEB and SFG application
• DEB equationsRate of energy ingestion (J/day):
Arrhenius temperature function:
• SFG equations
Ingestion (mg/day):
is the chlorophyll concentration
Standard ingestion function:
k is the half-saturation coefficient
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Models DEB and SFG application
• DEB equationsRate of energy ingestion (J/day):
Arrhenius temperature function:
• SFG equations
Ingestion (mg/day):
is the chlorophyll concentration
Standard ingestion function:
k is the half-saturation coefficient
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Models DEB and SFG application
• DEB equationsRate of energy ingestion (J/day):
Arrhenius temperature function:
• SFG equations
Ingestion (mg/day):
is the chlorophyll concentration
Standard ingestion function:
k is the half-saturation coefficient
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Models DEB and SFG application
• DEB equationsRate of energy ingestion (J/day):
Arrhenius temperature function:
• SFG equations
Ingestion (mg/day):
is the chlorophyll concentration
Standard ingestion function:
k is the half-saturation coefficient
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DEB Model application
Winter WinterSpring AutumnSummer Spring Summer Autumn
Winter Spring Summer Autumn Winter Spring Summer Autumn
Field data
In situ simulated data
Chl-a available
Chl-a available
Ch
loro
pyll
(mg
/m2
)C
hlo
rop
yll (m
g/m
2)
Px (J/d
ay)P
x (J/day)
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DEB Model application
Winter WinterSpring AutumnSummer Spring Summer Autumn
Winter Spring Summer Autumn Winter Spring Summer Autumn
Field data
In situ simulated data
Chl-a available
Chl-a available
Ch
loro
pyll
(mg
/m2
)C
hlo
rop
yll (m
g/m
2)
Px (J/d
ay)P
x (J/day)
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SFG Model application
Winter Spring Summer Autumn Winter Spring Summer Autumn
Winter Spring Summer Autumn Winter Spring Summer Autumn
Field data
In situ simulated dataChl-a available
Chl-a available
Ch
loro
pyll
(mg
/m2
)C
hlo
rop
yll (m
g/m
2)
I/Cm
i (mg
/m3
)I/C
mi (m
g/m
3)
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SFG Model application
Winter Spring Summer Autumn Winter Spring Summer Autumn
Winter Spring Summer Autumn Winter Spring Summer Autumn
Field data
In situ simulated dataChl-a available
Chl-a available
Ch
loro
pyll
(mg
/m2
)C
hlo
rop
yll (m
g/m
2)
I/Cm
i (mg
/m3
)I/C
mi (m
g/m
3)
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Carrying capacity of Alfacs BayApproximations
• Mussel Mytilus galloprovincialis: The only consumer species.
• Only the food availability (seston/chlorophyll) and temperature are considered as limiting factors. We omitted oxygen concentrations and other characteristics of the bay as limiting factors.
• We considered the circulation of the water inside the bay as unidirectional.
Results
The mussel farm can have 117 rafts similar to the current ones.
The bay, in its whole extension, is able to
accommodate 253 rafts.
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Conclusions
• Difficulty for working in shallow depths.
• Chlorophyll spots inside the bay in the central zone, farther from the bay’s mouth.
• Pycnocline variation – opened channels/closed channels.
• DR rate and CR rate are lower during the hottest months of the summer.
• The Χk parameter for Alfacs bay is variable throughout the year due to the wide range of temperatures in the bay water.
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• DEB model application in Alfacs bay and to the mussel species Mytilus galloprovincialis has provided satisfying results and also allowed to observe an important dependence between uptake and temperature.
• SFG model is not applicable in Alfacs bay because it does not give a correct dependence between temperature and ingestion. It does not reproduce the observations correctly.
• We were able to calculate a first approximation of the carrying capacity for Alfacs bay. This approximation shows that Alfacs bay is able to accommodate 3 times more rafts than there exist nowadays.
Conclusions
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Thank you!
INIA: RTA04-023-Estudio integrado de los factores biológicos y ambientales condicionantes de la producción de mejillón en las bahías del delta del Ebro.
XRAq: Ecofisiologia del musclo en relació a les característiquesambientals de les badies del Delta de l’Ebre.