MGCC: Mytilus galloprovincialis carrying capacity model POC, Ammonia NAMEMG-IBM (M....
5
MGCC: Mytilus galloprovincialis carrying capacity model POC, Ammonia NAME NAME MG-IBM MG-IBM ( M. galloprovincialis M. galloprovincialis growth model) growth model) HYDRODYNAMIC HYDRODYNAMIC MODEL OF MODEL OF THE ADRIATIC SEA THE ADRIATIC SEA Water temperature Chl-a POC STATE VAR. STATE VAR. Nitrate Nitrate Ammonia Ammonia Silicate Silicate Phosphate Phosphate DOC DOC POC POC Phytoplankton Phytoplankton Zooplankton Zooplankton Current velocities Local, scale A regional, scale B Solar radiation STATE VAR. STATE VAR. Somatic Somatic and gonadic and gonadic dry weight dry weight CURRENT METER CURRENT METER DATA DATA NAME NAME TRANSP TRANSP (transport sub-model) (transport sub-model) + PELADRI PELADRI (reaction sub-model) (reaction sub-model) ** Model development in collaboration with the University of Hamburg (D) and IIASA (A). Model testing in collaboration with ICRAM-Chioggia and NIB (partner 4).
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Transcript of MGCC: Mytilus galloprovincialis carrying capacity model POC, Ammonia NAMEMG-IBM (M....
MGCC: Mytilus galloprovincialis carrying capacity model
POC, Ammonia
NAMENAME
MG-IBMMG-IBM ((M. galloprovincialisM. galloprovincialis
growth model)growth model)
HYDRODYNAMIC HYDRODYNAMIC MODEL OFMODEL OF
THE ADRIATIC SEATHE ADRIATIC SEA
Water temperature
Chl-aPOC
STATE VAR.STATE VAR.NitrateNitrate
AmmoniaAmmoniaSilicateSilicate
PhosphatePhosphateDOCDOCPOCPOC
PhytoplanktonPhytoplanktonZooplanktonZooplankton
Current velocities
Local, scale A regional, scale B
Solar radiation
STATE VAR.STATE VAR.Somatic Somatic
and gonadicand gonadicdry weight dry weight
CURRENT METER CURRENT METER DATADATA
NAMENAME
TRANSP TRANSP (transport sub-model)(transport sub-model)
++PELADRI PELADRI
(reaction sub-model)(reaction sub-model)
** Model development in collaboration with the University of Hamburg (D) and IIASA (A). Model testing in collaboration with ICRAM-Chioggia and NIB (partner 4).
0 0.07 0.140.035Decimal Degrees
VISMAmussel farm
Venice
Chioggia
Mussellines
~ 2 km
~ 2
km
0 0.07 0.140.035Decimal Degrees
VISMAmussel farm
Venice
Chioggia
Mussellines
~ 2 km
~ 2
km
2. Mussel growth: trajectories atdifferent locations within the mussel farm
MGCC: preliminary run at scale A1. Study site: DCF-UNIVE WP5 site Adriatic sea 12 months simulation
3. Mussel dry weight [g] at six different locations within the mussel farm (after 1 yr of cultivation)
4. phytoplankton density [mg C L-1] at the farm site – local depletion
0 41 83 125 166 208 250 291 333
days from seed ing
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
g d
ry weig
ht
d ry we ight loca tion 1 dry we ight loca tion 2 dry we ight loca tion 3 dry we ight loca tion 4 dry we ight loca tion 5 dry we ight loca tion 6
1
2
3
4
65
WATERCOLUMN
EDM: Early diagenesis modelEDM: Early diagenesis model(developed under BRNS(developed under BRNSTMTM))
Sedimenttemperature
SEDIMENT
Deposition model(DEPOMODTM)
Faeces production
Organic carbon flux
MG-IBM: MG-IBM: Mytilus galloprovincialisMytilus galloprovincialis growth modelgrowth model
Nutrient fluxes, N, P
DEPOMOD + EDM (Early Diagenesis) modelsLocal, scale A
Current velocities
HYDRODYNAMIC HYDRODYNAMIC MODEL OFMODEL OF
THE ADRIATIC SEATHE ADRIATIC SEA
CURRENT METER CURRENT METER DATADATA
** Model development in collaboration with partner 1, SAMS, and the University of Utrecht (NL).
3. Diagenetic model output: profiles of the state variables in the sediment. __ reference simulation, _ _ impact scenario
10 14 18 22
S O 4 [m m ol L -1]
0
5
10
depth [cm]
0 4 8
NO 3 [m ol L -1]
0
1
2
3
4
5d
ep
th [cm
]0 400 800
NH+4 [m ol L -1]
0
5
10
de
pth
[cm]
0 400 800
F e 2+ [m ol L -1]
0
5
10
depth [cm]
0 40 80
M n2+ [m ol L -1]
0
5
10
depth [cm]
0.0 0.4 0.8
H2S [mmol L -1]
0
5
10
depth [cm]
-0.002 0.001 0.004
mol N O 3- Lpw
-1 yr-1
1
2
3
4
5
depth [cm]
ne t NO 3- ra te (impact scenario)
ne t NO 3- ra te (re ference simulation)
0 40 80 120 160 200
O 2 [m ol L -1]
0
0.5
1depth [cm
]0.0 0.4 0.8 1.2 1.6 2.0
O C [% ]
0
5
10
depth [cm]
a
2. Results of the MERAMOD particle tracking model: predicted OC flux at the sediment-water interface.
500 1000 1500 2000 2500 3000 3500
easting [m ]
500
1000
1500
2000
2500
3000
3500
nort
hing
[m]
Faeces flux [g C m -2 yr-1]
0
10
25
50
DEPOMOD + EDM: application to longline mussel farm
1. Study site: DCF UNIVE WP5 site
(Adriatic sea)
long-term impact simulation (15 yr)
0 0.07 0.140.035Decimal Degrees
VISMAmussel farm
Venice
Chioggia
Mussellines
~ 2 km
~ 2
km
0 0.07 0.140.035Decimal Degrees
VISMAmussel farm
Venice
Chioggia
Mussellines
~ 2 km
~ 2
km
2. EDM model calibration: profiles of the state variables in the sediment at the reference station (BRef). __ model . data
3. Results of the DEPOMOD particle tracking / resuspension model: predicted OC flux at the sediment-water interface.
DEPOMOD + EDM: application to salmon cages
1. Study site: SAMS WP5 site (Loch
Creran)
short-term impact simulation (6 months)
1 0 0 2 0 0 3 0 0 4 0 0 5 0 0
E astin g (m )
1 0 0
2 0 0
3 0 0
4 0 0
Nor
thin
g (m
)
EW
0
EW
25
EW
50
EW
75
ES
E25
ES
E50
BW
10
BW
40
1 0 0
5 0 0
2 5 0 0
1 0 0 0 0
3 0 0 0 0
g m y r-2 -1
0 40 80 120 160 200
F e 2+ [m ol L -1]
0
5
10
depth [cm]
b
0 400 800
NH+4 [mol L -1]
0
5
10depth [cm
]
d
0 40 80
HP O 42-
[m ol L -1]
0
5
10
depth [cm]
f
4. Model validation:profiles of the state variables in the sediment at the impacted station (BW10). __ model . data
0 1000 2000 3000 4000
NH+4 [mol L -1]
0
5
10
depth [cm]
d
0 200 400 600
HP O 42-
[m ol L -1]
0
5
10
depth [cm]
f
0 40 80
Fe 2+ [mol L -1]
0
5
10
depth [cm]
b
** In collaboration with partner 1, SAMS and COBO EU project
