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ó áó áAproximación a la dinámica de Aproximación a la dinámica de Ecosistemas MarinosEcosistemas MarinosEcosistemas MarinosEcosistemas Marinos
Máster Internacional en Gestión de Zonas Costeras y Estuáricasy
LIM-UPC
Nixon Nixon BahamónBahamón
[email protected]@ceab.csic.eswww marinecometrics comwww marinecometrics comwww.marinecometrics.comwww.marinecometrics.comwww.ceab.csic.es/~oceanswww.ceab.csic.es/~oceans
Centre Centre d’Estudisd’Estudis AvançatsAvançats de Blanes (CEABde Blanes (CEAB--CSIC)CSIC)
Barcelona, 15 de febrero de 2010Barcelona, 15 de febrero de 2010
Coastal Zone Ecosystem ManagementCoastal Zone Ecosystem Management
Coastal zone management requires a good understanding of marine ecosystem dynamics
Marine ecosystems are constituted by a large number of components y y g pshowing complex interactions.
Simplifying the marine ecosystem structure and its dynamics is helpful.
A way for such simplification is through conceptual models.
Modelling interactions of ecosystem components allows getting an h t t d iapproach to ecosystem dynamics.
An approach, but not a good understanding, on the ecosystem dynamics can be reached in a couple of teaching hours.
Here we go!
EcosystemEcosystem--basedbased managementmanagement
Source: http://www.ebmtools.org3
11--6: Dominio pelágico6: Dominio pelágico11. Región nerítica; . Región nerítica; 22. Región oceánica; . Región oceánica; 33. Zona . Zona EpipelágicaEpipelágica. . 44. Zona Batial (. Zona Batial (4a4a. Zona . Zona MesopelágicaMesopelágica; ; 4b4b. Zona Batipelágica); . Zona Batipelágica); 55 Zona Abisopelágica o Abisal; Zona Abisopelágica o Abisal; 66 Zona Zona HadalopelágicaHadalopelágica o o HadalHadal; ; 55. Zona Abisopelágica o Abisal; . Zona Abisopelágica o Abisal; 66. Zona . Zona HadalopelágicaHadalopelágica o o HadalHadal; ; (t: termoclina permanente)(t: termoclina permanente)
AA--D: Dominio bentónicoD: Dominio bentónico
4
AA. Plataforma continental; . Plataforma continental; BB. Talud continental (. Talud continental (B1B1. Talud continental superior; . Talud continental superior; B2B2. Talud continental inferior); . Talud continental inferior); CC. Llanura abisal; . Llanura abisal; DD. Fosa . Fosa hadalhadal..
Fuente: Fuente: WikipediaWikipedia
Clasificación de los ecosistemas marinosClasificación de los ecosistemas marinos
Según la distancia a la costa• Zona nerítica: desde la línea de la costa hasta el borde de la plataforma p
continental.• Zona oceánica: fuera del límite de la plataforma continental.
Según la profundidad• Zona fótica: zona iluminada.
– Zona epipelágica: hasta el límite de la plataforma continental (200 m de p p g p (profundidad). Tiene lugar la producción primaria (fotosíntesis).
• Zona afótica: zona oscura. – Zona mesopelágica: 200 - 1.000 m. Abundante zooplancton. Se
encuentra la termoclina permanente.– Zona batipelágica: 1.000 - 3.000 m.– Zona abisopelágica o abisal: 3.000 - 6.000 m.– Zona hadopelágica o hadal: más de 6.000 m; fosas oceánicas
5
Clasificación de los ecosistemas marinosClasificación de los ecosistemas marinos
Sistema bentónico (fondo marino)El fondo marino (rocoso, pedregoso, arenoso, fangoso) está poblado por ( , p g , , g ) p p
organismos bentónicos..• La región fótica:
– Zona supralitoral (no sumergida)– Zona mesolitoral (intermareal)– Zona sublitoral: (permanentemente sumergida en la plataforma)(p g p )
• La región afótica: – Zona circalitoral: (externa de la plataforma sin vegetación)( p g )– Zona batial: (talud continental entre 200-3.000 m.)– Zona abisal: (fondo oceánico, llanuras oceánicas, entre 3.000-6.000 m.)– Zona hadal: (Zonas de subducción o de fosasa oceánicas 6.000 - 10,000 Zona hadal: (Zonas de subducción o de fosasa oceánicas 6.000 10,000
m)
6
Adriatic SeaAdriatic Sea
Catalan SeaCatalan Sea
Gulf of LionsGulf of Lions Black SeaBlack Sea
Tyrrhenian SeaTyrrhenian Sea
AlboranAlboran SeaSeaIonian SeaIonian Sea
Aegean SeaAegean Sea
Levantine basinLevantine basin
AQUAAQUA--MODIS SeaMODIS Sea--surfacesurface chlorophyllchlorophyll, , MarchMarch 2009 2009
((SourceSource: http://oceancolor.gsfc.nasa.gov): http://oceancolor.gsfc.nasa.gov)
Adriatic SeaAdriatic SeaGulf of LionsGulf of Lions Black SeaBlack Sea
Adriatic SeaAdriatic Sea
Tyrrhenian SeaTyrrhenian SeaCatalan SeaCatalan Sea
AlboranAlboran SeaSeaIonian SeaIonian Sea
Aegean SeaAegean Sea
Ionian SeaIonian SeaLevantine basinLevantine basin
7AQUAAQUA--MODIS SeaMODIS Sea--surfacesurface chlorophyllchlorophyll, ,
SeptemberSeptember 2009 2009 ((SourceSource: http://oceancolor.gsfc.nasa.gov): http://oceancolor.gsfc.nasa.gov)
MFSPPMFSPP--VOS VOS CruisesCruises
SourceSource::A. Cruzado, A. Cruzado, ChiefChief SciSci..
OceanOcean. . LabLab., CEAB., CEAB--CSIC. CSIC.
8PrepPrep. . byby L. L. SimicSimic
25/01/01, Blanes, 25/01/01, Blanes, SpainSpain
What drives ocean circulation?What drives ocean circulation? Global surface current systemGlobal surface current system
10
Open University, Ocean Circulation, 2007Open University, Ocean Circulation, 2007
The Ocean Conveyor Belt
Ocean circulation driven by density differences. (Density is controlled by ocean temperature and saltiness.) Cold, dense water in the Arctic merges with salty water from the Gulf Stream to create the sinking North Atlantic Deep Water (NADW) in the Norwegian-Greenland Sea The NADW helps to drive global ocean circulationGreenland Sea. The NADW helps to drive global ocean circulation.
Illustration The M Factory © Smithsonian Institution. From: http://forces.si.edu/arctic/02_02_04.html
What drives ocean circulation?What drives ocean circulation?Seawater flows along the horizontal plane and in the vertical:
Typical speeds of the horizontal flow or currents: ~ 0.01-1.0 m/s Typical vertical speeds within the stratified ocean: ~ 0.001 m/syp p
1. Wind driven circulation: The wind exerting a stress on the sea surface induces movement of that water. This is called Ekman Layer transport, which extends to the surface 50 to 200 meters. The wind driven circulation is characterized by large clock-wise and counter clock-wise flowing gyres, such as the subtropical and sub polar gyres.
2 Thermohaline circulation: Buoyancy (heat and freshwater) fluxes between 2. Thermohaline circulation: Buoyancy (heat and freshwater) fluxes between the ocean and atmosphere that alter the density of the surface water.The thermohaline circulation engages the full volume of the ocean into the climate system, by allowing all of the ocean water to 'meet' and interact directly the atmosphere (on a time scale of 100-1000 years). directly the atmosphere (on a time scale of 100 1000 years).
3. Geostrophic Currents: The ocean currents are for the most part geostrophic, meaning that the Coriolis Force balances the horizontal pressure gradients pressure gradients.
4. Inertial Currents: Curve motion produced by the Coriolis force when wind ceases to blow.
http://eesc.columbia.edu/courses/ees/climate/lectures/o_circ.html
Sverdrup's Theory of the Oceanic Sverdrup's Theory of the Oceanic p yp yCirculation Circulation
• Answers to the questions can be found in a series of three• Answers to the questions can be found in a series of threeremarkable papers published from 1947 to 1951.
• In the first Harald Sverdrup (1947) showed that the• In the first, Harald Sverdrup (1947) showed that thecirculation in the upper kilometer or so of the ocean isdirectly related to the curl of the wind stress.
• Henry Stommel (1948) showed that the circulation in oceanic gyres is asymmetric because the Coriolis forcevaries with latitude.
• Finally, Walter Munk (1950) added eddy viscosity and calculated the circulation of the upper layers of the Pacific. pp yTogether the three oceanographers laid the foundations fora modern theory of ocean circulation.
http //ocean o ld tam ed / eso ces/ocng te tbook/chapte 11/chapte 11 01 htmhttp://oceanworld.tamu.edu/resources/ocng_textbook/chapter11/chapter11_01.htm
Ecuaciones de MomentoEcuaciones de Momento
En dinámica de fluidos, las ecuaciones de momento describen el movimiento de un fluido compresible no viscosomovimiento de un fluido compresible no viscoso.
Ecuaciones de momento = Navier-Stokes eq. ≈ Euler eq.- sin Fr) q q )Fuerza de Coriolis(~7.3 x105 radianes s-1Gradiente de presión
fricciónlatitud
Harald Sverdrup (1947). The Oceans: Their Physics, Chemistry and General Biology
Circulación termohalina y transporte de partículaspartículas
Open University, Mar.Biog.Cycles, 2005Open University, Mar.Biog.Cycles, 2005
Molar Molar redfieldredfield ratios ratios
Δ Δ P:P: Δ Δ N:N: Δ Δ Si:Si: Δ Δ C = 1:16:15:106 C = 1:16:15:106 ((BrzezinskiBrzezinski, 1985)., 1985).
16
Utilización aparente de oxígeno (AOU) Utilización aparente de oxígeno (AOU)
17
Parámetro conservativo POParámetro conservativo PO(Fosfato preformado)(Fosfato preformado)(Fosfato preformado)(Fosfato preformado)
18
Niveles troficos del ecosistema marinoNiveles troficos del ecosistema marino
c le
vel
c le
vel
hro
ph
ich
rop
hic
Th
Th
Coll et al., 2008
FishingFishing groundsgrounds in a in a benthicbenthic environmentenvironmentIn the Blanes canyon In the Blanes canyon A. antennatusA. antennatus
dwells from 600 to 900 m depth, dwells from 600 to 900 m depth, coinciding with the lower boundary coinciding with the lower boundary
Iberian Iberian
BarcelonaBarcelona The Blanes CanyonThe Blanes Canyon
coinciding with the lower boundary coinciding with the lower boundary of Levantine Intermediate Water of Levantine Intermediate Water (LIW) and the upper boundary of (LIW) and the upper boundary of
Western Mediterranean Deep Water Western Mediterranean Deep Water Iberian Iberian peninsulapeninsula
Western Mediterranean Western Mediterranean SeaSea
Western Mediterranean Deep Water Western Mediterranean Deep Water (WMDW).(WMDW).
The Blanes canyonThe Blanes canyonyy
Fuente: Sarda et al. 2009.Prog. Oceanog. 82: 227-238
Ecosistema pelágicoEcosistema pelágico
200 m
Seasonal changes in upper water layersg pp y
EUPHOTIC ZONE EUPHOTIC ZONEEUPHOTIC ZONE
MIXED-LAYER
EUPHOTIC ZONE
MIXED-LAYER
Phy -N Phy N Ph N
NO -N NO -N
Phy -N
NO -N
Phy -N
NO -N
Phy -N
NH4-N
NZoo -N
NO -NNH4-N
NZoo -N
NO -NNH4-N
NZoo -N
NO -NNH4-N
NZoo -N
NO -N
NONO33-N-N NONO33-N-N NONO33-NNONO33 -N
winter spring autumnsummer
Summer phytoplankton chlorophyll in the 24.5°North Atlantic WOCE section
01 02 03 05 1 2 3 5 1 2
North Atlantic WOCE section
01 .02 .03 .05 .1 .2 .3 .5 1 2
SeaWiFS Station 101 12035506783 122742597590SeaWiFS
-100
-50
Station 101 12035506783 122742597590
-300
-250
-200
-150
Dep
th (m
)
-450
-400
-350
D
Chlorophyll a (mg / m3)
-75° -70° -65° -60° -55° -50° -45° -40° -35° -30° -25° -20°
Longitude
Bahamon et al., 2003
Surface chlorophyll Surface chlorophyll aa and trophic levels of the oceansand trophic levels of the oceans
EutrophicEutrophicMesotrophicMesotrophic
Chl a(mg m-3)
OligotrophicOligotrophic
(mg m )
Depth-integrated PP<0.5 g C m-2 d-1
0 5 1 5 C 2 d 1
Surface Clorophyll aOligotrophic 0.05 mg Chl a m-3
M t hi 0 5 Chl 3
A.Morel(1996)S Nixon 0.5 -1.5 g C m-2 d-1
1.5 - 2.5 g C m-2 d-1Mesotrophic 0.5 mg Chl a m-3
Eutrophic >1 mg Chl a m-3
S. Nixon(1995)
Observation, Analysis and Modeling of Marine SystemsObservation, Analysis and Modeling of Marine SystemsBiBi directional communicationdirectional communication Antenna
Daily data reception &Daily data reception &Publication on the webPublication on the web
BiBi--directional communicationdirectional communicationTemperature
Humidity
Pressure
Irradiance
Antenna
Wind speed& direction
GPSData Data
processingprocessingChlorophyll
TemperaturePressure GPS
Data Data processing & processing &
assimilation in assimilation in i li l
Phone cardPhone cardData loggerData logger
BatteriesBatteries
Solar panels
Lab Lab numerical numerical
modelsmodels
Field sampling Field sampling on board R/V & on board R/V &
1 DVCoupled
CEAB-CSIC
Current-meter T, S
analysisanalysis
VOSVOSPhysicalBiogeochemical Model
Mooring Site Mooring Site
TemperatureSalinityPARDissolved Oxygen
IM125 m
3 DCoupled Physical
Biogeochemical M d l
Blanes StationBlanes Station OxygenTurbidityChlorophyll
IM250 m
Model
Operational Oceanography, CEAB-CSIC
Vertical resolution of models
•Mixed layer models (Evans - Parslow, 1985; Fasham et al., 1990)
V i ll l d d l•Vertically resolved models:
z-dependent: z-level systems (~1 to 5 m layer thickness) ith t b l t diff i t i ti (V l t l with turbulent diffusion parameterisations (Varela et al.,
1994; Oguz et al., 1996; Levy et al., 1998; Bahamon and Cruzado, 2003, etc…)
sigma-dependent: vertical coordinates are layers following terrain; of common use in ocean circulation models (e. g. Mellor and Yamada 1974; Zavatarelli et al 2000 Ahumada Mellor and Yamada, 1974; Zavatarelli et al., 2000, Ahumada & Cruzado, 2007, etc...)
Isopycnal-dependent: vertical coordinates are isopycnalsIsopycnal dependent: vertical coordinates are isopycnals
Grids used in 3D modelsGrids used in 3D modelsGrids used in 3D modelsGrids used in 3D models
27Some model references: Y. Tony Song & Yi Chao. 1999; Blumberg & Mellor. 1987;
Schopf, PS. 1995, etc.Figures from Open University, Ocean Circulation, 2007Open University, Ocean Circulation, 2007
z vs. sigma coordinate models
z vs. sigma coordinate models Simulation of the vertical temperatureSimulation of the vertical temperatureSimulation of the vertical temperatureSimulation of the vertical temperature
in an area of the Algerian Seain an area of the Algerian Sea
-100
-50
)
-150
Dep
th (m
-250
-200D
Model results
Time (days)
Model results300 330 360 30 9060 120
( y )
Bahamon, 2002
Modelos biogeoquímicosModelos biogeoquímicosg qg q
Los modelos biogeoquímicos representan un conjunto de interacciones entre procesos biológicos, geológicos y químicos
El acoplamiento de los procesos biogeoquímicos y ecológicos a los procesos hidrodinámicos (medioambientales) dan como resultado
un modelo acoplado
Un modelo acoplado representa la interacción de elementos bióticos y abióticos con diferentes aproximaciones
(relaciones funcionales)(relaciones funcionales)
Modelo físico + bio-geo-químico o biológico o ecológico o =bio geo químico o biológico o ecológico o
Modelo acoplado
The nitrogen cycling in a pelagic ecosystem The nitrogen cycling in a pelagic ecosystem
Heat, wind stress, H2O, N2 , O2 , CO2ATMOSPHEREAtmosphereHeat, wind stress, H20, N2 , O2 , CO2
Small phytoplankton Small zooplankton
OCEAN Ocean
Large phytoplankton
p y p
Large zooplankton
pGrazing PredationGrazing
DA
RIE
Sda
ry
ryUptake
Mortality+ Fecalpellets
Excretion
Mortality
RA
L BO
UN
Dra
l bou
nd
l bou
ndar
y
NO2DIN
Uptake
Exudation
P O ND O N pellets
LATE
RLa
ter
Late
ral
MortalitySinking
NO3
NH4
Nitrification
Mortality
MineralisationBacteria
Uptake ExcretionExcretion
DEEPER WATERS
Fasham et al., 1990
Mineralisation
Comparison between surface ChlComparison between surface Chl--a from a 3D model and a from a 3D model and satellite observations in NW Mediterranean Sea satellite observations in NW Mediterranean Sea satellite observations in NW Mediterranean Sea satellite observations in NW Mediterranean Sea
Bernardello et al. 2007
Cambio instantáneo de una población: Cambio instantáneo de una población: Modelo biológicoModelo biológicoModelo biológicoModelo biológico
Nt+1 = Nt - (d+e) + (b+i)
La población de una especie en un momento determinado (Nt+1)La población de una especie en un momento determinado (Nt+1)(i.e. una microalga seleccionada como posible indicadora ambiental) está determinada por:
el número actual de individuos (Nt)menos el número de individuos que mueren (d) o emigran (e), más los individuos que nacen (b) e inmigran (i)
Cambio instantáneo de una población:Cambio instantáneo de una población:Modelo biológico y físico (acoplado)Modelo biológico y físico (acoplado)Modelo biológico y físico (acoplado)Modelo biológico y físico (acoplado)
( ) PHYswwPHY
zKt
PHY+
∂∂
+−⎥⎦⎤
⎢⎣⎡
∂∂
∂∂
=∂
∂ ( )zszzzt ∂⎥⎦⎢⎣ ∂∂∂
( ) G PHYNH4UNO2UNO3UPHYEXU
−−+++
La variación temporal de un grupo funcional (PHY, fitoplancton) dependerá de componente difusivo ( K ) componente difusivo (…Kz…)
menos las pérdidas por advección vertical y hundimiento de las células (…w+ws…)más factores biológicos:
consumo de nitrógenogmenos pérdidas de nitrógeno y consumo por parte del zooplancton
Fases para la implementación de un modelo Fases para la implementación de un modelo ecológicoecológicoecológicoecológico
• Calibración¿E d d l t i ió d l d l ?– ¿Es adecuada la parametrización del modelo?
– ¿El modelo reacciona como se espera?
V ifi ió• Verificación– ¿El modelo es estable a largo plazo? – ¿ Conserva la masa?
• Validación– ¿Los datos observados se corresponden con los estimados?
A áli i lit ti tit ti d l i l ió l ió – Análisis cualitativo y cuantitativo de la simulación en relación con las observaciones.
• Sensibilidad• Sensibilidad– Sensibilidad a las formulaciones, parámetros, constantes,
submodelos, variables de estado.– Análisis estadístico de las simulaciones en relación a la Análisis estadístico de las simulaciones en relación a la
sensibilidad de parámetros, etc.
Example: 1DV model of the Example: 1DV model of the oligotrophic pelagic environmentoligotrophic pelagic environment
A physical/ecological model is proposed to assess the timedependent vertical variability of plankton and nutrients inoligotrophic pelagic ecosystems: western Mediterraneanand subtropical NE Atlantic
Model description
Irradiance,lenght of daylight
• Blanes is 1DV , z-dependent
Mixed layer
Surface = 0 m
Euphotic
lenght of daylight
• Simulates vertical fluxes in the upper 300 m of the water Euphotic
layer
N-stock
column
V ti l l ti 3δ z = 3
TurbulentMi i
• Vertical resolution = 3m
• Variable non-uniformMixing(Kz ,Wz )
Variable non uniform vertical turbulent diffusion (Osborn, 1980)
Bottom = 300 m
N-Input N-Output• Depth-uniform (0.05 m/d)
upward vertical velocityupward vertical velocity
A ti l t b l t diff i d l
Physical componentsA vertical turbulent diffusion model
K (m2 s-1)1 -3
Typical summerstratification
N (s-1)10 3 10-2
σθ(kg m-3)10
110-3 stratification10-3 10 2
Mixedlayer
0 m28.0 29.0
(Z)2 ρgN ∂
•−=100 m Pycnocline
Zw(Z)
ρN
∂•=
(Z)2
(z)(z) N
0.25K
ε =Water
Stability(Brunt-
200 m
Density
(Z)N
Turbulentε10-8 10-7
(Brunt-Vaisala)
300 m
Osborn, 1980
Densityanomaly
Turbulentdiffusion
ε(m 2 s -3)
TKE
Physical componentsp
Application of the pp c o o evertical turbulent diffusion model to
a subtropical North Atlantic
section (above 500section (above 500 m depth)
Bahamón et al., 2003
Physical components :Time evolution of irradiance
Th B k (1981) ti ll th l th f d li ht (L1)
Time evolution of irradiance
• The Brock (1981) equations allow the length of daylight (L1) to be computed according to latitude
• Time variation of PAR in surface:
⎟⎠⎞
⎜⎝⎛+=
365N 2 sinP1P0PAR(0) π
⎟⎟⎠
⎞⎜⎜⎝
⎛⎥⎦
⎤⎢⎣
⎡
⎭⎬⎫
⎩⎨⎧ −+
π+=L1
L1tcosPAR(0)t)PAR(0, 1221⎠⎝ ⎦⎣ ⎭⎩
Time evolution of daylight and PAR
D li h (h ) 2Daylight (hours) PAR (Watts m-2)
50018
300
400
Wat
ts m
-2)
12
15
t (H
ours
)
200
300
PAR
(W
9
12
Day
light
1000 2000 4000 6000 8000
Time (Hours)
60 2000 4000 6000 8000
Subtropical NE Atlantic
Time (Hours)Time (Hours)
Catalan Sea
Light extinction in sea waterBlanes Canyon head - NW Mediterranean, 2002 The depth variation of PAR
⎟⎟⎠
⎞⎜⎜⎝
⎛⎥⎦⎤
⎢⎣⎡ ∗∗+ zD PHY(i) ckwk -
)()(⎟⎠
⎜⎝ ⎥⎦⎢⎣= zexp t)1,-PAR(it)PAR(i,
100 %
1.0 %Water extinction+
Phytoplankton self-th
0.1%
Phytoplankton self-shadingD
ept
The biological model fuelling
The upward diffusive flux of nitrogen (μmol m-2 s-1) results
g g
from the diffusivity (Kz) multiplied by the nitrate gradient:
⎥⎦⎤
⎢⎣⎡∂∂
=zNK flux N z ⎥⎦⎢⎣ ∂z
The new production deduced from the Redfield ratio:
16 mol of nitrate = 106 mol of carbon
-50
VOS 2 3 5 6 8 9 104 7
-150
-100
Dep
th
Validation-250
-200
Field data
Validation of temperature
(°C) simulations306 333 73343 13 30 10341 119
( C) simulations in the
Algerian Sea
-150
-100
-50
h (m
)
Algerian Sea
-250
-200
-150
Dep
t
Time (days)
Model results300 330 360 30 9060 120
VOS 2 3 5 6 8 9 104 7
-50
VOS 2 3 5 6 8 9 104 7
-200
-150
-100
Dep
th (m
)
-250
-200
Field data306 333 73343 13 30 10341 119
Validation of
-50
306 333 73343 13 30 10341 119temperature (°C)
simulations in the C l S
-150
-100
epth
(m)
Catalan Sea
-250
-200
D
Model results
Time (days)300 330 360 30 9060 120
Biological components and interactions
A simplified nitrogen cycling conceptual model
NH4+ - N
ExcretionZooplankton - N4
UptakeF l ll t
p
Grazing
Phytoplankton - N
Uptake
Fecal pellets,deaths
NO2- - N
p
Exudation
Sinking
NO3- - N
Exudation
Upward transport
Best fitting parameters and coefficients
¿Which parameters are best?
Symbol Value Definition Units
p
KNO3KNO2KNH4
0.90.80.7
Half saturation constant for nitrate uptakeHalf saturation constant for nitrite uptakeHalf saturation constant for ammonium uptake
mmol N m-3
mmol N m-3
mmol N m-3
KNO3KNO2KNH4
0.90.80.7
Half saturation constant for nitrate uptakeHalf saturation constant for nitrite uptakeHalf saturation constant for ammonium uptake
mmol N m-3
mmol N m-3
mmol N m-3
ψγVPHY
1.50.0253.00 1
pAmmonium inhibition parameter for nitrate and nitrite uptakePhytoplankton exudation fraction of nitritePhytoplankton maximum growth rateZooplankton mortalit rate
mmol N m-3
%d-1
d-1
ψγVPHY
1.50.0253.00 1
pAmmonium inhibition parameter for nitrate and nitrite uptakePhytoplankton exudation fraction of nitritePhytoplankton maximum growth rateZooplankton mortalit rate
mmol N m-3
%d-1
d-1μ∈Ωλ
0.1802030
Zooplankton mortality rateAmmonium fraction of zooplankton excretionFaecal pellets fraction of zooplankton excretion (detrital)Zooplankton assimilation efficiency
d 1
%%%
μ∈Ωλ
0.1802030
Zooplankton mortality rateAmmonium fraction of zooplankton excretionFaecal pellets fraction of zooplankton excretion (detrital)Zooplankton assimilation efficiency
d 1
%%%λ
KgImax
301.681.2
oop a to ass at o e c e cyZooplankton half saturation for ingestionZooplankton maximum ingestion rate
%mmol N m-3
d-1
λKgImax
301.681.2
oop a to ass at o e c e cyZooplankton half saturation for ingestionZooplankton maximum ingestion rate
%mmol N m-3
d-1
Sensitivity analysis would give an insight on the effect of changing parameters on model simulations
The evolution equation of N-phytoplankton (PHY) q p y p ( )
( ) PHYPHYPHY ∂⎤⎡ ∂∂∂ ( )z
PHYsww
zPHY
zKzt
PHY+
∂∂
+−⎥⎦⎤
⎢⎣⎡
∂∂
∂∂
=∂
∂
( ) G PHYNH4UNO2UNO3UPHYEXU
−−+++
NH + NExcretion
Zooplankton NNH + NExcretion
NH + NExcretion
Zooplankton NZooplankton N
Phytoplankton - N
NH4 - N
Uptake
NO2- - N
Uptake
Exudation
Sinking
Fecal pellets,deaths
NO3- - N
Zooplankton - N
Grazing
Phytoplankton - NPhytoplankton - N
NH4 - N
Uptake
NH4 - N
Uptake
NO2- - N
Uptake
ExudationNO2
- - N
Uptake
Exudation
SinkingSinking
Fecal pellets,deathsFecal pellets,deaths
NO3- - NNO3- - N
Zooplankton - N
Grazing
Zooplankton - N
Grazing
Upward transportUpward transportUpward transport
Some model interactions
The phytoplankton uptake of nutrients (UNO3) is as follows:
(NH4)NO3VU Ψ
Uptake of nitrate:
(NH4)
NO3PHYNO3 e
NO3KNO3VU Ψ
+=
(NH4)NO2VU Ψ
Uptake of nitrite(NH4)
NO2PHYNO2 e
NO2KVU Ψ
+=
NH4VU PHYNH4 =
Uptake of ammonia
NH4KVU
NO4PHYNH4 +
BLANES (model) run-time display
Simulations of N-phytoplankton (mmol m-3)p y p ( )
-100
0(m
)
0.70.80.91.0
-200Dep
th (
0 20.30.40.50.6
Catalan Sea0 60 120 180 240 300
-3000.10.2
0
Catalan Sea
-100
h (m
)
0.3
0.4
0.5
-200Dep
t
0.2
0.3
Subtropical North Atlantic 0 60 120 180 240 300
-300 0.1
Seasonal validation of N-phytoplankton (mmol m-3)in the Catalan Seain the Catalan Sea
0
m) -100
-50
Dep
th (m
-200
-150
winter350
-300
-250
spring summer autumn
0.0 0.5 1.0-350
0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0
Lines indicate model results Points indicate field observationsLines indicate model results. Points indicate field observations
55
The evolution equations of nutrients:iii
Phytoplankton - N
NH4+ - N
Excretion
Uptake
NO2- - N
UptakeSinking
Fecal pellets,deaths
NO3- - N
Zooplankton - N
Grazing
Phytoplankton - NPhytoplankton - N
NH4+ - N
Excretion
Uptake
NH4+ - N
Excretion
Uptake
NO2- - N
Uptake
NO2- - N
UptakeSinkingSinking
Fecal pellets,deathsFecal pellets,deaths
NO3- - NNO3- - N
Zooplankton - N
Grazing
Zooplankton - N
Grazing
N - Nitrate:
PHYUNO3NO3KNO3 ∂⎤⎡ ∂∂∂
2 Exudation 3
Upward transport
2 Exudation2 Exudation 3
Upward transport
3
Upward transport
PHYUz
wz
Kzt NO3z ∗−
∂−⎥⎦
⎤⎢⎣⎡
∂∂=
∂
N - Nitrite:
PHYUPHYNO2NO2KNO2 ∂⎤⎡ ∂∂∂ PHYUPHYz
wz
Kzt NO2EXUz ∗−+
∂−⎥⎦
⎤⎢⎣⎡
∂∂=
∂
N - Ammonia:
PHYUNH4wNH4KNH4∗∈+
∂⎥⎤
⎢⎡ ∂∂
=∂ PHYU
zw
zK
zt NH4z ∗−∈+∂
−⎥⎦⎢⎣ ∂∂=
∂
Simulations of N-nitrate (mmol m-3)( )
0
6
7
8
-200
-100
Dep
th (m
)
2
3
4
5
6
0 60 120 180 240 300-300
1
2
0 4.0
Catalan Sea
-100
0
h (m
)
2 0
2.5
3.0
3.5
.0
300
-200Dep
th
0.5
1.0
1.5
2.0
Subtropical North Atlantic 0 60 120 180 240 300
-300
Seasonal validation of N-nitrate (mmol m-3) in the Catalan SeaCatalan Sea
0
(m) -100
-50
Dep
th
-250
-200
-150
winter-350
-300
250
spring summer autumn
0 2 4 6 8 0 2 4 6 8 0 2 4 6 8 0 2 4 6 8
Lines indicate model results and points indicate field observations
Simulations of N-nitrite (mmol m-3)( )
-100
0
m)
0.5
0.6
0.7
-200Dep
th (m
0 1
0.2
0.3
0.4
C t l S
00 40
0.45
0 60 120 180 240 300-300
0.1Catalan Sea
-100
epth
(m)
0.20
0.25
0.30
0.35
0.40
0 60 120 180 240 300-300
-200De
0.00
0.05
0.10
0.15
Subtropical North Atlantic 0 60 120 180 240 300
Seasonal validation of N-nitrite (mmol m-3) in the Catalan SeaCatalan Sea
0
m) -100
-50
Dep
th (m
-200
-150
winter-300
-250
spring summer autumn
0.0 0.1 0.2 0.3 0.4-350
p g
0.0 0.1 0.2 0.3 0.4 0.0 0.1 0.2 0.3 0.4 0.0 0.1 0.2 0.3 0.4
Lines indicate model results and points indicate field observationsLines indicate model results and points indicate field observations
Model productsp
Estimates of vertical nitrogen fluxes upwardthe euphotic zone
Depth Advective fluxes Diffusive fluxes Total fluxes2 1 2 1 2 1 2 1
g p p
m µmol m-2 d-1 µmol m-2 d-1 µmol m-2 d-1 mol m-2 y-1
Catalan Sea120 - 130 144 1632 1776 0.64120 130 144 1632 1776 0.64190 - 200 298 140 438 0.16290 -300 380 5 385 0.14
Subtropical NE Atlantic150 - 160 24 582 606 0.22190 200 120 197 317 0 11190 - 200 120 197 317 0.11290 - 300 187 5 192 0.07
Algunas ventajas de la modelación numéricaAlgunas ventajas de la modelación numérica
• Validar hipótesis sobre elementos que forzan el (eco) sistema( )
• Simular flujos realistas de cuencas oceánicas y topografía del fondo. Se pueden simular ( d i ) f t i i l l l (predecir) futuros escenarios a nivel local, regional, global.
• Interpolar información dispersa de barcos boyas • Interpolar información dispersa de barcos, boyas, satélites
Algunas desventajas de la simulación numérica Algunas desventajas de la simulación numérica
ó• La simulación no es fiel reflejo de la realidad. • Muchas posibles fuentes de error: condiciones
i i i l ódi f t (b ) ál l d l iniciales, códigos fuente (bugs), cálculo de la difusión turbulenta, supuestos…etc.
– Las ecuaciones algebraicas, esenciales en los códigos de los programas, son ecuaciones discretas o aproximaciones l b i d l i dif i l ( id )algebraicas de las ecuaciones diferenciales (grid approx.).
– Los modelos prácticos deben ser más simples que el sistema p p qreal
Referencias onReferencias on--linelineReferencias onReferencias on--lineline
• Numerical Modelling Theoryg y
http://www.physics.uq.edu.au/xmds/documentation/html/node65.html
• Introduction to physical oceanography. Robert Steward. Free web-based text book (and pdf) in physical oceanography and a chapter in numericalmodelling
http://www-ocean.tamu.edu/education/oceanworld-old/resources/ocng_textbook/contents.html
• Reference hidrodynamic model: Princeton Ocean Model (POM)Reference hidrodynamic model: Princeton Ocean Model (POM)
http://www.aos.princeton.edu/WWWPUBLIC/htdocs.pom/
• List of coastal models• List of coastal models
http://www.scisoftware.com/environmental_software/referral.phphttp://woodshole.er.usgs.gov/operations/modeling/ecomsi.htmlhttp://www.ebmtools.org/
• ….
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• Ecological modelling• Ecological modelling• Continental Shelf Research• Deep Sea Research• Dynamics of Atmospheres & Oceans• Encyclopedia of Ocean Sciences• Geophysical Research Letters• Journal of Atmospheric & Oceanic Technology• Journal of Geophysical Research• Journal of Geophysical Research• Journal of Marine Research• Journal of Marine Systems• Journal of Physical Oceanography• Ocean Dynamics • Ocean Modeling• Oceanography• Physics Today• Physics Today• Progress in Oceanography• Nature, Science, Tellus• PLoS (Public Library of Science)• …