Three-dimensional Modeling of the Seasonal Variation of Phytoplankton and Zooplankton in the
Iberian Upwelling System
Rosa Reboreda, Jesus Dubert, Rita Nolasco, Martinho Marta-Almeida, Henrique Queiroga, Carlos
Rocha, Nuno Cordeiro.
Group of Marine Ecosystems and Modeling, CESAM, University of Aveiro
Abstract
The Iberian upwelling system is characterized by a summer upwelling season driven by dominant
northerly winds. The cold, nutrient rich water upwelled along the coast makes this region a very
productive ecosystem, governed by the physical-biological interactions. Phytoplankton production is
the base of most marine trophic webs and thus its variability affects the dynamics of the whole
ecosystem, including some economically important fisheries. It depends on the temperature and the
availability of nutrients and light for growth. These are highly variable factors related with the
hydrodynamics and with seasonal changes.
This study is the first attempt to model the lower trophic levels in the upwelling region along the
Portuguese shelf and coast using The Regional Ocean Modeling System (ROMS) coupled to a
biogeochemistry module. ROMS is a three-dimensional (3D), high resolution circulation model,
adequate to resolve mesoscale phenomena such as eddies and filaments, both involved in the short-term
variability of primary production. The biogeochemical model is a simple Nitrogen based NPZD-type
(Nitrate-Phytoplankton-Zooplankton-Detritus). We adopted a horizontal grid resolution of 5 km for a
600 km x 250 km domain. The initial and boundary conditions for the physical variables were given
from a parent domain of 3 km resolution for the entire Iberian margin. The correspondent values for
biogeochemical variables were supplied by Levitus climatological means. The model was forced with
mean atmospheric conditions (wind and heat flux) (COADS) along 4 years. Results were compared to
satellite observations of ocean color in the region.
Monthly means of the biological variables reasonably reproduced the observed seasonal cycle of
primary
and
secondary
production
in
the
coast,
shelf
and
adjacent
open
ocean.
Phytoplankton/chlorophyll concentrations were generally low during winter, showing a noticeable
bloom in spring and early summer, coinciding with the onset of the upwelling season. Blooms were
also recurrent in late summer/early autumn. Differences in the timing and concentrations of such
blooms were evident between the coast and the open ocean.
Introduction
The West Iberian coast is the northern limit of the NE Atlantic Upwelling Region, which is
characterized by a summer upwelling season from April to September, driven by prevailing northerly
winds (Relvas et al., 2007). The autumn shift to dominant southerly winds ends the upwelling season in
the region and favors the onset of a warm poleward current over the slope (Peliz et al., 2005). The
coastal upwelling is an oceanographic phenomenon recurrent at the East margins of the oceans, caused
by equatorward wind parallel to coastline and Earth rotation. Surface coastal waters are moved offshore
and replaced by cold, nutrient rich deep water. The coastal upwelling along the coast from Cape
Fisterra (NW Spain) to Cape São Vicente (SW Portugal) makes this region a very productive ecosystem
governed by morphological-physical–biological interactions, and is highly related to biodiversity and
fishing resources. Phytoplankton production is the base of most marine trophic webs and thus its
variability affects the dynamics of the whole ecosystem. Also, phytoplankton growth involves uptake
of CO2, which may influence its atmospheric levels and thus climate (Falkowski et al., 1998), a reason
why high productive regions like upwelling areas are under the focus of research e.g. (Hales et al.,
2005). Factors underlying variability of biological production are mainly temperature, and the
availability of nutrients and light for growth, which are closely related to hydrodynamics and other
seasonal and interannual changes.
Some observational studies, both from in situ measurements and satellite ocean color images of
chlorophyll concentration (photosynthetic pigment) have monitored the biogeochemistry of the region
(e.g. (Alvarez-Salgado et al., 2003; Ribeiro et al., 2005)), verifying the large temporal and spatial
variability of biological production and relevant chemical elements involved in it, namely C and N.
Short-term mesoscale physical processes such as eddies, filaments and river buoyant plumes (reviewed
by (Peliz et al., 2005)) are thought to be a major factor influencing ecosystem functioning (Queiroga et
al., 2007; Santos et al., 2007). However, the current knowledge of the ecosystem functioning is not
enough to understand the described variability, the processes involved, and to predict responses of the
system to perturbations.
This study is the first attempt to model the lower trophic levels, namely phytoplankton and
zooplankton, in the upwelling region along the Portuguese shelf and coast. The model is The Regional
Ocean Modeling System (ROMS) coupled to a biogeochemistry module. ROMS is a three-dimensional
(3D) high resolution circulation model, able to resolve mesoscale phenomena such as those involved in
the short-term variability of primary production. We aim to develop a research tool that can help to
understand de ecosystem dynamics in the region, as well as forecast system for biogeochemical
variables, which could have diverse applications such as predicting harmful algal blooms. Here, we
show results for a simple NPZD (Nutrients-Phytoplankton-Zooplankton-Detritus) configuration of the
model, and compare them to satellite observations of ocean color in the region. We analyzed the
temporal and spatial distributions of the simulated variables, describing differences in the timing and
concentrations of algal blooms within the area under study.
Model description
Simulations were performed with ROMS, a three-dimensional (3D), high resolution, free surface with
vertical sigma coordinates oceanic model (Shchepetkin & McWilliams, 2005) and embedded nesting
capabilities (ROMS_AGRIF) (Penven et al., 2006). The model included a physical component to
simulate the ocean hydrodynamics, and a biogeochemical module to simulate the evolution of the
biological components. A detailed description of the physical model can be found in (Peliz et al., 2007).
We adopted a horizontal grid resolution of 5 km for a 600 km x 250 km domain, which spanned from
12º W to 8.5º W and from 37º N to 43º N. Vertical resolution was 30 sigma levels. The initial and
boundary conditions for the physical variables were given from a parent domain of 3 km resolution for
the entire Iberian margin (Fig. 1). The correspondent values for biogeochemical variables were
supplied by Levitus climatological means. This lower resolution of the nested domain relative to the
parent domain was adopted to reduce the time needed for biogeochemical runs, which are considerably
time demanding than the physical runs alone. The aim was to have a model configuration that
facilitated the parameters testing experiments within a reasonable computer time. Our aim, however, is
to implement the biogeochemical model in the parent domain and a nested higher resolution domain,
once we have selected the set of parameters that best reproduces observations. The model was forced
with mean atmospheric conditions (wind and heat flux) (COADS). The nested domain was run offline
for 8 years, letting a spin up of 4 years to obtain a stable annual cycle. Outputs shown in the results
section are means of the last 4 years of the run.
Figure 1. Parent domain (outer box) and nested domain (inner box). The biogeochemical module was
run in the nested domain only (12º W to 8.5º W longitude and 37º N to 43º N latitude).
The ROMS biogeochemical module used a simple Nitrogen based NPZD configuration, based in
(Fasham et al., 1990), computing 4 state variables: Nutrients (nitrate), and single groups of
Phytoplankton, Zooplankton and Detritus (Fig. 2), all expressed in mmolN m-3. Chlorophyll a (mg m-3)
is derived from phytoplankton concentration using a chlorophyll:C ratio of 0.02 (mg Chla/mg C) and a
C:N ratio of 6.625 (mmolC/mmolN), i.e., a Redfield ratio. The 3D time evolution of the concentration
of any of the biogeochemical variables (Bi) followed the general equation:
δB i
δt
=∇ K ∇ Bi −u ∇ h B i − w+w sink 
δBi
δz
+sms  Bi 
where the terms in the right hand side account for diffusion, horizontal advection, vertical mixing and
sink minus source (sms) biological processes, respectively. K is the eddy kinematic diffusivity tensor,
u is the horizontal velocity of the fluid, w and wsink are the vertical velocity of the fluid and the vertical
sinking rate of the biogeochemical tracer, respectively, with the exception of zooplankton and nitrate, to
which no sinking rate is attributed. Model parameters for the sink/source terms are listed in Table 1. A
detailed description of the biogeochemical model, including sink-source terms, can be found in (Kone
et al., 2005)
Parameter
Light attenuation in seawater
Light attenuation by chlorophyll
Initial slope of the P-I curve
C:N ratio for phytoplankton
Cellular chlorophyll:C ratio
Half-saturation for phytoplankton NO3 uptake
Zooplankton half-saturation constant for ingestion
Maximum zooplankton growth rate
Zooplankton assimilation coefficient
Phytoplankton mortality rate
Zooplankton mortality rate
Zooplankton specific excretion rate
Detrital mineralization to NO3 rate
Sinking velocity for phytoplankton
Sinking velocity for detritus
Table 1. Parameter values of the NPZD model
phytoplankton
grazing
Value
0.04
0.024
1
6.625
0.02
1.5
1
0.9
0.75
0.03
0.1
0.1
0.05
0.5
5
Unit
m-1
(m2 mg Chla)-1
mg C (mg ChlaW m-2 d)-1
mol C(mol N)-1
mg Chla(mg C)-1
mmol N m-3
mmol N m-3
d-1
n.d.
d-1
d-1
d-1
d-1
m d-1
m d-1
zooplankton
metabolism
uptake
mortality
nitrate
mineralization
sinking
detritus
sinking
Figure 2. Schematic representation of the NPZD model used.
Satellite data
Biogeochemical model outputs were compared to averaged remotely sensed chlorophyll-a
concentration, obtained from regional objective analysis for merging high resolution MERIS,
MODIS/Aqua and SeaWiFS Chlorophyll-a data from 1998 to 2008. A mean of 10 temporal series (one
series for each year) was calculated for four 0.1º x 0.1º squares centered at (1) 42ºN 10.5ºW, (2) 42ºN
9ºW, (3) 38ºN 10.5ºW and (4) 38ºN 9ºW) , respectively.
Results and discussion
a) Hydrodynamics
Ocean hydrodynamics of Western Iberia has been successfully reproduced with the ROMS model in
previous studies of the research group (e.g. Peliz et al. 2007). Here, we show monthly mean surface
values of the physical variables (temperature, salinity and velocity) for the current simulation
experiment that reasonably reproduce conspicuous patterns of seasonal ocean circulation in the
region, namely the winter Iberian Poleward Current (IPC) over the slope and the coastal summer
upwelling (Fig. 3). Fig. 3(a) shows the January means for these variables, representing a typical winter
situation. A northward tongue of warm water from the southern part of the domain was observable from
the sea surface temperature (SST) distribution and the v component of velocity, which corresponded to
the IPC, a winter circulation feature of Western Iberia characterized by a poleward current of warm
water, generated at latitudes of mid-western Iberia coast and spreading over the slope (Peliz et al.,
2003). Means of the same variables for the month of June, representative of a summer situation, are
shown in Fig. 3(b). The SST distribution was that expected from a typical upwelling situation, with a
colder band near the coast resulting from the deep, cold water upwelled under prevailing northerly
winds. The associated southward upwelling current is also evident from the negative v component of
velocity. The cooling of
coastal water was about 0.5-1ºC intensified (lower SST) in the model
compared to satellite observations for this month (mean SST data for 10 years, not shown), as
previously observed by (Oliveira et al., 2009)
b) Seasonal evolution of biogeochemical variables.
Mean surface concentrations of modeled nitrate, chlorophyll-a, zooplankton and detritus are shown in
Figure 4. for each of 4 months chosen to represent the 4 seasons: January (winter), April (spring), July
(summer) and October (fall). The winter situation presented low chlorophyll concentration in the entire
domain, typically under 0.5-0.6 mg/m3, and a similar behavior for zooplankton and detritus. This is in
agreement with observed surface ocean color from satellite data for this period (Fig. 5). April mean
surface chlorophyll-a evidenced the spring bloom offshore, related to higher light availability, reaching
concentrations about 1 mg/m3 in most parts of the domain. This was also reflected in zooplankton
January
June
Figure 3. January (left) and June (right) mean sea surface temperature (SST) (ºC), salinity, u velocity
component (W-E) (cm/s) and v velocity component (S-N) (cm/s) from ROMS model (n= 7 years ).
concentration, which considerably increased offshore, where it generally exceeded 0.5 mmol N/m3
(Fig. 4). When compared to satellite observations, modeled chlorophyll-a was similar in the northern
part of the domain, although it seemed to be overestimated in the southern part (Fig. 5). Summer
upwelling season, represented by July, was characterized by high chlorophyll-a concentration near the
coast, the mean exceeding 2 mg/m3, as a result of deep nutrient rich water upwelled along the Iberian
coast. The opposite trend was observed offshore, where reduced nutrient availability related to surface
ocean thermal stratification resulted in low chlorophyll-a concentration (Fig. 4). This was the same
pattern obtained by satellite data for this time of the year (Fig. 5). The fall month showed a decrease in
mean chlorophyll-a concentrations near the coast, as a result of the end of the upwelling season, while a
slight increase was observable offshore (Fig. 4), provided the eroding of the thermal stratification. The
latter was not evident in the satellite image. However, it should be noted that satellite chlorophyll-a
concentrations presented here were calculated using a case 2 waters algorithm, corresponding to coastal
waters, which may result in some inexactitudes in chlorophyll-a concentrations offshore. In general,
Figure 4. ROMS monthly mean surface concentration of nitrate (mmol N m-3), chlorophyll-a (mg m-3),
zooplankton (mmol N m-3) and detritus (mmol N m-3) for January (4 top left), April (4 top right), July (4
bottom left) and October (4 bottom right) (n=4years)
chlorophyll-a concentration in the coast was lower in the model than in the satellite data, with the
exception of July (upwelling season). This may be a consequence of the lack of river inputs in the
simulation, which would supply coastal zone with nutrients and stratified river plumes favorable for
phytoplankton growth.
April
January
July
October
Figure 5. Merged MERIS, MODIS/Aqua, SeaWiFS mean chlorophyll-a concentration for January,
April, July and Ocober from 1998-2008.
c) Spatial trends in the model
Hovmüller diagrams were constructed in order to analyze spatial variations in the timing of
phytoplankton blooms within the domain (Fig. 6). The first Hovmüller diagram allows analyzing
differences in the timing of blooms with latitude (N-S section, 600 km) along the fifth to eight year of
simulation (Fig. 6(a)). A spring bloom happened at about the same time for all latitudes in the 4 years
(time indices 20, 80, 140, 200). A second bloom occurred in fall (time indices 60, 120, 180, 240),
although this was more evident in the southern part of the domain. The second Hovmüller diagram
shows differences in the timing of chlorophyll-a maxima with distance from de coast (E-W section, 250
km) for the same period (Fig. 6(b)). The spring bloom was evident offshore for the 4 years, with the
same time indices described above. The same applies to the fall bloom. Near the coast, the effect of the
upwelling season was an extended chlorophyll-a maximum along the whole summer for the 4 years
(time indices 20-40, 60-100, 140-160, 200-220). There seemed to be a transition zone between the
offshore and the coastal zone (25-100 km from the coast).
The results described above were compared to time series derived from satellite data of chlorophyll-a
concentration from 1998 to 2008. In order to smooth the high interannual variability, means of the 10
times series were calculated as an approximation to an average evolution of chlorophyll-a
concentration along one year (Fig. 7). Offshore concentration of chlorophyll-a both in the North and
South presented a maximum occurring
(a)
(b)
Figure 6. Hovmüller diagrams of (a) temporal and meridional variations (North to the left) and (b)
temporal and coast vs offshore variations (coast to the left) of ROMS chlorophyll-a concentration (mg
m-3) within the domain along 4 years (60 time indices correspond to 1 year).
Offshore concentration of chlorophyll-a both in the North and South presented a maximum occurring
in spring, as described for the model, although concentrations were lower than the model ouputs. Near
the coast chlorophyll maxima were observed during spring and summer, both in the North and the
South. Also here modeled chlorophyll-a concentrations exceeded those from satellite data.
Figure 7. Averaged temporal
evolution of chlorophyll-a
concentration (mg m-3) along
the year, from 1998-2008, for
4 locations: a) 42ºN 10.5ºW
N-offshore b)42ºN 9ºW Ncoast c)38ºN 10.5ºW Soffshore d)38ºN 9ºW S-coast.
d) Vertical chlorophyll-a distribution.
Fig. 8 shows a vertical section of temperature and chlorophyll-a concentration at 42º N during an
upwelling event. A layer of high chlorophyll-a concentration is present in the coastal region, from the
surface to about 50 m depth, corresponding with the lowest temperature zone. Offshore, a sub-surface
maximum appeared at the base of the thermocline, at about 50 m depth. This vertical structure is
similar to in situ observations in the area (Castro et al., 2000).
Figure 8. ROMS vertical sections of (a) temperature (ºC) and (b) chlorophyll-a (mg m-3) at 42º N
across the shelf during an upwelling situation (fifth year run).
Conclusions
The outputs of the biogeochemical model reasonably reproduced the seasonality and spatial trends
remotely measured in phytoplankton/chlorophyll-a concentration in the study area. The offshore region
presented the most important bloom in spring and a secondary bloom in fall. The coastal region,
although also affected by these blooms, experienced prolonged high chlorophyll-a concentration during
summer, as a consequence of nutrient inputs from upwelling. During the upwelling season the model
seemed to overestimate chlorophyll concentration in the coast, maybe as a consequence of intensified
upwelling simulated (about 1º colder water than satellite data). An overestimation also seemed to
happen for the offshore spring bloom in the southern part of the domain. On the contrary, during the
rest of the year, chlorophyll concentration in the coast seemed to be underestimated, probably as a
consequence of the lack of river inputs in the model. Thus, next steps to continue improving the model
performance would consider introducing river inputs and continue exploring the best set of parameters
to improve quantitative comparisons with observations.
Acknowledgements
Thanks to Fundação para a Ciência e a Tecnologia (FCT) for funding a PhD studentship to Rosa
Reboreda (SFRH / BD / 33388 / 2008). This research was made within the frame of the RAIA project
(INTERREG-IV A).
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