Ocean Sci., 7, 111, 2011www.ocean-sci.net/7/111/2011/
doi:10.5194/os-7-111-2011© Author(s) 2011. CC Attribution 3.0 License.

Ocean Science

Corrigendum to“Influence of cross-shelf water transport on nutrients andphytoplankton in the East China Sea: a model study” published in
Ocean Sci., 7, 27–43, 2010
L. Zhao1 and X. Guo2
1 Physical Oceanography Laboratory, Ocean University of China, 238 Songling Road, Qingdao 266100, China
2 Center for Marine Environmental Studies, Ehime University, 2–5 Bunkyo-Cho, Matsuyama 790-8577, Japan

In the paper “Influence of cross-shelf water transport on
nutrients and phytoplankton in the East China Sea: a model
study” by L. Zhao and X. Guo (Ocean Sci., 7, 27–43, 2011)
an error occurred in the affiliation of X. Guo.
X. Guo is only affiliated to the second affiliation, Center
for Marine Environmental Studies, Ehime University, 2–5
Bunkyo-Cho, Matsuyama 790-8577, Japan, as seen above.

Correspondence to: X. Guo(guoxinyu@sci.ehime-u.ac.jp)
Published by Copernicus Publications on behalf of the European Geosciences Union.

Ocean Sci., 7, 27–43, 2011www.ocean-sci.net/7/27/2011/
doi:10.5194/os-7-27-2011© Author(s) 2011. CC Attribution 3.0 License.

Ocean Science

Influence of cross-shelf water transport on nutrients andphytoplankton in the East China Sea: a model study
L. Zhao1 and X. Guo1,2
1 Physical Oceanography Laboratory, Ocean University of China, 238 Songling Road, Qingdao 266100, China
2 Center for Marine Environmental Studies, Ehime University, 2–5 Bunkyo-Cho, Matsuyama 790-8577, Japan

Received: 12 June 2010 – Published in Ocean Sci. Discuss.: 26 July 2010
Revised: 31 December 2010 – Accepted: 5 January 2011 – Published: 17 January 2011

Abstract. A three dimensional coupled biophysical model
was used to examine the supply of oceanic nutrients to theshelf of the East China Sea (ECS) and its role in primary
production over the shelf. The model consisted of two parts:
the hydrodynamic module was based on a nested model witha horizontal resolution of 1/18 degree, whereas the biologicalmodule was a lower trophic level ecosystem model including
two types of phytoplankton, three elements of nutrients, andbiogenic organic material. The model results suggested thatseasonal variations occurred in the distribution of nutrientsand chlorophyll a over the shelf of the ECS. After comparison with available observed nutrients and chlorophyll a data,
the model results were used to calculate volume and nutrients
fluxes across the shelf break. The annual mean total fluxes
were 1.53 Sv for volume, 9.4 kmol s−1 for DIN, 0.7 kmol s−1
for DIP, and 18.2 kmol s−1 for silicate. Two areas, northeast of Taiwan and southwest of Kyushu, were found to be
major source regions of oceanic nutrients to the shelf. Although the onshore fluxes of nutrients and volume both had
apparent seasonal variations, the seasonal variation of the onshore nutrient flux did not exactly follow that of the onshore
volume flux. Additional calculations in which the concentration of nutrients in Kuroshio water was artificially increasedsuggested that the oceanic nutrients were distributed in thebottom layer from the shelf break to the region offshore of
the Changjiang estuary from spring to summer and appearedin the surface layer from autumn to winter. The calculations
also implied that the supply of oceanic nutrients to the shelf
can change the consumption of pre-existing nutrients fromrivers. The response of primary production over the shelf tothe oceanic nutrients was confirmed not only in the surface
Correspondence to: X. Guo(guoxinyu@sci.ehime-u.ac.jp)

layer (mainly at the outer shelf and shelf break in winter andin the region offshore of the Changjiang estuary in summer)
but also in the subsurface layer over the shelf from spring toautumn.

1

Introduction

In addition to receiving the terrestrial input of nutrients,
marginal seas also receive nutrients from the open ocean(hereafter referred to oceanic nutrients) through cross-shelfwater exchange. Over a timescale of several decades, terrestrial inputs are affected by both anthropogenic activities andclimate change, while oceanic nutrients are mainly affectedby climate change. Quantifying the oceanic nutrient flux andevaluating its role in driving primary production in marginalseas therefore addresses two key issues in understanding thepotential influences of climate change on these economicallyand ecologically important ecosystems.
The East China Sea (ECS) is one of the major marginalseas of the northwestern Pacific (Fig. 1). Many rivers, including the Changjiang River (Yangtze River), provide a substantial input of freshwater and nutrients into adjacent seas
(Zhang, 1996). On the other hand, the ECS also receives
water and associated nutrients from the South China Sea
through the Taiwan Strait, for which the volume transport isgreater than river discharge into the ECS by as much as twoorders of magnitude (Isobe, 2008). In addition to the Taiwan Strait, Chen (2008) suggested that the upwelling of theSouth China Sea water on the western side of the Kuroshio
in the ECS is also a possible pathway for the nutrients transported from the South China Sea to the ECS. The Kuroshio
in the ECS flows along the shelf break (see 200-m isobathin Fig. 1), and the onshore volume transport of the Kuroshio

Published by Copernicus Publications on behalf of the European Geosciences Union.

28

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplanktonLuan

Haihe R.

he

Liaohe R.
Yalujiang R.

R.

Bohai Sea
Han R.

.
he R

ng

Hua

Korea
Tsushima St.

Yellow Sea
Huaihe R.
Jeju Is.

China
Changjiang R.

KyushuEast China Sea

Tokara St.

Minjiang R.

Taiwan St.

TaiwanFig.1
Fig. 1. Model domain and bathymetry.
Rivers are denoted by dots
around the coastline; three observation sites for atmospheric dry andwet deposition of nutrients are denoted by stars; and observation
stations for the data used in Fig. 8 are denoted by crosses. Red
means data number less than 10, blue means data number between
10 and 40, and green means data number more than 40. Numberedcontours are isobaths in meters. The 200-m isobath along the shelf
break is overlapped by a line with dots and numbers, across which
the fluxes of volume and nutrients are calculated and presented in
Figs. 9–11.

do. Zhang et al. (2007b) revisited this calculation using datacollected in summer and winter, and confirmed that nutrients
supplied by Kuroshio subsurface water intrusion onto theshelf were important in both seasons, particularly for phosphate. These findings are supported by the distribution overthe shelf of a passive tracer released only in the Kuroshio region east of Taiwan in a three dimensional numerical model(Guo et al., 2006).
Although oceanic nutrients have been shown to be important to the nutrient budget of the ECS (Chen and Wang, 1999;
Zhang et al., 2007b), it is still unknown whether they arereadily utilized by phytoplankton over the shelf. If oceanic
nutrients significantly contribute to primary production overthe shelf in the ECS, we should clarify where and when primary production supported by oceanic nutrients occurs. In
this study, we applied a three dimensional numerical biophysical model to examine the onshore flux of oceanic nutrients across the shelf break, paying special attention to its spatial distribution along the shelf break, and to examine where
and when the primary production over the shelf in the ECS
responds to oceanic nutrients.
After configuring the model (described in Sect. 2), we
compared the model results (nutrients and chlorophyll a)with observational data and examined the nutrient flux acrossthe ECS shelf break by presenting its spatial distribution
along the shelf break and its seasonal variations. This work
is described in Sect. 3. We changed the concentration of nutrients in the Kuroshio water, and reran the simulations to
examine changes in concentrations of nutrients and chlorophyll a over the ECS shelf and in the onshore nutrient flux
across the shelf break. This is described in Sect. 4. Finally,
we summarize this study in Sect. 5.

2across the break has been reported to be of the same orderas the transport through the Taiwan Strait (Guo et al., 2006;
Isobe, 2008).
There are strong seasonal variations in the spatial distribution of nutrients in the ECS (Chen, 2009). The concentration of surface nutrients in the ECS is high in winter, isdepleted in spring and summer, and reverts smoothly in autumn to the winter concentration (Wang, et al., 2003; Chen,
2009). Such seasonal variations are tightly coupled to biological processes such as phytoplankton blooms in springand summer and the remineralization of detritus in autumn
as well as to physical processes such as summer stratification
and winter mixing. In addition, seasonal changes in inputs ofterrestrial nutrients from rivers and of oceanic nutrients fromthe Taiwan Strait and the shelf break are also important to theconcentration of nutrients in the ECS.
Using a box model, Chen and Wang (1999) calculated theannual nutrient budget over the shelf of the ECS and suggested that the Kuroshio subsurface water has a more important role in supplying nutrients onto the ECS shelf than rivers
Ocean Sci., 7, 27–43, 2011

Model configuration and data sources

Our model consisted of two parts: a hydrodynamic moduleand a biological module. The hydrodynamic module provided physical parameters, such as water temperature, velocities and diffusivity coefficients, to the biological module.
The two modules were run simultaneously in coupled runs.
The hydrodynamic module is based on the Princeton
Ocean Model (Blumberg and Mellor, 1987; Mellor, 2003)
and is configured with a nesting method to obtain a high horizontal resolution (1/18 degree) for the ECS, as described indetail by Guo et al. (2003). In the vertical direction, 21 sigma
levels were used. Differences from the previous version werethe explicit inclusion of freshwater input from the sea surface
and rivers and the addition of tidal forcing (M2 , S2 , K1 andO1 tides) along the lateral boundary (Wang et al., 2008).
The biological module (Fig. 2) is based on the biological part of NORWECOM (Aksnes et al., 1995; Skogen etal., 1995; Skogen and Søiland, 1998) and is reconstructed
for the ECS. The model components include three elementsof nutrients (dissolved inorganic nitrogen (DIN), dissolved
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L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton

29

atmospheric deposition
river input
NIT

PHO

SIL

Surface
SPM CHLa

Hydrodynamic Model (POM)
NIT

SIL

Velocity
Elevation

DIA

DET

FLA

Temperature
Diffusion

SIS

PHO

euphotic depth
SIL

SIS

DIA

FLA

DET

NIT

PHO

SPM

NIT

PHO

SPM

N2

Bottom
SIL

SIS

DET

Fig.2
Fig. 2. Schematic illustration of the biophysical model that has a hydrodynamic
module and a biological module. The hydrodynamic moduleis based on the Princeton Ocean Model (POM) (Mellor, 2003). The biological module includes three elements of nutrients (dissolved inorganic nitrogen (DIN), dissolved inorganic phosphorus (DIP), and silicate (SIL)), two types of phytoplankton (diatoms (DIA) and flagellates(FLA)), and two types of biogenic organic materials (dead organic matter containing nitrogen and phosphorus (DET) and biogenic silica(SIS)). See text for the processes included in this module.

inorganic phosphorus (DIP), and silicate (SIL)), two typesof phytoplankton (diatoms (DIA) and flagellates (FLA)), andtwo types of biogenic organic material (dead organic matter(DET) and biogenic silica (SIS)).
The biological module treats the water column and benthic layer as two individual parts (Fig. 2). Biological processes in the water column include photosynthesis, respiration, and mortality of phytoplankton, and remineralization of
detritus, while those in the benthic layer include remineralization, denitrification, resuspension, and burial of detritus.
The biological module also includes sinking of phytoplankton and detritus from the sea surface to the benthic layer,
diffusion fluxes of nutrients from the benthic layer to the water column, nutrient inputs from rivers, and atmospheric dry
and wet deposition of nutrients at the air-sea interface. The
equations for the biochemical processes follow those given
in Aksnes et al. (1995), Skogen et al. (1995), and Skogen
and Søiland (1998). Parameters used in the equations (Table 1) for biochemical processes were based on the values in
the literature (Moll, 1998; Skogen and Moll, 2000; Wei etal., 2004), but were adjusted by trial and error.
Because of the high turbidity in the ECS, not only chlorophyll a but also suspended particulate matter (SPM) was used
to determine the extinction coefficient of photosynthetically
active radiation (k).
Zzk = k0 + k1 CSPM + k2 CCHLa (z)dz(1)
0

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Here, k0 is the coefficient for clear water, k1 is the light attenuation due to SPM absorption, CSPM is the satellite derived
monthly SPM concentration (Wang and Jiang, 2008), k2 is
the self-shading by chlorophyll a, CCHLa (z) is the profile ofsimulated chlorophyll a. The values of these parameters arelisted in Table 1.
The reason we included three nutrient elements is because
any of them can limit primary production in the ECS. The
traditional idea is that primary production in the ECS is limited by DIN or DIP, depending on where observations are
made (Wong et al., 1998; Liu et al., 2003). Recently, silicate
was also suggested as a potential limiting nutrient (Chen etal., 2004; Zhang et al., 2007b).
Zooplankton are important in the ECS but were not included in our biological module. If we directly include zooplankton in our model, we need to consider two sizes of zooplankton (micro-zooplankton and macro-zooplankton) corresponding to the two sizes of phytoplankton. However, we
did not find sufficient field data on the micro-zooplankton
and macro-zooplankton in our study area. This is the primary reason why we did not directly include zooplankton.
On the other hand, the inclusion of zooplankton may introduce additional biological processes and parameters. As we
mentioned previously, our objective is to examine the onshore nutrient flux and its effects on primary production overthe shelf. To this end, zooplankton grazing on phytoplankton can be partly taken into account by increasing the mortality rate of phytoplankton in our model. Furthermore, theOcean Sci., 7, 27–43, 2011

30

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton

Table 1. Parameters used in the model simulation for the East China Sea.
Parameter description

Value

Unit

Diatom production maximum at 0 degree Celsius
Temperature dependent maximum production for diatoms
Flagellate production maximum at 0 degree Celsius
Temperature dependent maximum production for flagellates
Respiration rate at 0 degree Celsius
Respiration rate temperature dependence
Phytoplankton death rate
Rate of decomposition of detritus
Photosynthetic active irradiance
Chlorophyll a light extinction coefficient
Extinction due to clean water
Extinction due to SPM
Fraction of phosphate and nitrate in a cell
Fraction of silicate and nitrate in a cell
Fraction of nitrate and Chlorophyll a in a cell
Half saturation constant of nitrogen for flagellates
Half saturation constant of phosphate for flagellates
Optimum light intensity for flagellates
Half saturation constant of nitrogen for diatoms
Half saturation constant of phosphate for diatoms
Half saturation constant of silicate for diatoms
Optimum light intensity for diatoms
Reference temperature for nutrient half saturation
Rate of decomposition of silicate shells
Sinking rate of detritus
Sinking rate of flagellates
Sinking rate of diatoms
Sinking rate of biogenic silica

1.33
0.063
1.05
0.064
0.061
0.064
0.123
0.011
0.4
0.0138
0.04
0.032
0.138
1.75
8∼11
1.2
0.09
60
1.8
0.115
1.0
90
12
0.00562.0
0.25
0.3∼2.0
2.0

1/day
1/deg
1/day
1/deg
1/day
1/deg
1/day
1/day
/
m2 /mgCHLa
1/m
m2 /g
mgP/mgN
mgSi/mgN
mgN/mgCHLa
mmolN/m3
mmolP/m3
W/m2
mmolN/m3
mmolP/m3
mmolSi/m3
W/m2
deg
1/day
m/day
m/day
m/day
m/day

contribution of nutrients to primary production can be considered as a bottom-up issue in a low trophic-level ecosystem, for which the NPD type model used here is suitable(Valiela, 1995; Sarmiento and Gruber, 2006).
The model domain covers the Bohai Sea, Yellow Sea and
ECS with an open boundary along the southern and eastern boundaries (Fig. 1). With the objective of reproducing
seasonal variation, the hydrodynamic module was driven bymonthly river runoff, monthly heat flux, monthly evaporation and precipitation rates, and monthly ocean currents atthe open boundary. During model integration, the monthly
data were linearly interpolated to every time step. The tidal
currents were specified at the open boundary as described by
Wang et al. (2008). A regression relation with 9 coefficients(annual mean, every two harmonic constants for the annual
period, for the semi-annual period, for the 4 month period,and for the 3 month period, respectively) in the Scatterometer Climatology of Ocean Winds (Risien and Chelton, 2008)
was used to describe the wind fields at every time step. In
order to reproduce the seasonal variations of nutrients andchlorophyll a, the same monthly conditions were prescribed
Ocean Sci., 7, 27–43, 2011at river mouths, at the open boundary and at the air-sea interface for the biological module.
Calculation was started with an initial condition in winter and was spun up for two years; the model results fromthe third year were then analyzed. The initial conditions forthe three nutrient elements were given by referring to Chen
(2009). It is necessary to note that using the initial conditions
from the World Ocean Atlas 2005 (WOA2005) (Garcia et al.,2006a, b) or from the Marine Atlas of Bohai Sea, Yellow Sea,
East China Sea, Chemistry (Wang, 1991) did not change theresults much, indicating the strong dependence of the model
results on the open boundary conditions, which were fromWOA2005. Runoffs from the ten major rivers (Fig. 1) weretaken from the Marine Atlas of Bohai Sea, Yellow Sea, East
China Sea, Hydrology (Chen, 1992). The concentrations of
nutrients in rivers and the fluxes for atmospheric dry and wet
deposition of nutrients were obtained from published data
(Zhang, 1996; Liu et al., 2009; Wan et al., 2002; Zhang et al.,2007a). Solar radiation was calculated using the model given
by Dobson and Smith (1988) and cloud cover data was fromthe NCEP/NCAR reanalysis (Kalnay et al., 1996). Validationwww.ocean-sci.net/7/27/2011/

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton

31
DIN(mmol m-3 )

a)

c)

e)

g)

Surface

Surface

Surface

Surface

b)

d)

f)

h)

Bottom

Bottom

Bottom

BottomFig.3
Fig. 3. Horizontal distribution of simulated DIN (mmol m−3 ) at thesurface (2 m depth) and bottom layer (the deepest sigma layer) in four
seasons.

data for nutrients and chlorophyll a were from the Japan
Meteorological Agency’s (JMA) monitoring data around theshelf break and along the PN line (see Fig. 1 for its position)in the ECS.

3
3.1

Results
Temporal and spatial variations of nutrients andchlorophyll a

For a comparison with the observations (Chen, 2009), thehorizontal distribution of DIN, as an example of simulated
nutrients, in the surface and bottom layers for four seasons isshown in Fig. 3. The corresponding figures, based on observations, in February and August from Chen (2009) are given
in Fig. 4.
In winter, the surface DIN concentration was high along
the western coast of the ECS and the eastern coast of the
Yellow Sea, but was low in the central Yellow Sea and thenorthwestern coast of the Yellow Sea (Fig. 3a). The lowest DIN concentrations were found along and outside of the
shelf break where nutrient-poor Kuroshio surface water isfound. Because of strong wind stirring in winter and tidal
mixing, the DIN in the bottom layer of the Yellow Sea andthe inner shelf of ECS (Fig. 3b) displayed a similar distribution to that in the surface layer (Fig. 3a). However, inthe bottom layer of the middle and outer shelves, the DIN
concentration was higher than that of the surface layer. Although these features can be confirmed in Fig. 4, we still canfind inconsistencies between the model and observational results. For example, the concentration of DIN in winter in
www.ocean-sci.net/7/27/2011/

Fig.4 concentrations in February andFig. 4. Surface and bottom nitrate
August, taken from Chen (2009).

Ocean Sci., 7, 27–43, 2011

32

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton

the Yellow Sea is higher in the model results (Fig. 3) than inobservational results (Fig. 4). The physical explanation forsuch overestimation was a northward shift in the position of
Changjiang diluted water due to the usage of climatologicalwind fields. The associated biochemical processes could be
related to the satellite SPM concentrations in region offshoreof the Changjiang river mouth that were probably overestimated. The overestimation of SPM induced a lower underwater light intensity and therefore a lower production rate ofphytoplankton, which resulted in a somewhat higher concentration of nutrients in the Changjiang diluted water.
In spring, surface DIN concentrations were similar to levels observed in winter along the western coast of the ECS, butthey decreased sharply in the central Yellow Sea and from the
middle to outer shelf of the ECS (Fig. 3c). In the bottom layer(Fig. 3d), the DIN concentration decreased markedly in the
Taiwan Strait but increased from north Taiwan to the middle
shelf south of 30◦ N; the bottom DIN also increased in thecentral Yellow Sea. The decrease in surface nutrients can beeasily related to the intensification of biological activity andthe reduction of the nutrient supply from the bottom layer tothe surface layer in spring. With increasing solar radiation
and weakening of winds from winter to spring, stratificationin the ECS and Yellow Sea has developed by May. Thermal
stratification reduced the upward transport of nutrients fromthe bottom layer to the surface layer. At the same time, thedissolved nutrients released by remineralization of sinking
particulate organic matter in the bottom layer are kept there,causing an increase in DIN. In addition, the intensification of
the Kuroshio subsurface water intrusion in spring may also
influence the increase of DIN in the bottom layer over the
middle and outer shelves (Jacobs et al., 2000).
In summer, the dispersal of nutrient-poor water (DIN
<1 mmol m−3 ) from the central area to coastal areas in the
Yellow Sea and the offshore spreading of nutrient-rich water (DIN >1 mmol m−3 ) from the Changjiang estuary toward
Jeju Island in the ECS (Fig. 3e) caused a significant change
in the surface layer. This feature is also found in Fig. 4. The
reduction of surface nutrients in the Yellow Sea can be easily explained by the intensification of stratification in summer, while the mechanism of long distance offshore transportof nutrients from the Changjiang estuary has been given by
Isobe and Matsuno (2008). In the bottom layer, nutrients increased in the northern shelf of the ECS (southwest of Jeju
Island) but decreased in the offshore area of the Changjiang
estuary and the northern part of the Yellow Sea (Fig. 3e andf). According to Fig. 4, the nutrients within the bottom layerof the ECS shelf have higher concentrations in summer thanin winter, which can be found in model results too.
In autumn, the concentration of surface DIN was low inthe central Yellow Sea and over the middle and outer shelvesof the ECS, with increased levels in the western and eastern coasts of the Yellow Sea (Fig. 3g). In the bottom layer(Fig. 3h), nutrient-rich water was found from the central Yellow Sea to the northern shelf of the ECS, and as far as the
Ocean Sci., 7, 27–43, 2011shelf break, indicating a possible route of nutrient supply
from Kuroshio subsurface water.
In general, not only nutrients but also light intensity, water temperature and stratification controlled phytoplankton
growth in the surface water. With increasing surface temperatures in spring, the water column became stable, and highsurface concentrations of chlorophyll a initially appeared in
the central region of the Yellow Sea during April (Fig. 5).
From April to September, the high-density surface chlorophyll a area moved gradually to the coastal waters of the Yellow Sea. Meanwhile, a band of high-density surface chlorophyll a was maintained from the western Yellow Sea to theoffshore region of the Changjiang estuary. In autumn (e.g.
October) slightly higher chlorophyll a values were foundagain in the central region of the Yellow Sea. In the areafrom the Changjiang estuary to the ECS shelf break, a highdensity surface chlorophyll a area appeared first at the outer
shelf (northeast of Taiwan) in winter (e.g., January), thengradually moved to the inner shelf from spring to summer,
and remained offshore of the Changjiang estuary in autumn(e.g. October). The Changjiang River provides not only nutrients but also suspended sediments to the ECS. The reason
for the relatively low chlorophyll a levels in close proximity
to the estuary is the high turbidity caused by the amount ofsuspended sediments from the Changjiang River that significantly weakened subsurface light intensity.
3.2

Vertical distribution of chlorophyll a and nutrientsalong a transect across the shelf break

There is an established transect in the ECS, called the PN
line, where JMA has conducted hydrographic surveys formore than 40 years. Usually, the survey is carried out fourtimes a year, once per season. Here we first describe thecommon features of nutrients and chlorophyll a in the observational and model results (Figs. 6 and 7), then address thepossible causes for the differences between the observationaland model results. The observations are for nutrients (represented by DIN) and chlorophyll a averaged in each seasonfrom 1965 to 2004, whereas the model results are the same
variables but with monthly means from February, May, August and October, representing winter, spring, summer andautumn, respectively.
In winter, both nutrients and chlorophyll a were verticallyhomogenous over the shelf due to intensive mixing. Nutrient concentrations were higher in the inshore side than theoffshore side in the upper layer (water depth <100 m). The
highest nutrient concentrations were found in the lower layer(water depth >100 m) from the shelf break to the open ocean,and they are expected to be an important source of nutrientsto the upper layer and middle shelf. Chlorophyll a concentrations were high in the surface layer from the shelf break to
the open ocean.
In spring, nutrients in the surface layer were quickly
depleted with the advent of phytoplankton growth. This
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L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton33
Chla(mg m-3 )Fig. 5. Horizontal distribution of simulated chlorophyll a (mg m−3 ) at the surface layer (2 m depth) in 12 months.

Fig.5
occurred from the inshore side of the shelf to the shelf break,
Although we can confirm the above features from both thewith the maximum chlorophyll a concentration occurring inobservational and model results, differences were also apthe surface layer or shallow subsurface layer. With changes
parent. For example, the high chlorophyll a concentrationin phytoplankton production, the euphotic zone became shalobserved on the inshore side of the shelf in winter and aulower from the inshore side of the shelf to the shelf break, buttumn was not reproduced by the model. The high chlorophyllbecame deep farther offshore. In the bottom layer, nutrienta concentration at the open ocean side was always found inrich water could be identified from the inshore side of themodel results but could not be confirmed in the observational
shelf to the shelf break. From the depth of the euphotic zone
data. In addition, the concentration of chlorophyll a in theand the distribution of nutrients, it can be deduced that thesubsurface layer over the shelf in summer and the concennutrient-rich bottom water contributes greatly to phytoplanktration of nutrients below the subsurface layer from the shelf
ton growth.
break to the open ocean side were generally higher in the
In summer, the concentration of surface nutrients demodel results than in the observational data. These fundacreased and limited the growth of phytoplankton. With amental differences may have been caused by either incomdecrease in surface phytoplankton, the euphotic zone deepplete observational data specified along the open boundary orened and subsurface phytoplankton could utilize nutrients in
the incomplete structure of our biological module. Improvethe deeper layer. Consequently, the subsurface chlorophyll ament of the former depends on the extent of data collection
maximum over the shelf appeared deeper in summer than ineast of Taiwan and within the Taiwan Strait, while the latspring and the concentration of nutrients in the bottom layerter can be addressed by adding biological components suchdecreased slightly.
as zooplankton, or by including additional processes such as
In autumn, the concentration of surface nutrients recovthe microbial loop. Nevertheless, continuous effort to imered slightly due to the intensification of surface mixing.
prove model performance is necessary in the future.
Chlorophyll a still had a high concentration in the middle
Since we want to evaluate the onshore fluxes of nutrientslayer, indicating a persistent contribution of nutrient-rich botacross the shelf break, we need to confirm that the incontom water to subsurface primary production from spring tosistency between the model and observational results has no
autumn.
serious influence on this evaluation. In Fig. 8, we plot all

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Ocean Sci., 7, 27–43, 2011

34

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton
DIN(mmol m-3 )Model-Feb

Model-May

Model-Aug

Model-Oct

Clim-WinterClim-Spring

Clim-Summer

Clim-Autumn

Fig. 6. Simulated (upper panels) and observed (lower panels) distributions of DIN (mmol m−3 ) along the PN line in four seasons. Red lines
in the upper panels denote euphotic depth.
Fig.6

Chla(mg m-3 )Model-Feb

Clim-WinterModel-May

Clim-Spring

Model-Aug

Model-Oct

Clim-Summer

Clim-Autumn

Fig. 7. The same as Fig. 6 but for chlorophyll a (mg m−3 ).

the available DIN and DIP data from JMA routine observa-Fig.7 trients across the shelf break of the ECS (defined by the 200tions around the shelf break (the station depth was between
m isobath in Fig. 1). The volume transport of onshore wa150 and 250 m, see Fig. 1 for position of stations) and theter (VH i+ ) and offshore water (VH i− ) at the ith grid point
corresponding model results at the same places and for thealong the 200-m isobath as well as their corresponding nusame month and day as the observations. The observed nutrient fluxes (FH i+ and FH i− ) were calculated as follows:
trients around the shelf break show large variability and the
X i,k
V H+i =
u+ dzi,k dx i(2)model results represent this variability with an acceptable
k=1,M
precision, considering that the model was driven by climaX i,ktological forcing. Based on this comparison, the inconsisiVH=
u− dzi,k dx i(3)−tency between model and observational results that we prek=1,M
viously mentioned should have no serious influence on theXcalculation of nutrient fluxes that depend only on the simui,ki
F H+i =
C i,k ui,k(4)
+ dz dx
lated nutrient concentration along the 200-m isobath, more
k=1,M
specifically, the line given in Fig. 1.
Xi,ki
F H−i =
C i,k ui,k(5)
− dz dx
3.3 Seasonal and spatial variations in onshore fluxes ofk=1,M
nutrients across the shelf break
Here, u denotes onshore or offshore velocity; dx and dz are
horizontal and vertical intervals of grid points; C denotes
Using flow velocity and nutrient concentrations from themodel, we can calculate the onshore flux of water and nuconcentration of one nutrient element; subscripts + and −Ocean Sci., 7, 27–43, 2011www.ocean-sci.net/7/27/2011/

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton
DIN(mmol m-3 )30

y=1.04*x+2.43

a)2

R =0.77

25

model

20
15
10
5
0

5

2.5

10

15
observation

20

25
DIP(mmol m-3 )

y=0.99*x+0.15
2
R =0.75

b)

model

2.0

1.5

1.0

0.5

0.5

1.0

observation

1.5

2.0

Fig. 8. Scatter plot of all the available (a) DIN and (b) DIP data
Fig.8
from routine JMA observations around the shelf break (see Fig. 1
for position of stations) and corresponding model results at the sameplaces in the same month and same day as the observations.

denote onshore velocity and offshore velocity, respectively;
superscript i and k are horizontal and vertical indexes for thegrid points, respectively; and M is the total grid point numberin the vertical direction.
By integrating onshore and offshore fluxes of water andnutrients at each grid point along the 200-m isobath, we obtained the total volume transports of onshore water (Vol+ )and offshore water (Vol− ) as well as the total nutrient fluxes
transported by the onshore water (F+ ) and by the offshore
water (F− ) across the shelf break.
X
X
Vol+ =
V H+i ,Vol− =V H−i ,
i=1,N

F+ =

X
i=1,N

F H+i ,F− =

i=1,N

X

F H−i .

i=1,N

Here, N is the total number of grid points in the horizontal
direction. In addition, the mean concentration within the onshore water (C+= F+ Vol+ ), and that within the offshore
water (C− = F− Vol− ) were also calculated.
Since the main stream of the Kuroshio flows along theshelf break, the flux across the shelf break in the ECS is
also called the Kuroshio onshore flux. Because of this, thecalculated nutrient fluxes (F+ +F− ) can be compared to previous estimates of nutrient flux by Chen and Wang (1999)
www.ocean-sci.net/7/27/2011/35

and Zhang et al. (2007b) who used a box model for the ECS
shelf. For this reason, we first present total fluxes of waterand nutrients across the shelf break and then examine theirhorizontal distributions along the 200-m isobath, which cannot be given by a box model.
The volume of the Kuroshio onshore flux (Vol+ +Vol− )reached a minimum of ∼0.5 Sv (1Sv=106 m3 s−1 ) in Juneand a maximum of ∼3 Sv in November, displaying significant seasonal variations (Fig. 9). The annual mean volume of
the Kuroshio onshore flux was estimated to be 1.53 Sv witha standard deviation of 0.97 Sv. All are consistent with theresults calculated by a previous version of the hydrodynamic
module (Guo et al., 2006), in which tidal currents were excluded and river discharge was not explicitly included.
The Kuroshio onshore flux (F+ + F− ) of DIN and DIP(Fig. 9) generally followed the seasonal variation in volume
flux with the exception of from March to June. The fluxesof DIN and DIP reached a minimum in March, not in June
when the minimum volume flux occurred. Afterward, they
increased gradually until November when they reached maximums of ∼16.0 kmols−1 for DIN and ∼1.1 kmols−1 for
DIP; this was the same as for the volume flux. The Kuroshio
onshore flux of silicate showed different seasonal variationfrom those of volume, DIN and DIP. Silicate displayed a minimum in March as seen with DIN and DIP, but thereafter it increased erratically. Before November when silicate reached
its maximum, we observed three peaks in the Kuroshio onshore flux of silicate.
The annual mean of the Kuroshio onshore flux was
9.4 kmols−1 for DIN, 0.7 kmols−1 for DIP, and 18.2 kmols−1
for silicate; the standard deviation was 4.6 kmols−1 for DIN,
0.4 kmols−1 for DIP, and 12.0 kmols−1 for silicate. The
annual mean values given here are on the same order as
those estimated by the box models: 10.7 kmols−1 for DIN,
and 0.34 kmols−1 for DIP from Chen and Wang (1999);
9.7 kmols−1 for DIN, 0.65 kmols−1 for DIP, 14.95 kmols−1
for silicate from Zhang et al. (2007b).
The seasonal variations in the Kuroshio onshore flux of
DIN, DIP and silicate (Fig. 9) is essentially consistent withthose estimated by Zhang et al. (2007b), who showed a double input of DIN and DIP and a triple input of silicate fromthe Kuroshio to the shelf from summer to winter. The reason
why the total nutrient fluxes (F+ + F− =Vol+ C+ +Vol− C− )did not exactly follow the seasonal variation in total volume
flux (Vol+ + V ol− ) is because the nutrient concentration in
the inflow water (C+ ) was different from that in the outflow water (C− ). The inflow volume flux (Vol+ ) was always larger than the outflow volume flux (Vol− ) throughout the year (Fig. 10a). However, the mean DIN concentration (C+ ) in the inflow water was smaller (larger) than thatin the outflow water (C− ) from September to the following
March (from April to September) (Fig. 10b). The same thing
occurred for the mean concentrations of DIP and silicate in
the inflow and outflow water. The difference in the seasonalvariations between total onshore flux of nitrate and that of
Ocean Sci., 7, 27–43, 2011

36

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton

Table 2. Monthly mean nitrate concentration and volume transport of inflow and outflow across the 200-m isobath at the areas northeast of
Taiwan(NoT) and southwest of Kyushu(SoK). Positive values denote onshore transport.
mean nitrate concentration (mmol m−3 )
Month
1
2
3
4
5
6
7
8
9
10
11
12

NoT
inflow
5.70
4.52
3.68
4.29
4.19
3.86
3.82
4.23
3.77
3.81
4.26
4.30

outflow
6.45
5.24
4.27
4.74
4.57
4.06
3.94
4.48
4.27
4.50
5.11
5.15

SoK
inflow
9.63
9.28
9.12
9.07
9.22
10.20
10.42
10.06
10.06
9.95
10.03
10.02

NoT

outflow
9.55
8.86
8.51
7.96
7.42
8.24
8.54
8.86
10.23
9.83
9.28
9.55

Fig.9

Fig. 9. Monthly onshore flux of volume (Sv) and nutrients(kmol s−1 ) across the entire 200-m isobath shown in Fig. 1. The
positive flux direction is toward the ECS shelf. The black solid line
denotes volume, the red solid line DIN, the black dashed line DIP,
and the red dashed line SIL.

silicate is caused by the concentration specified at the southern open boundary (Fig. 10c). The silicate concentration has
three peaks, inducing three peaks in the onshore silicate flux
across the 200-m isobath.
In addition to quantifying the total flux across the shelf
break, the model results can also provide a spatial measure of
the Kuroshio onshore flux of volume and nutrients along theshelf break (Fig. 11). There were two areas where positive
onshore flux was concentrated. One was northeast of Taiwan where the Kuroshio bumps against the shelf break andinduces a large onshore flux of volume and nutrients. The
integration of the Kuroshio onshore flux northeast of Taiwan(from point 1 to point 6 in Fig. 11) gave values of 5.8 Sv
for volume, 21.1 kmols−1 for DIN, 1.8 kmols−1 for DIP and
Ocean Sci., 7, 27–43, 2011

volume transport (Sv)

inflow
9.20
9.52
9.83
10.45
10.68
10.50
11.25
10.84
10.44
10.73
10.68
10.09

outflow
−4.54
−4.53
−4.75
−4.86
−4.98
−4.89
−5.23
−5.22
−5.21
−5.11
−4.91
−4.79

SoK
inflow
3.64
3.87
3.96
3.68
3.59
3.79
4.14
3.97
3.63
3.93
4.36
4.25

outflow
−3.44
−3.65
−3.67
−3.58
−3.52
−43.71
−3.98
−3.50
−2.51
−2.68
−3.36
−3.51

48.3 kmols−1 for silicate. The other was located southwestof Kyushu where the Kuroshio veers toward Tokara Strait
and induces a large onshore flux of volume and nutrients.
The integration from this area (from point 22 to point 32
in Fig. 11) gave values of 0.5 Sv for volume, 7.8 kmols−1
for DIN, 0.6 kmols−1 for DIP and 18.7 kmmols−1 for silicate. Along the shelf break between them, the Kuroshio onshore flux of volume and nutrients was generally negative,
indicating an offshore transport of water and nutrients. Integration along the 200-m isobath from ∼26◦ N to ∼29◦ N(point 7 to point 21 in Fig. 11) gave values of −4.7 Sv forvolume, −19.7 kmols−1 for DIN, −1.6 kmols−1 for DIP and−48.9 kmols−1 for silicate.
When comparing the area northeast of Taiwan and thatsouthwest of Kyushu along 200-m isobath, we note that although the onshore volume transport northeast of Taiwan isabout ten times that southwest of Kyushu, the nutrient flux
is only about three times different. Again, the nutrient fluxes
are not exactly proportional to the volume flux, as in the total volume flux and total nutrient flux across the entire shelf
break.
As shown in Fig. 10, the net nutrient flux does not always follow the net water flux in a system with a large water
flux exchange because the concentration of nutrients in the
inflow water can be different from that in the outflow water. Here, we use nitrate as an example to demonstrate thisprocess. Table 2 presents monthly volume transports for inflow and outflow and monthly nitrate concentrations in the
inflow and outflow waters at regions northeast of Taiwan andsouthwest of Kyushu. The monthly nitrate concentrations in
the inflow and outflow waters were calculated in a similar
way as those in Fig. 10. According to Table 2, the nitrateconcentration in the inflow water is lower (higher) than thatin the outflow water at area northeast of Taiwan (southwest
www.ocean-sci.net/7/27/2011/

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton

37

Volume(Sv)
30.5

a)

30.0
29.5
29.0
28.5

inflow

28.0
27.5

outflow

27.0
26.5
26.0
25.5
1

2

3

4

5

6

7

8

9

10

11

12

DIN(mmol m-3 )
6.5

b)

6.0
Fig.11

outflow

5.5

inflow

5.0
1

10

2

3

4

5

6

7

8

9

10

11

DIN
SIL

c)

9

12

Fig. 11. Spatial distribution along the 200-m isobath of the annual
average onshore flux of volume (Sv) and nutrients (kmol s−1 ). The
value at each point is the integrated flux between two points denotedby dots along the 200-m isobath in Fig. 1. The positive direction is
toward the ECS shelf. The black solid line denotes volume, the redsolid line DIN, the black dashed line DIP, and the red dashed line
SIL.

8
7
6
5
4
3
2
1
1

2

3

4

5

6

7

8

9

10

11

12

Fig.10 outflow volume transports (Sv)Fig. 10. (a) monthly inflow andacross the 200-m isobath. (b) Monthly mean nitrate concentrations(mmol m−3 ) in the inflow water and outflow water. (c) Seasonalvariation of vertically averaged nitrate (black line) and silicate (blueline) concentrations above 200 m depth at the southern open boundary (123◦ E, 24◦ N).

of Kyushu) through a year. On the other hand, the volumetransport of the inflow is much larger (a little larger) thanthat of the outflow at the area northeast of Taiwan (southwest of Kyushu). Consequently, northeast of Taiwan, only
the difference in the volume transport of inflow and outflow
contributes to the onshore flux of nutrients; the difference inthe nutrient concentration of inflow and outflow waters has anegative effect on the onshore flux of nutrients. At the area
southwest of Kyushu, both the difference in the volume transport of inflow and outflow and that in the nutrient concentration of inflow and outflow waters have a positive contribution
to the onshore flux of nutrients.

4 Sensitivity experiments on the enrichment of oceanic
nutrients
Although we obtained a positive onshore flux of oceanic nutrients across the shelf break, we still do not know whether
these nutrients are involved in photosynthesis over the ECS
www.ocean-sci.net/7/27/2011/shelf. As presented in Guo et al. (2006), half of the water
through the Tsushima Strait is from the Kuroshio in summer
and this ratio increases to 80% in winter. If the oceanic nutrients that cross the shelf break from the Kuroshio have noopportunity to enter the euphotic zone over the shelf, they
only flow over the bottom layer of the shelf and finally passthrough the Tsushima Strait without any contribution to theprimary production over the ECS shelf.
Direct evaluation of how much the nutrients from theKuroshio area contribute to the primary production over the
ECS shelf must isolate the oceanic nutrients from nutrientsfrom other sources. This isolation is usually problematic ina nonlinear marine ecosystem. Instead of isolation, we usedsensitivity experiments, in which we artificially changed thenutrient concentration of the Kuroshio water specified along
the lateral boundary of the model and consequently changed
the supply of oceanic nutrients across the shelf break fromthe Kuroshio. The difference in the results between the sensitivity experiments and the simulation presented in Sect. 3(hereafter called the control experiment) is caused only by
the change in the supply of oceanic nutrients across the shelf
break, and therefore it can give us some insight to the role ofoceanic nutrients in the lower trophic level dynamics of the
ECS ecosystem.
We carried out four sensitivity experiments, in which only
the concentrations of nutrients (DIN, DIP and silicate) fromthe sea surface to the bottom along the southern boundary(from Taiwan to 124◦ E), occupied by Kuroshio water, were
multiplied by a constant of 1.1, 1.2, 1.3 and 1.4. The otherboundary conditions and initial conditions as well as themodel integration schedule were the same as those in thecontrol experiment. As a result, the onshore volume flux
across the shelf break was the same in all experiments, with
Ocean Sci., 7, 27–43, 2011

38

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton
DIN(mmol m-3 )Fig. 12. Anomaly of monthly DIN (mmol m−3 ) in the surface layer (2 m depth) between the sensitivity experiment, in which the oceanic
nutrients were enriched by 30%, and the control experiment.
Fig.12the onshore flux of nutrients artificially increased in the sensitivity experiments.
4.1

Changes in surface and bottom nutrients andsurface chlorophyll a over the shelf of the ECSThe additional oceanic nutrients (e.g. DIN) in the surface
layer appeared mostly offshore of the Changjiang estuary(Fig. 12). In summer (June–August), a positive DIN anomaly(sensitivity experiment – control experiment) was foundalong the coastal area from 29◦ N to 34◦ N, and offshore
the DIN anomaly was negative. After September, the areawith a positive DIN anomaly was enlarged and extended to
the Jeju Strait (the channel between Jeju Island and southerncoast of Korea) and farther to the Tsushima Strait in winter (December–February). After March, the positive DIN
anomaly gradually retreated to the coastal area. Although
not as obvious as offshore of the Changjiang estuary, the additional oceanic nutrients could also be identified over the
middle and outer shelves in winter.
The additional oceanic nutrients (e.g. DIN) in the bottom
layer over the shelf appeared mostly northeast of Taiwan andsouthwest of Kyushu (Fig. 13). In the area northeast of Taiwan, a positive anomaly in bottom nutrients can be identified throughout the year. However, its distribution over the
Ocean Sci., 7, 27–43, 2011shelf enlarged from April to September. In the area southwest of Kyushu, the area with a positive anomaly in bottom
nutrients was enlarged from June to September, after whicha northwestward branch with a positive nutrient anomaly appeared and reached the Yellow Sea. Because the supply ofoceanic nutrients to the middle and inner shelves weakened
after October, the high concentration of additional oceanic
nutrients in the surface layer offshore of the Changjiang estuary from November to the following April were those that
had intruded from April to September.
The response of chlorophyll a in the surface layer to additional oceanic nutrients in winter appeared in the pathway of
the Kuroshio, in particular northeast of Taiwan where a local maximum in the chlorophyll a anomaly between the sensitivity and control experiment can be identified (Fig. 14).
The additional oceanic nutrients did not produce additional
chlorophyll a over the shelf in winter, which can be understood from the low chlorophyll a levels over the shelf in thecontrol experiment (Fig. 5). In other words, primary production over the shelf in winter is not nutrient limited.
From May to September, the positive chlorophyll a
anomaly in the surface layer appeared offshore of the
Changjiang estuary. A part of the area with the positive
chlorophyll a anomaly (Fig. 14) corresponded to the area in
the inner shelf with a negative DIN anomaly offshore of thewww.ocean-sci.net/7/27/2011/

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton

39

DIN(mmol m -3)

Fig. 13. The same as Fig. 12 but for DIN (mmol m−3 ) in the bottom layer, defined as the deepest sigma layer. The color range is different
from that used in Fig. 12.

Changjiang estuary (Fig. 12). This feature was caused Fig.13
bydifferent ratios of DIN to DIP in the Changjiang River water and in the Kuroshio water and will be discussed in moredetail in Sect. 4.3.
4.2

Changes in subsurface nutrients andchlorophyll a across the shelf of the ECS

The increment of oceanic nutrients applied in the sensitivity
experiments depended on the original concentration in thecontrol experiment, and therefore it was small in the surface
layer and large in the subsurface and bottom layers. From
January to March, the contours of additional oceanic DIN
concentration were horizontally distributed along the PN section (Fig. 15), indicating a small supply of oceanic nutrientsto this section in winter. From April to June, the contourof 2 mmol m−3 of additional DIN concentration moved fromthe shelf break to the middle and inner shelf and remained
over the shelf (Fig. 15). An important point in Fig. 15 isthat some of the additional oceanic nutrients could enter the
euphotic zone.
The additional oceanic nutrients cause an increase in thechlorophyll a concentration in the surface layer in coldwww.ocean-sci.net/7/27/2011/

months (November to March) and in the subsurface in warm
months (June to October) (Fig. 16). April and May appear
to be a transition period when the increase in chlorophylla moves from the surface to subsurface layer. By observing shifts in euphotic depth in Fig. 15, we can infer the
consumption of additional oceanic nutrients in the subsurface layer. Therefore, the stable concentration of additional
oceanic DIN in the bottom layer over the shelf from Juneto October (Fig. 15) reflects a balance between the consumption and supply of oceanic nutrients. Similarly, an increase in
the additional oceanic DIN at the bottom layer over the shelfin November (Fig. 15) can be caused by either a reductionin phytoplankton growth (Fig. 16) or an increased supply ofoceanic nutrients, or both.
4.3

Changes in nutrient flux across the shelf break andthe influence of the elemental ratio of oceanic
nutrients on the consumption of nutrients over the
shelfWith an increase in the concentration of oceanic nutrientsin the sensitivity experiments, the onshore flux of DIN, DIP
and silicate across the 200-m isobath generally increased in
Ocean Sci., 7, 27–43, 2011

40

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplanktonChla(mg m-3 )Fig. 14. The same as Fig. 12 but for chlorophyll a (mg m−3 ) in the surface layer.
Fig.14DIN(mmol m -3)

Fig. 15. The anomaly of monthly DIN (mmol m−3 ) along the PN line between the sensitivity experiment, in which the oceanic nutrients are
Fig.15 depth.
enriched by 30%, and the control experiment. Red lines denote euphotic

Ocean Sci., 7, 27–43, 2011www.ocean-sci.net/7/27/2011/

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton

41
Chla(mg m -3)

Fig. 16. The same as Fig. 15 but for chlorophyll a (mg m−3 ).

Fig.16

Table 3. Annual onshore fluxes of nutrients across the 200-m isobath in control and four sensitivity experiments. The positive flux isdefined as onshore direction and the unit is kmol s−1 . “ctl” denotes the control experiment while “+10%”–“+40%” denote the sensitivity
experiments, in which the concentration of oceanic nutrients in the Kuroshio water was artificially increased by 10–40%, respectively. The
values in brackets denote the ratios of flux increases in sensitivity experiments to the initial flux in the control experiment.

DIN
DIP
SIL

ctl

+10%

+20%

+30%

+40%

9.4
0.72
18.2

10.4 (+10.8%)
0.80 (+11.2%)
20.4 (+11.7%)

11.4 (+21.5%)
0.88 (+22.3%)
22.5 (+23.3%)

12.3 (+32.0%)
0.96 (+33.2%)
24.6 (+34.8%)

13.3 (+42.3%)
1.03 (+44.1%)
26.6 (+46.2%)

the same ratio (Table 3). This is a natural result since theonshore flux of volume does not change in all of these calculations. However, there is also an apparent difference in
the increased ratio of the three nutrient elements. The increased ratio of silicate was highest, while that of DIN was
lowest. Such differences are probably related to the different
elemental ratios of nutrients in the pre-existing water over the
shelf that was transported in an offshore direction across theshelf break, and in the oceanic water that was transported in
an onshore direction.
The ratio of DIN to DIP in the total onshore flux of nutrients in the control experiment was 13 (= 9.4/0.72 in Table 3), which is less than the Redfield ratio of 16 used in
the model calculation; the average ratio of DIN to silicate is∼0.5, which is also less than the ratio of 16:15 used in themodel calculation; the average ratio of silicate to DIP was25, which is higher than the ratio of 15 used in the model
calculation. As shown in Fig. 12, the additional oceanic nutrients can reach the offshore area of the Changjiang estuary,
where the limiting nutrient has been reported to be DIP basedon the observed atomic ratio of DIN, DIP and silicate (Liu etal., 2003). In our simulation, the average ratio of DIN to DIP
in Changjiang River water was 59, the average ratio of DIN
www.ocean-sci.net/7/27/2011/

to silicate was 0.35, and the average ratio of silicate to DIP
was 166. Consequently, nutrient limitation in our simulation
was also dependent on DIP for the Changjiang diluted waterthat spreads offshore of the Changjiang estuary in summer.
This is why we obtained a negative anomaly in that region
for DIN between the control experiment and sensitivity experiments (Fig. 12). Therefore, the supply of oceanic nutrients to the shelf contributed to phytoplankton growth not
only by themselves but also from their element ratio, because
the low ratio of DIN to DIP in the Kuroshio water promotes
the consumption of DIN in the pre-existing shelf water.

5

Conclusions

By combining a low trophic level ecosystem model with ahydrodynamic model, we were able to reproduce the general features of spatial and temporal variations in nutrientsand chlorophyll a in the Yellow Sea and ECS. Horizontally,
the area with high chlorophyll a concentration first appearedin the central Yellow Sea in spring, and then moved toward coastal zones in summer; in the ECS, the area withhigh chlorophyll aconcentration first appeared northeast of
Ocean Sci., 7, 27–43, 2011

42

L. Zhao and X. Guo: Influence of cross-shelf water transport on nutrients and phytoplankton

Taiwan, i.e., at the outer shelf and shelf break in winter, andthen gradually moved toward the middle and inner shelves insummer and autumn. Vertically, high chlorophyll a concentration appeared in the surface layer in spring at the middle
and outer shelves and in the subsurface layer in summer andautumn, corresponding to changes in light intensity and nutrients.
The onshore flux of volume and nutrients across the shelf
break, calculated from the model results, have noticeable seasonal variations. The onshore volume flux reached a minimum in June and a maximum in November, while the nutrient flux reached a minimum in March and a maximum in
November. The difference in their seasonal variation wascaused by the difference in nutrient concentrations in the
inflow and outflow water across the shelf break. The annual average onshore flux was estimated to be 1.53 Sv forvolume, 9.4 kmol s−1 for DIN, 0.7 kmol s−1 for DIP, and18.2 kmol s−1 for silicate. Along the shelf break of the ECS,
areas northeast of Taiwan and southwest of Kyushu supply
onshore volume and nutrient fluxes, whereas the middle shelf
break between them provides an offshore volume and nutrient flux.
By artificially increasing the concentration of oceanic nutrients in the Kuroshio water, we confirmed the contributionof oceanic nutrients to primary production over the shelf ofthe ECS. The additional oceanic nutrients were distributed in
the bottom layer from the shelf break to the offshore region of
the Changjiang estuary from spring to summer, and appearedin the surface layer mainly from autumn to winter. The contribution of oceanic nutrients to primary production over the
shelf can be found not only in the surface layer (mainly at theouter shelf and shelf break in winter and in the region outside
the turbidity zone of the Changjiang estuary in summer), butalso in the subsurface layer over the shelf from spring to autumn.
Since the ratio of the three nutrient elements in the
Kuroshio water was different from that in the pre-existing
shelf water, in particular from the Changjiang plume, thecontribution of oceanic nutrients to photosynthesis over the
shelf promoted the consumption of residual DIN in that area.
Therefore, it can be concluded that the supply of oceanic nutrients to the shelf of the ECS contributes to phytoplankton
growth not only in itself but also because of its elemental
ratio.
Acknowledgements. The authors thank Jing Zhang at East China
Normal University for the discussions concerning the model results.
Liang Zhao was supported by the National Science Foundation ofChina (No. 40806001 and 40830854), National Basic Research
Program of China (973 Program 2010CB428904) and Global COE
Program from the Japanese Ministry of Education, Culture, Sports,
Science and Technology. Xinyu Guo was supported by the Global
COE Program from the Japanese Ministry of Education, Culture,
Sports, Science and Technology, JSPS KAKENHI (21310012), andOverseas, Hong Kong & Macao Scholars Collaborated Researching

Ocean Sci., 7, 27–43, 2011

Fund from National Science Foundation of China (No. 41028006).
We appreciate the critical comments from the three reviewers.
Edited by: P. Chapman

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