Progress in Oceanography 176 (2019) 102138

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Progress in Oceanography
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Seasonal variations in nutrients and biogenic particles in the upper andlower layers of East China Sea Shelf and their export to adjacent seas

T

Yucheng Wanga,1, Xinyu Guoa,b, , Liang Zhaoc, Jing Zhangd⁎aCenter for Marine Environmental Studies, Ehime University, Matsuyama, JapanKey Laboratory of Marine Environment and Ecology, Ocean University of China, Ministry of Education, Qingdao, Chinac
College of Marine and Environmental Sciences, Tianjin University of Science and Technology, Tianjin, ChinadState Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, Chinab

ARTICLE INFOABSTRACT

Keywords:
Nutrient budget
East China Sea
Biogenic particles
Lateral transport
Seasonal variation
Low-trophic ecosystem model

Based on a three dimensional low-trophic ecosystem model, we revaluated budgets of nutrients and biogenic
particles (phytoplankton and detritus) in the East China Sea (ECS), a continental shelf sea with high productivity
that is affected by a large river (Changjiang River) and a western boundary current (Kuroshio). Following careful
comparison of model results with available observation data, we calculated the monthly inventories of thenutrients and biogenic particles in the ECS and the fluxes of the nutrients and biogenic particles through thelateral and vertical interfaces of the ECS. As an improvement over previous nutrient budget calculations thattreated the ECS as one box, we divided the water column into two layers: upper and lower layers corresponding
to different light condition. Seasonal variations in inventories of nutrients and biogenic particles in both upperand lower layers are apparent but present different features, which are related to opposite contributions of
biological processes and physical processes in the two layers. Our calculation shows the necessity of evaluating
not only the horizontal fluxes of nutrients and biogenic particles into and out of the ECS through lateralboundaries with adjacent seas but also the exchange fluxes of nutrients and biogenic particles between the upperand lower layers because the latter is larger than the former. Our calculation also reveals two major export
pathways of biogenic particles generated locally in the ECS: from the ECS to the Japan/East Sea through the
Tsushima Strait and from the ECS to the Kuroshio region through the shelf break (200 m isobath). The export
amount of biogenic particles is larger through the Tsushima Strait than through the shelf break in the watercolumn. The depth for the biogenic particles exporting through the shelf break of the ECS is the middle layer(from ~60 m to ~160 m).

1. Introduction
Continental shelf seas with water depths shallower than 200 m occupy 7% of ocean surface in the global ocean but provide 14% of total
global ocean production (Chen et al., 2003). As important sinks andsources for CO2, the shelf seas play a non-negligible role in global
carbon cycle (e.g., Thomas et al., 2004). On the other hand, eutrophication, hypoxia and other disturbances in chemical and physicalparameters have been reported in the shelf seas in recent years (e.g.,Anderson et al., 2002; Daiz, 2001). High productivity and above environmental issues depend closely on the nutrient concentrations andtheir variations in the shelf seas.
The East China Sea (ECS) shelf is one of the most studied marginalseas in the northwestern Pacific Ocean and is characterized as having acomplicated hydrodynamic environment. Aside from being influenced
by the East Asia Monsoon, the sea takes discharge from a large river, theChangjiang River, whose diluted water covers most areas of thenorthern ECS shelf in summer (Bai et al., 2014). The Kuroshio, a western boundary current in northwestern Pacific Ocean, flows along theshelf break of the ECS and affects the ECS by two branch currents: theKuroshio Branch Current to the north of Taiwan and the Kuroshio
Branch Current to the west of Kyushu (Ichikawa and Beardsley, 2002).
Further, the Taiwan Strait Current that flows into the ECS from the
Taiwan Strait, the Tsushima Warm Current that flows out the ECS
through the Tsushima Strait, the Yellow Sea Warm Current that connects the ECS with the Yellow Sea, and the China Coastal Current that

Corresponding author at: Center for Marine Environmental Studies, Ehime University, 2-5 Bunkyo-Cho, Matsuyama 790-8577, Japan.
E-mail address: guoxinyu@sci.ehime-u.ac.jp (X. Guo).
1
Current address: Center for High Performance Computing and System Simulation, Pilot National Laboratory for Marine Science and Technology (Qingdao),
Qingdao, China⁎

https://doi.org/10.1016/j.pocean.2019.102138
Received 8 April 2018; Received in revised form 23 April 2019; Accepted 22 July 2019
Available online 23 July 20190079-6611/ © 2019 Elsevier Ltd. All rights reserved.

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50
00
1020

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40 N
50 50
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38 N

2 00

50

50

50

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36oN

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50
1500

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34 N

0
1050

15000

°

Fig. 1. Model domain and bathymetry. Rivers aredenoted by dots along the coastline. Trianglesaligned in a transect represent the hydrographic
stations of the PN line used for observations by theJapan Meteorological Agency. Red squares are forevery 30 grid points along 200 m isobath counted
from Taiwan and for every 10 grid points along atransect across the Tsushima Strait counted from
Korea Peninsula, respectively. The ECS shelf is defined here as the area bounded by four sections
named Taiwan Strait, 200 m isobath, Tsushima
Strait and 34.5° N section. Usually, the boundary
between the ECS and the Yellow Sea is the line from
Qidong (denoted by hexagon near Changjiang Rivermouth), China to Jeju Island, Korea. In the study,
34.5°N section is used for a purpose of easy calculation of flux. (For interpretation of the references tocolour in this figure legend, the reader is referred to
the web version of this article.)

50

0
10

50

o

20
0

32 N

200

50

50

50

o

30 N

5
1500
00

100

100

20
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0
10

28oN
100

o

118 E

o

120 E

o

122 E

o

124 E

2100
00

20
0

50

20
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50

100

0
20

50

50

o

26 N

200

o

126 E

o

128 E

flows along the western coast of the ECS also affect the sea as inflow or
outflow through the lateral boundaries or as part of the current systemin the ECS.
The complex hydrodynamic environment strongly impacts the nutrient dynamics of the ECS. Like most shelf seas, the ECS receives nutrients from both terrestrial areas and the open ocean. Terrestrial nutrients are delivered to the sea through river input (Zhang, 1996; Liuet al., 2009) and by atmospheric deposition (Zhang et al., 2011; Kimet al., 2011). Oceanic nutrients are delivered to the sea by waterflowing into the sea with one entry at the Taiwan Strait (Chung et al.,2001) and the other along the shelf break where intrusion of the Kuroshio subsurface water results in nutrient fluxes several times larger
than the riverine nutrient input (Chen, 1996; Chen and Wang, 1999;
Zhang et al., 2007). As outflows, the Tsushima Warm Current andYellow Sea Warm Current are two apparent exit routes for nutrientsfrom the ECS (e.g., Morimoto et al., 2009).
Nutrient fluxes into the ECS have been evaluated in several studies.
Using an end-member mixing box model, Chen and Wang (1999) calculated nutrients budget in the ECS. Using a similar method, but refining it with new data, Zhang et al. (2007) revaluated the nutrient

o

130 E

budget in the ECS. Although there are discrepancies in values for nutrient fluxes between these two studies, the conclusion that oceanic
nutrients, especially those from Kuroshio water, are the major sourcesof nutrients in the ECS remains the same. Using a three dimensional
low-trophic ecosystem model, Zhao and Guo (2011) demonstrated thatthe oceanic nutrients from the Kuroshio can be used by phytoplankton
over the shelf of the ECS. Treating phosphate as tracer in a hydrodynamic model, Yang et al. (2013) demonstrated that phosphate-rich
Kuroshio water can be upwelled into surface layer off the Changjiang
Estuary.
Compared to input processes of nutrients to the ECS, little is known
about the output processes for nutrients and plankton-related particulate materials from the ECS. From a steady state viewpoint, the input ofnutrients to the ECS must be balanced by an output of nutrients andparticulate materials from the ECS. In the concept of “Continental Shelf
Pump” initially proposed by Tsunogai et al. (1999), continental shelfseas export inorganic and organic carbonate to the open ocean. In
budget calculations by Chen and Wang (1999) and Zhang et al. (2007),the export of particulate organic materials to the open sea was partly
considered, but the output of nutrients from the ECS to the surrounding2

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N m−3. For a consistence, we keep this unit for budget calculation. It
must be noted that (1) rivers provide river discharge and concentrationof dissolved inorganic nutrients (i.e., DIN, DIP and SIL) to the modeland the transport of particulate matter from rivers is not considered inthis study; (2) both sedimentation and resuspension processes for detritus and biogenic silicate are considered in our model; (3) there is abenthic layer below water-sediment interface, which exchanges detritus
and biogenic silicate with water column by sedimentation and resuspension processes and releases DIN and other dissolved nutrients
into water column (Skogen and Søiland, 1998; Zhao and Guo, 2011).
Our model is designed to reproduce seasonal variations in physicaland biogeochemical variables (Zhao and Guo, 2011). It is driven byclimatological monthly forcing including wind, freshwater flux, heat
flux, deposition of nutrients at the sea surface, ocean currents, watertemperature, salinity and nutrient concentrations along lateral open
boundaries. The tidal currents of four major tidal constituents (M2, S2,
K1, and O1 tides) provided by NAO.99b (Matsumoto et al., 2000) arelinearly superposed to the subtidal currents at lateral open boundaries(Wang et al., 2008). The hydrodynamic module has been demonstrated
to be able to simulate the seasonal variation of the Kuroshio and circulation pattern in the ECS (Guo et al., 2003, 2006); the biogeochemical module has also been demonstrated to be able to simulate theseasonal variation of nutrients and Chl-a distributions in the ECS although there were still some discrepancies between model results andobservations (Zhao and Guo, 2011). To improve biogeochemical
module performance, we adjusted some boundary conditions for biogeochemical variables from the original model used by Zhao and Guo(2011). These adjustments include: (1) updating atmospheric deposition of nitrogen according to Zhang et al. (2011) that increased thenumber of observation stations from 3 (Zhao and Guo, 2011) to ~40;(2) specifying the climatological field of nutrients (World Ocean Atlas
2005, WOA2005) in the model to reduce the artificial error of horizontal diffusion terms along sigma coordinate (Mellor and Blumberg,1985), (3) updating nutrient concentrations at western part of south
open boundary (i.e., east of Taiwan) from WOA2005 data to Japan
Meteorological Agency observation data, and (4) updating suspended
particulate matter concentrations using data from Yamaguchi et al.
(2013) in order to improve precision of underwater light calculation.
With these adjustments, we can obtain a better distribution of nutrientsin the ECS and the adjacent Kuroshio region. For example, the unrealistically high concentration of DIN in the subsurface layer of theouter shelf region of the ECS in Zhao and Guo (2011) has been removed. It should be noted that DIN concentration in Changjiang River
was collected from 1986 to 1988 (Zhang, 1996) and that in atmosphericdeposition of nitrogen was observed from 1990s to 2000s (Zhang et al.,2011). Therefore, our simulation reflects a climatological condition of
the low-trophic ecosystem in the ECS before 2000s.
The model was run for three years to reach a state of seasonallystationary, i.e., the model results are almost the same in third year as insecond year. Model results from the third year of calculation were savedwith an interval of one hour for further analysis.

waters was not fully considered. Therefore, our understanding of thebudget and associated transport processes of nutrients and particulatematerials in the ECS remains limited.
Moreover, the limited understanding of budgets of nutrients andparticulate materials in the ECS shelf (Chen and Wang, 1999; Zhang
et al., 2007) has not been directly related to the changes in concentrations of nutrients and phytoplankton in the ECS, both of whichhave apparent seasonal variation (Chen, 2009; Yamaguchi et al., 2013).
As a general concept, seasonal variations of inventories of nutrients andphytoplankton in a sea depend on both the biological processes inside
the sea and fluxes of nutrients and particulate materials at the lateral,
surface and bottom boundaries of the sea. Further, nutrients and phytoplankton typically exhibit different behaviors in euphotic and aphotic
layers in coastal waters, such as the ECS (Chen, 2000, 2009). However,a quantitative assessment of the contributions of biological processes
and the transport of nutrients and particulate materials to seasonalvariations in the inventories of nutrients and phytoplankton in the ECS,
especially with division of the ECS into euphotic and aphotic layers, isstill not found in the literatures.
In this study, we use a three dimensional low-trophic ecosystemmodel of the ECS to examine seasonal variations of inventories of nutrients and biogenic particles (i.e., sum of phytoplankton and detritus)
inside the upper and lower layers, respectively, and to evaluate thecontributions of biological processes in the ECS shelf along with exchanges of nutrients and biogenic particles between the ECS shelf andadjacent seas to the seasonal variations of inventories of nutrients andbiogenic particles. In addition, as an improvement over box models(Chen and Wang, 1999; Zhang et al., 2007), we show also the spatial
distribution of nutrients flux and biogenic particles flux along the lateral boundaries of the ECS. As demonstrated later, the total flux
through some transects reflects the difference between the fluxes inonshore and offshore directions, demonstrating a two-way transport ofnutrients and biogenic particles across those transects.
A brief description of the model configuration is given in Section 2.
Comprehensive comparison of model results with available observation
data is presented in Section 3. The budgets of nutrients and biogenic
particles are provided in Section 4. Discussions about budgets of nutrients and biogenic particles and two-way transport in the ECS aregiven in Section 5. Finally, we give a summary of this study in Section
6.
2. Model configuration
The model used in this study is based on a three dimensional lowtrophic ecosystem model covering the Bohai Sea, Yellow Sea, ECS, andKuroshio region developed by Zhao and Guo (2011). Here, we focus on
shelf areas in the ECS having a water depth shallower than 200 m(Fig. 1): a section across the Taiwan Strait, the 200 m isobath along theshelf break, a section across the Tsushima Strait, and a zonal section at
34.5°N that reaches from the southern tip of the Korean Peninsula to
China.
The model in our study consists of two parts: a hydrodynamic
module and a biogeochemical module. The hydrodynamic module isbased on the Princeton Ocean Model (Guo et al., 2003, 2006; Wanget al., 2008) and provides physical variables such as sea surface elevation, water temperature, currents, and diffusivity coefficients to thebiogeochemical module. The biogeochemical module is based on biological part of NORWECOM (Skogen and Søiland, 1998) and includes
three nutrients (dissolved inorganic nitrogen (DIN), dissolved inorganic
phosphorus (DIP), and silicate (SIL)), two phytoplankton groups (diatoms and flagellates), and two biogenic organic material types (detritus
and biogenic silica). A schematic diagram and equations for these 7
biogeochemical variables (DIN, DIP, SIL, diatoms, flagellates, detritus,
and biogenic silica) as well as necessary parameters used in the equations can be found in Skogen and Søiland (1998) and Zhao and Guo(2011). Unit for all the biogeochemical variables in the model is mmol

3. Model validation
Since validation of hydrodynamic module can be found in Guo et al.
(2003, 2006) and Wang et al. (2008), we just compare our model results of biogeochemical variables with observations reported in literatures and datasets from the Japan Meteorological Agency (http://www.
data.jma.go.jp/gmd/kaiyou/db/vessel_obs/data-report/html/ship/
ship.php). There are 7 state variables in our biogeochemical module,
but these comparisons are based mainly on DIN and chlorophyll a (Chla). A qualitative comparison of model and observation data for detritus
is presented in final part. DIN is one of three elements of nutrients (i.e.,
DIN, dissolved inorganic phosphate, silicate) in the model, while Chl-a
represents the sum of two types of phytoplankton (diatoms and flagellates) in the model. It should be noted that some observation data3

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Fig. 2. Horizontal distribution of modeled DIN in surface layer (2 m depth, upper panels) and bottom layer (the deepest sigma layer, lower panels) in four seasons.
Contour lines with numbers denote 50 m and 100 m isobaths.

presented here was from snapshot cruises (Chung et al., 2001; Wanget al., 2016) while our model is designed to reproducing seasonalvariation driven by climatological monthly forcing.

the middle and outer shelf areas where the DIN concentration increases
from winter to spring. For example, the band representing a DIN concentration of 5–6 mmol N m−3 becomes more apparent from north of
Taiwan to 28°N in spring than in winter (Fig. 2f). In addition, DIN increases from 3 to 5–6 mmol N m−3 in the middle shelf of southern ECS.
In summer, surface DIN increases slightly in the northern ECS, from
Changjiang Estuary to Jeju Island (Fig. 2c). The bottom DIN also increases in the northern ECS, mainly around Jeju Island (Fig. 2g). Similar to that in spring, a band with high DIN is found in the bottom
layer from north of Taiwan Island to south of Changjiang Estuary(Fig. 2g).
In autumn, surface DIN decreases slightly in the northern ECS but
DIN remains high in the inner shelf (Fig. 2d). The high DIN band along
the China coast from Changjiang Estuary moves southward. Southwestof Jeju Island, bottom DIN is higher in autumn than in summer(Fig. 2h).
Comparing results of our model with the atlas of DIN presented byChen (2009), seasonal variations in observed DIN distribution are
generally reproduced by our model. For example, the region with highDIN (> 6 mmol N m−3) in the surface layer off Changjiang Estuary islarger in winter (Fig. 2a) than in summer (Fig. 2c); in the bottom layerof the middle shelf of southern ECS, relatively low DIN(~4 mmol N m−3) appears in winter while relatively high DIN(> 7 mmol N m−3) appears in summer; in the areas northeast of Taiwan
Island and southeast of Jeju Island, low concentration of DIN always
appears in the surface layer while high DIN occurs in the bottom layer(Fig. 2e&g). However, compared with observations (Chen, 2009), thehigh concentration area of DIN related to the Changjiang diluted water
is located a little north in the model. As a result, the high concentration
area of DIN near coast connects with the offshore high concentration
band of DIN in the bottom layer extended from southeast of Jeju Island(Fig. 2g&h). In the observations, we can find the high concentration
area of DIN near coast as well as the offshore high concentration bandof DIN in the bottom layer extended from south of Jeju Island (Chen,

3.1. Horizontal distribution of DIN and Chl-a in four seasonsChen (2009) presented the available DIN observation data in thesurface and bottom layers of the ECS in winter and summer. Here, we
present the spatial distribution of DIN from our model in each of thefour seasons (Fig. 2) and compare our results for winter and summer
with the atlas presented by Figs. 2c, 3a, 4c, and 5a in Chen (2009).
An apparent seasonal variation can be identified in the spatial distribution of DIN in the surface and bottom layers in the four seasons,e.g., February (winter), May (spring), August (summer), and October(autumn) (Fig. 2). In the surface layer in winter, a high concentration of
DIN is found near the Changjiang Estuary and nearby coastal areas
where the contours of ~10 mmol N m−3 almost overlap with the 50 m
isobath (Fig. 2a). High concentration of DIN also appears in the nearshore areas along the China coast from 24 to 30°N (Fig. 2a). A relatively
high concentration of DIN (~6 mmol N m−3) covers most of thenorthern ECS area and even reaches the Tsushima Strait. DIN is relatively low (less than 0.5 mmol N m−3) in the outer shelf (water depth
100–200 m) adjacent to the Kuroshio region. Due to strong verticalmixing in winter, DIN in the bottom layer of the inner shelf (water
depth 0–50 m) shows a pattern similar to that in the surface layer(Fig. 2e). In the middle shelf (water depth 50–100 m) and outer shelf(water depth 100–200 m), especially in areas northeast of Taiwan andsouthwest of Kyushu, low DIN is found in the surface layer while high
DIN is found in the bottom layer (Fig. 2a and e).
In spring, the surface DIN concentration over the middle and outer
shelf areas decreases significantly, especially in the northern ECS.
Similarly, the surface DIN over the inner shelf also decreases but sustains at a relatively high value (Fig. 2b). Reduction of DIN from winterto spring also appears in the bottom layer of the inner shelf but not in4

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Fig. 3. Horizontal distribution of surface Chl-a of model result (upper panels) and satellite data (lower panels) in four seasons. Satellite data is based on SeaWiFs from
Yamaguchi et al. (2013).

2009). However, the former is located a little south and does not connect with the latter (Chen, 2009). As suggested by Wu et al. (2011), thebathymetry and tidal currents around the Changjiang estuary are important to the offshore spreading of Changjiang dilute water in themodel. Compared to the horizontal resolution used by Wu et al., (2011)(~1 km around the Changjiang estuary), our model resolution (~5 km)
is too coarse to reproduce an accurate position of Changjiang diluted
water. Because the main purpose of this study is for an evaluation overentire shelf region and such northward shift in the location of Changjiang diluted water has little influence on the evaluation results overentire shelf area.
Similarly, a comparison of surface Chl-a given by our model(Fig. 3a–d) and satellite Chl-a data (Fig. 3e–h, Yamaguchi et al., 2013)
showed seasonally high Chl-a in the inner shelf in spring and summer
but low concentration in autumn and winter in both satellite data andin our model results. Low Chl-a (< 0.2 mg m−3) was confirmed in theouter shelf by both our model results and satellite data. This represents
an improvement in our model compared to previous version of themodel (Zhao and Guo, 2011) in which an unrealistically high concentration of Chl-a appeared northeast of Taiwan throughout the year.
One issue raised from this comparison is the low Chl-a concentrationfrom the inner shelf to the outer shelf in the ECS in winter given by ourmodel is not supported by satellite Chl-a data. A possible cause for thisdifference is the presence of pico-phytoplankton that is not consideredby our model but contributes significantly to total Chl-a over the shelfarea of the ECS (Chen, 2000; Fu et al., 2009).

autumn. We present the vertical distribution of DIN and Chl-a along thePN line in our model in the same months.
Similar features were identified for DIN in both our model results
and observations. In winter, vertically homogenous DIN is found in the
middle shelf (Fig. 4a and e); from spring to autumn, DIN is depleted in
the surface layer but remains at high concentration in the lower layer.
As an improvement over our previous model (Zhao and Guo, 2011),
the unrealistic high concentration in the subsurface and lower layers
from the outer shelf to the Kuroshio (Fig. 7 in Zhao and Guo, 2011) does
not appear in present study, which is likely the result of making twochanges in our model. The first is a modification of the nutrient concentration along the south open boundary. Nutrient concentrations at
the south open boundary in previous version (Zhao and Guo, 2011)were directly interpolated from WOA2005 and are now partly correctedby comparisons with observation data from the Japan Meteorological
Agency. The second change is a reduction in artificial horizontal diffusion along the sigma coordinates by specifying the climatologicalfield of nutrients that was not given in Zhao and Guo (2011). The sameprocedure has been applied to the calculation of water temperature andsalinity in the hydrodynamic module of POM (Mellor, 2003).
As was observed for the spatial distribution, the underestimation of
Chl-a in winter by the model is also confirmed in the vertical distribution (Fig. 5a and e). In spring, Chl-a in the model increases andforms a subsurface maximum over the shelf (Fig. 5b) that is also evident
in the observations (Fig. 5f). The subsurface Chl-a maximum concentration occurs at the depth of 30 m in spring and deepens to 50 m insummer. It weakens but can still be identified in autumn.
Besides the 200 m isobath, the Taiwan Strait and Tsushima Strait
are two important places for input and output of dissolved and particulate materials (Chung et al., 2001; Morimoto et al., 2009). Therefore,
validation of the vertical distribution of simulated DIN and Chl-a atthese two straits is also necessary for our diagnosis on the budget of
nutrients and biogenic particles in the ECS.
Observational reports on the nutrients and Chl-a in northern Taiwan
Strait are very limited. Chung et al. (2001) conducted two surveys including chemical samples and shipboard Acoustic Doppler Current

3.2. Vertical distribution of DIN and Chl-a in four seasons
For the comparison of vertical distribution of biogeochemical variables, we present the vertical distribution along the PN line (see Fig. 1)of the model results and observations for DIN (Fig. 4) and Chl-a (Fig. 5),
respectively. The reason for choosing PN line is that observations havebeen repeated there by the Japan Meteorological Agency since 1965.
The routine observations along the PN line are mainly conducted in
January for winter, April for spring, July for summer and October for5

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Fig. 4. Vertical distribution of DIN of modeled (upper panels) and observed (lower panels) along PN line in four seasons. Red lines in upper panels represents
euphotic depth calculated by our model. Unit is mmol N m−3 for DIN. (For interpretation of the references to colour in this figure legend, the reader is referred to the
web version of this article.)changed in the vertical direction, being only 1–2 mmol N m−3 in the layer
shallower than 50 m and ~10 mmol N m−3 near the sea bottom. In November, DIN concentration was ~2 mmol N m−3 in the layer shallower
than 50 m and ~8 mmol N m−3 near the sea bottom. Chl-a was greater than
0.8 mg m−3 through nearly the entire depth in April. In August, Chl-a in thesubsurface layer was as high as 1.2 mg m−3. In October and November, Chla concentration slightly decreased compared to that in August, but depth of
Chl-a larger than 0.4 mg m−3 increased to ~70 m.
For a comparison with observations by Morimoto et al. (2009), we
present model results in the Tsushima Strait in each of the 4 months (e.g.,
April, August, October, and November) in Fig. 7. In April, DIN concentration (Fig. 7a) has a clear vertical structure increasing with depth
while a high Chl-a concentration already appears in the surface layer(Fig. 7e). The DIN distribution is slightly different from that in Morimoto
et al. (2009) but the Chl-a distribution is consistent with that in Morimoto
et al. (2009). In August, vertical variation of DIN becomes strong: DIN
concentration in the upper 50 m layer is only 1–3 mmol N m−3 while thatin lower layer is > 10 mmol N m−3 (Fig. 7b). The subsurface maximum
Chl-a layer appears, except for in the central part of the eastern channel(Fig. 7f). Distributions of DIN and Chl-a in October (Fig. 7c and g) aresimilar with those in August. In November, DIN sustains a similar patternwith that in August and October (Fig. 7d), but Chl-a concentration in mostareas except for the coastal areas of Tsushima Strait decreases to a value

Profiler in northern Taiwan Strait in spring (May of 1999) and summer(August of 1999). Wang et al. (2016) conducted observations innorthern Taiwan Strait in early spring (March of 1998) and obtained a
distribution of DIN there. From these two papers, we obtain a generaldescription of the seasonal variations in nutrients at the Taiwan Straitfrom winter to summer. In winter, high DIN (> 10 mmol N m−3) isobserved at western Taiwan Strait while low concentration(2–4 mmol N m−3) is observed in the central and eastern Taiwan Strait(Wang et al., 2016). In spring, very low DIN (< 1 mmol N m−3) is observed in the central and eastern Taiwan Strait, while waters with
1–2 mmol N m−3 DIN are observed in the lower layer of the western
Taiwan Strait (Chung et al., 2001). In summer, DIN concentrations in
the central and eastern areas of the strait do not change much fromthose in spring, while DIN concentration in the western area increases
slightly to 3 mmol N m−3 (Chung et al., 2001). All of these features are
identifiable in our model results, though not perfectly replicated(Fig. 6).
Nutrient distribution at a section across the eastern channel of Tsushima
Strait based on repeated hydrographic observations from 2005 to 2007 wasreported by Morimoto et al. (2009). In their study, DIN and Chl-a distribution in April, August, October, and November were presented(Figs. 3–6 in Morimoto et al., 2009). In April, DIN was nearly homogenous
with a concentration of 1–3 mmol N m−3. From August to October, DIN

Fig. 5. Same as Fig. 4 but for Chl-a. Unit is mg m−3 for Chl-a.
6

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Fig. 6. Vertical distribution of DIN in (a) March (b) May and (c) August at a section across the Taiwan Strait (see Fig. 1 for its position). Red lines represent euphotic
depth calculated by our model. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

smaller than 0.2 mg m−3 (Fig. 7h). Considering the difference between
snapshot observations in Morimoto et al. (2009) and climatologicalmonthly forcing used in model calculations, the agreement in spatial
pattern is acceptable.

PON reported by Huang et al. (2000), concentration of POC also decreased in offshore direction as observed by Zhu et al. (2006). Further,
POC abundance is slightly higher in the lower layer than in the surface
layer. For example, PON abundance in the surface layer is~0.1–0.2 mmol N m−3 but is 0.2–0.4 mmol N m−3 above seabed over
the outer shelf (Zhu et al., 2006). Moreover, Cheng et al. (2011) reported very high concentrations with values of ~30 mmol N m−3 PON
in coastal areas in the north of the Changjiang Estuary in spring of
2009.
In our model, the reduction of PON from coastal areas to outer shelfregions was well represented, taking the result along the PN line forexample (Fig. 8, here we extend the PN line shoreward to 123°E). In
winter, PON abundance is homogenous with values of 1–2 mmol N m−3
in the nearshore regions, while that in the outer shelf is less than
1 mmol N m−3 (Fig. 8a). From spring to autumn, PON in the nearshore
regions is generally larger than 5 mmol N m−3 while that in the outer
shelf remains small (Fig. 8b–d). Besides, PON abundance is usuallyhigher in the lower layer than in the surface layer (Fig. 8b–d). Spatially,
the highest concentration of PON is found in the lower layer north of
Changjiang Estuary with a value of ~30 mmol N m−3 (results is notshown) in accordance with the observation by Cheng et al. (2011). In
general, PON concentration in the model results is at the same order as
the observations; the spatial distribution of PON in the model results
and observation are also consistent with each other.
After a careful comparison with the available observations, weconclude that the model can capture the general features of spatial

3.3. Distribution of particulate organic nitrogen (PON)
In our model, N-related variables include DIN, diatoms, flagellates
and detritus. Following validation of the distribution of DIN and phytoplankton, we check the distribution of detritus. In the marine environment, the sum of diatoms, flagellates, and detritus is usually surveyed as PON in hydrological observations. Moreover, in the ECS, PON
can also be estimated by particulate organic carbon (POC) because theratio of POC to PON in the ECS is relatively stable and is close to the
Redfield ratio of 6.63 (Redfield, 1963) as suggested by Hung et al.
(2000) and Zhu et al. (2006). Here, we compare the model results of
PON with observation data. If only POC data was available in previous
studies, we converted it to PON using the Redfield ratio. Chen et al.
(1996) reported a ratio of 7.69 for the C/N ratio in the ECS. Using a
different ratio in our converting calculation affects the value but does
not affect the spatial distribution.
Spatially, PON abundance is high in inner shelf regions and decreases in offshore direction based on observation data in previous
studies. For example, in the southern ECS in autumn, PON abundance is~1.5 mmol N m−3 at nearshore stations and only ~0.3 mmol N m−3 atoffshore stations (Huang et al., 2000). Similar to the decreasing trend of

Fig. 7. Vertical distribution of DIN (upper panels) and Chl-a (lower panels) of model in April, August, October and November. Red lines in upper panels represent
euphotic depth calculated by our model. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)7

Progress in Oceanography 176 (2019) 102138

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Fig. 8. Vertical distribution of modeled PON along PN line in four seasons. Red lines represent euphotic depth calculated by our model. Unit is mmol N m−3. (Forinterpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

distribution of DIN and biogenic particles (Chl-a and detritus) in the
ECS as well as their seasonal variations. We therefore use model results
to examine the budget of state variables in the model and the related
physical and biogeochemical processes in the ECS shelf.

February and a minimum of ~30 Gmol N in June (DIN in Fig. 10a). The
inventory of phytoplankton in the upper layer gradually increases fromFebruary, reaches a maximum of ~10 Gmol N in April, and decreases
gradually to ~5 Gmol N in December (phytoplankton in Fig. 10a). The
inventory of detritus in the upper layer increases in March, reaches amaximum of ~27 Gmol N in April, and gradually decreases to its
minimum of ~16 Gmol N in September and then increases again(detritus in Fig. 10a). The total inventory of DIN, phytoplankton anddetritus in the upper layer is maximum (~97 Gmol N) in February andminimum in September (~60 Gmol N), showing a similar range (~37
Gmol N) to that (40 Gmol N) of DIN in the same layer (Fig. 10a).
The inventory of DIN in the lower layer reaches a minimum value of~105 Gmol N in March, then gradually increases to a maximum of~145 Gmol N in October (DIN in Fig. 10b). The inventory of phytoplankton in the lower layer generally remains smaller than 5 Gmol N in
all months (phytoplankton in Fig. 10b). The inventory of detritus in thelower layer is at a minimum (~20 Gmol N) in January and increases
gradually to its maximum (~53 Gmol N) in July and August (detritus in
Fig. 10b). The total inventory of DIN, phytoplankton and detritus in thelower layer is at a minimum (~133 Gmol N) in February and maximum(~188 Gmol N) in August and September, showing a greater seasonalvariation range (~55 Gmol N) compared to that of DIN (40 Gmol N) in
the same layer (Fig. 10a).
Differences in the inventories of DIN, phytoplankton and detritus in
the upper and lower layers are evident. For example, inventory of DIN
in the upper layer is large in winter but small in early summer, whilethat in the lower layer is small in early spring but large in autumn,
although both show similar seasonal variation ranges (~40 Gmol N);
phytoplankton is mainly concentrated in the upper layer, while theinventory of detritus in the lower layer gets larger in summer and has alarger level and seasonal range than that in the upper layer.
The inventory of DIN in the entire water column shows seasonalvariation similar to that in the upper layer, while the inventory of
detritus in the entire water column shows seasonal variation similar tothat in the lower layer (Fig. 10). Seasonal variation of these two variables is close in range but out of phase. Seasonal variation range of theinventory of phytoplankton in entire water column is ~10 Gmol N
which is only ~25% of that for DIN or detritus. The sum of these threevariables (i.e., sum of DIN, phytoplankton and detritus) gives a maximum inventory in the total water column in August and September andshows a smaller range (~20 Gmol N) than that of DIN (~40 Gmol N) or
detritus (~33 Gmol N). Chen (2008) reported that DIN inventory in the
ECS shelf was 148.8 and 232.5 Gmol in summer and winter, respectively. Our model results give a comparable value in summer but asmaller value in winter.
The inventory of each variable shown in Fig. 10 is controlled bothby biological processes inside the target water volume and the input
and output of each variable through the boundaries of the target study
area. Photosynthesis and respiration affect the concentrations of DIN
and phytoplankton; mortality of phytoplankton affects the concentrations of phytoplankton and detritus; remineralization of detritus affects
the concentrations of DIN and detritus; particle sinking brings

4. Model results
4.1. Seasonal variations of inventories of nutrients and biogenic particles
Inventory is defined as the quantity integrated in the volume between two depths and over a target area. In this study, we divide thewater column into two layers, the upper layer and the lower layer, andcalculate the inventory in each of the two layers using Eqs. (1) and (2),respectively.

SCU (t ) =SCL (t ) =(x , y , t )ZU (x , y)
ZU (x , y )H (x , y )SCT = SCU + SCL¯
C (x , y , z , t ) dzdxdy¯
C (x , y, z, t ) dzdxdy

(1)
(2)
(3)

where SCU (t ), SCL (t ) , and SCT (t ) are inventories of a variable C in theupper layer, lower layer and total water column, respectively; x , y ,andz , are coordinates in eastward, northward, and upward directions,
respectively; t is time; ZU is vertical coordinate of upper layer bottom;
is sea level; H is depth of the sea bottom; overbar means monthly
averaging after a detiding to hourly output of model results using a tide
filter (Hanawa and Mitsudera, 1985).
Following Chen and Wang (1999) and Zhang et al. (2007), we set
the target area to the ECS shelf shallower than 200 m (Fig. 1). Variable
C can be each of the biogeochemical variables of the model. In thisstudy, we focus on the behavior of nitrogen and therefore choose DIN,
sum of two groups of phytoplankton (i.e., diatoms and flagellates) and
detritus, as C respectively.
In our model, the euphotic layer depth is defined as the penetration
depth of 1% of the surface light. The upper layer was initially designated as the euphotic layer. However, the depth of the euphotic layer isclosely dependent on the specified suspended particulate material
concentration and chlorophyll a (Chl-a), both of which show considerable temporal variations. If ZU in Eqs. (1) and (2) changes withtime, it is difficult to interpret changes in SCU (t ) and SCL (t ). Therefore, we
fixed ZU as being the half depth of the water column and consequently
ZU is only a function of (x , . The reason of the half depth of watercolumn for ZU is that the annual averaged euphotic thickness (Fig. 9a)
calculated by our model is although not exactly but roughly one half of
the water depth for the ECS shelf shallower than 200 m (Fig. 9b). This
choice retains the feature that the annual averaged euphotic layer
thickness gradually becomes thicker with increasing offshore distance(Fig. 9a). The differences of the values in Fig. 9b from 0.5 mean thischoice is only an approximation to the euphotic layer.
The inventory of DIN in the upper layer shows a large seasonalvariation range: a maximum of ~70 Giga moles of N (Gmol N) in
8

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Fig. 9. Horizontal distribution of (a) annual mean euphotic layer depth (unit: m) and (b) ratio of annual mean euphotic layer depth to water depth.

Fig. 10. Monthly mean inventories of DIN, phytoplankton (PHY), detritus (DET) and sum of them (DIN + PHY + DET) in (a) upper layer (b) lower layer and (c)water column in the ECS.

phytoplankton and detritus from the upper layer into the lower layer;
sediment and resuspension through the water-sediment interface affectthe concentration of detritus in the lower layer; input of DIN from rivers
and the atmosphere affects the DIN concentration in the upper layer;
remineralization of bottom sediment affects DIN in the lower layer;
Taiwan Strait Current and Kuroshio intrusion bring DIN into the target
water volume while the Tsushima Warm Current carries DIN and particulate materials out of the target water volume. For a full understanding of seasonal variations of the inventories of these biogeochemical variables shown in Fig. 10, we need to evaluate thecontribution of each of these processes.
The tendency of any inventory (tendency(S)) for DIN, phytoplankton
and detritus in the target water volume, which represents the time
variation term of each of these biogeochemical variables is described byfollowing equation,tendency (S ) = phy (S ) + bio (S )and respiration of phytoplankton and remineralization of detritus for
DIN, photosynthesis, respiration and mortality of phytoplankton for
phytoplankton, phytoplankton mortality and detritus remineralization
for detritus.
4.2. Processes related to seasonal variation of DIN inventory
The tendency of DIN inventory in the upper layer is negative fromFebruary to May, close to zero from June to September, and positivefrom October to the following February and has a similar seasonalpattern to the biological processes (bio, Fig. 11a). Further, the variation
range of biological processes (bio) is ~15 kmol N s−1, which is muchlarger than that of physical processes (phy) with a value of~5 kmol N s−1 (Fig. 11a). Horizontal fluxes through lateral boundaries
have apparent seasonal variations with relatively large fluxes across the
200 m isobath and through the Tsushima Strait from July to November
and relatively small fluxes through the Taiwan Strait and across 34.5°N
section (Fig. 11b). Vertical transports through the bottom of upper layer
due to advection (ver_adv) and turbulent diffusion (ver_diff) are relatively larger (Fig. 11c) while fluxes of river load (river) and atmosphericdeposition (atm) are relatively small. It should be noted that the direction of transport through the bottom of upper layer due to advection
is perpendicular to layer with the same sigma-coordinate (Mellor,(4)

where phy(S) denotes the sum of fluxes attributed to physical processes,
including horizontal fluxes through the four lateral boundaries (Taiwan
Strait, 200 m isobath, Tsushima Strait, and 34.5°N section) and transport fluxes through the sea surface, water layer interface between upperand lower layers, and water-sediment interface; bio(S) denotes thecontributions of all biological processes, which include photosynthesis
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Fig. 11. Tendency of DIN inventory (tendency), flux due to physical processes (phy) and flux due to biological processes (bio) in Eq. (4) in the (a) upper layer, (d)lower layer, (g) entire water column. Lines in the middle panels are DIN fluxes across four lateral boundaries of (b) upper layer, (e) lower layer and (h) entire watercolumn. Lines in lower panels are DIN fluxes across surface and bottom of the (c) upper layer, (f) lower layer, (i) entire water column. river and atm denote riverine
input and atmospheric deposition, respectively. ver_adv and ver_diff are for fluxes due to advection and turbulent diffusion across the bottom of the upper layer,
respectively. ver_bot is for flux across water-sediment interface.

2003). As first order approximation, it is likely that the DIN supplied byexchange between upper and lower layers (sum of ver_adv and ver_diff)supports primary production in the upper layer.
The tendency of DIN inventory in the lower layer is different fromthat in the upper layer (Fig. 11d). It is positive from April to September,close to zero in March and October, and is negative in other months.
Biological processes (bio, mainly remineralization of detritus in thislayer) are always positive and act to supply DIN while physical processes (phy) are negative and act to remove DIN (Fig. 11d). Among four
horizontal transport terms in phy in the lower layer, DIN is mainly input
through the 200 m isobath and is removed from the Tsushima Strait
with both fluxes being on the order of 5–10 kmol N s−1 (Fig. 11e),
which are larger than those in the upper layer. Both exchange fluxes
due to advection (-ver_adv) and due to turbulent diffusion (-ver_diff) areon an order of 5–10 kmol N s−1 that acts to supply DIN from the lower
layer to the upper layer; the supply of DIN from the sea bottom to thelower layer due to remineralization of sediments (ver_bot) is on theorder of 2–4 kmol N s−1 (Fig. 11f).
The DIN inventory in the entire water column shows a similar
pattern of seasonal variation with that in the upper layer (Fig. 11g). For
the tendency of DIN inventory in the entire water column, the contribution of biological processes is always negative (Fig. 11g), indicating that photosynthesis overcomes other biological processes (e.g.,
respiration of phytoplankton and remineralization of detritus) and theoverall effect of biological processes in the shelf area of the ECS is totransfer DIN to biogenic particles (i.e., phytoplankton and detritus).
From the viewpoint of the entire water column, the supply of DIN for
this transfer likely comes from the four lateral boundaries (Fig. 11h),surface and bottom of the ECS (i.e., riverine input, atmospheric deposition and sediment remineralization, Fig. 11i) as the DIN flux fromthe lateral boundaries is a result of the large influx through the shelf
break and a large outflux through the Tsushima Strait (Fig. 11h), while
the DIN flux from the surface and bottom of the ECS is the sum of threepositive fluxes (Fig. 11i). However, as we show for the tendency of DIN
inventory in the upper layer, the DIN flux through the bottom of theupper layer due to exchange between the upper and lower layers ismuch larger than those fluxes from lateral boundaries, riverine input
and atmospheric deposition (Fig. 11c). Therefore, the engine for thetransfer from DIN to biogenic particles in the euphotic layer in the shelfarea of the ECS is the exchange between the upper and lower layers.
This indicates that treating the ECS as one box as in previous studies is
not sufficient for understanding the mechanisms that support primary
production in the ECS.
The annual mean results for DIN budget in two layers are shown in
Table 1. In the upper layer, the annual mean flux due to biological processes (bio, −16.67 kmol N s−1) is balanced by annual mean flux due tophysical processes (16.77 kmol N s−1). For each term of flux due to physical processes, annual mean exchange flux across the water layer interface
10

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and mortality of phytoplankton and both act to reduce phytoplankton
in the lower layer. Horizontal transports of phytoplankton across thefour lateral boundaries in the lower layer are small compared withthose in the upper layer (Fig. 12e). As mentioned above, the transportof phytoplankton in the lower layer by advection (-ver_adv) and that due
to sinking of phytoplankton (-sink_up) act to bring phytoplankton fromthe upper layer to the lower layer (Fig. 12f). Contributions from turbulent diffusion (-ver_diff) across the surface of lower layer and sediment flux (ver_bot) across the bottom of the lower layer (i.e., watersediment interface) are quite small throughout the year. Compared totransports of advection (-ver_diff) and sinking processes (-sink_up) in thelower layer, horizontal transport is negligible.
The tendency of phytoplankton inventory in the entire watercolumn follows that in the upper layer (Fig. 12g) but with relatively
smaller fluxes due to physical and biological processes. For the twolayers together, seasonal variation of phytoplankton is generally controlled by biological processes because seasonal variations of phytoplankton fluxes through the vertical and lateral boundaries of target
water column area are very small (Fig. 12h and i). In other words,
examining the two layers separately reveals the importance of exchangeof phytoplankton between two layers in the water, which will disappear
if we treated the water column as one layer.
The annual mean results for the phytoplankton budget are shown in
Table 2. As mentioned above, biological processes in the upper layer
result in annual mean phytoplankton production of 9.17 kmol N s−1
while those in the lower layer act to remineralize phytoplankton withan annual mean value of −7.95 kmol N s−1. The net difference inbiological processes between the upper and lower layers(−1.22 kmol N s−1) is exported out of the ECS mainly via the shelf
break (200 m isobath), Tsushima Strait, and sediment process with anannual mean flux of −0.35, −0.75, and −0.21 kmol N s−1, respectively. Physical processes act to transport phytoplankton from the upper
layer to the lower layer. As shown in Table 2, 5.81 and 2.50 kmol N s−1
phytoplankton is transported from the upper layer to lower layer by
turbulent diffusion (ver_diff) and sinking process (sink_up), respectively.
On the whole, fluxes across the surface and bottom interfaces are small(~0.21 kmol N s−1).

Table 1
Annual mean of DIN budget for upper layer, lower layer and entire watercolumn, respectively. Positive values are for input fluxes and negative values
are for output fluxes.
Flux (kmol N s−1)

Terms

Upper layer

Lower layer

Water column

phy

16.77

−6.84

9.93

bio

−16.67

6.86

−9.81

3.67
−4.49
0.21
0.41
2.07
1.24
6.73
6.92
0.00

9.90
−6.92
−0.58
1.00
0.00
0.00
−6.73
−6.92
3.40

13.57
−11.41
−0.37
1.41
2.07
1.24
0.00
0.00
3.40

phy

200 m isobath
Tsushima Strait
34.5° N section
Taiwan Strait
atm
river
ver_adv
ver_diff
ver_bot

between the upper and lower layers (sum of ver_adv and ver_diff,
13.65 kmol N s−1) is the largest. Furthermore, among fluxes across thefour lateral boundaries, fluxes across 200 m isobath and through the
Tsushima Strait (3.67 and −4.49 kmol N s−1, respectively) are larger thanthose across 34.5°N section and through the Taiwan Strait (0.21 and0.41 kmol N s−1, respectively). Annual mean fluxes of riverine input andatmospheric deposition are 1.24 and 2.07 kmol N s−1, respectively. In thelower layer, annual mean fluxes due to physical processes and due tobiological processes are of −6.84 and 6.86 kmol N s−1, both of which aresmaller than those in the upper layer. Notably, these two fluxes are negative and positive, respectively, and opposite to those in the upper layer.
For each flux due to physical processes, −13.65 kmol N s−1 DIN is removed from the lower layer to the upper layer via transport across thewater layer interface between the upper and lower layers. Annual mean
fluxes across the four lateral boundaries in the lower layer are larger thanthose in the upper layer. At the water-sediment interface, regenerationfrom the bottom sediment into the lower layer is 3.40 kmol N s−1. For theentire water column in the ECS, flux due to physical processes is positive(9.93 kmol N s−1) while that due to biological processes is negative(−9.81 kmol N s−1). The 200 m isobath is the main site for input of DIN,
while the Tsushima Strait is the main site for output of DIN. DIN fluxes
through the Taiwan Strait and across the 34.5°N section is comparable tothat of the riverine input and atmospheric deposition.

4.4. Processes related to seasonal variation of detritus inventory
The tendency of the detritus inventory in the upper layer is positive
with values of 1–2 kmol N s−1 in February and March but approaches
zero during the rest of the year (Fig. 13a). Similar to the pattern for
phytoplankton, biological processes related to detritus (bio) over theyear have a positive contribution in the upper layer while flux due tophysical processes (phy) has a negative contribution (Fig. 13a). The
biological processes shown in Fig. 13a include mortality of phytoplankton and remineralization of detritus. Since the contribution of
biological processes related to detritus is positive over the year and its
peak appears 1 month later than that of phytoplankton, the mortality ofphytoplankton likely controls the presence of detritus in the upper
layer.
Detritus across the four lateral boundaries exhibits similar seasonalvariations (Fig. 13b) to phytoplankton. Among four lateral boundaries,
the Tsushima Strait and the 200 m isobath are the two major pathwaysfor detritus to leave the ECS. In particular, transport of detritus throughthe Tsushima Strait (~2kmol N s−1) is comparable to that of DIN(~3 kmol N s−1) in March and April. At the 200 m isobath, horizontaltransport readily exceeds 1 kmol N s−1 from February to April and is~0.5 kmol N s−1 in other months. Water exchange between the Yellow
Sea and the ECS across the 34.5°N section induces an input of detritus
into the ECS from November to March and an output of detritus fromthe ECS from May to October with orders of less than 1 kmol N s−1(Fig. 13b).
The flux of detritus through the vertical interface includes contributions by advection (ver_adv) and turbulent diffusion (ver_diff) and4.3. Processes related to seasonal variation of phytoplankton inventory
The tendency of phytoplankton inventory in the upper layer is positive with a value of 1–2 kmol N s−1 in February and March but approaches zero in other months (Fig. 12a). Over a year, the total biological processes (bio) have a positive contribution to the tendency ofphytoplankton inventory while the total physical processes (phy) have anegative contribution in the upper layer (Fig. 12a). In particular, fromJanuary to May, contributions of both biological processes and physicalprocesses are large and those in other months are relatively small.
Horizontal transports of phytoplankton across the four lateralboundaries show seasonal variations (Fig. 12b) and are smaller thanvertical transport across the bottom of the upper layer by one order ofmagnitude (Fig. 12c). The transports of phytoplankton in the upper
layer by diffusion (ver_diff) and sinking of phytoplankton (sink_up) areboth negative with peak values in March and July, respectively;transport flux due to advection (ver_adv) is relatively small (Fig. 12c).
The tendency of phytoplankton inventory in the lower layer is almost zero in all months (Fig. 12d). Flux of phytoplankton due to physical processes is always positive while that due to biological processes
is always negative, and both are relatively larger from February to May.
The biological processes in the lower layer are mainly due to respiration11

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Fig. 12. Same as Fig. 11 but for phytoplankton. sink_up is flux due to sinking process across the bottom of the upper layer. ver_bot is flux due to sediment processes atwater-sediment interface.

shown in Fig. 13c, ver_diff becomes large in summer when the difference
between the detritus inventory of the upper and lower layers becomelarger (Fig. 10).
The tendency of the detritus inventory in the lower layer is positivefrom February to June with a large value from March to May and negative from September to December with a large value in September
and October (Fig. 13d). The flux due to biological processes and horizontal fluxes through four lateral boundaries are not as large as thosein the upper layer, but the exchange flux of detritus between the upperand lower layers is still large (Fig. 13e and f).
In addition to advection (-ver_adv) and turbulent diffusion of detritus (-ver_diff) and sinking of detritus (-sink_up) through the top oflower layer, resuspension of detritus from the sea bottom and sinking ofdetritus to the sea bottom are involved in the vertical flux of detritus in
the lower layer (ver_bot, Fig. 13f). The sum of these three terms (i.e.,-ver_adv, -ver_diff, -sink_up, ver_bot) is much smaller than each of them.
In entire water column, the tendency of detritus inventory is positive from February to June and negative from August to December(Fig. 13g). Flux due to biological processes (bio) is about 10 kmol N s−1
or more from February to August and is sustained at ~5 kmol N s−1 inother months (Fig. 13g). Flux due to physical processes (phy) varies
from ~5 to ~12 kmol N s−1 and has a value of about 10 kmol N s−1
from March to September. As mentioned above, horizontal transports
across the four lateral boundaries are mainly concentrated in the upper
layer. Seasonal variations of these horizontal transports in the entire
water column follow those in the upper layer (Fig. 13b, e and h).

Table 2
Annual mean of phytoplankton budget for the upper layer, lower layer andentire water column, respectively. Positive values are for input fluxes and negative values are for output fluxes.
Flux (kmol N s−1)

Terms

Upper layer

Lower layer

Water column

phy

−9.16

7.88

−1.28

bio

9.17

−7.95

1.22

−0.26
−0.65
−0.01
0.08
−0.27
−5.54
−2.50
0.00

−0.09
−0.10
−0.05
0.02
0.27
5.54
2.50
−0.21

−0.35
−0.75
−0.06
0.10
0.00
0.00
0.00
−0.21

phy

200 m isobath
Tsushima Strait
34.5° N section
Taiwan Strait
ver_adv
ver_diff
sink_upver_botthat due to sinking of detritus (sink_up), and all these fluxes passthrough the bottom of upper layer (Fig. 13c). As expected, sinking
detritus always has a negative contribution to the tendency of detritus
inventory in the upper layer, but turbulent diffusion of water has apositive contribution to the tendency of detritus; contribution of advection is relatively small. This can also be interpreted as a larger
detritus inventory in the lower layer than that in the upper layer owing
to the two layers being of the same thickness at each grid point. As
12Progress in Oceanography 176 (2019) 102138

Y. Wang, et al.

Fig. 13. Same as Fig. 11 but for detritus. sink_up is flux due to sinking process across the bottom of the upper layer. ver_bot is flux due to sediment and resuspension
processes at water-sediment interface.

Among fluxes across the four lateral boundaries, fluxes across the 200 m
isobath is larger than 1 kmol N s−1 from February to August and thatthrough the Tsushima Strait is larger than 2 kmol N s−1 from March toJuly (Fig. 13h). These two boundaries are the main sites for export ofdetritus from the ECS to adjacent oceans compared with the other twoboundaries (34.5°N section and Taiwan Strait). Vertical transport ofdetritus at the water-sediment interface (ver_bot, Fig. 13i) denotes thesum of the resuspension of detritus from the sea bottom and the sinkingof detritus to the sea bottom and is relatively larger (> 5 kmol N s−1)
from March to October.
The annual mean results for detritus budget are shown in Table 3.
Flux due to physical processes is −7.45 kmol N s−1 in the upper layer
but only −1.06 kmol N s−1 in the lower layer. Similarly, flux due tobiological processes is 7.51 kmol N s−1 in the upper layer and1.08 kmol N s−1 in the lower layer. For the entire water column, biological processes (i.e., phytoplankton mortality and detritus remineralization) with an annual mean flux of 8.59 kmol N s−1 appears toprompt detritus production while physical processes with an annual
mean flux of −8.51 kmol N s−1 acts to remove detritus from the ECS.
Horizontal transports of detritus across the four lateral boundaries inboth the upper and lower layers are very small compared to thetransport across the interface between the upper and lower layers. At
the interface of the upper and lower layers, the net detritus flux is−5.54 kmol N s−1, indicating a downward transfer comprising ver_adv(4.54 kmol N s−1),
ver_diff(28.13 kmol N s−1)
andsink_up−1(−38.21 kmol N s ).
Onthewhole,
detritus
produced

Table 3
Annual mean of detritus budget for the upper layer, lower layer and entire
water column. Positive values are for input fluxes and negative values are for
output fluxes.
Flux (kmol N s−1)

Terms

Upper layer

Lower layer

Water column

phy

−7.45

−1.06

−8.51

bio

7.51

1.08

8.59

−0.70
−1.13
−0.04
−0.05
4.54
28.13
−38.21
0.00

−0.37
−0.76
−0.14
0.04
−4.54
−28.13
38.21
−5.36

−1.07
−1.89
−0.18
−0.01
0.00
0.00
0.00
−5.36

phy

200 m isobath
Tsushima Strait
34.5° N section
Taiwan Strait
ver_adv
ver_diff
sink_upver_bot(8.59 kmol N s−1) in the ECS is deposited at the sea bottom with anannual mean flux of −5.36 kmol N s−1 and is exported out of the ECS
by horizontal transport with an annual mean flux of −3.15 kmol N s−1.
Transports across the 200 m isobath and through the Tsushima Strait
account for most of the horizontal transport with an annual mean of−1.07 and −1.89 kmol N s−1, respectively.

13

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Table 4Comparison of DIN fluxes across four boundaries from our model and estimates from previous studies. ★ Negative value indicates nutrient flow out of the ECS
shelf. * Estimated here is only with consideration of the eastern channel while the Tsushima Strait is composed of the eastern channel and western channel.
■
DIN flux across the eastern and western channels in summer in our model are −5.9 and −6.5 kmol N s−1, respectively.
SectionSeasonDIN transport (kmol N s−1)

Reference

200 m isobath

Summer
WinterAnnualSummer
WinterAnnualModel (Jun-Aug)
Model (Dec-Feb)
Model (annual)

4.4
5.0
4.7
5.9
13.6
9.7
15.6
10.7
13.6

Chen and Wang (1999)
Chen and Wang (1999)
Chen and Wang (1999)
Zhang et al. (2007)
Zhang et al. (2007)
Zhang et al. (2007)
Our study
Our study
Our study

Taiwan Strait

Summer
WinterAnnualSummer
WinterAnnualMay
AugustModel (Jun-Aug)
Model (Dec-Feb)
Model (annual)

1.0
0.4
0.7
8.5
6.4
7.5
1.0
1.9
3.7
−0.2★
1.4

Chen and Wang (1999)
Chen and Wang (1999)
Chen and Wang (1999)
Zhang et al. (2007)
Zhang et al. (2007)
Zhang et al. (2007)
Chung et al. (2001)
Chung et al. (2001)
Our study
Our study
Our study

Tsushima Strait

Summer
WinterAnnualSummer
WinterAnnualJul-Aug, Oct
Model (Jun-Aug)
Model (Dec-Feb)
Model (annual)

−0.14
−0.18
−0.16
−14.2
−18.1
−16.2
−4.5*
−12.4 (−5.9 and −6.5■)
−8.9
−11.4

Chen and Wang (1999)
Chen and Wang (1999)
Chen and Wang (1999)
Zhang et al. (2007)
Zhang et al. (2007)
Zhang et al. (2007)
Morimoto et al. (2009)
Our study
Our study
Our study

gave a value of ~1.8 kmol N s−1 for DIN flux. Zhang et al. (2007) reported a flux there as high as 8.5 kmol N s−1 in summer, which is muchlarger than that reported by Chung et al. (2001). On the other hand, theresults of Chen and Wang (1999) and our model are close to the value
reported by Chung et al. (2001).
At the Tsushima Strait, based on repeated cruises across eastern
channel of the Tsushima Strait over several years, Morimoto et al.
(2009) obtained a value of −4.5 ± 1 kmol N s−1 in summer. In ourmodel, DIN flux across the eastern channel of the Tsushima Strait insummer is −5.9 kmol N s−1 (Table 4), which is close to the value given
by Morimoto et al. (2009). Our model result with values of −5.9 and−6.5 kmol N s−1 at the eastern and western channels of Tsushima Strait
in summer, respectively, is also consistent with the result that the DIN
flux is larger at the western channel than at the eastern channel(Morimoto et al., 2013; Onitsuka et al., 2007). On the other hand, theresults of Chen and Wang (1999, −0.14 kmol N s−1 in summer,−0.18 kmol N s−1 in winter) are likely too small as compared with thevalues given by Morimoto et al. (2009).
As stated above, estimations based on box model given by Chen andWang (1999) and Zhang et al. (2007) show large discrepancies for DIN
fluxes at the Tsushima Strait and the Taiwan Strait, respectively. Since
the volume transports through two straits are similar in these calculations, large discrepancies in DIN transports through two straits should
be caused by different DIN concentrations used by these studies. For
example, mean DIN concentration at the Tsushima Strait given by Chen
and Wang (1999) is 0.1 mmol N m−3, which is smaller than the valuesof 3–5 mmol N m−3 observed by Morimoto et al. (2012). Mean DIN
concentration at the Taiwan Strait used by Zhang et al. (2007) is 3.5
and 5.3 mmol N m−3 in summer and winter, respectively, both of which
are larger than the value of 0.9 and 0.2 mmol N m−3 in May and Augustof 1999 observed by Chung et al. (2001).
In general, our model results of DIN transport through the Taiwan

5. Discussion
5.1. DIN budget estimated by our model and previous studies
The DIN budget in the ECS has been calculated for entire watercolumn in previous studies (Chen and Wang, 1999; Zhang et al., 2007)
with the end-member mixing box model. However, this kind of model isusually based on some assumptions and results of this kind of model
depend closely on the properties of water masses involved and havelarge uncertainties. With our three dimensional low-trophic ecosystemmodel, we could also calculate the DIN budget for the ECS. Comparisonof our model results with those in previous studies would deepen our
understanding of the nutrient budget for the ECS. In this subsection, we
just focus on DIN fluxes across the four lateral boundaries (i.e., Taiwan
Strait, 200 m isobath, 34.5°N section and Tsushima Strait). Flux of atmospheric deposition and rivers in these studies and our model are at
the same order of 1–2 kmol N s−1.
DIN fluxes across the four lateral boundaries in previous studies andthe present study are listed in Table 4. Among four lateral boundaries,
DIN flux across the 200 m isobath in our model is also the largest one, as
estimated by Chen and Wang (1999) and Zhang et al. (2007). However,DIN fluxes at these four boundaries show large discrepancies among
these studies. Taking the example of DIN flux across the 200 m isobathin winter, the flux was only 4.4 kmol N s−1 in Chen and Wang (1999),
which is much smaller than 13.6 kmol N s−1 (Zhang et al., 2007) and10.7 kmol N s−1 (this work). Consequently, the annual mean DIN flux
across the 200 m isobath estimated by Chen and Wang (1999) was
4.7 kmol N s−1, which is also smaller than the values of 9.7 kmol N s−1(Zhang et al., 2007) and 13.6 kmol N s−1 (this work).
At the section across the Taiwan Strait, DIN flux in these studies also
shows a large discrepancy. Based on direct observation of ocean currents and DIN concentration in August of 1999, Chung et al. (2001)
14

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Y. Wang, et al.

Strait and Tsushima Strait are comparable with the estimation based onfield data (e.g., Chung et al., 2001; Morimoto et al., 2009). Moreover,
DIN transport at the 200 m isobath (shelf break) is at same order withthose given by Chen and Wang (1999) and Zhang et al. (2007).
Therefore, the nutrient budgets given by a three dimensional biogeochemical model likely improve the calculations by a box model.

and recent reports about export of low salinity waters and dissolved
materials in subsurface layer (Isobe et al., 2004; Ren et al., 2015).
Moreover, these previous studies assumed a constant cross-shelf velocity along the entire shelf break when calculating export flux of suspended materials which is also not supported by recent studies that
present a strong spatial variation of cross-shelf velocity along the shelf
break (Guo et al., 2006; Liu et al., 2014; Zhou et al., 2015; Zhang et al.,2017). This study shows that the annual mean fluxes of phytoplankton
and detritus are in an offshore direction in the middle layer (i.e., from
~60 m to ~160 m) at the middle part of 200 m isobath, in an onshore
direction at two ends of the 200 m isobath: northwest of Taiwan andsouthwest of Kyushu. The presence of such strong spatial structuresuggests that it is questionable for the result from those estimations that
did not carefully consider the spatial variation of cross-shelf current andconcentration of particulate materials along entire length of the 200 m
isobath.
As another important boundary for the ECS, the Tsushima Strait
connects the ECS with the Japan/East Sea. Spatial distributions of DIN,
phytoplankton and detritus flux density across the Tsushima Strait are
shown in Fig. 15. Although DIN flux density is relatively larger in thewestern channel than in the eastern channel (Fig. 15a and b), the total
DIN fluxes through two channels are comparable (Table 4). The maximum core of DIN flux density in the vertical direction appears at~70 m depth (Fig. 15c) and increases largely in autumn. Large standard
deviation of DIN flux density coincides with large averaged DIN flux
density (Fig. 15d). This is also true for phytoplankton and detritus(Fig. 15h and l).
Phytoplankton flux density is large in the western channel of the
Tsushima Strait (Fig. 15e and f). In spring, the maximum core of phytoplankton flux density appears near the surface and gradually deepens
in summer to a depth of 30 m (Fig. 15g). For detritus, flux density is also
large in the western channel (Fig. 15i and j). One difference between
phytoplankton and detritus is that the maximum core of detritus flux
density is at a depth of 60 m, being deeper than that of phytoplankton.
Export of organic materials from the ECS shelf to Japan/East Sea has
been reported by Onitsuka et al. (2013) based on observation datacollected on four cruises in the eastern channel of the Tsushima Strait.
In their study, export flux of PON through the eastern channel of the
Tsushima Strait was calculated by the product of PON concentrationand current velocity after detiding and estimated to be 1.3, 1.0, 0.7 and0.7 kmol N s−1 in March, June, September and November, respectively.
Besides, they found that the percentage of organic material flux in total
nitrogen flux (i.e., sum of inorganic and organic nitrogen) in the eastern
channel of Tsushima Strait decreased from ~70% in March to ~20% in
November. In our model, export flux of PON there is calculated by adirect detiding to the PON flux, which is the product of the PON concentration and the sum of tidal current and subtidal current. The
monthly mean of PON export flux is 1.8, 1.0, 0.3, 0.3 kmol N s−1 inMarch, June, September and November, respectively, which are at thesame order as those reported by Onitsuka et al. (2013); the seasonalvariation in ratio of organic material flux (i.e., phytoplankton anddetritus) to total nitrogen flux in both channels shows the largest valueof 40% in March and smallest value of 10% in October.
One important thing should be noted here is that the export ofbiogenic particles at the shelf slope of the East China Sea in the nepheloid layer. Chen and Wang (1999) reported that the export flux of
POC across the shelf break is of −16.0 kmol s−1 in the surface waterand is of −22.0 kmol s−1 in the nepheloid layer, which is equivalent to−2.4 and −3.3 kmol s−1 PON with the Redfield ratio of POC/PON(106:16). In our model, export flux of PON at 200 m isobath is−1.42 kmol N s−1, which is smaller than that estimated by Chen andWang (1999). This may be because we did not consider direct input ofparticulate matter from rivers. Further, previous studies (Yanagi et al.,
1996; Chen and Wang, 1999; Hoshika et al., 2003) provided different
levels of POC export. Considering the large uncertainty in the previously reported values, our estimation on the export of biogenic

5.2. Spatial distribution of flux density of DIN and biogenic particles alongthe 200 m isobath and Tsushima Strait
The 200 m isobath (shelf break) is the most important entrance fornutrients loading into the ECS shelf, while the Tsushima Strait is themost important output for exporting materials out of the ECS shelf. The
current across the 200 m isobath has a nature of two-way, i.e., thepresence of onshore and offshore flows there (Zhang et al., 2017). Zhao
and Guo (2011) noted that the total transport of DIN across the 200 m
isobath was the sum of onshore flux and offshore flux. However, they
did not examine the spatial variation of DIN flux density (the product ofcross-shelf velocity and DIN concentration) along the 200 m isobath
and also did not pay attention to the spatial variation of the flux densityof biogenic particles along the 200 m isobath.
To help the understanding on the budgets given in Section 4, we
present the flux density of DIN and biogenic particles along the 200 m
isobath (Fig. 14). Annual mean flux density of DIN (Fig. 14b) is positive
northeast of Taiwan and southwest of Kyushu, consistent with the
Kuroshio intrusion pattern (e.g., Guo et al., 2006; Zhang et al., 2017).
On the other hand, negative DIN flux density at the middle part of the
200 m isobath is also apparent (Fig. 14b). Vertical integration of DIN
flux density along the 200 m isobath in different months is relatively
stable, except for that in the southwest of Kyushu (Fig. 14a). Horizontal
integration of DIN flux density is nearly 0 in the upper 40 m through ayear but shows a seasonal variation below 40 m depth (Fig. 14c). As
shown in Fig. 11, net DIN transport across the 200 m isobath is landward (i.e., onshore direction) all year round and is large in summer andautumn, which is likely caused by the intensification of onshore DIN
flux density between 120 m and 160 m depths (Fig. 14c), occurring
mainly southwest of Kyushu (Fig. 14d).
The annual mean flux density of phytoplankton (product of crossshelf velocity and phytoplankton concentration) also suggests two-way
transport (Fig. 14f). Different from that of DIN, the inflow of phytoplankton southwest of Kyushu is not as apparent as that northeast of
Taiwan (Fig. 14e). The maximum core of phytoplankton flux density
appears at a depth of 60 m in spring and deepens to 100 m in summer(Fig. 14g). Large seasonal variations in phytoplankton flux density
occur at the middle part of the 200 m isobath where the outflow ofphytoplankton is apparent (Fig. 14h). For detritus, the spatial distribution of the annual mean flux density is similar to that of phytoplankton but with greater flux density at the middle part of the 200 m
isobath. The flux density maximum of detritus appears at a deeper placethan that of phytoplankton (Fig. 14g and k). The sinking of detritus
following mortality of phytoplankton likely contributes to this difference. Another difference in horizontal transport of phytoplankton anddetritus is the large standard deviation of detritus flux density at boththe middle part and southwest of Kyushu while that of phytoplankton
appears only at the middle part (Fig. 14h and l). This difference is likely
related to downstream advection of detritus following mortality ofphytoplankton at the middle part of the 200 m isobath. Therefore, theonshore transport of detritus is relatively stable northeast of Taiwan(Fig. 14j) but undergoes an apparent seasonal variation southwest of
Kyushu (Fig. 14l).
Most previous studies suggested that the export of suspended matterfrom the ECS to the shelf break was concentrated near the sea bottom(Yanagi et al., 1996; Chen and Wang, 1999; Iseki et al., 2003; Oguri
et al., 2003) where concentration of suspended matter was usually high.
However, this calculation is not supported by the presence of bottom
onshore currents (Hu, 1994; Yoshikawa et al., 2010; Zhang et al., 2017)15

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Y. Wang, et al.

Fig. 14. Spatial distribution of annual mean flux density of (b) DIN, (f) phytoplankton and (j) detritus along the 200 m isobath. (a), (e) and (i) are for vertical
integration of each variable in 12 months. (c), (g) and (k) are for horizontal integration of each variable in 12 months. (d), (h) and (i) are for standard deviation ofeach variable, respectively. Grid point starts from northeast of Taiwan and increases in northeast direction (Fig. 1). Two times of 7-points running mean are
conducted.

particles in the water column across the shelf slope is acceptable.

while that of physical processes is positive (negative) in the upper layer(lower layer).
Further, the vertical exchange flux of nutrients between the upperand lower layers is comparable to or much larger than the horizontaltransports across lateral boundaries of the ECS shelf. For example, annual mean transport of DIN due to vertical advection and diffusion is13.65 kmol N s−1, which is the sum of detritus remineralization(6.86 k mol N s−1), sediment remineralization (3.40 kmol N s−1) andhorizontal transports through lateral boundaries in the lower layer(3.40 kmol N s−1). This indicated the important roles of vertical exchange between the upper and lower layers and biological processes(detritus remineralization) in affecting DIN inventory.
Among horizontal transports of external nutrients, nutrients fromthe Kuroshio are the largest nutrient input source for the ECS shelf,
which is consistent with previous studies. The net flux across the shelf
break is the sum of the onshore transport in the lower layer northeast of
Taiwan and southwest of Kyushu and the offshore transport in the

6. Conclusions
Using a three dimensional low-trophic ecosystem model, we simulated the seasonal variations of nutrients and biogenic particles (i.e.,
phytoplankton and detritus) in the ECS shelf. After a careful comparison
with available observation data, we judge that our model results can beused for diagnosing budgets of nutrients and biogenic particles in the
ECS shelf.
Unlike previous studies, which considered the entire water column
as one target, we divided the ECS into two layers, upper and lower
layers and found an apparent but different seasonal variation in inventories of nutrients and biogenic particles in these two layers. Thiswas induced by opposite contributions of biological processes andphysical processes in the upper and lower layers. For example, contribution of biological processes is negative (positive) for DIN inventory16

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Y. Wang, et al.

Fig. 15. Same as Fig. 14 but for a section across the Tsushima Strait. The location of grid points along the section is given in Fig. 1.

middle layer (from ~60 m to ~160 m) at the middle part of the 200 m
isobath. This reflects a two-way transport for DIN. Seasonal variationsin the horizontal transport of DIN is more apparent in the lower layersouthwest of Kyushu; seasonal variations of phytoplankton is apparent
in the middle part of the shelf break, while that of detritus is apparent in
the middle part of shelf break and southwest of Kyushu.
Another two-way transport of materials in the ECS shelf occurs as
the input of oceanic DIN into the ECS shelf through the Taiwan Strait(1.4 kmol N s−1) and 200 m isobath (13.6 kmol N s−1) and the output ofbiogenic particles out of the ECS shelf through the 200 m isobath(1.42 kmol N s−1) and Tsushima Strait (2.64 kmol N s−1). Export ofbiogenic particles from the ECS shelf to open ocean is important tosustain CO2 absorption in the ECS, which is consistent with the concept
of “Continental Shelf Pump”.

careful reading and useful comments. X. Guo is supported by JSPS
KAKENHI grant numbers (26287116/JPH05821), the National Natural
Science Foundation of China (NSFC) (No. 41576010), the Fundamental
Research Funds for Central Universities from the Ministry of Educationof China (No. 201512004). L. Zhao is supported by the Strategic
Priority Research Program of the Chinese Academy of Sciences(XDA11020305), the National Natural Science Foundation of China(NSFC, 41276016), and the Ministry of Education, Culture, Sports,
Science and Technology, Japan (MEXT) to a project on Joint Usage/
Research Center, Leading Academia in Marine and Environmental Research (LaMer). The data used in this paper are available on request tocorresponding author.
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