Assessing depth-integrated phytoplankton biomass in the East China Sea using a unique empirical protocol to estimate euphotic depth

doi:10.1016/j.ecss.2014.11.017

Elsevier

Estuarine, Coastal and Shelf Science

Volume 153, 5 February 2015, Pages 74-85

Estuarine, Coastal and Shelf Science

https://doi.org/10.1016/j.ecss.2014年11月01日7 Get rights and content

Highlights

•
A unique empirical protocol for the estimation of euphotic depth (Z_e) is developed.
•
Depth-integrated Chl-a from the surface to the Z_e $(\sum C h l_{Z_{e}})$ is evaluated spatially.
•
The $\sum C h l_{Z_{e}}$ is higher within the river plume than outside the plume.
•
The impact of the plume extension on phytoplankton biomass is discussed.

Abstract

The Changjiang (Yangtze) River plume has a direct impact on phytoplankton biomass in the East China Sea (ECS). The present study aimed to analyze the spatial distribution of depth-integrated chlorophyll a (Chl-a) concentrations from the surface to the euphotic depth (Z_e;

\sum C h l_{Z_{e}}

) using samples collected at 50 stations in the ECS during a cruise in June 2007. However, spatial coverage was limited because the Z_e, obtained from radiometric measurement of the vertical diffuse attenuation of solar irradiance, was only available at the 20 daytime stations. To address this limitation, it was determined that Z_e could be expressed empirically using the vertical means of Chl-a concentration, turbidity , and salinity in the euphotic zone. Using this relationship, the potential value of Z_e at night-time or low-light stations was calculated, and a dataset of

(\sum C h l_{Z_{e}})

for the entire research area was obtained. A low salinity surface water mass (LSSW) was identified on the eastern continental shelf (125.0°–126.5°E, 30.0°–31.0°N), probably part of the Yellow Sea Mixed Water, but clearly influenced by Changjiang Diluted Water (CDW) extending from the west. The Taiwan Current Warm Water mass (TCWW) was located to the south of the LSSW. Other oceanic water masses, including Kuroshio Surface Water, were located to the east of the LSSW. The means of the Z_e and

\sum C h l_{Z_{e}}

in the LSSW were significantly shallower and higher, respectively, compared with the TCWW and other oceanic water masses (p < 0.01). The present study suggests that the extension of the Changjiang River plume beyond the CDW affects the phytoplankton biomass on the eastern continental shelf of the ECS, more than 300 km from the river mouth.

Graphical abstract

Introduction

Large river plumes have important impacts on marine ecosystems, not only in estuaries, but also on adjacent continental shelves. The Amazon River plume enhances primary production for hundreds of km along the neighboring continental shelf (e.g., Dagg et al., 2004). For some large rivers with highly populated watersheds, additional anthropogenic influences on marine ecosystems occur through the extended plume. For example, the extended plume of the Mississippi River has both natural and anthropogenic impacts on the ecosystem in the Gulf of Mexico (Lohrenz et al., 1997).

The Changjiang (Yangtze) River is ranked fifth in the world in terms of discharge volume and is one of the large rivers thought to have considerable anthropogenic impacts on the marine ecosystem on the continental shelf of the East China Sea (ECS). Since the 1980s, algal bloom events have become more frequent and the chlorophyll a (Chl-a) concentration has increased in the Changjiang estuary and in the adjacent western shelf area of the ECS (122°–123.5°E, 30.5°–32°N) where surface shading by suspended particulate matter is less marked (e.g., Chen, 2003, Chai et al., 2006). During the summer wet season, the waters at the leading edge of the plume, referred to as Changjiang Diluted Water (CDW) and with a salinity of less than 31, often extends east or northeast beyond the adjacent western shelf and reaches the eastern shelf around 124°–125°E, 30°–33°N, more than 300 km from the river mouth (Hu, 1994, Su and Weng, 1994). Siswanto et al. (2008) identified an increase in dissolved inorganic nitrogen on the central and eastern shelf (123.5°–125.5°E, 31°–32°N) in conjunction with an increase in nitrogen fertilizer use in China during the last few decades, suggesting that anthropogenic river-borne nutrients are transported in the plume. A recent analysis of satellite images showed that an eastward shift of areas of high surface Chl-a coincided with the movement of CDW from the river mouth to the east of Jeju Island during summer (e.g., Yamaguchi et al., 2012). Therefore, the extension of the plume might affect the surface phytoplankton biomass on the eastern shelf beyond the estuary and on the adjacent western shelf, especially in summer.

The distribution of surface Chl-a as an index of phytoplankton biomass can be estimated from satellite data. However, in eastern shelf waters in summer, phytoplankton aggregates in subsurface waters rather than in surface waters (Zhao and Guo, 2011), forming a subsurface chlorophyll maximum (SCM) (Kim et al., 2009, Wang et al., 2014). The SCM cannot be clearly determined from satellite data but is a substantial component of the phytoplankton biomass in the water column (Kim et al., 2009). The SCM in eastern shelf waters of the ECS could be maintained by the supply of nutrients from deep waters (Kim et al., 2009, Zhao and Guo, 2011), implying that the plume extension could have less influence on the SCM than on surface Chl-a. To date, however, it is not clear whether the plume extension towards the eastern shelf and beyond the CDW is directly associated with the SCM and/or phytoplankton biomass on the shelf. One way to investigate this uncertainty is to determine whether the phytoplankton biomass in the water column differs between waters inside and outside the plume, using depth-integrated Chl-a (∑Chl) measured with an in situ optical chlorophyll sensor.

Many previous studies have investigated the spatial distribution of Chl-a in the ECS (e.g., Ning et al., 1988, Gong et al., 2003, Chai et al., 2006). However, most of these studies have reported the Chl-a as concentrations at specified depths or at the SCM, and the results have not provided detailed information on the spatial distribution of ∑Chl.

There have been few studies of the spatial distribution of ∑Chl in the ECS (e.g., Gong et al., 1996, Kim et al., 2009), possibly as a result of the practical difficulties involved in defining the vertical integral interval. From an ecological viewpoint, the ∑Chl should be integrated within the euphotic zone (

\sum C h l_{Z_{e}}

). The euphotic zone is defined as the depth interval from the surface to the euphotic depth (Z_e), at which the downward irradiance of photosynthetic active radiation (PAR) is 1% of the surface value. However, the widely used radiometric measurement of Z_e can only be carried out during daytime. Research cruises generally operate on 24-h schedules and Z_e data cannot be collected at night-time stations, resulting in poor spatial coverage of the Z_e dataset. Although some of the missing Z_e data can be interpolated geo-statistically using data from other stations, the accuracy of such interpolation tends to be poor, first, because the geometrical relationship between the actual and interpolated Z_e data is not ideal, and second, because there can be a large variation in Z_e between neighboring stations associated with changes in water masses.

Gong et al. (1996) investigated ∑Chl in the upper 50 m of the water column, and found a very high phytoplankton biomass in the region of the CDW. Kim et al. (2009) investigated ∑Chl from the surface to the sea floor, or to 100 m if the depth was more than 100 m (∑Chl_Total), and found that ∑Chl varied little among different water masses, including CDW.

Both of the depth-integration methods described above have some inherent problems. First, ∑Chl_Total may include Chl-a present below the Z_e, which may not be actively involved in primary production. Second, especially when the depth from the surface to the sea floor is used as the integral interval, high concentrations of suspended non-algal particles near the sea floor may lead to significant errors in the in situ optical measurements of Chl-a (Omand et al., 2009). Suspended non-algal particles are present as a result of strong tidal flows and turbulence on the shallow continental shelf of the ECS (Matsuno et al., 2006). This problem may be addressed by using a specified water depth instead of the sea floor as one edge of the integral interval, but there is still uncertainty in estimating living phytoplankton biomass if the actual Z_e varies widely across the specified depth.

If the waters of the ECS are classified as Case I water, in which internal optical properties are well parameterized by the concentration of Chl-a as an optically active compound (OAC), some existing empirical or theoretical models for the diffuse attenuation coefficient of PAR (K_d; m⁻¹) (Morel, 1988, Platt and Sathyendranath, 1988, Morel and Maritorena, 2001) could be used to predict the mean K_d within the euphotic zone (

K_{d, (0 \to Z_{e})}

) in the ECS. Consequently, the Z_e (m) could be calculated based on the assumption of a natural logarithmic relationship between Z_e and

K_{d, (0 \to Z_{e})}

(Eq. (1); (Kirk, 1994)

K_{d, (0 \to Z_{e})} = - \frac{1}{Z_{e}} \ln 0.01

However, the surface waters of the ECS have been categorized as Case II water, with high levels of river-borne colored dissolved organic matter (CDOM) and sometimes suspended silt particles (Gong, 2004, Siswanto et al., 2011). Unlike the K_d estimation model for Case I water, the model for Case II water is still under development because of its optical complexity (Morel et al., 2006, Odermatt et al., 2012). However, Devlin et al. (2009) successfully explained the variation in K_d from coastal to offshore waters around the United Kingdom (probably Case II water) using a simple linear equation.

K_{d} = k_{w}^{*} + k_{CD}^{*} \cdot CDOM + k_{PH}^{*} \cdot chloro + k_{SP}^{*} \cdot SPM

where CDOM, chloro, and SPM are concentrations of CDOM, phytoplankton, and suspended particulate matter, respectively, as representative OACs, the parameter

k_{w}^{*}

is the partial attenuation coefficient of water, and

k_{CD}^{*}

,

k_{PH}^{*}

, and

k_{SP}^{*}

are specific attenuation coefficients per unit concentrations of CDOM, chloro, and SPM, respectively. Regression analysis between K_d and concentrations of these OACs generated fitting parameters that provided a good empirical explanation of the variation in K_d in that study (Devlin et al., 2009). It should be noted that Eq. (2) may only have physical meaning when the four attenuation effects are independent and additive, and this is unlikely, even in Case I water. Therefore, the fitting parameters used by Devlin et al. (2009) to estimate K_d may only work empirically and for water masses similar to where the survey data were obtained. Nevertheless, the application of a similar protocol was expected to produce practical fitting parameters to explain the variation in K_d in the ECS. Appropriate fitting parameters could be used to estimate

K_{d, (0 \to Z_{e})}

and Z_e for night-time stations based on vertical measurements of OACs and Eq. (1). It is important to note that the Z_e calculated for night-time stations should be considered as a potential value based on the assumption that the same water column is exposed to the mean incident light conditions during daytime observation.

The primary objective of the present study was to determine whether the Changjiang River plume, extending towards the east of the ECS shelf, influences phytoplankton biomass in the euphotic zone. Data were collected in June 2007 during a research cruise over the eastern shelf and the adjacent outer shelf area of the ECS. Using a similar method to that described by Devlin et al. (2009), a practical protocol was developed to calculate Z_e at night-time stations. This improved the spatial coverage of the Z_e dataset and enabled evaluation of the spatial distribution of

\sum C h l_{Z_{e}}

over the entire research area. Although CDW (with a salinity of <31) barely extended into the research area, the phytoplankton biomass within the euphotic zone was significantly higher in an area of the shelf with a low salinity surface water mass (LSSW; salinity range 31.99–32.24). This water mass was probably part of the Yellow Sea Mixed Water but was clearly influenced by the Changjiang River plume. This paper presents the results of the analysis of the relationship between water masses in the ECS and the

\sum C h l_{Z_{e}}

, describes the protocol used to estimate the Z_e, and discusses the impact of the Changjiang River plume on the phytoplankton biomass on the eastern shelf of the ECS.

Section snippets

Study area

Data were collected in June 2007 during a research cruise on the R/V Shoyo Maru (Fisheries Agency of Japan). There were 50 observation stations, including 25 on the eastern continental shelf of the ECS (stations #13 to #37 located between 123.75° and 126.75°E and 29.5°–31.75°N with water depths of 50–100 m). The remaining stations were outside the shelf (stations #1 to #12, and #38 to #50; Fig. 1).

Previous studies (Su and Weng, 1994, Gong et al., 1996, Chang and Isobe, 2003) have suggested that

Classification of surface water masses

A low salinity water mass was identified at a depth of 10 m in the northwestern part of the research area (stations #20, #33, #19, #31, #35, #14, and #15; salinity 32.1–32.6; Fig. 2a and b). The low salinity, the geographical distribution, and previous knowledge of the possible movement of the Changjiang River plume (see Section 2.1) suggest that this water mass was highly influenced by CDW. Conversely, the salinity at 0 m at the same stations ranged from 31.99 to 32.24, which was higher than

Major findings

Simple comparison of

\sum C h l_{Z_{e}, m e a s .}

among water masses showed that the highest

\sum C h l_{Z_{e}}

was in the LSSW (91.7 ± 37.6 mg m⁻²; Table 2). However, it was not possible to make a quantitative conclusion from this result because

\sum C h l_{Z_{e}, m e a s .}

was only available for three stations in the LSSW area, including the outlying data from station #31 (131.8 mg m⁻²; Fig. 4b). Furthermore,

\sum C h l_{Z_{e}, m e a s .}

was available for a limited number of stations in other water masses (Fig. 4b; see also Fig. 1 which shows stations

Conclusions

The spatial variation in

\sum C h l_{Z_{e}}

in the ECS in June 2007 was statistically evaluated using vertical measurements of Chl-a concentration and the measured or calculated Z_e, which was derived from the newly developed empirical equation for

K_{d, (0 \to Z_{e})}

. The

\sum C h l_{Z_{e}}

dataset, with improved spatial coverage, showed that the highest

\sum C h l_{Z_{e}}

was in the LSSW, a water mass with relatively low surface salinity and a highly stratified water structure and Chl-a maximum at subsurface depths. The salinity in the

Acknowledgments

The authors would like to thank the captain and crew of the R/V Shoyo Maru for assistance with the collection of field data. Special thanks also to M.S. Mitsuru Muramatsu, B.S. Yuko Kumagai, and M.S. Yukiko Okada for assistance with the sample collection and analyses on board and in the laboratory. Dr. Hideki Akiyama, Dr. Yasuo Nakamura, and Dr. Akio Imai provided insightful comments and encouragement. We are grateful to the anonymous reviewers and the editor for helpful suggestions and

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View full text

Assessing depth-integrated phytoplankton biomass in the East China Sea using a unique empirical protocol to estimate euphotic depth

Highlights

Abstract

Graphical abstract

Introduction

Section snippets

Study area

Classification of surface water masses

Major findings

Conclusions

Acknowledgments

Cont. Shelf Res.

Cont. Shelf Res.

Estuar. Coast. Shelf Sci.

Cont. Shelf Res.

Deep-Sea Res. Part Ii-Topical Stud. Oceanogr.

Cont. Shelf Res.

Deep-Sea Res. Part Oceanogr. Res. Pap.

Remote Sens. Environ.

Prog. Oceanogr.

Quasi-inherent characteristics of the diffuse attenuation coefficient for irradiance

SPIE

Variations of light absorption by suspended particles with chlorophyll a concentration in oceanic (case 1) waters: analysis and implications for bio-optical models

J. Geophys. Res. Oceans

The status and characteristics of eutrophication in the Yangtze River (Changjiang) estuary and the adjacent East China Sea, China

Hydrobiologia

A numerical study on the Changjiang diluted water in the Yellow and East China Seas

J. Geophys. Res. Oceans

Physical-biological sources for dense algal blooms near the Changjiang River

Geophys. Res. Lett.

Absorption coefficients of colored dissolved organic matter in the surface waters of the East China Sea

Terr. Atmos. Ocean. Sci.

Some striking features of circulation in Huanghai sea and East China sea

Influence of hydrographic conditions on picoplankton distribution in the East China Sea

Aquat. Microb. Ecol.