Influence of river discharge on phytoplankton absorption properties : a case study in the East China Sea and Tsushima Strait

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concentration (Tchl a), a * ph (λ), of these samples was substantially higher than values derived from global regressions between a * ph (λ) and the Tchl a.Using the pigment data derived from HPLC, the increase of a * ph (λ) was found to be mainly caused by the phytoplankton size structure, which indicated that both surface and SCM samples in the ECS still incorporated considerable portions of picophytoplankton (cyanobacteria), even though the Tchl a was high.When water from the surface and the SCM were merged, variations in the phytoplankton size-fractions and a * ph (λ) vs. Tchl a that were consistent with values for the global ocean were found in the TS but not in the ECS.Data for the ECS indicated that there was no correlation between Tchl a and the sizefraction or total pigment absorption.As a consequence, a * ph (λ) was poorly correlated with Tchl a and displayed large variability within a small Tchl a range.These findings suggest the need for care when considering the changing patterns of size-fractions vs. Tchl a and the relationship between a * ph (λ) and Tchl a in coastal regions that are significantly influenced by fresh water.

Introduction
Phytoplankton light absorption is a major factor in determining the optical properties of oceanic and coastal waters.The process has the potential to change the underwater light fields, modulate photosynthesis, and alter the ocean colour (Gordon et al., 1988;Morel, 1988).Knowledge of phytoplankton light absorption and its variation is vital for understanding the optical variability of water bodies, and therefore improving a variety of bio-optical algorithms, such as for remote sensing of chlorophyll a concentration (Chl a) (Garver and Siegel, 1997;He et al., 2000), primary production (Platt and Sathyendranath, 1988;Ishizaka, 1998), and phytoplankton size classes (Ciotti and Bricaud, 2006;Hirata et al., 2008;Devred et al., 2011).
In recent decades, phytoplankton light absorption has been extensively investigated in various regions of the world.It is well documented that the phytoplankton absorption coefficient, a ph (λ), is positively correlated with Chl a and that this correlation holds fairly well for various water bodies (Cleveland, 1995;Babin et al., 2003;Bricaud et al., 2004).The Chl a-specific absorption coefficient, a * ph (λ), is defined as the ratio of a ph (λ) to Chl a, and its temporal/spatial variations have been reported for various water bodies (Babin et al., 1993;Bricaud et al., 1995;Suzuki et al., 1998;Harimoto et al., 1999;Staehr et al., 2004).The general tendency is that a * ph (λ) decreases with an increase in Chl a, and Bricaud et al. (1995) found that both horizontal and vertical covariations of a * ph (λ) and Chl a followed similar trends.The packaging effect and pigment composition are suggested to be the major factors causing the variability in a * ph (λ) (Morel and Bricaud, 1981;Stuart et al., 1998;Lohrenz et al., 2003).These two factors are different among and within phytoplankton populations growing under various environmental conditions (e.g., nutrient levels, irradiance).
Large phytoplankton generates a strong packaging effect, producing low a * ph (λ), while the packaging effect of small phytoplankton is less and results in high a Figures as the sum of absorption by two populations with a distinct cell size, and this model was further extended to a three population model by Brewin et al. (2011).More recently, absorption models based on two or three population sizes have been improved to estimate the a * ph (λ) of different populations as well as to derive phytoplankton sizefractions from the a ph (λ) (Devred et al., 2006(Devred et al., , 2011)).Note that these models are based on the hypothesis that small and large cells dominate in low and high Chl a waters, respectively, which has been clearly observed in the global ocean (Brewin et al., 2010;Hirata et al., 2011).
However, in coastal waters it is not known whether this hypothesis is valid.Because of the dynamic hydrographic conditions in coastal regions (e.g., discharge, upwelling, and mixing), the optical properties of water are complex (Babin et al., 2003).Some studies have shown that freshwater discharges could significantly change the optical properties of seawater, especially the light absorption budget among phytoplankton, detritus, and colored dissolved organic matter (Babin et al., 2003;Matsuoka et al., 2011;Brunelle et al., 2012).However, freshwater effects, specifically on the phytoplankton absorption properties, such as the variability in a * ph (λ) and the correlations between Chl a with a ph (λ) and a * ph (λ), have not been well examined.The East China Sea (ECS), the largest marginal sea in the western North Pacific, is significantly influenced by river discharge from the Changjiang (Gong et al., 1996).In summer, the ECS receives enormous amounts of fresh water containing very high concentrations of nitrogen (Gong et al., 1996;Siswanto et al., 2008).The nutrient-rich fresh water mixes with the surrounding high-salinity waters forming Changjiang diluted water (CDW), which extends offshore and moves north-eastward near Jeju Island to the Tsushima Strait (TS) (Yamaguchi et al., 2012).It has been suggested that the CDW enhances Chl a, resulting in high primary production in the upper layer of the ECS (Hama et al., 1997;Yamaguchi et al., 2012).The phytoplankton community has also been reported to be modulated by Changjiang fresh water in the estuary and adjacent coastal waters (Zhou et al., 2008).Therefore, Changjiang fresh water is likely Introduction

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Full to have an influence on phytoplankton light absorption in the ECS, especially in the surface layer.
The TS, which is a narrow and shallow strait between Korea and Japan, connects the ECS and the Sea of Japan.Water in the TS originates partly from the Kuroshio but mainly from the ECS in summer (Guo et al., 2006).Fresh water and nutrients are transported from the ECS through the TS to the Sea of Japan (Isobe et al., 2002;Morimoto et al., 2009).Yamaguchi et al. (2012) observed that about two months was required for the CDW to reach the TS, where the enhancement in surface Chl a was very small with a slight peak in September.Morimoto et al. (2009) suggested that when the CDW extended into the TS, nutrients were consumed by phytoplankton and depleted.These studies imply that the influence of Changjiang fresh water on phytoplankton in the TS may be weak.
In this study, considering the strong influence of Changjiang fresh water on the ECS in summer, we hypothesize that the phytoplankton absorption properties in the ECS may be different from those in the TS.The objective of this study was to test this hypothesis on the basis of phytoplankton light absorption and pigment data derived from high-performance liquid chromatography (HPLC).For this purpose, (1) differences in the phytoplankton light absorption between the ECS and TS were characterized at both the surface and subsurface Chl a maximum (SCM).The vertical variations in phytoplankton absorption (differences between the surface and SCM) were also compared between the ECS and TS.(2) Correlations between total Chl a (Tchl a) with a ph (λ) and a * ph (λ) in all samples from the surface and SCM were investigated in both the ECS and TS.To completely understand these differences in phytoplankton light absorption between the ECS and TS, the size structure derived from HPLC pigment data, the packaging effect, and pigment composition were studied.Introduction

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Sampling
Sampling in the TS was conducted during a cruise in July 2008 aboard the T/V Nagasaki maru.Four cruises were conducted in the ECS in August 2008 and July 2009-2011 aboard the R/V Tansei maru and the T/V Nagasaki maru, respectively (Table 1).
The locations of sampling stations are shown in Fig. 1.Water samples at discrete depths were collected using Niskin bottles (12 L on the R/V Tansei maru; 5 L on the T/V Nagasaki maru) mounted on a CTD/rosette system.According to the fluorescence profile, the sampling depth of the SCM was determined from its prominent biological features.Samples collected at the surface and SCM were used to measure a ph (λ) and pigment concentrations.

Measurement of absorption coefficient
The quantitative filter technique (QFT) was used to determine a ph (λ) (Mitchell, 1990).Water samples were filtered through Whatman GF/F glass fibre filters (25 mm) under low vacuum pressure (< 0.01 MPa).Subsequently, the optical density of particles retained on the filter (OD f (λ)) was measured between 350 and 750 nm at 1 nm intervals, using a dual beam multi-purpose spectrophotometer (MPS-2400, Shimadzu Inc.).
A blank filter soaked with 0.2-µm-filtered seawater (FSW) was used as the reference.
The OD f (750) was subtracted from all wavelengths to minimize the difference between the sample and reference filter, assuming no absorption at 750 nm.To correct for the path length amplification effect caused by multiple scattering in the glass-fibre filter, the following equation was utilized according to Cleveland and Weidemann (1993): (1) Introduction

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Full where OD s (λ) is the optical density of particulate matter in suspension.The absorption coefficient of the particulate matter (a p (λ)) was calculated using the following equation: where 2.303 is the factor used to convert log 10 to log e , S is the filter clearance area (m 2 ), and V is the filtered volume (m 3 ).The ratio of S to V stands for the geometrical light pass length.
After measurements of the optical density of the particulate matter, the filters were soaked in methanol for at least 24 h to extract phytoplankton pigments, and then rinsed with FSW.The absorbance of a decolorized filter was re-measured using the same method to obtain the optical density of the non-phytoplankton particles (Kishino et al., 1985).Similarly, the absorption coefficient of non-phytoplankton particles (a d (λ)) was determined using Eqs.( 1) and ( 2).The a ph (λ) was then obtained from the following equation: The reported values in this study are averages from duplicated measurements.The a * ph (λ) was calculated by standardizing a ph (λ) by the Tchl a measured by HPLC.Tchl a refers to the sum of Chl a, chlorophyllide a, and divinyl Chl a.

Pigment measurements and pigment-based size structure
Water samples used for the measurement of pigment concentrations were filtered onto 25 mm Whatman GF/F glass fibre filters under low vacuum pressure (< 0.01 MPa).
The filtered volumes of most of samples were 1 L. The filters were immediately frozen in liquid nitrogen, and were then stored in a −80 • C freezer on shore for later laboratory analysis.Pigments were analyzed by reverse-phase HPLC with a Zorbax Eclipse XDB-C8 column (150 mm × 4.6 mm, 3.5 µm; Agilent Technologies), and 19 pigments were separated and quantified following the method of Van Heukelem and Thomas (2001).Introduction

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Full Diagnostic pigment analysis (DPA) was then used to estimate the Tchl a fractions of pico-(< 2 µm), nano-(2-20 µm) and micro-phytoplankton (> 20 µm), from HPLC pigment data.The DPA approach was originally proposed by Vidussi et al. (2001), and refined by Uitz et al. (2006).Briefly, seven marker pigments (MP) (i.e., fucoxanthin (Fuco), peridinin (Per), 19 -hexanoyloxyfucoxanthin (Hex), 19 -butanoyloxyfucoxanthin (But), alloxanthin (Allo), chlorophyll b (Chl b), and zeaxanthin (Zea)) were selected as being representative of distinct phytoplankton groups and were used to calculate the Tchl a fractions of three size classes (detailed pigment taxonomic significance reported previously by Vidussi et al., 2001 andUitz et al., 2006).Subsequently, Hirata et al. (2008) further revised the approach of Uitz et al. (2006) to account for the occurrence of Chl b in larger eukaryotes, e.g., chlorophytes (nano-phytoplankton).According to Hirata et al. (2008), the size-fractions of each size class can be expressed as The numerical coefficients used in the above equations, which were derived by multiple regressions (Uitz et al., 2006), represent the ratios of Tchl a to each diagnostic pigment.Hirata et al. (2008) suggested that a particular phytoplankton size class was dominant if its fraction was greater than 0.45.It should be noted that there are some potential anomalies in DPA, e.g., in some cases, a given diagnostic pigment possibly occurs in two size classes.Despite these potential limitations, DPA is a useful approximation, and the results are reasonably robust at a global as well as at a regional scale.Introduction

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Packaging effect index and total pigment absorption
The packaging effect index, Q * a (λ), is defined as the ratio of the in vivo absorption coefficient (a ph (λ)) to the absorption coefficient of the same cellular material in solvent condition (a sol (λ)) (Bricaud et al., 2004).The computation is expressed as follows: The theoretical maximum and minimum values of Q * a (λ) are 1 and 0, corresponding to conditions without a packaging effect and with the maximal packaging effect, respectively.Bricaud et al. (2004) stated that the a sol (λ) reconstructed from all individual pigments was systematically lower than the measured a ph (λ) and argued that differences between measured and reconstructed absorption spectra could be attributed to missing pigments or other light-absorbing compounds extracted by methanol but not measured by HPLC.Considering the missing absorption term, a sol (λ) is calculated as where C i and a * pigm,i (λ) are the concentration and the pigment-specific absorption coefficient of the ith pigment, respectively, and a miss (λ) is the missing absorption.In this study, a miss (440) was estimated according to Bricaud et al. (2004), and then Q * a (440) was calculated.
The total pigment-specific absorption coefficient is defined as the Tchl a normalized absorption coefficient of all the pigments (Bricaud et al., 2004), as in Eq. ( 10): approach used to obtain a * pigm (λ) was completely independent of a * ph (λ), whereas the approach used for Q * a (λ) depended on a * ph (λ).In addition, the analyses performed in this study mainly focused on the 440 nm region because the effects of both pigment packaging and composition are more pronounced in the blue region (Stuart et al., 1998).

Variations in Tchl a
Tchl a in water from the Tsushima Strait surface (TS_S), the Tsushima Strait SCM (TS_SCM), the East China Sea surface (ECS_S), and the East China Sea SCM (ECS_SCM) displayed clear differences (Table 2).The average Tchl a in the TS_S was lower than that in the ECS_S, and the average Tchl a in the TS_SCM was also lower than in the ECS_SCM.The difference between the average Tchl a values in the ECS_S and the ECS_SCM was larger than the difference between the corresponding values in the TS_S and TS_SCM.The coefficient of variation of Tchl a was similar among the TS_SCM, ECS_S, and ECS_SCM, and was lowest for the TS_S.

Variations of absorption coefficient
The average a ph (λ) values in the TS_S, TS_SCM, ECS_S, and ECS_SCM clearly differed (Fig. 2a and Table 2).The average a ph (λ) was lowest in the TS_S and much higher in the ECS_S.The average a ph (λ) in the TS_SCM was also much lower than in the ECS_SCM.The difference in average a ph (λ) between the surface and SCM was larger in the ECS than in the TS.The coefficients of variation of a ph (440) and a ph (675) of the ECS_S were the highest with values of 69.7 % and 73.7 %, respectively, and those of TS_S were the lowest with values of 27.9 % and 25.2 %, respectively.However, the coefficients of variation of a ph (440) and a ph (675) were similar for the TS_SCM Introduction

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Full and ECS_SCM.The different characteristics of a ph (λ) in each area generally corresponded to the variations in Tchl a.
As in previous studies (Bricaud et al., 1995(Bricaud et al., , 2004)), the a ph (440) and a ph (675) were positively correlated with the Tchl a in the TS and ECS (Fig. 3a and b).Here, a ph (λ) in the surface and SCM waters were combined for analysis.The fitted power law functions were as follows.For the TS, and for the ECS, where R 2 and N are the determination coefficients and the number of samples, respectively.The power law functions for the TS agreed well with those given by Bricaud et al. (1995), whereas most of the ECS samples significantly diverged from the regressions of Bricaud et al. (1995) (Kolmogorov-Smirnov test, P < 0.01), especially at high Tchl a.In comparison to a ph (675), a ph (440) was more scattered, with the differences caused by the absorption of accessory pigments as discussed later (Bricaud et al., 1995;Stuart et al., 1998).

Variations of Tchl a-specific absorption coefficient
Large variations were observed among values of the a * ph (λ) from all the samples (Table 2).The a * ph (440) and a * ph (675) ranged from 0.017 to 0.158 m 2 mg −1 (average and standard deviation of 0.068 ± 0.023 m 2 mg −1 ) and from 0.008 to 0.055 m 2 mg −1 (average and standard deviation of 0.026 ± 0.007 m 2 mg −1 ), respectively.The coefficients of Introduction

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The average a * ph (λ) in the TS_S, TS_SCM, ECS_S, and ECS_SCM displayed distinct differences in both their magnitude and spectrum shape (Fig. 2c and Table 2).The largest differences were observed in the magnitude of absorption in the blue wavelength.The highest average a * ph (λ) in the blue region was observed in the TS_S, and the lowest average a * ph (λ) at most wavelengths and the flattest spectral shape was observed in the TS_SCM.The average a * ph (λ) in the ECS_S and ECS_SCM lay between the average values in the TS_S and TS_SCM, and the average a * ph (λ) in the ECS_S was higher than the value in the ECS_SCM.The standard deviation of a * ph (440) indicated high variances in the TS_S and ECS_S, lower variances in the ECS_SCM, and the lowest variance in the TS_SCM.In addition, the a * ph (λ) in the TS_S and ECS_S had distinct peaks around 490 nm, probably owing to the presence of the photoprotective pigment zeaxanthin (Barlow et al., 2002).A significant positive correlation between a ph (490) and the zeaxanthin concentration (P < 0.01, R 2 = 0.751) was observed in those samples (data not shown).The a * ph (λ) of most samples from the ECS_SCM exhibited a clear peak around 540 nm, which possibly resulted from the absorption of phycoerythrin (Hoge et al., 1999;Ciotti et al., 2002).
The variations in a * ph (440) and a * ph (675) were different between the TS and ECS.Negative power correlations of Tchl a with a * ph (440) (P < 0.01, R 2 = 0.708) (Fig. 3c) and with a * ph (675) (P < 0.01, R 2 = 0.287) were recorded in the TS (Fig. 3d).The fitted power law functions for the TS were close to those obtained by Bricaud et al. (1995) in the global ocean.However, in the ECS, the power correlation between a * ph (440) and Tchl a was poor (P < 0.01, R 2 = 0.094) and there was also no significant power correlation between a * ph (675) and Tchl a (P = 0.84, R 2 = 0.000).Introduction

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Full The salinity clearly differed between the TS_S and ECS_S (Fig. 3).The salinity in TS_S was higher than 32 (average of 32.5).However, the salinity of most of the ECS_S samples (60 out of 67) was lower than 32 (average of 29.9).All the TS_SCM samples were taken from waters beneath the TS_S high-salinity water.Most of the ECS_SCM samples (45 out of 51) were collected beneath the ECS_S low-salinity water.Even at the SCM, the local salinity was also lower in the ECS than in the TS, with average values of 31.8 and 34.0, respectively (data not shown).From Fig. 3c and d, it was also found that the a * ph (440) and a * ph (675) of high salinity water samples from the TS and ECS were clustered around the regression lines of Bricaud et al. (1995).However, most of samples from the ECS_S low salinity water (< 32) and the corresponding ECS_SCM samples taken from waters beneath them displayed higher a * ph (440) and a * ph (675) comparing with values from the regressions of Bricaud et al. (1995).

Variations in the packaging effect
The Q * a (440) showed very similar variations to those observed for the a * ph (440) (Fig. 4a).The determination coefficients (R 2 ) of a linear regression between a * ph (440) and Q * a (440) were 0.869, 0.978, and 0.843 for all locations, the TS, and the ECS, respectively.In general, the average Q * a (440) in the TS_S, TS_SCM, ECS_S, and ECS_SCM were consistent with the average a * ph (440) in these regions.The highest and lowest average Q * a (440), with values of 0.72 ± 0.17 and 0.40 ± 0.11, were recorded in the TS_S and TS_SCM, respectively, and the average Q * a (440) in the ECS_S and ECS_SCM were 0.64 ± 0.19 and 0.61 ± 0.16, respectively.The variations in the Q * a (440) vs. Tchl a relationship were also clearly different between the TS and ECS (Fig. 4a).The Q * a (440) of surface and SCM waters from the TS were inversely correlated with Tchl a (P < 0.01, R 2 = 0.704), but such a correlation was not observed in the ECS (P = 0.27, R 2 = 0.011).These differences were consistent with those of the a * ph (440) vs. Tchl a relationship in the TS and ECS (Fig. 3c).Introduction

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Full In this study, phytoplankton cell size was not measured directly, relationships between Q * a (440) and the size-fractions of micro-, nano-, and pico-phytoplankton for all samples were investigated to assess the effects of cell size on Q * a (440) (Fig. 4b-d).

Variations in phytoplankton size classes estimated from pigments identified by HPLC
The size structure of algal populations was clearly different among samples from the TS_S, TS_SCM, ECS_S, and ECS_SCM (Fig. 5 and Table 3).The most oligotrophic waters from the TS_S were characterized by a high fraction of pico-phytoplankton (average of 0.54) and low fractions both for micro-(average of 0.14) and nanophytoplankton (average of 0.32).However, the pico-phytoplankton fractions of TS_SCM were extremely low, with a range from 0.00 to 0.13, while micro-(range: 0.23-0.85)and nano-phytoplankton (range: 0.14-0.72)had high average fractions of 0.58 and 0.39, respectively.The ECS_S contained mixed populations, and the fractions of micro-, nano-, and pico-phytoplankton ranged from 0.00-0.75(average of 0.26), from 0.13-0.73(average of 0.39), and from 0.05-0.84(average of 0.34), respectively.Most of the samples from the ECS_SCM contained an abundance of nano-phytoplankton (average fraction of 0.50), while fraction of pico-phytoplankton was also considerable (range: 0.02-0.51,average value of 0.19).Interpreting HPLC pigment data, those pico-phytoplankton in the ECS_S and ECS_SCM might be cyanobacteria.
The variations in the phytoplankton size-fractions as a function of Tchl a were also different in the TS and ECS (Fig. 6).Size-fractions in the TS displayed a clear rela-Introduction

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Full tionship with Tchl a (Fig. 6a).The micro-phytoplankton fraction increased as the Tchl a increased, and they became the dominant algal population (> 0.45) when Tchl a levels were around 0.90 mg m −3 .The pico-phytoplankton fraction decreased with an increase in Tchl a, with a steep decrease at Tchl a levels of around 0.58 mg m −3 , and becoming very low (< 0.05) at Tchl a levels greater than 0.80 mg m −3 .Nano-phytoplankton were abundant at medium Tchl a levels, with a maximum fraction of 0.54 at Tchl a levels around 0.78 mg m −3 .However, these relationships between the size-fraction and Tchl a were not observed in the ECS (Fig. 6b).

Variations in phytoplankton pigment composition
Accessory pigments were classified into four groups (Bricaud et al., 2004) ments were then normalized by Tchl a (Fig. 7).The ratio of PPC to Tchl a was higher in surface waters than in SCM waters in both the TS and ECS.The ratio of PSC to Tchl a had a relatively uniform distribution between the surface and SCM waters in the ECS but there was a large difference in the TS, and the ratio in the TS_S was relatively higher than in the ECS_S.The distribution of Tchl b/Tchl a ratios displayed no clear characteristics.The Tchl c/Tchl a ratio in the TS_S was almost 0, while in the ECS_S it was similar to in the ECS_SCM.The Tchl c/Tchl a ratios in the TS_SCM were higher than in the ECS_SCM.The diversity of pigment composition caused small but significant variations in the a * pigm (440) (Fig. 8).The linear regression analysis between a * ph (440) and a * pigm (440) in all samples indicated that 35.1 % of the variation in a * ph (440) could be explained by a * pigm (440) (Fig. 8a).The corresponding contributions for TS and ECS were 45.7 % and Introduction

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Full 39.1 %, respectively.In addition, a * pigm (440) had a weak power correlation with Tchl a (P = 0.02, R 2 = 0.218) in the TS, and a very poor correlation in the ECS (P = 0.04, R 2 = 0.037) (Fig. 8b).The variability in a * pigm (675) was smaller than that in a * pigm (440) (data not shown).A linear regression analysis between a * ph (675) and a * pigm (675) revealed that the pigment composition was responsible for only 13.2 % of the variation in a * ph (675), which confirmed that the main variation of a * ph (λ) originated from the packaging effect.The larger contribution of a * pigm (440) to the variation of a * ph (440) than a * ph (675) explained why a ph (440) vs. Tchl a was more scattered than a ph (675) vs. Tchl a (Fig. 3a and b).

General factors influencing phytoplankton light absorption
The packaging effect and pigment composition are the two main causes of the variations in a * ph (λ) (Morel and Bricaud, 1981;Bricaud et al., 1995).Of the two factors, the packaging effect is considered to be the dominant cause of variability in a * ph (λ) (Morel and Bricaud, 1981;Stuart et al., 1998).This was confirmed in the present study by the high correlation between a * ph (440) and Q * a (440) in all samples.Linear regression analyses between a * pigm (λ) and a * ph (λ) at both 440 nm and 675 nm also indicated the dominance of the packaging effect in causing variability in a * ph (λ) (Fig. 8a).These results agree with those of Stuart et al. (1998) who also used a multiple regression analysis between a * ph (440) and the concentrations of all the major pigments normalized to Introduction

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Full Chl a, and suggested that 58 % to 71 % of variability in a * ph (440) could be explained by the packaging effect.
In turn, phytoplankton cell size is considered to have a key role in the determination of the packaging effect (Morel and Bricaud, 1981;Ciotti et al., 2002;Zhang et al., 2012).It is well known that large phytoplankton produce a strong packaging effect, which results in low a * ph (λ), while the a * ph (λ) of small phytoplankton is high because of the lower packaging effect (Stuart et al., 1998;Babin et al., 2003).Ciotti et al. (2002) stated that differences in the phytoplankton cell size were responsible for more than 80 % of the variability in the absorption spectrum.Bricaud et al. (2004) also reported that change in the phytoplankton size structure was the main factor leading to variations in a * ph (λ) through the packaging effect.Costa Goela et al. ( 2013) stated that the packaging effect could be evaluated by the a ph (440)/a ph (678) ratio, and found that this ratio was negatively correlated with the micro-phytoplankton fraction and positively correlated with the nano-and pico-phytoplankton fractions.In this study, the relationships between Q * a ( 440) and the phytoplankton size-fractions estimated from HPLC pigment data for all samples indicated that the packaging effect increased and decreased when microand pico-phytoplankton become abundant, respectively (Fig. 4b-d), which is consistent with the results of Costa Goela et al. (2013).
Note that the intracellular pigment concentration, which usually changes with light conditions due to photo-acclimation, also affects the a * ph (λ) through the packaging effect in the same way as cell size (Morel and Bricaud, 1981).Lohrenz et al. (2003) reported that the packaging effect clearly operated even when the cell size was smaller than 3 µm in SCM samples from west Florida.Babin et al. (2003) also suggested that the a * ph (λ) was relatively low in deep waters, despite small cell size, because of the high intracellular pigment concentration, which generated some packaging effect.The dataset collected in this study incorporated SCM samples from the TS and ECS, which might both possess high intracellular pigment concentrations as an adaption to the low irradiance conditions.Even in surface waters, the intracellular pigment concentration is variable due to changes in light conditions (Bricaud et al., 2004).Therefore, although Introduction

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Full phytoplankton cell size seems a key factor controlling the a * ph (λ) through the packaging effect in our study, the intracellular pigment concentration may be another factor causing variations in a * ph (λ), especially between the surface and SCM.

Differences of phytoplankton absorption and its influencing factors between the ECS and TS
Our results revealed a clear difference in salinity and the phytoplankton bio-optical properties between the ECS_S and TS_S.The low salinity (< 32) in the ECS_S and the relatively high salinity (> 32) in the TS_S confirmed the strong and weak influence of Changjiang fresh water on the ECS_S and TS_S, respectively (Fig. 3).The lowsalinity waters of the ECS_S indicate that there is a higher Tchl a than in the TS_S (Table 2), which agrees with the results of Yamaguchi et al. ( 2012) who suggested that the CDW could enhance Chl a in the ECS_S.As a consequence, a higher a ph (λ) was observed in the ECS_S than in the TS_S (Figs. 2 and 3).However, the a * ph (λ) in the ECS_S was lower on average than in the TS_S (Figs. 2 and 3).Comparisons of the packaging effect and a * pigm (440) indicated a slightly lower Q * a (440) in the ECS_S than in the TS_S and a similar a * pigm (440) between the ECS_S and TS_S (Figs. 4a and  8).These results suggest that the difference in a * ph (λ) between the ECS_S and TS_S may be primarily caused by the packaging effect.The phytoplankton size structure revealed that the stronger packaging effect in the ECS_S may be caused by increase of large phytoplankton (Figs. 5 and 6).It should be noted that though the a * ph (λ) was generally lower in the ECS_S than in the TS_S, the majority of low-salinity water in the ECS_S had much higher values than those produced by the regressions of Bricaud et al. (1995) (Fig. 3).From Fig. 6b, it can be seen that pico-phytoplankton which might be cyanobacteria were still abundant in the ECS_S, even though Tchl a was high.This result contradicts previous studies, which have indicated that small and large cells are abundant in low-and high-Chl a waters, respectively (Brewin et al., 2010;Hirata et al.,

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Full ).The abundance of pico-phytoplankton in the ECS_S may result in a higher a * ph (λ) than the values from the regressions of Bricaud et al. (1995).
The ECS_SCM also differed from TS_SCM.Most ECS_SCM samples were taken from waters beneath the CDW, and these samples also had a lower local salinity than those taken from the TS_SCM, implying that ECS_SCM was to some extent influenced by the CDW.The average Tchl a of the ECS_SCM was nearly twice as high as that of the TS_SCM, and the average a ph (λ) of the ECS_SCM was almost three times larger than that of the TS_SCM (Table 2).As a result, the a * ph (λ) was much higher in the ECS_SCM than in the TS_SCM.By comparing the packaging effect (cell size) and a * pigm (440), we found that the packaging effect (cell size) was the main cause for the differences in a * ph (λ) between the ECS_SCM and TS_SCM (Figs. 4a and 8).The ECS_SCM was generally characterized by an abundance of large phytoplankton, while pico-phytoplankton which might be cyanobacteria still composed considerable fractions (Figs. 5 and 6).However, the high-salinity waters in the TS_SCM indicated a low abundance of pico-phytoplankton, with large phytoplankton being dominant.Finally, the small cells might generate a higher a * ph (λ) in the ECS_SCM than in the TS_SCM.In addition, as with the ECS_S, the a * ph (λ) in the ECS_SCM was also higher than the values produced by the regression of Bricaud et al. (1995) (Fig. 3), which might be because of the relatively abundant pico-phytoplankton.These findings indicate that the ECS_SCM was also influenced by the CDW, and this influence was reflected by the considerable pico-phytoplankton and relatively high a * ph (λ) in the ECS_SCM.A clear difference was found in a * ph (λ) between the TS_S and TS_SCM, but no such difference was obvious between the ECS_S and ECS_SCM (Figs. 2 and 3).The difference in the packaging effect between the TS_S and TS_SCM was significant (Fig. 4a), while the a * pigm (λ) was very similar in the two layers, although the proportions of pigment groups present were quite different (Figs. 7 and 8).This result is consistent with those of Bricaud et al. (2004), who suggested that even if the variations in the pigment composition were large, the effects of various pigments on absorption might be compensated for, so that the actual influence of pigment composition on a Introduction

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Full mately reduced.These findings indicated that the significant vertical variation of a * ph (λ) in the TS was mainly driven by the packaging effect (cell size).However, in the ECS, both the packaging effect (cell size) and a * pigm (440) were similar in the surface and SCM (Figs. 4a,5,6,and 8).These factors eventually resulted in a small vertical variation in a * ph (λ) in the ECS.
It is well known that phytoplankton community structure is related to local nutrient availability.Oligotrophic and eutrophic waters are dominated by small and large phytoplankton, respectively (Staehr et al., 2004;Uitz et al., 2008).Consistently, oligotrophic waters in the TS_S were dominated by pico-phytoplankton, and micro-phytoplankton dominated in the TS_SCM where the nutrients were abundant (unpublished data).For the ECS, large amounts of nitrogen were supplied by the CDW to the shelf area during summer (Gong et al., 1996), which was expected to induce the large phytoplanktondominated structure.However, despite of the sufficient nutrients, significant numbers of pico-phytoplankton (cyanobacteria) were still found in the ECS_S as well as in the ECS_SCM in this study.This phenomenon may be related to the nutrient structure.Herbland et al. (1998) found that waters in the shelf of the south Bay of Biscay with high N/P ratios were dominated by pico-phytoplankton (< 3 µm, proportion ranged from 40 % to 70 %).The previous studies also found that the N/P ratios were high in the ECS_S and ECS_SCM, particularly in the western part of the ECS_S (unpbulbished data; Wang et al., 2003;Zhang et al., 2007).These findings imply that the N/P ratio may be an important factor influencing the phytoplankton size structure in the ECS.

Correlations among Tchl a, phytoplankton size-fraction, and Tchl a-specific absorption coefficient
For the global ocean, micro-phytoplankton are abundant in high-Chl a waters and their fraction increases with an increase in Chl a.In contrast, pico-phytoplankton prevail in low-Chl a waters and their fraction decreases with an increase in Chl a, while nanophytoplankton dominate in medium-Chl a waters (Kameda and Ishizaka, 2005;Brewin et al., 2010).According to our study, variations in the phytoplankton size classes in

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Full the TS were similar to those reported by Brewin et al. (2010).This suggests that the TS possess the typical characteristics of the global ocean, and implies that the sizebased two or three population absorption models (Sathyendranath et al., 2001;Devred et al., 2006Devred et al., , 2011;;Brewin et al., 2011) and the size-fraction estimation models (Uitz et al., 2006;Brewin et al., 2010;Hirata et al., 2011), which were proposed based on the correlations of size-fractions with Chl a in the global ocean, could be adapted for the TS.However, in the ECS there were no clear tendencies noted in the variations of size-fractions vs. Tchl a.When we applied the model of Hirata et al. (2011) in the ECS, the relative RMSEs between model-retrieved and HPLC-estimated fractions for micro-, nano-and pico-phytoplankton were 338.0 %, 66.9 % and 103.8 %, respectively.At high Tchl a range, the model-retrieved fractions displayed clear overestimation and underestimation for micro-and pico-phytoplankton, respectively.These findings indicate that the models mentioned above may not be applicable to the ECS.Bricaud et al. (1995) found that the a * ph (λ) was negatively correlated with Chl a in the global ocean, and these correlations were very stable even when subsurface samples were incorporated.In this study, consistent negative correlations between a * ph (λ) and Tchl a with those of Bricaud et al. (1995) were observed in the TS, but not in the ECS (Fig. 3c and d).The factors responsible for these differences between the TS and ECS can be clearly seen in Fig. 9 Babin et al. (2003) pointed out that the specific parameterizations for the global ocean, such as the relationships between a ph (λ) and Chl a, might not necessarily hold in coastal waters.They found that if they merged data from all of the coastal regions, most of the a ph (λ) vs. Chl a data displayed a similar tendency to that established in the global ocean by Bricaud et al. (1995).However, some samples did depart from the regression undertaken by Bricaud et al. (1995).Most of the samples from the ECS also displayed obvious departures from the regression of Bricaud et al. (1995), especially at high Tchl a (Fig. 3), which was consistent with the findings of Babin et al. (2003).In addition to the findings of Babin et al. (2003), our study implies that not only the specific parameterizations for the global ocean may become invalid, but even the correlation between a * ph (λ) and Chl a may not exist in some coastal regions.It should be noted that samples from the ECS that deviated from the regressions of Bricaud et al. (1995) were mainly taken from the low-salinity CDW (< 32) and the SCM waters beneath them (Fig. 3).These outliers had a higher a * ph (λ) and a larger variability at the same Tchl a than those in the TS and the global regressions, which resulted in a poor correlation between a * ph (λ) and Tchl a.However, it should also be noted that some samples from the ECS_S with high surface salinity (> 32) and samples from the ECS_SCM beneath them followed similar trends to the TS and the global regressions (Fig. 3).These results imply that the departure of the ECS samples from the global regressions as well as the poor correlation between a * ph (λ) and Tchl a may be influenced by the Changjiang fresh water.

Conclusions
In this study, the influence of fresh water on phytoplankton light absorption properties was studied in the East China Sea by comparison with the Tsushima Strait.Our analysis showed that the freshwater discharge could significantly change the size structure at the surface, and even in the subsurface chlorophyll a maximum.The discharge also generated absorption characteristics that were distinctly different from those of the Figures

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Full However, such characteristics were not found in the East China Sea, probably due to the influence of Changjiang freshwater.These findings provide evidence that the correlation between Tchl a with phytoplankton size classes as well as a * ph (λ), which have been observed in the global ocean, may become invalid in coastal regions because of the freshwater discharge and possibly high N/P ratio.We suggest that more attention should be given to applying the models proposed based on the general relationship between a * ph (λ) and Tchl a and on the patterns of size-fractions changing with Tchl a in regions influenced by fresh water.Introduction

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Full  Full  Full Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | λ)/Tchl a (10) Linear regression analysis was performed to assess the relative contribution to the variation in a * ph (λ) from the packaging effect and pigment composition, taking a * ph (λ) as the dependent variable and Q * a (λ) or a * pigm (λ) as the independent variable.Note that the Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | variation of a * ph (440) and a * ph (675) were 34.0 % and 29.0 %, respectively.The ratio of a * ph (440)/a * ph ( Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | photoprotective carotenoids (PPC) including zeaxanthin, diadinoxanthin, alloxanthin, carotenes, violaxanthin, and lutein; (2) photosynthetic carotenoids (PSC) including fucoxanthin, peridinin, 19 -butanoyloxyfucoxanthin, and 19 -hexanoyloxyfucoxanthin; (3) total Chl b (Tchl b) as the sum of Chl b and divinyl Chl b; and (4) total chlorophyll c (Tchl c) as the sum of chlorophyll c 1 , c 2 , and c 3 .The four groups of accessory pig- Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 2011 Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | . In the TS, Q * a (440), which played a leading role in determining a * ph (440), was strongly correlated with Tchl a, whereas a * pigm (440) had a relatively weak correlation with Tchl a.This implies that the significant correlation with a power function for a * ph (440) with Tchl a was mainly driven by the Q * a (440).The significant correlation between Q * a (440) and Tchl a was primarily controlled by the cell-size variations by the fact that pico-phytoplankton with a large Q * a (440) dominated at low Tchl a, nano-phytoplankton with moderate Q * a (440) at medium Tchl a, and micro-phytoplankton with small Q * a (440) at high Tchl a.However, in the ECS, the phytoplankton size-fractions displayed irregular trends, which resulted in a poor correlation between Q * a (440) and Tchl a.The a * pigm (440) was also not correlated with Tchl a. Due to the influence of these factors, a * ph (440) was poorly correlated with Tchl a. Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | global ocean.At the same Tchl a range, most of samples influenced by fresh water had a high magnitude and large variability of a * ph (λ).By combining the surface and subsurface chlorophyll a maximum samples, the Tsushima Strait displayed consistent patterns of size-fraction changing with Tchl a and correlations between a * ph (λ) and Tchl a with those established in the global ocean.
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Fig. 3 .Fig. 4 .
Fig. 3. Correlations between Tchl a and a ph (440) (a), a ph (675) (b), a * ph (440) (c), and a * ph (675) (d).The unfilled circle, filled circle, unfilled triangle, and filled triangle represent samples from the Tsushima Strait surface, Tsushima Strait SCM, East China Sea surface, and East ChinaSea SCM, respectively.Green symbols are samples with a surface salinity lower than 32, and blue symbols are samples with a surface salinity greater than 32.Black and grey lines indicate power law functions fitted in the Tsushima Strait (TS) and East China Sea (ECS), respectively.Black dashes correspond to the regressions ofBricaud et al. (1995).

Table 1 .
Details of the cruises where both HPLC and a ph (λ) were collected from the Tsushima Strait surface (TS_S), Tsushima Strait SCM (TS_SCM), East China Sea surface (ECS_S), and East China Sea SCM (ECS_SCM).