FIGURE 1 Sampling sites at (a) the Krka River Estuary and (b)
the Wenchang River Estuary.
The water samples were collected in the Krka River Estuary from 4 to 9
September 2014 and in the Wenchang River Estuary from 8 to 10 May 2015.
The samples were collected from the surface (0 m) using 5-litre Niskin
bottles along the salinity gradient.
2.2 Basic environmental analysis
The salinity and temperature of the water in the Krka River Estuary were
measured on site using an HQ40D portable probe (Hach Lange, Germany),
while a portable multiparameter WTW multi 350i probe (Geotech
Environmental Equipment, Denver, USA) was used for the Wenchang River
Estuary.
The samples (50 mL) for the analysis of ammonium
(NH4+) were stabilized by the addition
of 2 mL phenol solution (1 mol L-1; 95 % ethanol)
(Ivančić and Degobbis, 1984) and stored in the dark at 4 °C. The samples
(500 mL) for all other nutrients were stored at -20 °C. The
concentrations of dissolved inorganic nitrogen (DIN=nitrate
(NO3¯), nitrite (NO2¯), and ammonium
(NH4+) and orthophosphate
(PO43¯) were determined using
spectrophotometric methods according to Strickland and Parsons (1972).
Their method accuracies are ±3%, ±3%, ±5% and ±6%, respectively,
while detection limits are 0.05 µmol L-1, 0.01 µmol
L-1, 0.1 µmol L-1 and 0.05 µmol
L-1, respectively.
2.3 Pigment analysis
While Chlorophyll a (Chl a ) is used as a suitable proxy
for phytoplankton biomass, many other phytoplankton pigments show
chemotaxonomic associations that can be used to characterize
phytoplankton assemblages (Gibb et al., 2000). Pigment-based
measurements can be a good tool to determine phytoplankton diversity
(Schlüter et al., 2016 and references therein). Analyses of
phytoplankton diversity in estuaries using microscopy can be very
difficult due to the complex composition of marine and freshwater
phytoplankton, cells degraded by osmotic shock in the halocline layer,
and the usual taxonomic challenges of smaller cells and unresolved
identification issues. Although the assignment of pigments to different
phytoplankton groups has its drawbacks, e.g. if some of the
phytoplankton groups have similar pigment profiles, the method can be
used as a useful tool to describe the functional diversity of
phytoplankton in combination with rapid screening of samples under the
microscope to identify the dominant species (Sarmento and Descy, 2008,
Schlüter et al., 2006). In the Krka River Estuary and in other saltwedge
estuary studies, which have combined both methods, pigment analyses have
been proposed as a reliable method for determining phytoplankton
diversity (Viličić et al., 2008, Šupraha et al., 2014).
We have detected the following marker pigments of the
microphytoplankton: fucoxanthin (Fuco , diatoms),peridinin (Perid , dinophytes); mostly nanophytoplankton
marker pigments: 19’–hexanoyloxyfucoxanthin (Hex ,
prymnesiophytes), chlorophyll b (Chl b , chlorophytes),violaxanthin (Viola , chlorophytes and prasinophytes),alloxanthin (Allo , chrysophytes and cryptophytes),lutein (Lut , chlorophytes and prasinophytes); and the
marker pigment of picophytoplankton: zeaxanthin (Zea ,
cyanobacteria) (Jeffrey and Vesk, 1997).
For pigment determination, 1 L of seawater was filtered through 0.7 µm
Whatman GF/F filters, which were pre-burned at 450°C/5h. Extraction was
performed in 4 mL of cold 90% acetone by sonication, followed by
centrifugation. The pigments were separated by reversed-phase HPLC
(Barlow et al., 1997). The composition of the phytoplankton pigments was
analyzed by HPLC following Barlow et al. (1997) method. The extracts
were mixed 1:1 (v/v) with 1 M ammonium acetate and injected into the
HPLC system with the 3-mm Thermo Hypersil-Keystone column MOS2, C-8, 120
A pore size, 150×4.6 mm (Thermo Hypersil-Keystone, Bellefonte, PA, USA).
The pigments were separated at a flow rate of 1 mL
min–1 using a linear gradient programme lasting 40
min, using solvents A and B. Solvent A consisted of 70:30 (v/v)
methanol: 1 M ammonium acetate and solvent B was 100% methanol.
Chlorophylls and carotenoids were detected by absorbance at 440 nm
(SpectraSYSTEM, Model UV 2000, Thermo Fischer Scientific, USA). The
qualitative and quantitative analyses of individual pigments were
performed by external standard calibration with authentic pigment
standards (VKI, Denmark).
2.4 Lipid class analysis
To determine the lipid classes, 3 L of seawater were collected in glass
containers and passed through the 200 µm stainless steel screen to
remove zooplankton and larger particles. Immediately afterwards, the
seawater was filtered through 0.7 µm Whatman GF/F filters pre-burned at
450 °C for 5 h. The filters of Krka River Estuary samples were stored in
liquid nitrogen for six months, while the samples from the Wenchang
River Estuary were stored at -80 °C for 2-3 weeks before analysis. The
particulate lipids were extracted with a modified one–phase solvent
mixture of dichloromethane–methanol–water (Bligh and Dyer, 1959).
N–hexadecanone was added to each sample as an internal standard to
estimate recoveries in the subsequent steps of sample analysis. The
extracts were evaporated to dryness under a nitrogen atmosphere, stored
at -20 °C for one day and dissolved in 20 µL dichloromethane immediately
prior to analysis.
The lipid classes were determined using TLC–FID (Iatroscan MK–VI,
Iatron, Japan) (Gašparović et al., 2015). The lipid classes were
separated on Chromarods SIII and quantified by an external calibration
with a standard lipid mixture at a hydrogen flow of 160 mL/min and an
air flow of 2000 mL/min. The standard deviation determined from
duplicate runs accounted for 1–14% of the relative abundance of the
lipid classes. Eighteen lipid classes were detected by this technique.
The separation scheme comprised of successive elution steps in solvent
systems of increasing polarity, followed by a subsequent partial
combustion of Chromarods. Total lipid concentrations were determined by
summing all lipid classes quantified by TLC-FID. Detailed procedures are
described in Gašparović et al. (2015). However, in Gašparović et al.
(2015) there was an error for the elution of the solvent mixture MGDG
and DGDG (chloroform–acetone (72:28, v:v), which should be
“chloroform–acetone (28:72, v:v)” (Gašparović et al. 2017). So, we
tested the elution of the standards for MGDG, DGDG and SQDG with that
incorrect protocol (Gašparović et al. 2015) and found that the MGDG
standard mixture splits into two peaks (termed first and second MGDG,
fMGDG and sMGDG, respectively), while DGDG and SQDG co-elute in one peak
in the next elution step.
2.5 MGDG fatty acid composition
The separation of the MGDG lipids present in the sample mixture was
carried out using the UltiMate 3000 Rapid Separation HPLC (Dionex,
Germany) system. The Acquity UPLC BEH C18 (2.1 × 100 mm with 1.7 µm
particles) (Waters, Milford, Massachusetts, USA) column was maintained
at 50 ºC while a gradient elution was employed. The solvent system
comprised solution A: LC-MS-grade methanol:ultrapure water (1:1, v:v; 10
mM ammonium-acetate/0.1 % formic acid) and solution B: LC–MS-grade
isopropanol (10 mM ammonium-acetate, 0.1 % formic acid). The gradient
started with 55% A/45% B, reached 90% B in 40 min, 99% B in 2 min
and remained there for 10 min, then 45% B in 1 min, followed by
equilibration for 22 min. The flow rate was 0.15 mL/min and sample
mixture injected volume was 10 µL. Immediately before the analysis,
dichloromethane was evaporated and the sample was redissolved in a
solution of methanol:chloroform (1:2, v:v). The HPLC system was
connected online to the amaZon ETD ion trap mass spectrometer (Bruker
Daltonik, Bremen, Germany) for analyzing the fatty acid composition. The
mass spectrometer was equipped with a standard electrospray ionization
ion source (nebulizer pressure 8 psi; drying gas flow rate 5 L/min;
drying gas temperature 250 ºC; the potential on the capillary –/+ 4500
V). Lipid profiling was performed in both positive and negative ion
mode. Data were collected in the mass range of m/z = 100–1200. ESI
MS/MS was performed using collision energy of 1 eV. The MGDG species
were identified as [M+NH4]+ ions
in the positive mode. The derived elemental compositions were matched
with an internally compiled lipid library from LIPID MAPS
(http://www.lipidmaps.org/).
2.6 Data analysis
Principal-component analysis (PCA) was performed to determine how the
environmental variables (salinity (S), temperature (T), DIN and
PO43¯) related to the accumulation
unsaturated MGDG. It was performed using Origin 7 computer software.
Linear fits (Origin 7 computer software, Origin Lab) were performed to
analyze the correlations of interest.
3 RESULTS
3. 1 Environmental conditions
The environmental conditions differed significantly between the
estuaries studied (Figure 2 and Table S1). Much higher T were measured
in the Wenchang River Estuary (27.9-31.5 °C) compared to the Krka River
Estuary (21.5-26.2 °C). The Wenchang River Estuary was enriched in DIN
(4.0-154.9 µmol L-1), while
PO43- concentrations were much lower
(0.08-2.99 µmol L-1), as previously observed (Liu et
al., 2011). Both DIN (1.0-5.8 µmol L-1) and
PO43¯ (0.21-0.70 µmol
L-1) were notably lower in the Krka River Estuary than
in the Wenchang River Estuary.