Introduction
Marine heterotrophic prokaryotes play a key role in pelagic ecosystems both
in terms of carbon sequestration and organic matter remineralisation. Their
distribution is controlled by biotic (bottom-up control, top-down control by
grazing, virus lyses) and abiotic variables (temperature, salinity,
pressure, irradiance and nutrient concentrations). These possible limiting
variables are shared with the autotrophic community and competition for
resources inevitably occurs in order for each to survive in the same pelagic
ecosystem. Competition between heterotrophic prokaryotes and phytoplankton
for different forms of inorganic nitrogen and phosphorus has been clearly
demonstrated both in laboratory experiments and in the open ocean (Currie
and Kalff, 1984; Vadstein, 1998; Thingstad et al., 1998). Moreover, several
studies have reported that dissolved organic compounds can be an alternative
nutrient source for some nutrient-stressed phytoplankton (Duhamel et al.,
2010; Girault et al., 2013a). The common utilization of the inorganic and/or
organic matter, such as dissolved organic phosphorus, could lead to a tight
coupling between the heterotrophic prokaryotes and photoautotrophs along an
oligotrophic gradient. However, the relationship between heterotrophic
prokaryote abundance and oligotrophic conditions is unclear, especially in
terms of mesoscale structures such as eddies (Baltar et al., 2010; Lasternas
et al., 2013). The differences within the same type of mesoscale circulation
reported in the literature highlights that the relationship between
heterotrophic prokaryotes and photoautotrophs can be dependent on the
identification of the different microorganisms making up the community
(Girault et al., 2013b).
In this study, using analytical flow cytometry combined with fluorescent
dyes, we were able to identify three different subgroups among the bulk of
heterotrophic prokaryotes: a group characterized by a very high nucleic acid
content (VHNA), another by a high nucleic acid content (HNA), and finally a
group with a low nucleic acid content (LNA). Previous studies have reported
that the more active microorganisms seem to have the higher nucleic acid
contents (Gasol et al., 1999; Lebaron et al., 2001). Complementary results
have suggested that heterotrophic prokaryote activities are influenced by
environmental parameters especially under oligotrophic conditions (Zubkov et
al., 2001; Grégori et al., 2001, 2003a; Nishimura et al., 2005; Sherr et
al., 2006; Bouvier et al., 2007). Using the basis of these previous reports,
the oligotrophic conditions investigated in the western part of the NPSG
during the Tokyo–Palau Cruise enabled us to examine the relationship
between different groups of heterotrophic prokaryotes, as defined by
different nucleic acid contents, and their environmental conditions.
Investigations into the heterotrophic prokaryote distribution in the western
part of the NPSG are scarce and mostly restricted to the Kuroshio Current or
the area near the Japan shelf during El Niño events (Mitbavkar et al.,
2009; Kataoka et al., 2009; Kobari et al., 2011). In contrast, the Tokyo–Palau cruise was conducted during a strong La Niña condition and over a
large latitudinal gradient to include various seawater masses. In this work,
we studied the extent to which abundance and distribution of various
heterotrophic prokaryotic groups, defined by flow cytometry (VHNA, HNA, LNA)
were influenced by phytoplankton distribution and environmental variables.
The relationships between each heterotrophic prokaryote group and two
different mesoscale eddies (one anticyclonic and one cyclonic) were also
examined in order to identify any modification in organism distribution
which could be related to the oligotrophic conditions found during the
cruise.
Materials and methods
Study area and sample collection
This study was conducted from 17 January to 8 February 2011 on board
research training vessel Shinyo Maru during the Tokyo–Palau cruise. Samples were collected in the
western part of the NPSG between 33.60 and 13.25∘ N along the
141.5∘ E transect (Fig. 1). Twelve stations (Sta.) were sampled
using 2.5 L Niskin bottles mounted on a rosette frame equipped with the
Conductivity–Temperature–Depth (CTD) and in situ fluorometer system.
Seawater was sampled without replicates at several depths between the
surface and 200 m. Due to bad weather conditions, the seawater samples
between Stations 1 and 4 were collected only at the surface (3 m) using a
single Niskin bottle. At these 4 stations, Expendable
Conductivity/Temperature/Depth profiling systems (XCTD) were used to measure
temperature and salinity. The Brunt-Väisäla buoyancy frequency
(N2) was calculated using the exact thermodynamic expression reported
by King et al. (2012) (Eq. 1).
N2=g2dρdp-1cs2,
where dρdp is the vertical gradient of in situ density (ρ).
The acceleration (g) due to the gravity was assumed to be constant during
the Tokyo–Palau cruise (g= 9.81) and the speed of sound (cs) was
calculated depending on the depth, salinity, and temperature according to Del Grosso (1974).
The mixed layer depths were estimated as the depths at which
the maximum stratification occurred (i.e. a maximum of N2 at each
station). The irradiance was monitored at five stations (5, 7, 9, 11, 12)
using a Profiling Reflectance Radiometer (PRR 600 Biospherical
Instrument®). The depth of the euphotic layer was estimated
as the depth of 1 % of photosynthetically active radiation at noon.
Map of the sea level anomaly (cm) in the west part of the North
Pacific subtropical gyre. The sampling stations (black crosses) were
separated depending on temperature and salinity into 3 areas: Kuroshio
region (Stations 1–4), subtropical gyre (Stations 5–8) and the transition
zone (Stations 9–12).
Altimetry and large-scale climatic conditions
The altimetry data (sea level anomaly) were produced by Ssalto/Duacs and
distributed by Aviso, with support from CNES
(http://www.aviso.oceanobs.com/duacs/). The sea level anomaly map centred
on the 18 January 2011 was plotted using the Panoply software from NASA
(http://www.giss.nasa.gov/tools/panoply/). This map was processed by
compiling the data collected over a six week period before and after the
chosen date (Fig. 1). The current sea maps provided by the bulletin of the
Japanese coast guard were used to validate the satellite data and display
the paths of both the cyclonic gyre and the Kuroshio Stream
(http://www1.kaiho.mlit.go.jp/KANKYO/KAIYO/qboc/index_E.html).
Nutrient analyses
Nutrient samples were collected from Niskin bottles, immediately put into
cleaned plastic tubes in the dark, plunged into liquid nitrogen and stored
in the deep freezer (-60 ∘C) until analyses. The highly sensitive
colorimetric method incorporating the AutoAnalyzer II (SEAL Analytical) and
Liquid Waveguide Capillarity Cells (World precision Instruments), was used
to determine nutrient concentrations (nitrate + nitrite, soluble reactive
phosphorus and silicic acid) according to the methods listed in Hashihama et al. (2009) and Hashihama and Kanda (2010). Seawater collected at the surface
of the western part of NPSG, which had been preserved for > 1 year,
was used as nitrate + nitrite blank water. The blank water was
analyzed using the chemiluminescent method described in Garside (1982). The
detection limits for nitrate + nitrite, soluble reactive phosphorus and
silicic acid were 3, 3 and 11 nM, respectively. Because soluble reactive
phosphorus consists mainly of orthophosphate and nitrite was not
substantially detectable, soluble reactive phosphorus and nitrate + nitrite are hereafter referred to as phosphate and nitrate.
The nutrient fluxes into the surface mixed layer were calculated using the
equation KdNutdz where K is the local vertical diffusivity, Nut is the
concentration in nutrients (phosphates, nitrates or silicic acid) and
dNutdz the vertical nutrient gradient. To compensate for
irregular sampling depths among the stations, the nutrient profiles were
linearly interpolated onto the 1 m grid. Then, vertical nutrient gradients
were calculated between sequential depth bins (Painter et al., 2013). This
method has the advantage of showing the nutrient flux from a particular part of
the water column. Due to the lack of an Acoustic Doppler Current Profiler
(ADCP) on the ship, the local vertical diffusivity (K) was estimated using
the literature (Table 1). Among the K values reported in the oligotrophic
conditions, a vertical diffusion coefficient of 0.5 cm2 s-1 was
chosen as a standard value (Table 1).
Literature estimates of vertical turbulent diffusivity rates
obtained using different methods in the oligotrophic condition. NA indicates
information not mentioned.
Domain
Location
Depth (m)
Diffusivity (cm2 s-1)
Reference
North Pacific subtropical gyre
22∘ N–158∘ W 35–44∘ N, 150–170∘ W 10–40∘ N 22∘ N–158∘ W
300–500 NA 0–1000 Euphotic
0.1–0.5 0.2–0.4 0.3 1–2
Christian et al. (1997) White and Berstein (1981) Van Scoy and Kelley (1996) Emerson et al. (1995)
Pacific Ocean
20∘ S–20∘ N 20–60∘ N
125 100
0.5 1.8
Li et al. (1984) Li et al. (1984)
Tropical North Pacific Ocean
5–10∘ N, 90∘ E 10–15∘ N, 85∘ E
NA NA
0.05–0.16 0.44–1.10
King and Devol (1979) King and Devol (1979)
Subtropical North Atlantic
25∘ N, 28∘ W 28.5∘ N, 23∘ W 31∘ N, 66∘ W
300 100–400 < 100
0.12–0.17 0.37 0.35
Ledwell et al. (1998) Lewis et al. (1986) Ledwell et al. (2008)
Vertical profiles of the Brunt-Väisäla buoyancy frequency
(N2) calculated from the temperature–salinity measurements. The white
circles display the thermocline depth and the black triangles display the depths of
1 % of photosynthetically active radiation (limit of the euphotic zone).
Chlorophyll a and flow cytometry analyses
The depth of the deep chlorophyll a maximum was determined from fluorescence
profiles using the pre-calibrated in situ fluorometer. To measure
chlorophyll a concentration, 250 cm3 of seawater was filtrated through
Whatman® nucleopore filters (porosity ∼ 0.2 µm)
using a low vacuum pressure (< 100 mm of Hg). Filters were then
immersed into tubes containing N,N-dimethylformamide (DMF) and stored in
the dark at 4 ∘C until analyses on shore. Chlorophyll a was
analysed using a Turner Designs fluorometer pre-calibrated with pure Chl a
pigment (Suzuki and Ishimaru, 1990).
Samples for heterotrophic prokaryotes were collected from the Niskin bottles
and pre-filtered onto disposable 100 µm porosity nylon filters to
prevent clogging of any in the flow cytometer. Seawater aliquots of
1.8 cm3 were fixed with 2 % (w/v final dilution) formaldehyde
solution, quickly frozen in liquid nitrogen and stored in the deep freezer
onboard (-60 ∘C) until analysis at the flow cytometry core
facility PRECYM of the Mediterranean Institute of Oceanology
(http://precym.mio.osupytheas.fr). In the PRECYM, samples were thawed
at room temperature and stained using SYBR Green II (Molecular
Probes®) methods detailed in Marie et
al. (1999), Lebaron et al. (1998) and modified by Grégori et al. (2003b).
The analyses were performed on a FACSCalibur flow cytometer (BD
Biosciences®) equipped with an air-cooled
argon laser (488 nm, 15 mW). For each particle (cell), five optical
parameters were recorded: two light scatter signals, namely forward and right
angle light scatters and three fluorescences corresponding to emissions in
green (515–545 nm), orange (564–606 nm) and red (653–669 nm) wavelength
ranges. Data were collected using the CellQuest software (BD
Biosciences®) and the analysis and optical
resolution of the various groups of heterotrophic prokaryotes were performed
a posteriori using the SUMMIT v4.3 software (Beckman Coulter). For each
sample, the runtime of the flow cytometer was 2 min and the flow rate set to
50 µL min-1 (corresponding to the “Med” flow rate of the flow
cytometer). Trucount™ calibration beads
(Becton Dickinson Biosciences) were also added to the samples just prior to
analysis as an internal standard to monitor the instrument stability and
accurately determine the volume analyzed. Following the staining of the
nucleic acid with SYBR Green II, heterotrophic prokaryotes, excited at
488 nm, were recorded and enumerated according to their right angle light
scatter intensity (SSC) which relates to the cell size and their green
fluorescence intensity (515–545 nm) which relates to the nucleic acid
content. As already widely described in the literature, several heterotrophic
prokaryote groups can be optically resolved by flow cytometry depending on
their average green fluorescence intensities related to their nucleic acid
content: in this study, a group of cells with a lower green fluorescence
corresponding to heterotrophic prokaryotes with a lower nucleic acid content
(LNA), a group of cells displaying a higher green fluorescence corresponding
to a higher nucleic acid content (HNA) and a last group of cells with the
highest green fluorescence intensity corresponding to the highest nucleic
acid content (VHNA) (Supplement Fig. S1). The overlap between the stained
phytoplankton, in particular Prochlorococcus and Synechococcus,
and the heterotrophic prokaryotes (in terms of green fluorescence and side
scatter intensity) was resolved by using red fluorescence (induced by the
chlorophyll) to discriminate and identify the photoautotrophs (Sieracki et
al., 1995). The heterotrophic prokaryote abundances were also expressed for
each cluster (LNA, HNA and VHNA) in terms of carbon biomass using a
conversion factor of 15 fg C cell-1 (Caron et al., 1995). The carbon
biomass was integrated between the surface and the 200 m depth in order to
better characterise the upper water column. Although this study focuses on
the distribution of the heterotrophic prokaryotes, ultraphytoplankton was
also investigated during the Tokyo–Palau project. Briefly, the
ultraphytoplankton was sampled thanks to Niskin bottles and filtrated through
a 100 µm mesh size. 4.5 cm-3 of subsamples preserved with
0.5 cm-3 of a 20 % formaldehyde solution (i.e., 2 % final
concentration) were put into 5 cm-3 Cryovials tubes. Similar to the
heterotrophic prokaryote samples, Cryovials tubes were rapidly frozen in
liquid nitrogen and stored in a deep freezer (-60 ∘C) until
analysis. Analyses were performed in the same period as the heterotrophic
prokaryotes and based on their light scatter and fluorescence emission
properties. Ultraphytoplankton was discriminated in this study into five flow
cytometry clusters (Synechococcus, Prochlorococcus,
Picoeukaryotes, Nanoeukaryotes and Nanocyanobacteria-like) as described in
Girault et al. (2013b).
Statistical analysis
To analyse the multivariate data set, principal component analyses (PCA) and
redundancy analysis (RDA) were performed using the R software (vegan
package) and the Biplot macro for Excel® (Lipkovich and Smith,
2002). PCA was performed in order to qualitatively identify the
relationships between heterotrophic prokaryotes and the environmental
variables (Pearson, 1901). Possible links between each heterotrophic
prokaryote subgroup and their environmental variables were quantitatively
examined using the RDA. For the RDA, the data set was log10
(x+1)-transformed to correct for the large differences in scale among the
original variables. A Monte Carlo test was used in order to test the
significance of the RDA results. Partial RDAs were also carried out to
evaluate the effects of each explanatory variable set on the heterotrophic
prokaryote composition (Liu, 1997). The first RDA was performed on the whole
data set by taking into account the heterotrophic prokaryotes as one single
group. Additional partial RDAs were performed for each subgroup (LNA, HNA,
and VHNA). The environmental variables in the additional partial RDAs were
classified into three intercorrelated variable groups, namely: the
depth-related parameters (phosphate, nitrate, depth), spatial-related
parameters (temperature and salinity) and the phytoplankton-related
parameters (Chl a and silicic acid). This decision was made considering the
results of the PCA (environmental variables were separated into three
groups).
Results
Sampling sites and ultraphytoplankton distribution
The cruise took place along a north–south transect in the western part of
the NPSG (141.5∘ E) during a strong La Niña climatic event.
According to the temperature–salinity diagram presented in the study made
by Girault et al. (2013b), three main areas corresponding to the Kuroshio
region (Sta. 1–4), the subtropical gyre (Sta. 5–8) and the transition zone
(Sta. 9–12) were discriminated (Fig. 1). Separation between the transition
zone and the subtropical gyre was made using the salinity front observed
south of station 8. The discrimination between the Kuroshio area and the
subtropical gyre seawater masses was confirmed by comparing the Tokyo–Palau
data set and the studies of Sekine and Miyamoto (2002) and Kitajima et al. (2009).
The cruise crossed two main eddies identified in this study as a
cold-core cyclonic eddy (C), and a warm-core anticyclonic eddy (A) (Fig. 1).
Eddy C (31∘ N, 141∘ E) is located in the Kuroshio region
and eddy A (20.5∘ N, 142∘ E) in the transition zone.
Thanks to the satellite data and daily surface currents of the bulletin of
the Japanese coast guard, the creation of the cold-core structure was
explained by the instability in the meander of the Kuroshio Current between
9 and 12 July 2010. The cold core was continuously reported all along the
cruise. The distribution of the ultraphytoplankton assemblages observed
during the Tokyo–Palau cruise was reported in detail in the study of Girault
et al. (2013b). Briefly, ultraphytoplankton was characterized by a
heterogeneous distribution of its phytoplankton groups associated with the
complex distribution of the various seawater masses met during the cruise
(including salinity front, subtropical countercurrent, eddies). Among the
phytoplankton communities Prochlorococcus numerically dominated the ultraphytoplankton
assemblages in the samples collected in the stratified oligotrophic areas
such as the subtropical gyre area and the transition zone. Picoeukaryotes,
Nanoeukaryotes and Synechococcus also constituted a significant part of the carbon
biomass in the region depleted in phosphate and nitrate. The role of the
cold-core eddy C was reported at the surface where the highest concentration
of Nanoeukaryotes in the surface sample was found in the very core of the
cyclonic eddy (Sta. 3) and where, the Synechococcus outnumbered the Prochlorococcus abundance in the path
of the cold-core cyclonic eddy (Sta. 4). The Nanocynaobacteria-like group
was reported to be controlled by the frontal system observed at station 9
rather than the concentration of inorganic nutrients.
Stratification of seawater masses and vertical nutrient fluxes
The Brunt-Väisäla buoyancy frequencies calculated from the CTD data
set are characterized by low N2 values (< 2 × 10-4 s-2)
from the surface down to the 90 m depth (Fig. 2). Below this depth, the
vertical distribution of N2 was more irregular and reached the
maximum 1.09 × 10-3 s-2 at station 11 (90 m). Figure 2 also shows
that the depth of the N2 maximum (thermocline depth) tended to be
shallower in the southernmost part of the transect (Sta. 11, 85 m to Sta. 11, 90 m)
underlying the strengthening of the upper thermocline when the
heat flux at the surface is positive and wind mixing is low in the south
part of the transect. Along the latitudinal transect, two particular values
of the thermocline depths were found at station 3 (145 m) and at station 9
(140 m) corresponding to the cyclonic and anticyclonic eddies, respectively.
Moreover, excepted at stations 3 and 9, the first increases of
N2 (> 2 × 10-4 s-2) from the surface to the 200 m
depth corresponded to the depth of the thermocline and indicated the lack of
seasonal thermocline as already described in Sprintall and Roemmich (1999).
The limit of the euphotic layer (defined by the depth with 1 % of the
irradiance at the surface) was also plotted in Fig. 2. During the cruise,
this limit varied from 84 m (Sta. 7) to 115 m (Sta. 12). Except station 11,
the limit of the euphotic layer was located upper the thermocline. The
average of the absolute difference between the euphotic layer and the
thermocline depths was 34 ± 11 m.
Figure 3 shows the vertical gradient of nutrients (phosphates, nitrates and
silicic acid). The vertical phosphate profiles were characterized by a very
low gradient (< 1 nM m-1) in the upper 100 m from Stations 6 to
12. Both positive and negative gradients were observed and no
specific distribution between them was found. Under the depth of 100 m,
higher phosphate gradients (> 3 nM m-1) were found and
defined the phosphacline depths as displayed in Fig. 4 of the study made
by Girault et al. (2013b). Nitrates showed that vertical profiles closely
corresponded to phosphates with negative or positive values lower than 5 nM m-1
and higher gradient below 100 m. The vertical distribution of
the silicic acid gradient was more complex and moderate gradients ranging
from 0.01 to 0.02 µM m-1 were observed in the upper 100 m depth
at stations 5, 6, 7, and 12. Similar to phosphates and nitrates, the
highest gradients of silicic acid (0.04 µM m-1) were found
below a
100 m depth from stations 6 to 10. Taking into account all the panels
of Fig. 3, station 8 showed a particular pattern between 100 and 160 m
depths where two superimposed high gradients were observed. The depths of
these high gradients were found to be similar for phosphates and silicic
acid (100–115 and 130–155 m) but the vertical profile of nitrates gradient
showed a slightly lower depth (130–140 and 155–170 m).
By using a vertical diffusion coefficient of 0.5 cm2 s-1, the
nutrient fluxes were calculated from stations 5 to 11 (Table 2).
Phosphate fluxes into the surface mixed layer were negative at Stations 5
and 6 (-0.52 and -1.34 µmol m-2 d-1, respectively) and
positive from stations 7 to 11. The positive phosphate fluxes were
maximum at station 7 (9.43 µmol m-2 d-1) and decreased to
reach 1.38 µmol m-2 d-1 at station 11. The percentages of
diffuse flux per day relative to the standing stock in the mixed layer were
particularly low and varied from -0.03 (Sta. 6) to 0.76 % (Sta. 8).
Nitrate fluxes into the mixed layer were positive and highly variable along
the transect (∼ 0 to 81.3 µmol m-2 d-1). The
percentage of daily diffuse supply relative to the pool reflects this result
and varied from ∼ 0 (Sta. 7 and 10) to 432 % (Sta. 8). The
silicic acid fluxes were globally higher than the phosphate and nitrate
fluxes calculated in the mixed layer (up to 571.1 µmol m-2 d-1; Sta. 9).
The daily diffuse supply relative to the
mixed layer pool was low and spread from 0.002 (Sta. 5) to 0.48 %
(Sta. 9).
Vertical nutrient gradient (dNutrient / dz) of Phosphate (a),
Nitrate (b) and Silicic acid (c), between stations 5 and 12. The
black dots display the sample depths and the names of the stations are
indicated in the upper axes.
Vertical concentration (cells cm-3) of LNA, HNA, and VHNA
heterotrophic prokaryotes interpolated along the transect during the
Tokyo–Palau Cruise. The black dots are the depths sampled.
Phosphate, nitrate and silicic acid diffusive fluxes into the
surface mixed layer and the importance of supply term relative to the
standing pool size.
Station
Latitude
Mixed layer
Phosphate flux
Daily diffusive
Nitrate flux
Daily diffusive supply
Silicic acid flux
Daily diffusive supply
depth (m)
(µmol m-2 d-1)
supply relative to pool (%)
(µmol m-2 d-1)
relative to pool (%)
(µmol m-2 d-1)
relative to pool (%)
5
28.98
141
-0.52
-0.01
3.63
0.01
2.25
0.002
6
27.16
136
-1.34
-0.03
12.88
0.04
54.09
0.03
7
24.83
109
9.43
0.69
0
0
142.21
0.21
8
22.83
101
7.78
0.76
81.3
432
351.36
0.39
9
20.78
140
6.48
0.68
13.91
5.7
571.1
0.48
10
19.98
95
1.38
0.16
0
0
0.006
0.01
Distribution of the heterotrophic prokaryotes
After staining with the SYBR green II fluorescent dye, three clusters of
heterotrophic prokaryotes were characterized by their different green
fluorescence mean intensities (Fig. S1). In the surface samples of the
Kuroshio region the average concentrations of LNA, HNA and VHNA were
8.71 × 105±3.8 × 105, 3.27 × 105±1.4 × 105 and
2.64 × 105±1.2 × 105 cells cm-3, respectively. In the
subtropical area the average concentrations of LNA, HNA and VHNA were
6.01 × 105±1.2 × 105, 2.97 × 105±1.4 × 105 and
1.84 × 105±6.4 × 104 cells cm-3, respectively. In the
transition zone the average concentrations of LNA, HNA and VHNA were
5.18 × 105±1.8 × 105, 4.38 × 105±1.6 × 105 and
1.15 × 105±6.2 × 105 cells cm-3, respectively (Fig. S2).
Despite the high variability between the concentrations along the
north-south transect, the distribution of the three heterotrophic prokaryote
groups was characterized by a common maximum at station 4 and a minimum at
station 9. At station 4 the concentrations of LNA, HNA and VHNA were
1.39 × 106, 5.03 × 105 and 4.35 × 105 cells cm-3, respectively.
In contrast, the concentrations of LNA, HNA and VHNA at station 9 were
2.07 × 105, 1.6 × 105 and 5.07 × 104 cells cm-3,
respectively. To a lesser extent, high concentrations of LNA
(9.13 × 105 cells cm-3) and HNA (3.62 × 105 cells cm-3) were
identified at the northernmost station of the Kuroshio region at station 1.
The vertical distributions of heterotrophic prokaryotes were also
investigated along the transect (Fig. 4). As for surface, the vertical
distributions of all heterotrophic prokaryote groups are characterized by
lower cell concentrations at station 9. In this very station both LNA and
HNA concentrations are significantly lower than at the other stations
(Kruskal Wallis test, n= 90, P value < 0.05). The LNA cluster is
numerically dominant in 99 % of the samples. The VHNA concentrations are
lower than the HNA in 75 % of the samples. In terms of carbon biomass, the
LNA cluster numerically dominated the other clusters from stations 5 to
12 (Fig. S3). The latitudinal contribution of the LNA cluster to the
total heterotrophic prokaryotes in terms of carbon biomass varied from 47 %
(Sta. 9) to 63 % (Sta. 6). Contribution of the HNA cluster is
characterized by a low percentage at stations 5 and 6 (22 and 16 %,
respectively) and a near constant contribution between station 7 and the
southernmost station 12 (33 ± 2 %; n= 6). The contribution of the
VHNA cluster was nearly constant from stations 5 to 9 (19 ± 2 %;
n= 5). Then, it reached the lower values in the transition zone (14 % at
Sta. 10, 5 % at Sta. 11, and 12 % at Sta. 12).
List of observations from Stations 1 to 11 and their classification
into six clusters according to the principal component analysis (PCA).
PCA Cluster
Observations
Latitude (∘ N)
Station
Depth (m)
1
1
33.6
1
0
1
2
33
2
0
1
3
31.6
3
0
1
4
31
4
0
2
5,6,7,8,9,10,11,12,13
28.6
5
0,40,60,70,78,80,100,120,140
2
15,16,17,18,19,20,21,22,23
27.1
6
0,25,60,75,80,90,100,115,125
2
32,33,34
24.5
7
75,90,101
2
40,41
22.5
8
110,125
2
55
20.5
9
200
3
14
28.6
5
160
3
24
27.1
6
150
3
42,43,44
22.5
8
135,150,165
3
54
20.5
9
160
3
61
19.6
10
125
4
25,26,27,28,29,30,31
24.5
7
0,10,25,40,58,59,60
4
35,36,37,38,39
22.5
8
0,25,50,75,95
5
45,46,47,48,49,50,51,52,53
20.78
9
0,25,50,75,100,120,130,140
5
59,60,62
19.6
10
75,100,150
6
56,57,58
19.6
10
0,25,50
6
63,64,65,66
17.2
11
0,30,45,60
Ratios of the abundances between the heterotrophic prokaryote
clusters according to depth. (a) shows the ratio of the abundances of HNA / LNA
clusters while (b) shows the ratio of abundances of VHNA / HNA clusters. The
white circles are stations 1, 2, 3, and 4. The white triangles and the
squares are stations 5 and 6, respectively. The grey circles, triangles, and
squares characterize stations 7, 8 and 9, respectively. The black squares,
circles and triangles are stations 10, 11, and 12, respectively.
Figure 5a displays the ratios of HNA / LNA concentration depending on depth.
In the Kuroshio region, ratios are low and varied from 0.29 (Sta. 2) to 0.44
(Sta. 3). In the subtropical gyre area, the ratios varied from 0.16 (Sta. 5,
70 m) to 0.82 (Sta. 7, 10 m). The higher ratios (up to 1.03 at Sta. 10, 10 m)
were observed in the surface layer of the transition zone. In the
transition zone and the subtropical gyre area the higher ratios measured
were found between the surface and 100 m. Figure 5b shows the ratio of
VHNA / HNA concentrations depending on depth. In the Kuroshio region the ratio
varied from 0.53 (Sta. 3) to 1.46 (Sta. 2). In the subtropical gyre area,
the ratio varied from 0.10 (Sta. 7, 58 m) to 1.93 (Sta. 9, 175 m). In the
transition zone the ratio varied from 0.10 (Sta. 12, 70 m) to 1.47 (Sta. 12,
180 m). The average of the VHNA / HNA ratio (0.37 ± 0.35) in the
transition zone was the lowest of the three sampled regions (0.78 ± 0.44
in the subtropical gyre; 0.88 ± 0.41 in the Kuroshio region).
Statistical analysis
Results of the Principal Component Analysis (PCA) and the Redundance
Analysis (RDA) are shown in Figs. 6 and 7, respectively. The correlation
circle of the PCA displays the first two principal components (PC1 and PC2)
which accounted for 32.44 and 27.67 % of the total inertia, respectively.
The third and fourth principal components are not shown due to the low
inertia exhibited (11 and 8 % of the total inertia, respectively) and the
lack of any clear ecological understanding. Silicic acid, Chl a, VHNA and LNA
were differentiated from temperature and salinity by PC1, while PC2 mainly
differentiated depth, nitrate, and phosphate (negative coordinates) from the
HNA clusters (positive coordinate). Using hierarchical classification the
sampling depths were separated into six different clusters (Table 3 and
Fig. 6).
Cluster 1 characterized all the stations located in the Kuroshio region.
Cluster 2 corresponded to samples collected at the edge of the subtropical
gyre and contains the deepest sample collected at station 9 (200 m), the station
in the anticyclone eddy in the transition zone. Samples in cluster 3 were
collected below a depth of 125 m where nitrate and phosphate concentrations
were higher than for surface samples. This cluster was defined as the deep
layer group. Cluster 4 samples were collected in the centre of the
subtropical gyre (Stations 7 and 8), where heterotrophic prokaryote
concentrations were at their maximum in the seawater column. Cluster 5
represented the samples collected in the anticyclonic eddy where a marked
salinity has been reported (Girault et al., 2013b). Located in the
transition zone, at the southernmost stations the sixth and last cluster
group was characterized by the highest salinity and temperature values. This
last cluster (blue dots in Fig. 6a) is distinguished from the deep layer
group (cluster 3, green dots) by the low nutrient concentrations measured in
the upper layer.
Hierarchical clustering illustrated for the first two principal
components of the principal component analysis performed with the data
collected from stations 1 to 11 (a). According to the classification (Table 1)
the sampling depths (numbers) were discriminated into 6 clusters: one
characterizes the Kuroshio region (cluster 1, black), another incorporates
stations 5 to 9 (cluster 2, red), a third one the deep layer (cluster 3,
green) and the last three clusters characterize the subtropical gyre
(cluster 4, white) and the southernmost stations (5, blue and 6, dark grey).
The circle (b) shows the first two dimensions of the principal component
analysis. The environmental variables taken into consideration are
temperature, salinity, depth, nitrate (N), phosphate (P), silicic acid (Si),
and chlorophyll a (Chl a).
A redundancy analysis (Fig. 7) was then performed to find out how the
measured environmental factors influenced the distribution of heterotrophic
prokaryote subgroups sampled during the cruise. The cumulative percentage of
all canonical eigenvalues indicated that 69.1 % of the observed
heterotrophic cluster variations were explained by environmental factors.
The first two axes of the RDA explained 38 and 24 % of the total
variance, respectively. Monte Carlo tests for these two axes were
significant (P value < 0.05, using 999 permutations) and suggested
that environmental parameters might be important in explaining heterotrophic
prokaryote distribution. The first axis is negatively correlated with
salinity and positively correlated with the LNA cluster. The second axis is
negatively correlated with temperature and the HNA cluster and positively
correlated with the VHNA cluster. RDA suggested two main correlations
between the LNA cluster and the phytoplankton-related variables (Chl a and
silicic acid) and the HNA cluster with the depth-related variables
(nutrients such as nitrate and phosphate and depth).
Correlation plot of the redundancy analysis (RDA) on the
relationships between the environmental variables and the three subgroups of
heterotrophic prokaryotes observed during the cruise (LNA, HNA, VHNA). Chl a,
N, P, and Si stand for chlorophyll a, nitrate, phosphate, and silicic acid,
respectively.
To confirm and quantify these possible correlations, four partial RDAs were also
performed: one partial RDA using all the heterotrophic prokaryotes at once
and one additional partial RDA for each heterotrophic prokaryote subgroup
(LNA, HNA and VHNA). Results of the partial RDA performed on all the
heterotrophic prokaryotes showed that among the six environmental variables
measured during the cruise, salinity and temperature statistically
contribute for 24 and 7.5 % of the variation of the heterotrophic
prokaryotes, respectively. To a lesser extent, phosphate alone explained 3.5 %
of the variability, whereas Chl a, nitrate, depth and silicic acid
explained only 1.8, 1.7, 1.7 and 0.86 %, respectively. The partial RDAs
performed either on LNA, or HNA, or VHNA indicated that environmental
parameters can explain 60, 55 and 27 % of the total variance,
respectively (Table 4). Partial RDA results showed that the spatial related
parameters alone can explain up to 31 % of the variation in the
heterotrophic prokaryote distribution. The depth-related parameters
explained between 6 and 8 % of the variance and finally the
phytoplankton-related group explained a maximum 4 % of the variance in
the LNA heterotrophic prokaryotes. As far as the HNA cluster is concerned,
the joint variation of the spatial- and phytoplankton-related parameters
explained 22 % of the variance.
Partial redundancy analysis performed on each heterotrophic
prokaryote cluster optically resolved by flow cytometry: low nucleic acid
content (LNA), high nucleic acid content (HNA) and very high nucleic acid
content (VHNA). According to the PCA results, Chl a and silicic acid are the
phytoplankton-related variables. Temperature and salinity are the
spatial-related variables. Nitrate, phosphate and depth are the
depth-related variables. Negative values characterized the lack of any
correlation between heterotrophic prokaryote clusters and the variables
tested.
LNA
HNA
VHNA
Total explained variance
60 %
55 %
27 %
Joint variation
Phytoplankton-related and spatial- and depth-related
6 %
-1%
-1%
Partial joint variation
Spatial-related and phytoplankton-related
-1 %
22 %
-4 %
Spatial- and depth-related
9 %
1 %
5 %
Depth-related and phytoplankton-related
3%
1%
0%
Unique variation
Phytoplankton-related
4 %
1 %
1 %
Depth-related
8 %
8 %
6 %
Spatial-related
31 %
23 %
20 %
Discussion
Latitudinal distribution of heterotrophic prokaryotes and
interaction with phytoplankton
The heterotrophic prokaryote clusters defined by flow cytometry are
distributed according to three main areas corresponding to different
seawater masses: (i) the Kuroshio region, where the highest heterotrophic
prokaryote concentrations were measured, (ii) the subtropical gyre and (iii)
the transition zone both characterized by a high variability in the
heterotrophic prokaryote concentrations in the seawater column (Figs. 1, 4
and S2). Influence of the seawater masses was also evidenced at the subgroup
level, where ratios of heterotrophic prokaryote abundances varied along the
latitude (Fig. 5). As a latitudinal partition of the ultraphytoplankton
assemblages was also reported in the same region as described in the study
of Girault et al. (2013b), heterotrophic prokaryotes-phytoplankton
interactions are expected, as already observed in some oligotrophic
conditions (Gasol and Duarte, 2000; Gomes et al., 2015). However, “pure”
phytoplankton-related parameters such as a bottom-up control of the VHNA,
HNA, and LNA distributions only accounted for a small fraction (1–4 %)
of the explained variations and significantly differed from some previous
experiments conducted in oligotrophic conditions (Sherr et al., 2006;
Bouvier et al., 2007; Van Wambeke et al., 2011). The lack of important
correlation between such phytoplankton-related parameters and heterotrophic
prokaryotes should be nuanced by the high percentage (22 %) of the
partial joint variation (spatial- and phytoplankton-related parameters)
found for the HNA cluster. It highlighted that phytoplankton-related
variables were less important for VHNA and LNA than HNA. This variability
may indicate that the species in the HNA cluster better interacted with the
phytoplankton than those in the LNA or VHNA clusters. This is in agreement
with a study of Gasol et al. (1999). This interaction can be reinforced by
the predominant role of the temperature, confirmed by the statistical
analysis. Indeed, temperature is known to control the activity of
heterotrophic prokaryotes in the NPSG (White et al., 2012). Consequently,
the partial RDA evidenced and quantified that: (i) the LNA distribution is
mainly explained by temperature and salinity and (ii) HNA distribution is
mainly explained by an association of variables (temperature, salinity, Chl a, and silicic acid) rather than a single environmental factor.
The choice of the association of Chl a and silicic acid in the
phytoplankton-related cluster was motivated by the PCA and RDA results.
Considering the Chl a concentration as a proxy of phytoplankton biomass,
evidences of local Si depletion associated with blooms of diatoms was
reported in the Kuroshio Current area (Hashihama et al., 2014). This study
also pointed out that large phytoplankton can be in part controlled by the
availability of the silicic acid in this very region. However, the effect of
silicic acid on phytoplankton over a larger scale was unexpected, such as
the lowest concentrations of phosphate and nitrate reported in the euphotic
layer of the western part of the NPSG area (Hashihama et al., 2009, 2014;
Girault et al., 2013b). Moreover, Si : N : P stoichiometry identified nitrogen
and/or phosphorus to be potential limiting factors during the Tokyo–Palau
cruise. As far as the smaller phytoplankton sizes are concerned, the nature
and the importance of silicic acid uptakes are still controversial. It is
the case in this cruise especially when low concentrations of large
silicified organisms were measured. However, a high efficient uptake of
silicic acid in the NPSG explained by a regeneration mechanism initiated
from the marine bacterial assemblages and/or Si-bioaccumulation in some
strains of Synechococcus could in part explain the statistical association of Chl a-Silicic
acid as found in this study and already described in the
literature (Bidle and Azam, 1999; Baines et al., 2012; Krause et al., 2012).
Nutrient fluxes and their biological relevance in a stratified
system
In addition to the latitudinal pattern, the hierarchical classification also
demonstrated a vertical variation of the heterotrophic prokaryotes
distributions during the Tokyo–Palau cruise (Cluster 3; Table 3; Fig. 6).
Association of both latitudinal and vertical variations of VHNA, HNA and LNA
abundances are uncommon in oligotrophic conditions and it confirmed the
complexity of mesoscale structures reported in Aoki et al. (2002) and Van
Wanbeke et al. (2011). This stratified environment was particularly well
defined by the pronounced thermocline and nutricline and lead to a possible
relationship between nutrient concentrations and heterotrophic prokaryotes
clusters (Girault et al., 2013b). Although the partial RDA showed that the
“pure” depth-related variables poorly explained the total heterotrophic
prokaryotes variance (6–8 %), the sum of their joint effect can explain
more than 26 % of the total variation in the LNA distribution, underlying
the differences in nutrient utilisation and requirements at the subgroup
levels. From the perspective of nutrients these results also suggested that
LNA cluster was less abundant than HNA under low phosphate and nitrate
conditions (Fig. 4). This is in contrast with the hypothesis proposed for
severely P-limited environments which suggests that inorganic phosphorus can
exert more severe physiological constraints on the growth of HNA than LNA
(Nishimura et al., 2005; Wang et al., 2007). However, it is important to
note that both LNA and HNA clusters are likely to include different strains
of microorganisms including species adapted to the warm, which have been
shown to have lower minimal P cell quotas (Hall et al., 2008). The link
between these warm-adapted species and the cell nucleic acid content is
however still unclear and depends on the type of environment (Andrade et
al., 2007; Van Wanbeke et al., 2011). According to Andrade et al. (2007),
the variation in the HNA / LNA ratio observed suggests that low nutrient
conditions favoured HNA cells over LNA cells. This result along with the
statistical analysis performed in this study may suggest that HNA species
are more warm-adapted than LNA in the subtropical gyre and transition zone.
Decrease of the VHNA / HNA ratio also suggests that the numerically dominant
species with high nucleic acid content (HNA) might be more warm-adapted than
the cells with the highest nucleic acid content (VHNA). These contrasting
results highlight the complex and non linear link between the cell nucleic
acid contents and the various ecological meanings as reported in Bouvier et
al. (2007) and Van Wanbeke et al. (2009).
As the PCA and RDA analyses did not integrate the nutrient supplies from the
mixed layer, a theoretical estimation of the nutrient inputs was calculated
using the Brunt-Väisäla buoyancy frequencies (Tables 1 and 2). The
results obtained should obviously be taken with caution, especially for
nitrates due to the importance of diazotrophy and to episodic dust
deposition not negligible in the NPSG (Wilson, 2003; Kitajima et al., 2009;
Maki et al., 2011). Moreover, the oscillation of positive and negative
values in phosphate-depleted conditions also pointed out the approximation
linked to the limit of detection of the phosphate concentration (3 nM) in
the oligotrophic upper layer. At the cruise scale, the comparison between
phosphate or silicic acid fluxes and the mixed layer integrated
concentration of nutrients suggested that the daily diffuse fluxes were of
minor importance to resupply nutrients to the surface. Both phosphate,
nitrogen and silicic acid diffuse fluxes were in the range of values
reported in oligotrophic conditions (Gasol et al., 2009; Painter et al.,
2014). This result emphasizes the important role of the microbial loop to
sustain the growth of organisms in the western part of the NPSG. At the
local scale (Sta. 8), signature of the subtropical counter current (STCC)
was also evidenced by the nutrient fluxes despite no noticeable pattern of
observed buoyancy frequency. Due to the various locations of high gradients,
utilisation of nutrients was not uniform and indicated that nitrate from the
bottom layer could support the growth in the vicinity of the STCC layer. The
vertical nitrate input appeared to be important because the association of
nitracline with thermocline mathematically maximized the daily flux related
to the standing pool. Although, Fig. 4 did not evidence particular
distribution of heterotrophic prokaryotes close to the STCC layer,
integrated heterotrophic prokaryote abundance and carbon biomass of HNA in
the subtropical gyre area were maximum at station 8 (Fig. S3). This result
is also observed for the ultraphytoplankton distribution where high
concentrations were found at this very station (Girault et al., 2013b). In
contrast to the low nutrient fluxes observed at the cruise scale,
relationships between the STCC and microbial food web via the nutrients fluxes
appeared to be an important mechanism to sustain the ecosystem in the very
subtropical pacific gyre area.
Distribution of heterotrophic prokaryotes and eddies
In oligotrophic conditions, environmental factors controlling the
distribution of the heterotrophic prokaryotes have usually been compared for
two extreme cases: under and outside the influence of an eddy (Baltar et al.,
2010). However, few investigations have only addressed the distribution of
heterotrophic prokaryotes along a spatial oligotrophic gradient (Thyssen et
al., 2005) or taken into account the age of the eddy (Sweeney et al., 2003;
Rii et al., 2008). Among the two notable eddies crossed during the
Tokyo–Palau cruise, the cold-core mesoscale structure C was found at
station 3 (Fig. 6). With a lifespan exceeding 6 months, this cold-core eddy
was particularly older than common cyclonic eddies generated by the Kuroshio
instability as reported by the Japan Coast Guard data centre
(∼ 1 month). A six month old cyclonic eddy in the “closed” model can
be associated with its decay phase, where intense blooms can be observed but
which lack significant diatom abundance (Seki et al., 2001). As the pumping
effect and the highest microphytoplankton concentration were found at
station 3, the classical biogeochemical properties normally associated with
an eddy (i.e. single nutrient pulse, “closed system”) cannot correctly
describe the cyclonic eddy encountered during the Tokyo–Palau cruise. This
shift between theory and observation was also reported in other oligotrophic
areas (Seki et al., 2001; Bidigare et al., 2003; Vaillencourt et al., 2003;
Landry et al., 2008). With three stations only (Stations 2, 3, and 4), only a
snapshot of the eddy effects could be presented and it remains difficult, not
to say impossible, to describe further the local effect of the eddy during
the cruise. By being aware of this limitation, a more complex approach
including the path of the eddy associated with multiple nutrient inputs has
been purposed to explain the variability in microorganisms as demonstrated by
Nencioli et al. (2008). This scenario did match well with the Tokyo–Palau
data set, where the cold core of the cyclonic eddy moved to the north-west
between December and the sampling time of the cruise. The path of the cold
core cyclonic eddy could explain the possible decrease in the nutrient uptake
from the bottom layer at station 4 and lead to an oligotrophic system
dominated by regeneration processes. The high abundance of heterotrophic
prokaryotes measured at the edge of the cyclonic eddy could be explained by
the high activity in the microbial loop. This activity can be in part
enhanced by a more efficient vertical exchange of seawater masses at the
periphery rather than at the centre of the eddy (Stapleton et al., 2002;
Klein and Lapeyre, 2009). Similarly, the numerical dominance of Synechococcus, observed only once in the surface samples during the cruise,
may be the result of the change in trophic conditions (Girault et al.,
2013b).
In contrast to the frontal structures reported in the literature
(Arístegui and Montero, 2005; Baltar et al., 2009; Lasternas et al.,
2013), the second eddy (A) located between the subtropical gyre and the
transition zone was characterized by the lowest concentrations of
heterotrophic prokaryotes found during the cruise. These low concentrations
were noticeable for all the clusters (LNA, HNA and VHNA) and suggested that
the anticyclonic eddy did not enhance nor limit one particular heterotrophic
prokaryote cluster between the surface and the bottom of the thermocline
(Fig. 4). The high increase in VHNA and LNA compared to HNA, below the
thermocline were uncommon in the meso- and bathypelagic zones of
oligotrophic areas where the concentration of HNA and LNA decreased
significantly with depth (Van Wambeke et al., 2011; Yamada et al., 2012).
Among the environmental variables apt to influence the ratio of the
heterotrophic clusters, increase in nutrient concentrations associated with
the sloppy feeding mechanism may partially lead to the high abundance of
VHNA observed at the bottom of the euphotic layer, as previously reported by
Thyssen et al. (2005). The sloppy feeding hypothesis is ecologically
coherent because the limit of the euphotic layer was not coupled with the
thermocline, underlying that a part of the organic material produced in
surface could be transported below the euphotic layer by vertical migration
of organisms, improving the grazing activity.
Conclusions
This study along a 2300 km transect in the North Pacific subtropical gyre
area during strong La Niña conditions showed that the heterotrophic
prokaryote distribution is correlated with three different seawater masses
identified as (i) the Kuroshio, (ii) the subtropical gyre and (iii) the
Transition zone. A latitudinal increase in the HNA / LNA ratio was found along
the equatorward oligotrophic gradient and suggested different relationships
between the various heterotrophic clusters and the environmental variables
measured in situ during the cruise. The statistical analyses highlighted
that the majority of the heterotrophic prokaryote distribution is explained
by temperature and salinity. Nutrients and phytoplankton-related variables
had different influences depending on the LNA, HNA and VHNA clusters. LNA
distribution is mainly correlated with temperature and salinity while HNA
distribution is mainly explained by an association of variables
(temperature, salinity, Chl a and silicic acid). During the cruise, two
eddies (one cyclonic and one anticyclonic) were crossed. The vertical
distributions of LNA, HNA and VHNA were investigated. Based on the current
surface map and the microorganism distribution, it is reasonable to form the
hypothesis that the high concentration of heterotrophic prokaryotes observed
at station 4 was linked to the path of the cold cyclonic eddy core. In
contrast, in the warm core of the anticyclonic eddy, lower heterotrophic
prokaryote concentrations are suggested to be linked to the low nutrient
concentrations. Results described in this study highlight the high
variability of each heterotrophic prokaryote cluster defined by their
nucleic acid content (LNA, HNA, and VHNA) with regard to the mesoscale
structures and the oligotrophic gradient observed in situ within the area of
the North Pacific subtropical gyre.