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Author's personal copy
Journal of Experimental Marine Biology and Ecology 368 (2009) 59–66
Contents lists available at ScienceDirect
Journal of Experimental Marine Biology and Ecology
j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / j e m b e
Trophic interactions within the microbial food web in the South China Sea revealed
by size-fractionation method
Bingzhang Chen a, Hongbin Liu a,b,⁎, Zongling Wang c
a
b
c
Atmospheric, Marine, and Coastal Environment (AMCE) Program, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
Department of Biology, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
First Institute of Oceanography, State Oceanic Administration, Xianxialing Road, Hi-tech Industrial Park, Qingdao, 266061, Shandong, People's Republic of China
a r t i c l e
i n f o
Article history:
Received 10 April 2008
Received in revised form 9 October 2008
Accepted 9 October 2008
Keywords:
Grazing
Microbial food web
Picoplankton
Size­fractionation
a b s t r a c t
To define nanoflagellate-bacteria interactions and potential trophic levels within the microbial food web in
the oligotrophic South China Sea, we conducted fourteen size-fractionation experiments in which seawater
was filtered through 1, 2, 5, 10, 20, 60, and 200 μm membranes or meshes and the growth of four groups of
picoplankton, Prochlorococcus, Synechococcus, high DNA heterotrophic bacteria, and low DNA heterotrophic
bacteria were monitored in each filtrate after 24 hours of incubation. Removing grazers by filtration would
relieve the grazing pressure on lower trophic levels which finally influenced the net growth rates of
picoplankton. The growth patterns of Prochlorococcus and Synechococcus were similar, with higher growth
rates in the b 1 μm or b 2 μm treatments, a second peak in the b10 μm treatments and often a third peak in the
b 200 μm treatments. The net growth rates of low DNA heterotrophic bacteria were little influenced by sizefractionation. Due to a subgroup of high DNA heterotrophic bacteria with larger size and higher DNA content
which appeared to resist the grazing by b5 μm nanoflagellates, the net growth rates of high DNA
heterotrophic bacteria were higher in the b 2 μm or b 5 μm treatments with a second peak in the b 60 μm
treatments. A general pattern of five potential trophic levels (b 2 μm, 2-5 μm, 5-10 μm, 10-60 μm, 60-200 μm)
was revealed combining all the experiments, confirming the existence of multiple trophic levels within the
microbial food web in the oligotrophic South China Sea.
© 2008 Elsevier B.V. All rights reserved.
1. Introduction
The South China Sea (SCS) is the second largest marginal sea in the
world that resembles other subtropical oceans in the warm and
oligotrophic condition. In spite of nutrient inputs delivered by several
large rivers including Pearl River and Mekong River, the upper water
column of SCS is often stratified and remains oligotrophic especially in the
summer and, as such, primary production is often limited by the
availability of inorganic nutrients (Wong et al., 2007). Picophytoplankton
dominate phytoplankton biomass and primary production in the central
South China Sea (Ning et al., 2005; Liu et al., 2007). The food web structure
of SCS is not well studied as compared to the physical oceanography (e.g.
Su, 2004). Due to its warm and oligotrophic nature and the predominance
of picoplankton, it is anticipated that the microbial loop should be the
dominant pathway of carbon cycling and energy flow. Bacterivory is the
first step by which energy and material are transferred from bacteria to
upper trophic levels. The major bacterivores are nanoflagellates in the
nutrient-scarce open ocean, which in turn are grazed by microzooplankton such as ciliates (Azam et al., 1983).
⁎ Corresponding author. Department of Biology, Hong Kong University of Science and
Technology, Clear Water Bay, Hong Kong. Tel.: +852 23587341; fax: +852 23581559.
E-mail address: [email protected] (H. Liu).
0022-0981/$ – see front matter © 2008 Elsevier B.V. All rights reserved.
doi:10.1016/j.jembe.2008.10.012
We used the size-fractionation method, which is often used to
separate predator and prey in aquatic systems (e.g. Wikner and
Hagstrom, 1988; Calbet et al., 2001; Christaki et al., 2001), to study the
food web structure in the SCS by simplifying the complex food web
into a linear food chain. Our main goal is to characterize bacteriananoflagellate interactions and find out potential trophic levels within
the microbial food web in the SCS. In aquatic environments, defining
trophic levels based on size may be more useful than based on taxonomy (Jennings, 2005). Generally, single-cell phagotrophic protists are
only able to ingest prey cells smaller than themselves except for
heterotrophic dinoflagellates which can ingest prey similar to or even
larger than their own sizes (Hansen, 1992). A synthesis by Hansen
et al. (1994) reveals that within the microbial loop, the optimal
predator-prey linear size ratio may range from 1:1 (for heterotrophic
dinoflagellates) to 8:1 (for ciliates). Moreover, the predator-prey size
ratio tends to be smaller at lower trophic levels (Jennings, 2005). For
example, the optimal predator-prey linear size ratios were around 2 or
3:1 for the smallest grazer, nanoflagellates, and around 8:1 for larger
grazer, ciliates (Hansen et al., 1994). Hansen et al.'s synthesis provides
a reasonable rationale to study the trophic interaction of microbial
food web simply by size based manipulation. After removing grazers
of different sizes, grazing pressures on their prey will be relieved
and the growth rate of the prey will be affected. Inclusion of larger
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B. Chen et al. / Journal of Experimental Marine Biology and Ecology 368 (2009) 59–66
Fig. 1. Experimental stations in the South China Sea. Summer stations: E207, E 305, E412, E802, E409, B02, E709, E404. Winter stations: A1, M02, Y24, Y32, Y44, Z98.
predators will indirectly increase the net growth of bacteria by feeding
on bacterivores if the direct grazing effect of larger predators on
bacteria is smaller than that of bacterivores. Using similar approach,
Wikner and Hagstrom (1988) showed that small nanoflagellates
(1 ~ 5 μm) had the greatest bacterivory impact on bacteria in the
Mediterranean Sea. Caron et al. (1991) also demonstrated that nanoplankton (b20 μm) accounted for most of the grazing mortality of
Synechococcus and heterotrophic bacteria in the coastal waters of
Massachusetts.
2. Materials and methods
A total of fourteen experiments were conducted in late summer
(September, 2006) and early winter (December, 2006). The stations in
summer were B02, E404, E709, E207, E305, E412, E409, and E802 and
the winter stations were A1, M02, Y24, Y32, Y44, and Z98 (Fig. 1).
Seawater was collected from the surface using a clean plastic bucket
Table 2
Abundances of major microbial components at sampling stations measured by flow
cytometry
Abundances (103 cells mL- 1)
Table 1
Depth (m) and temperature (°C), salinity, and size-fractionated Chl α concentrations
(μg L- 1) in the surface water at 14 sampling stations
Station
Date
Total
depth
Temperature
Salinity
b 5 μm
Chl α%
Total
Chl α
B02
E412
E409
E404
E305
E207
E709
E802
A1
Y44
M02
Y24
Y32
Z98
2006-9-15
2006-9-16
2006-9-17
2006-9-19
2006-9-20
2006-9-21
2006-9-26
2006-9-27
2006-11-27
2006-12-1
2006-12-5
2006-12-6
2006-12-8
2006-12-16
1449
3265
3935
3619
147
61
42
1150
976
1593
3740
4100
2390
4030
29.0
29.1
29.7
29.2
28.5
27.9
26.8
28.6
26.8
27.6
28.3
28.1
27.8
26.5
33.8
33.8
34.0
33.6
33.6
33.8
33.4
33.6
33.7
33.7
33.3
33.4
33.6
33.8
71.1%
82.4%
74.3%
80.6%
87.0%
73.7%
49.9%
93.0%
78.2%
80.2%
69.5%
74.4%
77.5%
64.5%
0.185
0.082
0.117
0.228
0.262
0.319
0.492
0.177
0.110
0.110
0.164
0.089
0.096
0.335
Station
Pro
Syn
Peuk
HNAbac
LNAbac
Total
hbac
Anan
Hnan
LNAbac/
Hbac
B02
E412
E409
E404
E305
E207
E709
E802
A1
Y44
M02
Y24
Y32
Z98
128.4
112.4
81.0
176.5
121.9
119.4
0
189.9
174.2
204.7
142.3
141.7
144.4
143.1
15.10
25.00
19.21
4.14
7.63
30.96
36.65
9.55
14.41
10.22
7.63
3.66
3.91
38.28
0.74
1.15
0.95
1.22
1.19
3.87
2.21
0.89
1.14
1.05
0.71
0.62
0.75
17.69
166.7
207.8
185.3
158.8
83.1
208.0
362.9
112.6
49.0
90.6
105.2
57.2
96.6
240.1
219.4
451.5
389.9
280.0
228.3
342.6
532.4
297.1
283.6
326.9
289.6
219.8
246.8
400.4
386.1
659.3
575.2
438.8
311.4
550.6
894.3
409.7
332.6
417.5
394.7
277.0
343.4
640.5
ND
0.14
0.39
ND
0.38
0.31
ND
0.39
0.43
0.23
0.74
0.22
0.71
1.24
ND
0.27
0.43
ND
0.29
0.14
ND
0.57
0.34
0.50
1.11
0.52
0.42
0.91
0.57
0.68
0.68
0.64
0.73
0.62
0.60
0.73
0.85
0.78
0.73
0.79
0.72
0.63
(Pro:Prochlorococcus, Syn: Synechococcus, Peuk: picoeukaryotes, HNAbac: high DNA
heterotrophic bacteria, LNAbac: low DNA heterotrophic bacteria, Hbac: heterotrophic
bacteria, Anan: autotrophic nanoplankton, Hnan: heterotrophic nanoplankton). ND: not
determined.
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and was gently siphoned into a clean 10 liter polycarbonate (PC)
carboy. Immediately, the seawater was filtered through 1 (only in
summer), 2, 5, 10 μm PC membranes and 20, 60, and 200 μm nylon
meshes under low vacuum or by gravity. In the winter, we used
unscreened seawater to replace the 200 μm screened water. The
filtered seawater was gently filled into triplicate 250 ml (1, 2, 5, 10 μm)
or 500 ml (20, 64, 200 μm) clean PC bottles to capacity. All the bottles,
61
tubings, and meshes were acid washed and rinsed with distilled water
before and between each use. All the bottles were tightly capped after
filling and incubated on deck for 24 h cooled by running seawater. A
neutral screen covered the bottles to avoid strong solar radiation.
For picoplankton analysis, one 2 ml subsample was taken from
each bottle before and after incubation. The samples were fixed with
0.2% seawater buffered paraformadehyde and frozen in liquid nitrogen
Fig. 2. Net growth rates of Prochlorococcus (Pro, solid line) and Synechococcus (Syn, dotted line) in different treatment bottles at summer (E207 – E404) and winter (A1 – Z98) stations.
Error bar = SD.
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B. Chen et al. / Journal of Experimental Marine Biology and Ecology 368 (2009) 59–66
until analysis (Vaulot et al., 1989). After thawing, a FACSCalibur cytometer (Becton-Dickson) was used to count the densities of picophytoplankton and heterotrophic bacteria. Different populations of
picophytoplankton (Prochlorococcus (Pro), Synechococcus (Syn), and
picoeukaryotes (Peuk)) were distinguished based on side scattering,
orange and red fluorescence (Olson et al., 1993). Yellow-green fluorescent beads (1 μm, Polysciences Inc.) were added to the samples as
an internal standard. For counting of heterotrophic bacteria (Hbac),
SYBR Green I was added to the sample at the final concentration of
0.01% of the original stock (Molecular Probes Inc.) (Marie et al.,
1997). The flow rate was 1 μL s- 1 for picophytoplankton analysis,
and 0.25 μL s- 1 for bacteria analysis. The cytograms were analyzed
using the software Cytowin 4.3 (Vaulot, 1989). To distinguish high
DNA heterotrophic bacteria (HDNAbac) from low DNA heterotrophic bacteria (LDNAbac), the software of WINMDI 2.9 (developed
by Joseph Trotter) was used to enumerate the two groups. Because
Fig. 3. Net growth rates of high DNA heterotrophic bacteria (HDNAbac, solid line) and low DNA heterotrophic bacteria (LDNAbac, dotted line) in different treatment bottles at summer
(E207 – E404) and winter (A1 – Z98) stations. Error bar = SD.
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B. Chen et al. / Journal of Experimental Marine Biology and Ecology 368 (2009) 59–66
surface Pro cells could not be distinguished from HDNAbac when stained
by SYBR Green I, the number of HDNAbac was calculated by deducting the
number of Pro from the total high DNA bacterial number. Assuming
picoplankton grew exponentially, the net growth rates (k, d- 1) were
calculated as k =ln(N24h/N0h) where N24h and N0h were the abundances of
picoplankton at 0 h and 24 h of the incubation respectively.
For the initial chlorophyll a (Chl a) analysis, 500 ml seawater was
first filtered through a 5 μm PC membrane and then through a GF/F
glass fiber filter (Whatman). The filters were kept frozen at -20 °C
until analysis. Chl a concentrations were determined on a Turner
designed fluorometer (Model # 040) after extraction by 90% acetone
at 4 °C in the dark for 20 hours using the acidification method
(Strickland and Parsons, 1972).
We counted the initial abundances of nanoplankton for 11 experiments. For counting of nanoplankton, seawater with the volume
ranging from 20 to 50 mL was first fixed with glutaradehyde (final
concentration 0.5%) and stained by 4'6-diaminodino-2-phenylindole
(DAPI), then filtered onto a dark 0.8 μm PC membrane under low
vacuum within 24 hours of fixation (Port and Feig, 1980). The membranes were immediately mounted on slides after a quick breath. A
drop of immersion oil was used between the membrane and the
coverslip. The slides were kept frozen at -20 °C until being inspected
with an epifluorescence microscope (Olympus BX51) under UV excitation at the magnification of 1000X and at least 50 cells were
enumerated for each slide. Autotrophic cells were distinguished from
heterotrophic cells based on the appearance of red fluorescence under
blue light excitation.
Meta-analysis was performed to combine the data from all the
experiments to see the general effect of the exclusion of grazers in
various sizes (Hedges et al., 1999). Each experiment was weighed
according to its standard error (precision). Assuming that the weighed
effect had a normal distribution, we chose the random model to
investigate whether the growth responses of picoplankton were
significantly different between treatments using the software Comprehensive Meta Analysis (Version 2, Biostat). We chose the mean
differences in growth rates as the effect sizes since they were the same
as natural log of response ratios (Hedges et al., 1999). A treatment
effect was considered significant when the 95% confidence interval
did not overlap with zero.
63
treatments. In the b200 μm treatments, the net growth rates of Pro
and Syn sometimes also showed a third peak. Lower net growth rates
in the b5 μm treatments showed that the primary grazers for Pro and
Syn were small HNFs in the size range between 2 μm and 5 μm. The
second peak in the b10 μm or b20 μm treatments was related to the
trophic cascading, i.e. the presence of 5 ~ 20 μm sized HNFs (may also
include some small dinoflagellates and ciliates) significantly increased
the net growth of Pro and Syn presumably due to the consumption of
b5 μm HNFs by 5-20 μm grazers. The second peak of Pro or Syn was
not obvious at some stations like E207 and B02 which may reflect a
compensated effect of both increased grazing activity on Pro or Syn of
5 ~ 10 μm grazers and reduced grazing activity of 2 ~ 5 μm HNFs. The
net growth rates of Pro or Syn often decreased again in the b60 μm
treatments in which most ciliates and heterotrophic dinoflagellates
were included. These microzooplankton might primary feed on nanozooplankton (5 ~ 10 μm), which relieved the grazing pressures on the
2 ~ 5 μm HNFs, which then consequently enhanced the grazing
pressures on Pro or Syn. At most of the stations, the increased net
growth rates of Pro or Syn in the b200 μm treatments suggested that
60 ~ 200 μm microzooplankton (mostly large ciliates, large heterotrophic dinoflagellates and small metazoans) mainly fed on 10 ~ 60 μm
microzooplankton. In some experiments where the net growth rates
of Syn were not significantly influenced by filtration, the lack of impact
might be due to low grazing rates or nutrient limitation on Syn growth
since removing grazers could block the pathway of nutrient regeneration. Syn has been shown to be more easily nutrient limited than
Pro (Glover et al., 1988; Campbell et al., 1997).
Next, we examined the growth patterns of heterotrophic bacteria
which were separated into HDNAbac and LDNAbac (Fig. 3). The variation of the net growth of LDNAbac was much small among different
size-fractionated treatments compared to that of HDNAbac, suggesting that the overall grazing pressure on LDNAbac was small although
they constituted a greater portion of total bacterial abundance than
HDNAbac did. Less grazing pressure on LDNAbac compared to HDNAbac
has been reported elsewhere, and LDNAbac have been referred as
“inactive cells” (Gasol et al., 1999).
The overall growth patterns of HDNAbac were different from those
of Pro or Syn in that the most intense grazing pressure occurred in the
3. Results and discussion
3.1. Ambient biological parameters
Size-fractionated Chl a concentrations of the 14 experimental
stations are given in Table 1. Abundances of picoplankton and nanoplankton are given in Table 2. Generally, these stations represented
oligotrophic conditions of SCS, with the biomass dominated by small
phytoplankton. Chl a concentrations in the surface water ranged from
0.08 to 0.49 μg L- 1, with 50% to 93% of the Chl a passing through 5 μm
membranes. Pro was absent at an onshore station E709, while at other
stations its abundances ranged from 8.1 × 104 to 2.0 × 105 cells mL- 1.
The abundances of Syn ranged from 3.7 × 103 to 3.8 × 104 cells mL- 1. The
abundances of Peuk were more variable, ranging from 6.2 × 102 to
1.8 × 104 cells mL- 1. The abundances of Hbac ranged from 2.8 × 105 to
8.1 × 105 cells mL- 1, with LNAbac accounting for 60% to 85% of the total
Hbac abundance. The abundances of heterotrophic nanoflagellates
(HNFs), which were numerically dominated by b5 μm HNFs, varied
from 267 to 1108 cells mL- 1 (Table 2).
3.2. Variations of picoplankton growth in different treatments
We first examined the growth responses of autotrophic prokaryotes (Pro and Syn) (Fig. 2). The growth patterns of Pro and Syn were
generally similar, with the highest net growth rates in the b1 or b2 μm
treatments and another peak in the b10 μm (sometimes b20 μm)
Fig. 4. A typical flow cytometric cytogram of heterotrophic bacteria showing B-IV
bacteria in b 60 μm treatments after incubation at A1.
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B. Chen et al. / Journal of Experimental Marine Biology and Ecology 368 (2009) 59–66
b10 μm treatments, not the b5 μm treatments. The average net growth
rates of HDNAbac in the b5 μm treatments were even slightly higher
than in the b2 μm treatments (Fig. 3). This phenomenon was related
with the occurrence of a subgroup of HDNAbac with larger size (side
scattering) and greater DNA content (green fluorescence) (Fig. 4),
which was similar to the “B-IV bacteria” described by Jochem (2001).
This group of bacteria was presumably resistant to small nanoflagellate (b5 μm) grazing due to their large size or shape and subject to
grazing by larger flagellates (5 ~ 10 μm). Microscopic observations also
confirmed the existence of filamentous heterotrophic bacteria
retained on 0.8 μm membrane filters in some treatments. In the
initial samples of the experiments, the numbers of bacteria of this
subgroup were quite small and they often could not be clearly distinguished from other HNAbac on the cytograms. Given the low
abundances of this B-IV like bacteria in natural samples, it was highly
possible that some of other groups of heterotrophic bacteria might
Fig. 6. Results of meta-analysis comparing the net growth rates (k, d- 1) of Prochlorococcus (Pro), Synechococcus (Syn), and high DNA heterotrophic bacteria (HDNAbac)
between the treatments of the b5 μm and b 2 μm (kb 5 – kb 2), the b 10 μm and b 5 μm
(kb 10 – kb 5), the b 60 μm and b10 μm (kb60 – kb10), and the b200 μm and b60 μm
(kb 200 – kb 60). Effect sizes are the differences of the means and error bars show the
95% confidence intervals. The net growth rates are significantly different if the error
bars do not overlap with zero (p b 0.05). A positive value of effect size means the net
growth rate in the former treatment is higher than in the later treatment. N is 12 for Pro
and 13 for Syn and HDNAbac when comparing the treatments of b 5 μm and b 2 μm and
the treatments of b10 μm and b5 μm. N is 13 for Pro and 14 for Syn and HDNAbac when
comparing the treatments of b 60 μm and b 10 μm and the treatments of b 200 μm and
b60 μm.
have changed into this group in the presence of grazers (Pernthaler
et al., 1997; Hahn and Hofle, 1998). Hahn and Hofle (1998) have
reported that even one single species of bacteria could increase the
cell volume and change from non-filamentous to filamentous shape
when nanoflagellates were introduced. If excluding the B-IV like group
of bacteria, the variations of net growth rates of other HDNAbac were
similar to Pro or Syn (Fig. 5), i.e. high in b2 μm treatments, low in
b5 μm treatments, high in b10 μm treatments, low in b20 μm or
b60 μm treatments, and high again in b200 μm treatments.
Due to the occurrence of the B-IV like bacteria, the growth patterns
of HDNAbac were totally different to the patterns of Pro or Syn. Their
growth was severely suppressed in the b10 μm treatments, enhanced
again in the b20 μm or b60 μm treatments and suppressed again in the
b200 μm treatments (Fig. 3). However, the food web structure revealed by this pattern were essentially the same with that revealed by
the dynamics of Pro or Syn, i.e. 10 ~ 60 μm grazers primarily fed on
5 ~ 10 μm HNFs and 60 ~ 200 μm grazers fed on 10 ~ 60 μm grazers.
We used meta-analysis to check if differences between treatments
were statistically significant. The net growth rates of Pro and Syn in
the b5 μm treatments were significantly lower than in the b2 μm
treatments, while no significant differences of net growth rates of
HDNAbac were observed between b5 and b2 μm treatments (Fig. 6).
The net growth rates of Pro in the b10 μm treatments were significantly higher than in the b5 μm treatments, while the 95% confidence intervals of net growth rate differences of Syn between b10
and b5 μm treatments slightly overlapped with zero. In contrast, the
net growth rates of HDNAbac in the b10 μm treatments were significantly lower than in the b5 μm treatments. The net growth rates of
Syn in the b 60 μm treatments were significantly lower than in the
b10 μm and b200 μm treatments, while the net growth rates of
HDNAbac were significantly higher in the b60 μm treatments than
other two treatments. The net growth rates of Pro in the b60 μm
treatments, however, were not significantly different from the b10 or
b200 μm treatments, but the general pattern was the same as of Syn.
3.3. Implications for marine microbial food web
Fig. 5. Net growth rates of B-IV bacteria (left panel) and other high DNA bacteria
(not including Prochlorococcus) in different treatments at five stations where the occurrences of the B-IV bacteria were most pronounced.
Although our assumption that one size range represents one trophic level is an oversimplification of the real complex microbial food
web, chain-like responses of picoplankton net growth rates were often
observed in our experiments, which support that multiple trophic
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B. Chen et al. / Journal of Experimental Marine Biology and Ecology 368 (2009) 59–66
levels do exist within the microbial food web (Wikner and Hagstrom,
1988; Calbet et al., 2001; Landry, 2002). A general pattern of 5 trophic
levels on average defined by size (b2 μm, 2 ~ 5 μm, 5 ~ 10 μm,
10 ~ 60 μm, 60 ~ 200 μm) within the microbial food web appeared to
be a common feature in the oligotrophic SCS. Although SCS is an
unproductive, oligotrophic ecosystem which is suggested to sustain
short food chain length (Oksanen et al., 1981; Kaunzinger and Morin,
1998), large ecosystem size and small predator-prey size ratios can
support longer food chain lengths (Post et al., 2000; Jennings, 2005).
Wikner and Hagstrom (1988) also demonstrated that even within the
nanoplanktonic size range, 4 trophic levels could exist. It is possible
that some grazers are within the b2 μm range which could be overlooked in our experiments (Fuhrman and McManus, 1984). A longer
food chain implies less efficient carbon flux and energy flow within
the food web because most of the carbon would be respired and only a
small amount of biomass can be transferred to higher trophic level or
exported to the deep sea (Landry and Calbet, 2004). For example,
assuming a trophic transfer efficiency of 30%, the percentage of picoplankton production that is directly transferred to mesozooplankton
production will be only 0.35 = 0.24%.
However, as phytoplankton size can range from b1 μm to N100 μm,
the microbial food web can consist of multiple food chains which start
from different sizes of primary producers and are composed of different food chain lengths (Armstrong, 1994). Therefore, assessing the
transfer efficiency of total primary production to mesozooplankton
production can only be achieved by incorporating all the microbial
food chains with knowing the contribution of primary production and
trophic transfer efficiency in each respective microbial food chain.
One inference from our experimental results is that grazers of
picophytoplankton could be limited by predation by larger predators.
This leads us to be aware of the effects of possible changes of microzooplankton composition on the estimates of growth and mortality of
picoplankton when using the dilution technique (Landry and Hassett,
1982). According to Agis et al.'s (2007) observation, large ciliates had
a negative growth in diluted treatments due to starvation which
would release grazing pressure on HNFs. Increased abundances of
HNFs would increase grazing rates on picoplankton in diluted treatments and therefore grazing rates on picoplankton derived from the
dilution technique would be underestimated. Our results showed that
the microbial trophic levels in the South China Sea might be even
more complex than the generally accepted three trophic level paradigm (picoplankton-HNF-ciliate). It still remains unclear how the
dilution manipulation will affect the microbial food web structure with
several trophic levels and how accurate our estimates of picoplankton
growth and grazing rates are with the dilution technique.
The different responses of HDNAbac and LDNAbac to size-fractionation suggest that in the oligotrophic open ocean, only a small
proportion of heterotrophic bacteria is active and selectively grazed by
HNFs. Current methods to measure bacterivory are often limited at the
community level using killed prey surrogates (e.g. Sherr et al., 1987)
which lack the information of grazing selectivity. It may be interesting
to know the grazing rates of HNFs on both active and inactive bacteria
in the sea with combined approaches such as radioactively labeled live
bacteria (Zubkov et al., 1998) and fluorescently labeled dead tracers
(Vazquez-Dominguez et al., 1999).
Acknowledgements
We thank Prof. D. Wang in the South China Sea Institute of
Oceanology and Prof. M. Dai in Xiamen University, P. R. China, for
providing the cruise opportunities and data of temperature and salinity.
We also thank Y. K. Tam and L. He for logistical help. This study was
supported by the Hong Kong RGC research grant HKUST6414/06M
provided to H. L and a HKUST postgraduate scholarship provided to B. C.
Additional support was provided by the State Key Lab of Marine
Environmental Science (Xiamen University), China. [SS]
65
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