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Transfer of bacterial production based on labile
carbon to higher trophic levels in an oligotrophic
pelagic system
Carolyn Faithfull, Magnus Huss, Tobias Vrede, Jan Karlsson, and
Ann-Kristin Bergström
Abstract: Additions of labile organic carbon (C) enhanced bacterial production (BP) and were associated with increases in
crustacean zooplankton and planktivorous fish biomasses. This was shown in a mesocosm experiment where we traced the
contribution of BP to zooplankton and fish using stable isotopes and labile glucose-C as a biomarker. BP increased with
glucose-C addition, and all zooplankton and fish incorporated some glucose-C. However, the effect of labile-C addition on
zooplankton was taxa-dependant, as although cladocerans incorporated the most labile-C, increased BP did not affect cladoceran biomass. Instead, calanoid copepod biomass increased with glucose addition. This suggests that the ability to selectively graze on high quality food, such as bacterial grazing protists capable of trophic upgrading, had a stronger positive
effect on calanoid copepods biomass than unselective grazing on bacteria and protists had on cladoceran biomass. Higher
BP was associated with increased survival and population growth of young-of-the-year perch (Perca fluviatilis) when
stocked at high densities, which suggested that BP had a density-dependant positive effect on fish growth.
Résumé : Les additions de carbone (C) organique labile augmentent la production bactérienne (PB) et sont associées à des
accroissements des biomasses des crustacés zooplanctoniques et des poissons planctonophages. Cela est bien démontré dans
une expérience en microcosme dans laquelle nous avons pu suivre la contribution de la BP au zooplancton et aux poissons
à l’aide d’isotopes stables et du C-glucose comme biomarqueur. La BP augmente avec l’addition de C-glucose et tout le
zooplancton et les poissons incorporent du C-glucose. Cependant, les effets de l’addition de C labile sur le zooplancton dépend des taxons, puisque même si les cladocères incorporent le plus le C labile, l’augmentation de la BP n’affecte pas la
biomasse des cladocères. En revanche, la biomasse des copépodes calanoïdes augmente avec l’addition de glucose. Cela
laisse penser que la capacité de brouter de façon sélective des aliments de haute qualité, tels que des protistes qui se nourrissent de bactéries et sont capables d’un surclassement trophique, a un effet positif plus fort sur les copépodes calanoïdes, que
le broutage non sélectif de bactéries et de protistes peut avoir sur la biomasse des cladocères. La BP plus élevée est associée
à une survie et une croissance de population plus fortes des jeunes perches (Perca fluviatilis) de l’année lorsqu’elles sont
empoissonnées à forte densité, ce qui laisse croire que la BP a un effet positif dépendant de la densité sur la croissance des
poissons.
[Traduit par la Rédaction]
Introduction
Labile organic carbon (labile-C) can increase in the pelagic
zone because of inflows of low molecular weight allochthonous carbon (originating from terrestrial sources; Berggren et
al. 2010) or in lake processes, such as photo-chemical degradation of allochthonous carbon (Moran and Zepp 1997) or
phytoplankton extracellular carbon release (Sundh and Bell
1992). Changes in labile-C concentrations differ from inputs
of total allochthonous organic carbon in that they do not directly affect the light or nutrient climate (Jones 1992; Jansson
1998). However, the effect of increasing labile-C on basal
production and in turn higher trophic levels is not clear. For
example, increasing labile-C may increase bacterial production (BP) and the total amount of basal energy available for
higher trophic levels (Jones 1992). Alternatively, increased
Received 6 May 2011. Accepted 5 October 2011. Published at www.nrcresearchpress.com/cjfas on 21 December 2011.
J2011-0182
Paper handled by Associate Editor Yves T. Prairie.
C. Faithfull, M. Huss*, T. Vrede†, and A.-K. Bergström. Department of Ecology and Environmental Science, Linnaeus väg 6, SE90187, Umeå University, Sweden.
J. Karlsson. Climate Impacts Research Centre (CIRC), Department of Ecology and Environmental Science, Umeå University, Box 62,
981 07 Abisko, Sweden.
Corresponding author: Carolyn Faithfull (e-mail: [email protected]).
*Present
address: Department of Aquatic Resources, Institute of Coastal Research, Swedish University of Agricultural Sciences,
Skolgatan 6, SE-74242, Öregrund, Sweden.
†Present address: Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Box 7050, SE-750 07
Uppsala, Sweden.
Can. J. Fish. Aquat. Sci. 69: 85–93 (2012)
doi:10.1139/F2011-142
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86
BP may be accompanied by a reduction in basal carbon production in oligotrophic lakes if phytoplankton primary production (PPr) decreases because of competition with bacteria
for phosphorus (Jansson 1998). Although a relatively large
number of studies have examined the effects of labile-C on
the ratio of BP:PPr and total basal production (Bell et al.
1993; Jansson et al. 2006; Stets and Cotner 2008), few have
examined the transfer of labile-C additions to higher trophic
levels such as zooplankton (Daniel et al. 2006; Karlsson et
al. 2007; Berggren et al. 2010), and none have measured the
direct contribution of labile-C to fish biomass.
The transfer of labile-C via bacteria to higher trophic levels depends upon several factors (i.e., the magnitude of BP
(Karlsson et al. 2007), the feeding mode of grazers (Grey et
al. 2001; Persaud et al. 2009), and trophic level of the consumers (Karlsson et al. 2004)). The fraction of bacterial carbon that in turn is transferred to cladocerans and copepods
appears to be proportional to the relative rates of BP and
PPr and also depend on grazing mode (i.e., nonselective filter
feeding versus selective predation; Karlsson et al. 2007). Unselective filter feeding cladocerans are capable of grazing directly on bacteria (Riemann 1985), whereas bacterial cells are
too small for copepods to ingest (Zöllner et al. 2009). However, bacterial carbon can also be transferred to higher trophic levels indirectly through the microbial food chain
(Burns and Schallenberg 2001). Thus, we would expect the
structure of the zooplankton community to affect how efficiently bacterial carbon is transferred through the food web
up to fish, as fewer trophic levels would result in fewer opportunities for respiratory carbon losses (Cottingham et al.
1997; Pace and Cole 2000). Increased BP may also affect
the structure of the zooplankton community by increasing
the number of trophic levels in the food web (Berglund et al.
2007).
In this study we examine the mobilization of glucose via
bacterial grazing. Glucose additions stimulate BP, and by using the distinct stable isotopic signature of glucose compared
with natural carbon sources in the lake, we aim to determine
the fraction of bacterial glucose-C transferred to cladocerans,
copepods, and young-of-the-year (YOY) perch (Perca fluviatilis). We hypothesize that if bacteria are being consumed either directly or indirectly through the microbial loop,
increased BP due to glucose addition should be reflected by
an increased fraction of glucose-C incorporated by metazooplankton and YOY perch. The response to glucose addition
should be more pronounced in zooplankton taxa grazing directly on bacteria (cladocera) than in taxa that utilize bacterial carbon through a longer trophic pathway (copepods). We
expect that taxa incorporating a higher proportion of glucoseC into their tissues may also reach a higher biomass in treatments where BP is stimulated, if BP is an important energy
source supporting somatic growth of zooplankton and fish.
Materials and methods
Experimental design
The experiment was conducted in a small (0.093 km2,
mean depth 6.3 m, maximum depth 12 m), clear oligotrophic
dimictic lake in northern Sweden (64°29′N, 19°26′E) over
44 days in May–July 2007, when epilimnetic temperatures in
the lake were 15.4–19.7 °C and the thermocline was stable at
Can. J. Fish. Aquat. Sci. Vol. 69, 2012
3–3.5 m. Measurements on day 1 (3 June 2007) revealed relatively nutrient poor and low dissolved organic carbon
(DOC) conditions in the mesocosms (mean ± 1 standard error (SE) total nitrogen: 500 ± 35 µg·L–1, total phosphorus
(TP): 8.2 ± 0.29 µg·L–1, DOC: 5.4 ± 0.71 mg·L–1). The 27
mesocosms consisted of transparent cylindrical polyethylene
bags (9 m deep × 1.6 m diameter and 18 m3 volume), filled
with filtered lake water (100 µm mesh size), floated on
wooden rafts at >10 m depth and sealed at the bottom. On
23–28 May we inoculated the mesocosms with zooplankton
at the natural lake density. Zooplankton were collected from
the lake using net hauls (100 µm mesh size), and the pooled
sample was divided equally into separate buckets for each
mesocosm for removal of predatory zooplankton (mainly Bythotrephes sp.). Three levels of YOY perch density and glucose addition were crossed in a full-factorial design and
applied randomly in triplicate to the mesocosms. Glucose (DGlucose, AnalaR) addition treatments were added to the mesocosms 12 times over 6 weeks to give cumulative additions
of 0, 420, and 2100 µg glucose-C·L–1 (control, low, and high
treatments). After each addition, the epilimnion was mixed
with a round disk attached to a 2 m long pole. YOY perch
were added 2 days after hatching at densities of 0 (no fish),
10 (medium), and 30 (high) larvae per mesocosm on day 1.
These densities reflect the naturally observed YOY perch
densities in the lake (Byström et al. 2003). A subsample of
perch larvae was preserved for initial size measurements.
Sampling and analyses
Sampling of the mesocosms occurred on days 1, 16, 31,
and 44 of the experiment. Samples for stable isotope analyses
were collected on days 1 and 44. A Ruttner sampler was used
to obtain a composite epilimnetic sample (5 L). From this
sample, subsamples were taken for total phosphorus and total
nitrogen, DOC, dissolved inorganic carbon (DIC), bacterial
biomass (BB), epilimnetic BP, chlorophyll a (chl-a), and epilimnetic PPr analyses. 10 mL samples for DOC were filtered
through 0.2 µm Millipore filters, acidified with 1 mL of
2 mol·L–1 HCl, and measured using a Shimadzu TOC 5000
analyzer. DIC was determined with the headspace equilibration technique using 350 mL bottles and a 50 mL headspace
and following the methods of Sobek et al. (2006). Bacterial
biomass samples were preserved with filtered glutaraldehyde
(1% final concentration) and measured using acridine orange
staining and the image analysis system LabMicrobe (BioRAS). Biovolume was converted to carbon biomass as
0.106 pg C·µm–1 (Nagata 1986). BP was estimated by incubating triplicate 1.2 mL aliquots plus one trichloroacetic acid
(TCA)-killed control from the epilimnetic subsample, with
8 µL leucine isotope (specific activity 161 Ci mmol·L–1) for
60–90 min in darkness at eplimnetic temperatures (Smith and
Azam 1992). The incubation was ended with 100% TCA and
followed the method in Karlsson et al. (2002). Chl-a samples
were filtered onto Whatman GF/F filters, extracted for 24 h
with 95% ethanol, and measured with a luminscence spectrometer (Perkin Elmer LS45). Chl-a was converted to C using 50 µg C per chl-a unit (Ahlgren 1983). Integrated
epilimnion samples for PPr were incubated in duplicate light
bottles and a dark bottle for 4 h at 1.5 m and followed the
14C method. For more details on PPr methods see Faithfull et
al. (2011). Crustacean zooplankton were captured with a
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Faithfull et al.
100 µm mesh net, hauled from the thermocline (3.5 m) to the
surface, and preserved with Lugol’s solution. Crustacean zooplankton were counted and identified using inverted microscopy (100×). Lengths of 15 (all if fewer) individuals from
each taxa were measured and transformed to dry mass (Bottrell et al. 1976). Carbon content for each taxon was measured
as a proportion of dry mass obtained during isotope analysis
(see below). On day 44 crustacean zooplankton were collected
and stored in filtered lake water at 4 °C overnight before sorting and isotopic analysis. Rotifers, ciliates, and flagellates
were also analyzed; see Faithfull et al. (2011). YOY perch
were removed on day 45 using a 1.6 m diameter (2 mm
mesh) net. Fish dorsal muscle for two fish per mesocosm
was separated, freeze-dried, and homogenized before weighing and packing in tin capsules. As YOY perch had a large
influence on calanoid and Bosmina spp. abundance (Faithfull
et al. 2011), fish treatments were excluded from analyses of
variance (ANOVAs), where we compared zooplankton biomasses between glucose-C treatments. Fish density treatments
were pooled for statistical analysis and graphical representation, unless indicated otherwise.
Stable isotope analysis
We used stable carbon (d13C) isotope to trace the incorporation of glucose-C into zooplankton and YOY perch larvae
and stable nitrogen (d15N) isotope to examine the trophic positions of the main taxa in the food web. Glucose d13C
(–11.6‰) is 13C enriched compared with natural organic C
sources (–27‰ to –43‰) found in northern Swedish lakes
(Karlsson et al. 2007). d13C and d15N isotopic analysis and
C and N content were measured for the most abundant crustacean zooplankton taxa, Bosmina spp. (mostly Bosmina
longirostris), Holopedium gibberum, calanoid copepods
(mostly Eudiaptomus gracilis), and YOY perch using a Carlo
Erba EA 1108 elemental analyzer connected to a Fison Optima isotope ratio mass spectrometer at continuous flow
(University of California Davis stable isotope facility, Davis,
California). All stable isotope values are expressed in the d
per mil (‰) notation: d13C, d15N = (Rsample/Rstandard – 1) ×
100, where R = 13C/12C or 15N/14N. We used the global
standards PeeDee belemnite for d13C and atmospheric nitrogen for d15N, with an analytical precision of <0.3‰. d13C
values of zooplankton and fish were normalized for lipid
content: d13Cnormalized = d13C – 3.32 + 0.99 × C:N (Post et
al. 2007). The lipid normalization affected the results by <1
SE. We assumed that the difference between d13C of zooplankton and fish in the glucose treatments (d13Ctreatment)
compared with the control treatment (d13Ccontrol) was an effect of incorporation of glucose-C (d13Cglucose). Therefore,
the percentage of zooplankton and fish carbon consisting of
glucose-C (%Biomassglucose) in each treatment was estimated
as %Biomassglucose = (d13C – d13Ccontrol)/[d13Cglucose + (TL –
1) × F – d13Ccontrol] × 100, where trophic level (TL) was estimated as 2 for Bosmina spp. and H. gibberum, 3 for calanoid copepods (Karlsson et al. 2007), and 3.5 for YOY perch
(see Results). The assumptions of TL involve a small potential error in the results presented (i.e., ±1 zooplankton TL
corresponds to <1% variation in %Biomassglucose). The trophic fractionation (TF) between zooplankton and its diet
was estimated as 0.4 ‰ (Post 2002). To test the influence
of different fractionation factors on %Biomassglucose, we as-
87
sumed a range in TF values of 0‰–3.8‰ as found in Post
(2002) and Caut et al. (2010). This TF value range affected
%Biomassglucose estimates by <1 standard deviation (SD).
Energy mobilization model
Total epilimnetic energy mobilization (EEM; Bano et al.
1997) was estimated as the sum of PPr and BP in the epilimnion based on allochthonous C (BPaoc): EEM = PPr +
BPaoc. BPaoc was calculated as BP – PPr(0.37) × BGEPPr.
We assumed that 37% of net PPr is available as a C source
for BP (Jansson et al. 2003) and that bacteria have a growth
efficiency of 26% on phytoplankton-produced carbon
(BGEPPr) (del Giorgio and Cole 1998). To calculate BPglucose,
we assumed that the amount of BPaoc remained the same in
the glucose treatments as in the control treatment (BPcontrol)
and that any additional BP in the glucose treatments could
be attributed to bacterial growth on glucose: BPglucose =
BPaoc – BPcontrolaoc. The percentage of BP based on glucose
(%BPglucose) in the glucose addition treatments was calculated
as %BPglucose = BPglucose/BP × 100. The percentage of EEM
based on glucose was calculated as %EEMglucose = BPglucose/
EEM × 100. All production calculations were based on the
sum of production in the epilimnion over the experimental
duration (44 days), but are presented as day–1. We tested the
sensitivity of the above assumptions by using a range of
BGEPPr of 5%–37% and a range in availability of PPr to bacteria of 28%–46%, as in Jansson et al. (2003); this range of
values affected %BPglucose estimates by <1 SD. Bacterial
growth efficiency on glucose (BGEglucose) was calculated as
BGEglucose = BPglucose/glucose uptake. As DOC concentration
did not increase with glucose addition, we assumed that bacteria consumed all added glucose. Individual (averaged per
fish) and population (total fish growth per mesocosm) growth
was calculated as [ln(final mass) – ln(initial mass)]/(no. of
days).
Results
Glucose-C affects basal energy mobilization
BP and DIC increased with glucose addition, although BB
did not (Table 1). DOC did not accumulate in the mesocosms
with glucose addition (Table 1). Additionally, PPr and chl-a
concentrations did not change significantly with glucose addition (Table 1). Thus, the increase in BP could not have
been supported by an increase in organic C availability triggered by increased PPr. Rather, the glucose-C addition must
have increased BP. The increase in BP resulted in an increase
in EEM with glucose addition (Table 1). We estimated that
glucose-C supported 14.8%–20.1% of BP and 2.80%–4.34%
of EEM in the low glucose treatment and 25.0%–30.6% of
BP and 5.64%–6.03% of EEM in the high glucose treatment.
The increases in BP and EEM based on glucose-C from the
low to high glucose treatment (BP: 1.55–2.57× increase and
EEM: 1.30–2.16× increase) were not proportional to the increase in glucose addition (fivefold increase). The fivefold increase in glucose addition halved BGEglucose (low glucose,
420 µg C·L–1: 4.50%–6.75% BGE; high glucose,
2100 µg C·L–1: 2.09%–2.56% BGE). Total EEM was dominated by PPr (81.5%–98.8%) even in the high glucose-C addition treatments.
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Table 1. Means or sums (±1 standard error, SE) of carbon biomasses and production rates for each glucose treatment.
Glucose
addition
Control
Low
High
DIC±SE
(mg·L–1)
0.936±0.011
0.946±0.032
1.02±0.033
DOC±SE
(mg·L–1)
5.94±0.568
6.20±0.547
5.64±0.085
BB±SE
(µg C·L–1)
34.1±3.71
32.7±2.71
36.6±2.73
Chl-a±SE
(µg C·L–1)
52.2±3.91
49.6±3.02
49.2±3.75
BP±SE
(µg C·L–1·day–1)
2.7±0.22
3.2±0.30
4.0±0.48
PPr±SE
(µg C·L–1·day–1)
15.1±1.93
14.0±2.14
16.5±2.05
EEM*
(µg C·L–1·day–1)
16.4 (15.3–17.6)
15.8 (14.8–17.0)
18.9 (17.7–20.3)
F[df]
P
F[2,17] = 14.5
<0.001
F[2,18] = 0.513
0.61
F[2,18] = 0.517
0.61
F[2,18] = 0.624
0.55
F[2,16] = 4.47
0.029
F[2,18] = 0.594
0.56
NA
NA
Note: DIC, dissolved inorganic carbon; DOC, dissolved organic carbon; BB, bacterial biomass; Chl-a, chlorophyll a; BP, bacterial production; PPr, primary
production; EEM, epilimnetic energy mobilization.
*The ranges for EEM (shown in parentheses) are based on a range of values for bacterial growth efficiency and PPr availability for BP.
Isotopic signatures of zooplankton and fish
The d13C signal of crustacean zooplankton and YOY perch
became less negative in treatments with glucose-C addition
(no glucose: –29.5‰ ± 0.163‰, high glucose: –27.9‰ ±
0.163‰), and this was more pronounced with decreasing trophic level (Fig. 1). The d15N signal of crustacean zooplankton
and YOY perch did not change with glucose addition (Fig. 1,
F[2,11] = 0.233, P = 0.800). Bosmina spp. had the lowest d15N
signal (4.07‰ ± 0.181‰), followed closely by H. gibberum
(4.48‰ ± 0.131‰). Assuming a trophic fractionation of
3.4‰ (Post 2002), calanoid copepods (mostly Eudiaptomus
gracilis; d15N: 7.06‰ ± 0.065‰) were located approximately
one trophic level higher than Bosmina spp. and H. gibberum,
and YOY perch were 0.59 of a trophic level above calanoids
(d15N: 9.04‰ ± 0.094‰) (Fig. 1). Up to 12.3% of the biomass of H. gibberum and Bosmina spp. was obtained from
glucose-C, in contrast with 4.70% for calanoids and YOY
perch (Fig. 2). The amount of glucose-C assimilated by individual perch did not vary with fish density (two-tailed t test:
T[9] = –1.32, P = 0.22). The %Biomassglucose for crustacean
zooplankton and fish increased nonlinearly with glucose addition (Fig. 2a), but linearly with BP for all taxa (Fig. 2b). The
slope of %EEMglucose versus %Biomassglucose was 2.05 for
H. gibberum, 2.01 for Bosmina spp., 0.898 for calanoids, and
0.718 for fish (Fig. 2c). Hence, if H. gibberum and Bosmina spp. were consuming BP and PPr proportionally to the
contribution of BP and PPr to EEM, we would expect a slope
of 1; thus, they are consuming twice as much BP relative to
the amount of BP available. Bosmina spp. and H. gibberum
biomass did not differ over time or with glucose addition
(Table 2; Fig. 3). In the treatments without fish, calanoid copepod biomass was higher in the high glucose treatment, but
did not vary significantly between sampling dates (Table 2;
Fig. 3). There was no relationship between calanoid biomass
and BP or PPr. However, calanoid biomass was correlated
with the ciliate Strombilidium spp. biomass (linear mixed
model: Strombilidium = –0.153(calanoid biomass) + 0.316;
P = 0.012) (Faithfull et al. 2011). BP was marginally negatively correlated with Strombilidium biomass (linear mixed
model: Strombilidium = –0.271(BP) + 0.667; P = 0.084);
however, neither Bosmina spp. nor H. gibberum biomasses
were significantly correlated with Strombilidium biomass
(P = 0.769 and P = 0.961, respectively).
Effects on fish survival and growth
Glucose addition did not influence individual growth
(F[1,14] = 1.50, P = 0.24) or survival (general linear model:
Fig. 1. d13C and d15N concentrations (mean ± 1 standard error (SE),
n = 3 per treatment) for the crustacean zooplankton taxa, Bosmina spp. (□), H. gibberum (∇), calanoid copepods (○), and
young-of-the-year (YOY) perch (D) over three levels of glucose-C
addition: no addition (open symbols), low addition (420 µg glucoseC·L–1) (grey symbols), and high addition (2100 µg glucose-C·L–1)
(black symbols).
Z = 1.24, P = 0.21) of YOY perch (Faithfull et al. 2011). Individual growth of YOY perch was lower at high density than
at low density (two-tailed t test: T15 = 2.52, P = 0.024), but
there was no difference in survival between perch densities
(two-tailed t test: T[15] = 0.374, P = 0.71). However, at high
fish density individual growth decreased with increasing survival (y = –0.613x + 75.8; r2 = 0.492, P = 0.032), but not at
low density (y = –1.04x + 132; r2 = 0.274, P = 0.085). At
high perch density there was a positive relationship among
BP and survival and population growth (Figs. 4b, 4d), but a
negative relationship between BP and individual perch
growth (Fig. 4f). At low perch density survival, population
growth and individual perch growth were unaffected by BP.
EEM was not correlated with individual growth rates or survival of YOY perch (Figs. 4a, 4e) at high or low fish densities. However, EEM was positively correlated with
population growth rate at high fish density, but not at low
density (Fig. 4c).
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Fig. 2. The percentage of glucose-C accumulating in the crustacean zooplankton taxa, Bosmina spp. (□), H. gibberum (∇), calanoid copepods (○), and young-of-the-year (YOY) perch (D) biomass (mean %Biomassglucose ± 1 standard error (SE), n = 3 per treatment) for (a) glucose addition (mg·L–1) and (b) bacterial production (BP, µg C·L–1), and (c) the percentage of epilimnetic energy mobilization based on
glucose (%EEMglucose). Three levels of glucose-C addition are indicated: no addition (open symbols), low addition (420 µg glucose-C·L–1)
(grey symbols), and high addition (2100 µg glucose-C·L–1) (black symbols).
Table 2. Results of analyses of variance (ANOVAs) comparing the effects of day (biomass
change during the experiment) and glucose addition on crustacean zooplankton biomass.
Taxa
Bosmina spp.
H. gibberum
Calanoids
Factor
Day
Glucose
Day × glucose
Residuals
Day
Glucose
Day × glucose
Residuals
Day
Glucose
Day × glucose
Residuals
df
1
1
1
32
1
1
1
32
1
1
1
32
Sum of
squares
0.323
0.228
0.030
2.65
0.075
0.415
0.004
7.59
0.015
1.078
0.270
3.64
F
3.91
2.76
0.365
P
0.057
0.11
0.55
0.316
1.75
0.015
0.58
0.20
0.90
0.131
9.47
2.37
0.72
0.004*
0.13
*P value represents a significant difference at a = 0.05.
Discussion
As expected, BP was stimulated by glucose-C in our experiment. In agreement with the first part of our hypothesis,
increased BP due to glucose addition resulted in increased incorporation of glucose-C by all zooplankton taxa and YOY
perch. The importance of glucose-C mobilization through
the bacteria was exemplified by the linear correlation between BP and %Biomassglucose of crustacean zooplankton
and YOY perch. Crustacean zooplankton and YOY perch
%Biomassglucose was not correlated with glucose addition;
therefore; zooplankton and YOY perch must have incorporated glucose-C via bacterioplankton. The fraction of glucose
incorporated into biomass was higher for Bosmina spp. and
H. gibberum, which grazed a trophic level below calanoid
copepods and 1.5 trophic levels below YOY perch. Bosmina spp. and H. gibberum can incorporate bacterial carbon
either directly (Hessen 1985; Vaqué and Pace 1992) or indirectly through flagellate or small ciliate grazing (DeMott and
Kerfoot 1982; Persson 1985). The enriched d13C and d15N
signals of calanoid copepods and YOY perch suggest that
although these taxa usually do not directly ingest bacteria
(Hansen et al. 1994; Burns and Schallenberg 1996), bacterial
consumers (i.e., flagellates and ciliates) are contributing to a
proportion of their diet, thus acting as a conduit for nutrients
and energy to higher trophic levels.
We expected that the more direct trophic pathway from
bacteria or phytoplankton to cladocerans would be more efficient than the indirect pathway to copepods (from bacteria
via several levels of protozoans to copepods) owing to energy
losses associated with additional trophic levels (Vaqué and
Pace 1992; Cottingham et al. 1997). However, despite the observation that cladocerans incorporated higher amounts of
glucose-C and consumed bacteria via a more direct pathway
than calanoid copepods, glucose addition did not affect the
biomass of cladocerans. In contrast, calanoid copepod biomass increased with glucose addition. However, this biomass
increase was not correlated with an increased incorporation
of glucose-C or BP, but was positively correlated with the
biomass of large ciliates (such as Strombilidium sp.). Ciliate
predation by calanoid copepods is consistent with both the
d15N and d13C signal of calanoid copepods, as the d15N signal
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Fig. 3. Changes in mean crustacean zooplankton taxa, (a) Bosmina spp., (b) H. gibberum, and (c) calanoid copepod biomass over
time with three levels of glucose addition: no addition (open symbols), low addition (420 µg glucose-C·L–1) (grey symbols), and high
addition (2100 µg glucose-C·L–1) (black symbols) (n = 9). Fish
treatments are pooled.
indicates copepods were grazing a trophic level above cladocerans, and the d13C signal suggests that the copepods were
partially sustained by glucose-C, which is presumably mediated via bacteria and bacterivorous protists. Strombilidium sp.
had a greatest axial length dimension of 47.7 ± 0.5 µm
(mean ± 1 SE), so was outside the grazing size range for
H. gibberum and Bosmina spp. (Cyr and Curtis 1999). This
agrees with studies indicating that diaptomid copepods often
graze approximately a trophic level above cladocerans, for
example on small rotifers and ciliates, but not on the cladocerans themselves (Vanderploeg 1990; Karlsson et al. 2004;
Zöllner et al. 2009).
Can. J. Fish. Aquat. Sci. Vol. 69, 2012
Although cladocerans can also consume bacterivorous
flagellates and small ciliates, Bosmina spp. and H. gibberum
are not benefiting from bacterial-based food to the same extent as copepods in our experiment. We offer two potential
explanations for this: (i) the proportion of bacteria consumed
directly by Bosmina spp. and H. gibberum is sufficient to account for the %Biomassglucose of these zooplankton taxa, but
the proportion of bacterial grazing protists consumed is not
sufficient to enhance the growth of these cladocerans. Bosmina spp. and H. gibberum are considered to be unselective
grazers with regard to food quality (Cyr and Curtis 1999;
Hambright et al. 2007), and therefore high quality protists
may have been “diluted” with poor quality bacteria or detritus (Brett et al. 2009). In contrast, calanoid copepods are
considered to be selective grazers and can discriminate particles based on food quality (Vanderploeg 1990). Consequently, bacterial grazers able to perform trophic upgrading
may have made up a substantial proportion of the calanoid
copepod diet. (ii) The bacterial grazing protists consumed by
Bosmina spp. and H. gibberum may not have been as efficient trophic upgraders as the protists consumed by calanoid
copepods (e.g., Strombilidium sp.). Different species of protists differ in their abilities to synthesize fatty acids and therefore the extent to which they function as “trophic upgraders”
(Klein Breteler et al. 1999; Bec et al. 2010). Bacteria do not
contain polyunsaturated long chain fatty acids (PUFA) or
sterols that are essential to animals (Brett and Müller-Navarra
1997), and seston in nutrient-poor lakes (TP < 10 µg·L–1; our
mesocosms: TP = 7.4 ± 0.2, mean ± 1 SE) is generally poor
in PUFA relative to zooplankton demands (Persson and
Vrede 2006). Since a diet poor in PUFA results in slow
growth and reproduction of crustacean zooplankton (Brett et
al. 2009), the growth of cladocerans in the mesocosm experiment may at least partly have been determined by the availability of PUFA. Copepods may have been stimulated by
increased availability of Strombilidium sp., as ciliates may
perform trophic upgrading (i.e., de novo synthesis of PUFA;
Klein Breteler et al. 1999). Although the microbial pathway
can possibly off-set biochemical limitation of zooplankton
growth, we suggest that this off-set may benefit different zooplankton taxa depending on the selectivity of zooplankton
grazing and the “trophic upgrading” abilities of their prey.
The positive linear relationship between BP and the glucose fraction of zooplankton and YOY fish biomass is consistent with the results of Karlsson et al. (2007), who
showed that this relationship also holds for up to eight times
higher glucose additions. Zooplankton (Karlsson et al. 2007;
our study) and YOY fish (our study only) appear to be incorporating a consistent fraction of bacterial carbon into their
tissues, suggesting they are passively consuming bacteria depending on the rate of BP. However, in our study cladocerans
are consuming twice as much BP as would be expected if
they are grazing on the BP and PPr parts of EEM proportionally. Selection of prey is generally a passive process based on
particle size for H. gibberum and Bosmina spp. (Cyr and
Curtis 1999) and is a more active process based on taste for
calanoids (Vanderploeg 1990). Therefore, a higher proportion
of BP may be consumed by cladocerans if some of the PPr
can be contributed to large or inedible phytoplankton taxa
and large inedible bacteria do not become abundant (Jürgens et al. 1994). Dinobryon colonies and cyanobacteria
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Faithfull et al.
91
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Fig. 4. The relationship between fish survival (%) and (a) epilimnetic energy mobilization (EEM, mg C·day–1) and (b) bacterial production
(BP, mg C·day–1); between perch population (Pop.) growth rate and (c) EEM and (d) BP; and between individual (Ind.) perch growth rate and
(e) EEM and (f) BP. Each data point represents a mesocosm: low fish density (10 perch, open circles, n = 9), high fish density (30 perch,
closed circles, n = 8). Significant regression lines are shown with a solid line for the high fish density treatments.
(Anabena spp. and Merismopedia spp.) were both present in
the mesocosms at the start of the experiment; Dinobryon
colonies are difficult for zooplankton to consume and cyanobacteria are often avoided (Cyr and Curtis 1999; Hambright et al. 2007). Average bacterial biovolume did not
differ among treatments (0.081 ± 0.0029 µm3, F[8,98] =
1.63, P = 0.13); thus, bacteria remained within an edible
size range in all treatments. Additionally, bacterial biomass
did not change, even though BP increased, which is usually
attributed to a compensatory increase in bacterial grazing
rates (Cottingham et al. 1997; Jansson et al. 2006).
BP was positively correlated with YOY perch survival and
population growth rates at high fish density, but negatively
correlated with individual fish growth. The effect of bacteria
is expected to be an indirect bottom-up effect mediated via
the microbial food web resulting in increased prey quality, as
calanoid copepods, which increased with glucose addition,
are a favored prey of YOY perch (Huss et al. 2007). Given
density-dependant growth, increased survival can in turn explain the lower individual growth rates observed with increasing BP at high fish density (i.e., YOY perch were more
resource limited at high survival; Persson et al. 2000). The
total amount of zooplankton prey available did not differ
with glucose treatment, and EEM was not correlated with either BP or perch survival. Thus, our estimation of EEM is a
poor predictor of fish growth and survival. This may be due
to errors in the calculation of EEM, as although we used a
range of published values of BGE and the availability of PPr
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92
to bacteria to estimate EEM, these parameters can vary
greatly with season and nutrient availability (Baines and
Pace 1991; del Giorgio and Cole 1998). Additionally, EEM
excludes metalimnetic and hypolimnetic production, which
may have been important for YOY perch. Rather, the availability of favored prey (i.e., calanoid copepods) was the most
important determinant of growth rate. However, given that
BP only influenced fish survival and population growth at
high densities, it appears that the “quality effect” of this resource only appears once preferred resources are limited.
Three main conclusions can be drawn based on the results
of this study: (i) Labile-C was transferred up the food web
from bacteria to higher trophic levels, including fish, thus
demonstrating that bacterial production based on an external
carbon source can be an energy source for higher trophic levels. (ii) The transfer of labile-C from bacteria to fish was
mediated via calanoid copepods rather than cladocerans,
even though cladocerans incorporated more glucose-C than
calanoid copepods. This was probably due to selective grazing by calanoids on high quality prey and in turn YOY perch
predation on calanoid copepods. (iii) Responses of planktivorous fish to variation in BP and possibly subsequent trophic
upgrading (improved food quality) can be dependent on trophic pathway and density.
Carbon additions alone may have little influence on the total amount of energy available for higher trophic levels in oligotrophic lakes (see also Faithfull et al. 2011). However, our
study suggests that the origin of the basal energy source and
the zooplankton community composition matters for energy
transfer in pelagic food webs. Hence, future studies should
consider the quantity and quality of food and food web structure when investigating the influence of variation in BP on
higher trophic levels.
Acknowledgements
Mårten Söderquist, Emma Göthe, Blair Daniel, and Daniel
Lussetti’s help in the field was appreciated. Comments of
two anonymous reviewers improved the quality of the manuscript. This study was conducted as part of Lake Ecosystem
Response to Environmental Change (LEREC) and was supported with grants from the Wallenberg foundation, the
Göran Gustafsson foundation, and the Swedish Research
Council for Environment, Agricultural Sciences and Spatial
Planning (Formas).
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