Introduction
Stable carbon (C) and nitrogen (N) isotope analyses of diverse inorganic and
organic components have been successfully used to assess the origin of
organic matter (OM) and better understand its cycling in aquatic systems
(Lehmann et al., 2004). For instance, an extensive sampling of diverse C and
N pools over an annual cycle in the Loch Ness showed important seasonal
variation of the 13C / 12C and 15N / 14N ratios in the
crustacean zooplankton biomass, reflecting a diet switch from allochthonous
to autochthonous OM sources (Grey et al., 2001). In small humic boreal lakes
with permanently anoxic waters, stable C isotope analyses demonstrated that methanotrophic bacteria could be an important food source for
crustacean zooplankton, and hence methane-derived C contributed to a
large fraction of the lake food web (Kankaala et al., 2006). Analyses of the
stable C isotope composition of carbonates and OM in sedimentary records of
stratified lakes can also provide reliable information about past land use
of the catchment (Castañeda et al., 2009), or be used to infer changes in
lake productivity and climate (Schelske and Hodell, 1991). However, a
detailed understanding of the stable isotope dynamics in the water column is
a prerequisite for a good interpretation of isotope data from sedimentary
archives (Lehmann et al., 2004).
A new paradigm has progressively emerged over the last decade, proposing that
freshwaters ecosystems are predominantly net heterotrophic, as respiration of
OM exceeds autochthonous photosynthetic production (Del Giorgio et al., 1997;
Cole, 1999; Duarte and Prairie, 2005). This concept seems to hold especially
true for oligotrophic unproductive ecosystems (Del Giorgio et al., 1997),
that are subsidised by substantial inputs of allochthonous OM of
terrestrial origin, which support the production of heterotrophic organisms.
Net heterotrophy has been recognised as one of the main cause for the net
emission of carbon dioxide (CO2) from freshwater ecosystems to the
atmosphere (Prairie et al., 2002), although there is growing evidence of the
contribution from external hydrological CO2 inputs from the catchment
(Stets et al., 2009; Finlay et al., 2010; Borges et al., 2014; Marcé et
al., 2015). However, the current understanding of the role of inland waters
on CO2 emissions could be biased because most observations were obtained
in temperate and boreal systems, and mostly in medium-to-small lakes,
during open-water (ice-free) periods, but tropical and temperate lakes
differed in some fundamental characteristics. Among them, the constantly high
temperature and irradiance have strong effects on water column stratification
and biological processes (Sarmento, 2012). For instance, primary production
in tropical lakes has been recognised to be 2 times higher than in
temperate lakes on a given nutrient base (Lewis, 1996). Also, the
contribution of dissolved primary production in oligotrophic tropical lakes
has been found to substantially more important than in their temperate
counterparts (Morana et al., 2014).
East Africa harbours the densest aggregation of large tropical lakes
(Bootsma and Hecky, 2003). Some of them are among the largest (lakes
Victoria, Tanganyika, Malawi), and deepest lakes in the world (lakes
Tanganyika, Malawi, Kivu) and consequently remain stratified all year round.
Due to the size and the morphometric traits of the East African Great Lakes,
pelagic processes are predominant in these systems, with the microbial food
web playing a particularly essential role in OM transfer between primary
producers and higher levels of the food web, and in nutrient cycling
(Descy and Sarmento, 2008). Most of them are also characterized by highly
productive fisheries that provide an affordable food source to local
populations (Descy and Sarmento, 2008). However, while these lakes are
potentially important components of biogeochemical cycles at the regional
scale (Borges et al., 2011), and significant for local populations
from an economic perspective (Kaningini, 1995), the East African Great Lakes
are relatively poorly studied, most probably because of their remote
location combined with frequent political unrest.
In this study, we present a comprehensive data set covering a full annual
cycle, including hydrochemical data and measurements of the concentration of
dissolved methane (CH4) and the concentrations and stable isotope
compositions of dissolved inorganic carbon (DIC), dissolved and particulate
organic carbon (DOC and POC), particulate nitrogen (PN), and zooplankton.
Data were acquired over one full year at a fortnightly/monthly temporal
resolution. We aimed to assess the net metabolic status of Lake Kivu, the
seasonal and depth variability of sources of OM within the water column, and
the relative contribution of autochthonous or allochthonous OM to the
zooplankton. To our best knowledge, this is the first detailed study to
assess the seasonal dynamics of different OM reservoirs by means of their
stable isotope composition in any of the East African Great Lakes. The
detailed analysis of the stable isotope composition of diverse organic and
inorganic components carried out during this study allowed one to trace the OM
dynamics in Lake Kivu over a seasonal cycle, and might be useful to
improve the interpretation of sedimentary archives of this large and deep
tropical lake.
Material and methods
Lake Kivu (East Africa) is a large (2370 km2) and deep
(maximum depth of 485 m) meromictic lake located at the border between the
Democratic Republic of the Congo and Rwanda. Its vertical structure consists
of an oxic and nutrient-poor mixed layer down to a maximum depth of 70 m,
and a permanently anoxic monimolimnion rich in dissolved gases (CH4,
and CO2) and inorganic nutrients. Seasonal variation of the vertical
position of the oxic–anoxic transition is driven by contrasting air humidity
and incoming long-wave radiation between rainy (October–May) and dry
(June–September) seasons (Thiery et al., 2014). The euphotic zone, defined at
the depth at which light is 1 % of surface irradiance, is relatively
shallow (annual average: 18 m, Darchambeau et al., 2014).
Sampling was carried out in the southern basin (02∘20′ S,
28∘58′ E) of Lake Kivu between January 2012 and May 2013 at a
monthly or fortnightly time interval. Vertical oxygen (O2), temperature
and conductivity profiles were obtained with a Hydrolab DS5 multiprobe. The
conductivity cell was calibrated with a 1000 µS cm-1
(25 ∘C) Merck standard and the O2 membrane probe was
calibrated with humidity saturated ambient air. Water was collected with a 7 L
Niskin bottle (Hydro-Bios) at a depth interval of 5 m from the lake
surface to the bottom of the mixolimnion, at 70 m. Additionally, zooplankton
was sampled with a 75 cm diameter, 55µm mesh plankton net hauled along the
whole mixolimnion (0–70 m).
Samples for CH4 concentrations were collected in 50 mL glass serum
bottles from the Niskin bottle with a tube, left to overflow, poisoned with
100 muL of saturated HgCl2 and sealed with butyl stoppers and aluminium
caps. Concentrations of CH4 were measured by headspace technique using
gas chromatography (Weiss, 1981) with flame ionisation detection (SRI 8610C),
after creating a 20 mL headspace with N2 in the glass serum bottles,
and then analysed as described by Borges et al. (2011).
Samples for stable C isotopic composition of dissolved inorganic carbon
(δ13C-DIC) were collected by filling water directly from
the Niskin bottle 12 mL headspace vials (Labco Exetainer) without bubbles.
Samples were preserved with the addition of 20 µL of a saturated HgCl2
solution. Prior to the analysis of δ13C-DIC, a 2 mL helium
headspace was created, and 100 µL of phosphoric acid (H3PO4, 99 %)
was added in the vial in order to convert all inorganic C species to
CO2. After overnight equilibration, 200 µL of gas was injected with a
gastight syringe into a elemental analyser – isotopic ratio mass spectrometer (EA-IRMS; Thermo FlashHT with Thermo DeltaV
Advantage). The obtained data were corrected for isotopic equilibration
between dissolved and gaseous CO2 as described in Gillikin and Bouillon
(2007). Calibration of δ13C-DIC measurement was performed with
the international certified standards IAEA-CO1 and LSVEC. The
reproducibility of δ13C-DIC measurement was typically better
than ±0.2 ‰. Measurements of total alkalinity
(TA) were carried out by open-cell titration with HCl 0.1 mol L-1
according to Gran (1952) on 50 mL water samples, and data were quality
checked with certified reference material obtained from Andrew Dickinson
(Scripps Institution of Oceanography, University of California, San Diego,
USA). Typical reproducibility of TA measurements was better than ±3 µmol L-1.
DIC concentration was computed from pH and TA measurements
using the carbonic acid dissociation constants of Millero et al. (2006).
Samples for DOC concentration and stable C isotopic composition (δ13C-DOC) were filtered through pre-flushed 0.2 µm syringe filters, kept
in 40 mL borosilicate vials with Teflon-coated screw caps and preserved with
100 µL of H3PO4 (50 %). Sample analysis was carried out with a IO
Analytical Aurora 1030W coupled to an IRMS (Thermo delta V
Advantage). Quantification and calibration of DOC and δ13C-DOC
was performed with IAEA-C6 and an internal sucrose standard (δ13C = -26.99 ± 0.04 ‰) calibrated against
international reference materials.
Samples for POC and particulate nitrogen (PN) concentration and stable
carbon and nitrogen isotope composition (δ13C-POC; δ15N-PN) were obtained by filtering a known volume of water on
pre-combusted (overnight at 450 ∘C) 25 mm glass fiber filters
(Advantec GF-75; 0.3 µm), kept frozen until subsequent processing. The
filters were later decarbonated with HCl fumes for 4 h, dried and packed in
silver cups prior to analysis on a EA-IRMS (Thermo FlashHT with Thermo
DeltaV Advantage). Calibration of δ13C-POC, δ15N-PN, POC and PN measurements was performed with acetanilide
(δ13C = - 27.65 ± 0.05; δ15N = 1.34 ± 0.04)
and leucine (δ13C = - 13.47 ± 0.07;
δ15N = 0.92 ± 0.06) as standards. All standards were
internally calibrated against the international standard IAEA-C6 and
IAEA-N1. Reproducibility of δ13C-POC and δ15N-PN
measurement was typically better than ±0.2 ‰ and
relative standard deviation for POC and PN measurement were always below
5 %. Samples for δ13C and δ15N of zooplankton
were collected on precombusted 25 mm glass fiber filters (Advantec GF-75;
0.3 µm), and dried. Subsequent preparation of the samples and analysis on the
EA-IRMS were performed similarly as described for the δ13C-POC
and δ15N-PN samples.
Pigment concentrations were determined by high performance liquid
chromatography (HPLC). 2–4 L of water were filtered through
Macherey-Nägel GF-5 filter (average retention of 0.7 µm). Pigment
extraction was carried out in 10 mL of 90 % HPLC grade acetone. After two
sonication steps of 15 min separated by an overnight period at 4 ∘C,
the pigments extracts were stored in 2 mL amber vials at -25 ∘C.
HPLC analysis was performed following the gradient elution method
described in Wright et al. (1991), with a Waters system comprising photodiode
array and fluorescence detectors. Calibration was made using commercial
external standards (DHI Lab Products, Denmark). Reproducibility for pigment
concentration measurement was better than 7 %. Pigment concentrations were
processed with the CHEMTAX software (CSIRO Marine Laboratories) using input
ratio matrices adapted for freshwater phytoplankton (Descy et al., 2000).
Data processing followed a procedure similar to that of Sarmento et al. (2006)
in Lake Kivu that allows one to estimate chlorophyll a (Chl a) biomass
of cyanobacteria, taking into account variation of pigment ratios with
season and depth.
Discussion
Stable isotope analysis of DIC is a useful tool for understanding the fate of
C in aquatic ecosystems and could provide information on the lake metabolism,
defined as the balance between gross primary production and community
respiration of OM. Primary producers preferentially incorporate the lighter
isotope (12C) into the biomass with the consequence that the heavier
isotope (13C) accumulates into the DIC pool, whereas mineralisation
releases 13C-depleted CO2 from the OM being respired into the DIC
pool. Therefore, increasing primary production leads to higher
δ13C-DIC but increasing respiration should tend to decrease
δ13C-DIC (Bade et al., 2004). For instance, several studies
conducted in temperate lakes have reported a significant increase in
δ13C-DIC during summer, resulting from primary production (Herczeg,
1987; Hollander and McKenzie, 1991). In Lake Kivu, the δ13C-DIC
increased linearly with time during the stratified rainy season, deviating
gradually from the δ13C-DIC value expected if the DIC pool was at
equilibrium with the atmospheric CO2 (∼ 0.49 ‰). It
appears unlikely that this linear isotopic enrichment of the DIC pool is due
to physical processes: the δ13C-DIC signature of the DIC input from
the inflowing rivers (Borges et al., 2014) and deep waters (Fig. 3a) was
indeed lower than the measured δ13C-DIC in the mixed layer.
Therefore, biological processes (i.e. photosynthetic CO2 uptake)
are likely responsible of the
isotopic enrichment of the DIC pool observed during the stratified rainy
season. Nevertheless, a small decrease in δ13C-DIC was recorded at
the beginning of the dry season (early in July 2012), but was concomitant
with the characteristic deepening of the mixed layer observed during the dry
season. As the depth profile of δ13C-DIC revealed that the DIC
pool was isotopically lighter in the bottom of the mixolimnion, the
measurement of lower δ13C-DIC values during the dry season could
have resulted from the seasonal vertical mixing of surface waters with bottom
waters containing relatively 13C-depleted DIC.
Overall, the data suggest that the input of DIC originating from the
monimolimnion during the dry season had a strong influence on δ13C-DIC in the mixolimnion, but the seasonal variability of δ13C-DIC observed in the mixed layer holds information on biological
processes. The gradual increase with time of the δ13C-DIC in
the mixed layer supports the conclusions of other studies carried out in
Lake Kivu (Morana et al., 2014; Borges et al., 2014) which showed, based on a
detailed DIC and DI13C mass balance approach and several microbial
processes measurements, that photosynthetic CO2 fixation should exceed
the respiration of OM. Indeed, in Lake Kivu, riverine inputs of
allochthonous OM from the catchment (0.7–3.3 mmol m-2 d-1,
Borges et al., 2014) are minimal compared to primary production (49 mmol m-2 d-1;
Darchambeau et al., 2014) and the export of organic
carbon to the monimolimnion (9.4 mmol m-2 d-1) reported by Pasche
et al. (2010). The outflow of organic carbon through the Ruzizi River is
also relatively low and was computed to be 0.6 mmol m-2 d-1 (this
study) based on the long-term discharge average of Ruzizi (83.2 m3 s-1,
Borges et al., 2014), the average POC and DOC in surface waters
(0.052 and 0.142 mmol L-1, this study). It implies that the outputs of
OM (9.4 + 0.7 = 10.1 mmol m-2 d-1) are higher than the inputs
of OM from the catchment (0.7–3.3 mmol m-2 d-1) suggesting a net
autotrophic status of Lake Kivu.
However, these results contradict the commonly held view that
oligotrophic lacustrine and marine systems tend to be net heterotrophic (Del
Giorgio et al., 1997; Cole, 1999). Net heterotrophy implies that
heterotrophic prokaryotes rely on a substantial amount of allochthonous OM;
however, in Lake Kivu, riverine inputs of allochthonous OM from the catchment
(0.7–3.3 mmol m-2 d-1, Borges et al., 2014) are
minimal. Indeed, the magnitude of allochthonous OM inputs relative to
phytoplankton production depends strongly on the catchment to surface area
ratio (Urban et al., 2005), that is particularly low (2.2) in Lake Kivu.
Therefore, Lake Kivu is relatively poor in organic C, with DOC concentrations
of ∼ 0.15 mmol L-1 in contrast to smaller boreal humic lakes
which show DOC concentrations of on average ∼ 1 mmol L-1 (Sobek
et al., 2007), and with
values up to ∼ 4.5 mmol L-1 (Weyhenmeyer and Karlsson, 2009).
Humic substances are usually low-quality substrates for bacterial growth
(Castillo et al., 2003), but limit primary production by absorbing incoming
light. Hence, heterotrophic production in the photic zone of humic lakes
usually exceeds phytoplankton production and DOC concentrations, despite the
low substrate quality of humic substances, have been found to be a good
predictor of the metabolic status of lakes in the boreal region, with a
prevalence of net heterotrophy in organic-rich lakes (Jansson et al., 2000).
However, low allochthonous OM inputs and low DOC concentration do not
necessary cause a system to be net autotrophic. For instance, Lake Superior, subsidised by a similar
amount of allochthonous OM (∼ 3 mmol m-2 d-1), has a lower catchment-to-surface area ratio (1.6), and its water has a DOC
concentration even lower than in Lake Kivu (∼ 0.1 mmol L-1).
However, it has been found to be net heterotrophic despite the limited
allochthonous OM inputs (Urban et al., 2005). Lake Superior, as the majority
of the lakes of the world, is holomictic, meaning that the mixing of its
water column can seasonally reach the lake floor, and a substantial amount of
sediments, including OM, could then be resuspended during these mixing events
and hence re-exposed to microbial mineralisation in well-oxygenated waters
(Meyers and Eadie, 1993; Cotner, 2000; Urban et al., 2005). The resuspension
of bottom sediments could be important in the ecological functioning of these
systems. In contrast, Lake Kivu, as other East African Great Lakes such as
Tanganyika and Malawi, are particularly deep meromictic lakes, so that
their water column is characterized by an almost complete decoupling between
the surface and deep waters, preventing any resuspended bottom sediment to
reach the surface waters in this system. In consequence, the coupling between
the phytoplankton production of DOC and its heterotrophic consumption by
prokaryotes in the clear, nutrient-depleted waters of Lake Kivu was found to
be high throughout the year (Morana et al., 2014).
Besides morphometrical features, the net autotrophic status of Lake Kivu
might also be related to general latitudinal and climatic patterns. Due to
the warmer temperature in the tropics, phytoplankton production is
comparatively higher in the East African Great Lakes compared with the
Laurentian Great Lakes, despite similar phytoplankton abundance (Bootsma and
Hecky, 2003). Alin and Johnson (2007) examined phytoplankton primary
production and CO2 emissions to the atmosphere fluxes in large lakes of
world (> 500 km2). At the global scale, they found a
statistically significant increase of the areal phytoplankton production in
large lakes with the mean annual water temperature and the insolation; as a
consequence, a significant decrease of phytoplankton production with
latitude. Also, they report a significant decrease of the CO2 emissions
to the atmosphere with the mean annual water temperature and therefore an
increase of the CO2 emission with the latitude. According to their
estimations, less than 20 % of the phytoplankton primary production is
sufficient to balance the carbon loss through CO2 evasion and OM burial
in sediments in large lakes located between the equator and the latitude
30∘, but the CO2 emission and OM accumulation in sediments
exceed the phytoplankton primary production in systems located at latitude
higher than 40∘ (Alin and Johnson, 2007). Overall, in
morphometrically comparable systems, this global analysis suggests a trend
from autotrophic to increasingly heterotrophic conditions with increasing
latitude and decreasing mean annual water temperature and insolation (Alin
and Johnson, 2007). Therefore, our study supports the view that paradigms
established with data gathered in comparatively small temperate and boreal
lakes may not directly apply to larger, tropical lakes (Bootsma and Hecky,
2003). It also highlights the need to consider the unique limnological
characteristics of a vast region of the world that harbours 16 % of the
total surface of lakes (Lehner and Döll, 2004), and account for 50 %
of the global inputs of OM from continental waters to the oceans (Ludwig et
al., 1996).
The δ13C data indicate a difference in the origins of the POC and
DOC pools in the mixed layer. Indeed, the δ13C-DOC showed very
little variation and appeared to be vertically and temporally uncoupled from
the POC pool in the mixed layer (Fig. 6). A recent study (Morana et al.,
2014) demonstrated that phytoplankton extracellular release of DOC is
relatively high in Lake Kivu, and the fresh and labile autochthonous DOC
produced by cell lysis, grazing or phytoplankton excretion, which reflects
the δ13C signature of POC, is quickly mineralised by heterotrophic
bacteria. Therefore, it appears that the freshly produced autochthonous DOC
contributes less than 1 % of the total DOC pool (Morana et al., 2014),
and as the standing stock of phytoplankton-derived DOC seems very small, it
can be hypothesised that the bulk DOC pool is mainly composed of older, more
refractory compounds that reach the mixed layer through vertical advective
and diffusive fluxes. Indeed, the δ13C signature of the DOC in the
monimolimnion (80–370 m, -23.0 ± 0.2 ‰,
n= 24) did not differ from the δ13C-DOC in the mixolimnion (0–70 m, -23.2 ± 0.2‰,
n= 5), suggesting that they share the same
origin (Fig. 4).
Relationship between the δ13C signature of the
particulate and dissolved organic carbon pool (POC and DOC, respectively) in
the mixed layer.
The concentration of the POC pool varied largely with depth, being the
highest in the 0–20 m layer, i.e. roughly the euphotic zone. However,
during the dry season, POC concentrations were almost as high in the oxycline
than in surface waters. High POC concentrations in deep waters have
frequently been observed in lakes, usually as a result of the resuspension of
bottom sediments near the lake floor or the accumulation of sedimenting
material in density gradients (Hawley and Lee, 1999). However, in the deep
Lake Kivu, this maximum POC zone is located approximately 300 m above the
lake floor and is characterized by a strong depletion in 13C of the POC
pool. While DIC is probably the major C source of the POC pool in the mixed layer, the
important decrease of δ13C-POC values observed in the oxycline
suggests that another 13C-depleted C source was actively incorporated
into the biomass at the bottom of the mixolimnion. Slight depletion in
13C of the POC pool in oxyclines, such as in the Black Sea, has
sometimes been interpreted as a result of to the heterotrophic mineralisation
of the sedimenting OM (Çoban-Yıldız et al., 2006), but it seems
unlikely that, in Lake Kivu, heterotrophic processes could have caused an
abrupt excursion of δ13C-POC to values as low as -41.6 ‰
(65 m, 22 August 2012). Such large isotopic depletion of the
POC pool in the water column has been reported by Blees et al. (2014), who
measured δ13C-POC as low as -49 ‰ in Lake Lugano, and it
was related to high methanotrophic activity. In Lake Kivu, CH4
concentrations were found to decrease sharply with decreasing depth at the
oxic–anoxic transition (Borges et al., 2011), and the dissolved CH4 that
reached the oxycline via turbulent diffusivity and vertical advection (Schmid
et al., 2005) is known to be isotopically light, with a δ13C
signature of approximately -60 ‰ (Pasche et al., 2011; Morana et
al., 2015). Therefore, the vertical patterns in CH4 concentrations and
δ13C-POC values observed during this study suggest that a
substantial part of CH4 was consumed and incorporated into the microbial
biomass in the oxycline. Indeed, experiments carried out in Lake Kivu in
February 2012 and September 2012 showed that microbial CH4 oxidation was
significant in the oxycline, and phospholipid fatty acid analysis revealed
high abundance of methanotrophic bacteria of type I at the same depths
(Morana et al., 2015). With estimates of the isotope fractionation factor
during microbial CH4 oxidation (1.016, Morana et al., 2015), and of the
δ13C-CH4 at each sampling point, it is possible to estimate
the theoretical δ13C signature of methanotrophic organisms at each
depth. Note that the δ13C-CH4 was not directly measured
during this study but a very strong linear correlation between the
log-transformed CH4 concentrations and δ13C-CH4 was found
along vertical profiles performed in February and September 2012 in Lake Kivu
(δ13C-CH4= -7.911 log(CH4) - 13.027;
r2= 0.87, n= 34; Morana et al., 2015). Hence the δ13C-CH4 at each sampling point between January 2012 and May 2013 can
be approximated from the measured CH4 concentrations using this
empirical relationship. Then, a simple isotope mixing model with the
calculated δ13C signature of methanotrophs and the average
δ13C-POC in the mixed layer as end-members allows us to determine the
contribution of CH4-derived C to POC at each sampling depth. It appears
that 4.4 ± 1.9 % (n= 13) and 6.4 ± 1.6 % (n= 5)
of the depth-integrated POC pool in the mixolimnion was derived from CH4
incorporation into the biomass during the rainy and dry season, respectively,
and these percentages did not significantly differ between seasons
(two-tailed t test, p= 0.055). Nevertheless, the low δ13C
signatures measured locally in the oxycline indicate that the contribution of
CH4-derived C could be episodically as high as 50 % (65 m, 22
August 2012). We hypothesise that microbial
CH4 oxidation could play an important role in the ecological functioning
of Lake Kivu. Along with heterotrophic mineralisation of the sinking OM, and
presumably other chemoautotrophic processes occurring in the oxycline such as
nitrification (Llirós et al., 2010), CH4 oxidation contributed
substantially to O2 consumption in the water column and was partly
responsible for the seasonal uplift of the oxycline observed after the
re-establishment of the thermal stratification during the rainy season.
Furthermore, the methanotrophs in the oxycline actively participated in the
uptake of dissolved inorganic phosphorus (DIP), and hence exerted an indirect
control on phytoplankton by constantly limiting the vertical DIP flux to the
illuminated surface waters (Haberyan and Hecky, 1987). Indeed, phytoplankton
in Lake Kivu suffer from a severe P limitation throughout the year as pointed
out by the relatively high sestonic C : P ratio (256 ± 75; Sarmento
et al., 2009; Darchambeau et al., 2014).
Relationship between the relative contribution of cyanobacteria to
the phytoplankton assemblage (percentage of biomass) and the δ15N
signature of the particulate nitrogen pool in the mixed layer.
The δ15N signature of the autochthonous OM in the mixed layer of
Lake Kivu oscillated around 0 ‰ during the rainy season in Lake Kivu
but was significantly higher during the dry season (3–4 ‰). Also,
the δ15N-PN in the mixed layer correlated negatively with the
proportion of cyanobacteria in waters (Fig. 7, Pearson's r: -0.65, p= 0.004, n= 17). This pattern may highlight the seasonal importance of
N2-fixing cyanobacteria in Lake Kivu during the rainy season. Indeed,
the δ15N signature of atmospheric N2 is close to 0 ‰,
and isotope fractionation during cyanobacterial N2-fixation is known to
be small (Fogel and Cifuentes, 1993). Several studies carried out in marine
(Pacific Ocean and Gulf of Mexico) and lacustrine (Lake Lugano) systems have
shown that δ15N-PN varied between -2 and +1 ‰ when
N2-fixing cyanobacteria were dominating the phytoplankton assemblage
(Wada and Hattori, 1976; Macko et al., 1987; Lehmann et al., 2004). Moreover,
a good relationship between the δ15N-PN and the abundance of
N2-fixing cyanobacteria has already been reported for others systems,
such as coastal lagoons (Lesutienė et al., 2014). In Lake Victoria,
biological N2 fixation has been identified as having the largest input
of N, exceeding atmospheric deposition and river inputs, and N2 fixation
has been found to increase with light availability (Mugidde et al., 2003).
This suggests that during the rainy season, when thermal stratification of
the mixolimnion leads to reduced nitrogen supply combined with exposure to
high light levels, N2-fixing cyanobacteria have a competitive
advantage which may explain their seasonally higher
contribution to the autochthonous OM pool (Sarmento et al., 2006). Indeed,
the significantly higher molar C : N ratio during the rainy season than the
dry season indicates that N limitation in the mixed layer was stronger during
the rainy season (this study, Sarmento et al., 2009). By contrast, the
deepening of the mixed layer during the dry season leads to increased
nutrient input and reduced light availability that favours alternative
phytoplankton strategies (Hecky and Kling, 1987, 2006; Sarmento et al., 2006;
Darchambeau et al., 2014), and consequently the proportion N2-fixing
cyanobacteria decreases. A similar seasonal pattern of N2 fixation was
reported in Lake Victoria by Mugidde et al. (2003). In contrast with the
rather constant δ13C signature of zooplankton
(-22.9 ± 0.8 ‰), the δ15N analysis revealed that
the δ15N of zooplankton varied significantly, following well the
seasonal change in δ15N-PN in the mixed layer. The difference
between δ15N-zooplankton and δ15N-PN
(Δ15NZoo-PN) was on average 3.2 ± 1.0 ‰
throughout the year while it was on average enriched in 13C
(Δ13CZoo-POC) by 0.9 ± 0.8 ‰. In nature,
comparison of the δ15N signature of consumers and their diet
indicates that the δ15N value increases consistently with the
trophic level, because of the preferential excretion of the isotopically
lighter 14N (Montoya et al., 2002). However, the C isotope fractionation
between consumers and diet is usually considered to be less than 1 ‰
(Sirevåg et al., 1977). The constant Δ15NZoo-PN value
found in Lake Kivu is within the range of trophic level enrichment between
algae and Daphnia magna (∼ 2 to 5 ‰) estimated in
laboratory experiment (Adams and Sterner, 2000), and very close to the
cross-system trophic enrichment value (3.4 ± 1.0 ‰) proposed
by Post (2002). Together with the slight enrichment in 13C compared with
the autochthonous POC pool, δ13C and δ15N analysis
suggests that zooplankton directly incorporate phytoplankton-derived OM in
their biomass (Masilya, 2011), and they rely almost exclusively on this
source of OM throughout the year. This is in general agreement with the very
low allochthonous OM inputs from rivers in Lake Kivu (Borges et al., 2014).
In conclusion, stable isotope data revealed large seasonal variability in the
δ15N signature of the PN pool, most likely related to changes in
the phytoplankton assemblage and to N2-fixation. Contradicting
the common observation that oligotrophic aquatic ecosystems tend to be net
heterotrophic, the seasonality of δ13C-DIC supports the view that
the mixed layer of Lake Kivu is net autotrophic, as demonstrated by Borges et
al. (2014) based on DIC and DI13C mass balance considerations. The
δ13C-POC showed an important variation with depth due to the
abundance of methanotrophic bacteria in the oxycline that fixed the lighter
CH4-derived C into their biomass. The δ13C-POC and
δ13C-DOC appeared to be uncoupled vertically and temporally, which
could indicate that most of the DOC pool was composed of relatively
refractory compounds. Finally, the δ13C of zooplankton mirrored the
δ13C signature of the autochthonous POC pool, and its
δ15N signature followed the seasonal variability of the
δ15N-PN pool in good agreement with the expected consumer–diet
isotope fractionation. This suggests that zooplankton rely throughout the
year on phytoplankton-derived biomass as a organic C source.