BGBiogeosciencesBGBiogeosciences1726-4189Copernicus PublicationsGöttingen, Germany10.5194/bg-14-1631-2017Effects of low oxygen concentrations on aerobic methane oxidation in
seasonally hypoxic coastal watersSteinleLealea.steinle@unibas.chMaltbyJohannaTreudeTinahttps://orcid.org/0000-0001-6366-286XKockAnnetteBangeHermann W.https://orcid.org/0000-0003-4053-1394EngbersenNadineZopfiJakobhttps://orcid.org/0000-0002-8437-7344LehmannMoritz F.NiemannHelgehttps://orcid.org/0000-0002-3468-8304Department of Environmental Sciences, University of Basel, 4056 Basel,
SwitzerlandGEOMAR Helmholtz Centre for Ocean Research Kiel, Marine
Biogeochemistry Research Division, 24148 Kiel, GermanyDepartment of Natural Sciences, Saint Joseph's College, Standish,
Maine, USADepartment of Earth, Planetary & Space Sciences and Atmospheric
& Oceanic Sciences, University of Los Angeles, Los Angeles, California,
USACAGE – Centre for Arctic Gas Hydrate, Environment and Climate,
Department of Geology, UiT the Arctic University of Norway, 9037 Tromsø,
NorwayLea Steinle (lea.steinle@unibas.ch)29March2017146163116455October201619October201625February20171March2017This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://bg.copernicus.org/articles/14/1631/2017/bg-14-1631-2017.htmlThe full text article is available as a PDF file from https://bg.copernicus.org/articles/14/1631/2017/bg-14-1631-2017.pdf
Coastal seas may account for more than 75 % of global oceanic
methane emissions. There, methane is mainly produced microbially in anoxic
sediments from which it can escape to the overlying water column. Aerobic
methane oxidation (MOx) in the water column acts as a biological filter,
reducing the amount of methane that eventually evades to the atmosphere. The
efficiency of the MOx filter is potentially controlled by the availability of
dissolved methane and oxygen, as well as temperature, salinity, and
hydrographic dynamics, and all of these factors undergo strong temporal
fluctuations in coastal ecosystems. In order to elucidate the key
environmental controls, specifically the effect of oxygen availability, on
MOx in a seasonally stratified and hypoxic coastal marine setting, we
conducted a 2-year time-series study with measurements of MOx and
physico-chemical water column parameters in a coastal inlet in the
south-western Baltic Sea (Eckernförde Bay). We found that MOx rates
generally increased toward the seafloor, but were not directly linked to
methane concentrations. MOx exhibited a strong seasonal variability, with
maximum rates (up to 11.6 nmol L-1 d-1) during summer
stratification when oxygen concentrations were lowest and bottom-water
temperatures were highest. Under these conditions, 2.4–19.0 times more
methane was oxidized than emitted to the atmosphere, whereas about the same
amount was consumed and emitted during the mixed and oxygenated periods.
Laboratory experiments with manipulated oxygen concentrations in the range of
0.2–220 µmol L-1 revealed a submicromolar oxygen optimum
for MOx at the study site. In contrast, the fraction of methane–carbon
incorporation into the bacterial biomass (compared to the total amount of
oxidized methane) was up to 38-fold higher at saturated oxygen
concentrations, suggesting a different partitioning of catabolic and anabolic
processes under oxygen-replete and oxygen-starved conditions, respectively.
Our results underscore the importance of MOx in mitigating methane emission
from coastal waters and indicate an organism-level adaptation of the water
column methanotrophs to hypoxic conditions.
Introduction
Methane is a potent greenhouse gas, but the contributions of individual
natural sources to the atmospheric budget are still not well constrained
(Kirschke et al., 2013). Coastal (shelf) seas are estimated to account for
more than 75 % of the global marine methane emissions, even though they
cover only about 15 % of the total ocean surface area (Bange et al.,
1994; Bakker et al., 2014). In coastal systems, methane is mainly produced
via degradation of organic matter by methanogenic archaea in anoxic sediments
(Ferry, 1993; Bakker et al., 2014). Part of the produced methane is consumed
via anaerobic or aerobic oxidation of methane within the sediments (Knittel
and Boetius, 2009; Boetius and Wenzhöfer, 2013), but a significant
fraction often escapes into the overlying water column (Reeburgh, 2007). In
the water column, methane can also be oxidized anaerobically in the case of
water column anoxia, but most of it is consumed via aerobic oxidation of
methane (MOx; R1), mediated by aerobic methane-oxidizing bacteria (MOB;
Reeburgh, 2007).
CH4+2O2→CO2+2H2O
MOx is hence an important sink for methane before its potential release into
the atmosphere, but little is known about the efficiency of MOx in shallow
coastal ecosystems, where the distance between the sediment source and the
atmosphere is short, leaving little time for exhaustive methane oxidation
during vertical advective or turbulent-diffusive transport. Coastal
ecosystems undergo large temporal variations, for example, with regard to
temperature, oxygen, salinity, or organic matter input (e.g. Lennartz et
al., 2014; Gelesh et al., 2016). Additionally, over the past decades, the
number of seasonally or permanently hypoxic or even anoxic coastal zones has
increased worldwide, most often as a consequence of anthropogenic
eutrophication and/or climate change (Diaz and Rosenberg, 2008; HELCOM: 2009;
Rhein et al., 2013; Lennartz et al., 2014; Rabalais et al., 2014). Model
results also predict that such oxygen-depleted zones will expand in the
future since increasing surface water temperatures will lead to enhanced
stratification and, thus, to less oxygen supply to bottom waters (Keeling et
al., 2010; Friedrich et al., 2014). Several definitions for water column
oxygenation levels were suggested in the literature (Diaz and Rosenberg,
2008; Canfield and Thamdrup, 2009; Middelburg and Levin, 2009; Naqvi et al.,
2010). Here, we adopt the threshold adapted by Middelburg and Levin (2009)
and Naqvi et al. (2010), where hypoxia is defined as
[O2] < 63 µmol L-1.
Multiple environmental factors can affect MOx in seasonally stratified
coastal marine environments. Oxygen concentrations, for instance, are likely
to impact MOx, which is an aerobic or, in some cases, a micro-aerobic process
(Carini et al., 2005; Schubert et al., 2006; Blees et al., 2014). Hence, the
organic matter flux and, consequently, the rate of oxygen consumption due
to organic matter remineralisation may influence how much methane is oxidized
via MOx. Enhanced organic matter input can also increase methane production
rates (Maltby, 2015), which in turn may stimulate MOx rates. Moreover,
increasing ocean water temperatures as a result of climate change may
directly impact metabolic rates of microbes, e.g. methanogens or
methanotrophs (Madigan et al., 2015). Increasing surface water temperature
could also have an indirect effect on MOx, as it will influence water column
stratification and thus oxygenation levels during summer time (Diaz and
Rosenberg, 2008; Keeling et al., 2010; Friedrich et al., 2014). Finally, water
mass circulation, transporting methanotrophs to or away from methane sources
can also affect MOx rates (Steinle et al., 2015). In order to predict the
fate of coastal methane, knowledge of the seasonality of water column methane
oxidation, and the environmental controls thereupon, are of great importance
for predicting future changes in methane emissions (Bakker et al., 2014).
The seasonally hypoxic Boknis Eck time series station located in
Eckernförde Bay (SW Baltic Sea) is an excellent site for investigating
coastal water column MOx under different oxidation/stratification regimes
(see e.g. Bange et al., 2010). Here, we present results from a 2-year
study, during which we investigated MOx rates, methane concentrations, and
physicochemical parameters in the water column at Boknis Eck on a quarterly
basis. The aim was to assess seasonal dynamics of, and the environmental
controls on, MOx in this coastal inlet. Combining field observations and
laboratory experiments, we specifically addressed the role of oxygen as a
modulator of MOx by determining minimum oxygen requirements and potential
oxygen concentration optima.
Materials and methodsSite description
The time-series station Boknis Eck (54∘31.15 N, 10∘02.18 E;
www.bokniseck.de; Fig. 1) is situated at the entrance of the coastal
inlet Eckernförde Bay in the SW Baltic Sea, with an approximate water
depth of 28 m at the sampling site (Bange et al., 2011). Physico-chemical
water column parameters have been measured regularly since 1957, making this
station one of the longest-operated marine time-series stations worldwide
(Lennartz et al., 2014). The hydrography of Eckernförde Bay is
characterized by the outflow of low-salinity Baltic Sea water and the inflow
of higher-salinity North Sea water through the Kattegat and the Great Belt.
From mid-March to mid-September, the water column is stratified with a
pycnocline at ∼ 15 m water depth (Lennartz et al., 2014). Large
phytoplankton blooms generally occur in early spring (February–March) and in
autumn (September–November), and minor blooms occasionally occur during
summer (July–August; Smetacek et al., 1984; Smetacek 1985; Bange et al.,
2010). The resulting high organic matter fluxes and respiration rates result
in a high oxygen demand and, as a consequence, in bottom-water hypoxia (or
occasionally even anoxia) during summer (Hansen et al., 1999). The frequency
of water column hypoxia in Eckernförde Bay has increased since the 1960s
(Lennartz et al., 2014). The high organic matter sinking flux and rapid
sedimentation of organic matter also lead to enhanced methanogenesis in the
muddy sediment, and to high methane concentrations in the overlying water
column (Jackson et al., 1998; Whiticar 2002; Treude et al., 2005; Bange et
al., 2010). Results from monthly samplings during the last 10 years have
revealed year-round methane seepage from the seafloor and methane
supersaturation (with respect to the atmospheric equilibrium) of surface
waters (Bange et al., 2010).
Map of the North Sea and the western Baltic Sea with a close-up of the study
area. (a) Overview map of the western Baltic Sea including the Kattegat,
the Skagerrak and parts of the North Sea. (b) Close-up of the study area
with the sampling site (time-series station Boknis Eck) marked with a white
dot. Red arrows indicate sporadic inflow of North Sea water.
The stratification period in Eckernförde Bay ends in autumn
(October–November), with the onset of surface-water cooling and water-column
mixing during autumn storms (Bange et al., 2010). Besides these seasonal
water-column stability changes, episodic perturbations of the water column
can be observed during occasional major saltwater injections from the North
Sea. Such events occur over short time periods (days to weeks) when easterly
winds are followed by strong westerly winds, leading to the inflow of salty,
oxygen-enriched (autumn/winter) or oxygen-poor (summer) bottom water,
respectively (Nausch et al., 2014; Mohrholz et al., 2015). As a result of
variable exchange (not only during major saltwater injections) between North
Sea and Baltic Sea water, bottom water salinity fluctuates strongly between 17
and 24 psu (Lennartz et al., 2014).
Seasonal variability of physico-chemical parameters and aerobic
methanotrophy at the Boknis Eck station. Distribution of salinity (a),
oxygen (b), temperature (c), methane (d), first-order rate constants of
aerobic methane oxidation k(e), and aerobic methane oxidation rates
rMOx(f). Positions of discrete samples (dots) and continuous
measurements (dashed lines) are indicated. Depths of water used for oxygen
and temperature incubation experiments (Figs. 3 and 5) are indicated with
circles in (b) and (c). Depths of water used for biomass incorporation
experiments at different oxygen concentrations (Figs. 4, S2) are
indicated with crosses in (b).
Sampling
Sampling was conducted every 3 months over a time period of 2 years
(October 2012–September 2014). On board R/V Alkor, RC
Littorina or RB Polarfuchs, water-column samples were
collected from 1, 5, 10, 20, and 25 m below sea level (m b.s.l.) using a
rosette sampler equipped with 6 × 4 L Niskin bottles and CTD
(conductivity, temperature, depth) and O2 probes for continuous
measurements of conductivity, temperature, density, and dissolved oxygen,
respectively (Hydro-Bios, Kiel, Germany; O2-sensor: RINKO III). In the
following, we use the common term CTD for the combined suite of sensors,
including the O2 sensor. We note that water column zones where the CTD
oxygen sensor indicated 0 µmol L-1 O2 are not
necessarily anoxic in the strict sense. Given that the detection limit of the
Winkler method applied to calibrate the CTD oxygen sensor is
1–2 µmol L-1, micro-aerobic concentrations at the
sub-µM levels were likely not detected as such. Water aliquots were
sampled for measurements of methane concentration and MOx activity. For an
overview of sampling dates and corresponding parameters or incubations, see
Table 1. In the following, samples from 1 and 5 m b.s.l. will be referred
to as “surface waters”, and samples from 20 and 25 m b.s.l. are
considered “bottom waters”.
Overview of sampling dates and sampled parameters. “Temp. dep.”
indicates samples used for temperature dependency incubations,
“O2 dep.” indicates samples used for O2
incubations with 3H-CH4 and
14C-MOx for O2 incubations with
14C-CH4 and determination of
14C-incorporation into biomass.
SamplingDateCH4rMOxTemp. dep. O2 dep. 14C-MOx 5 m b.s.l.20 m b.s.l.5 m b.s.l.20 m b.s.l.5 m b.s.l.20 m b.s.l.Oct 201217.10.2012xxMar 201313.03.2013xxJun 201327.06.2013xxSep 201305.09.2013xxxNov 201308.11.2013xxxxxbxFeb 201424.02.2014xxxxaxxaxxaJun 201418.06.2014xxxxxxxxSep 201417.09.2014xxxx
a Because of disturbance of the water column, we used water from 25 m b.s.l. instead of 20 m b.s.l.
b Because of disturbance of the water column, we used water from 15 m b.s.l. instead of 20 m b.s.l.
Dissolved methane concentration
For dissolved methane (hereafter just methane) measurements, three 25 mL
vials per sampling depth were filled bubble free immediately after
CTD rosette recovery, poisoned with saturated mercury chloride solution
(50 µL) and stored at room temperature. Methane concentrations were
then determined by gas chromatography and flame ionization detection with a
headspace method as described in Bange et al. (2010).
Methane oxidation rate measurements
MOx rates (rMOx) were determined in quadruplicates from ex
situ incubations of water samples with trace amounts of 3H-labelled
methane as described in Steinle et al. (2015) based on a previously
described method (Reeburgh et al., 1991). In brief, 25 mL crimp-top vials
were filled bubble free and closed with bromobutyl stoppers that are known to
not affect MOx activity (Helvoet Pharma, Belgium; Niemann et al., 2015).
Within a few hours after sampling, 6 µL of a gaseous
3H-CH4/ N2 mixture (∼ 15 kBq, < 30 pmol
CH4, American Radiolabeled Chemicals, USA) were added and samples were
incubated for 3 days in the dark at in situ temperature
(±0.5 ∘C, Fig. 2c). The linearity of MOx during a time period up
to 5 days was verified in selected samples by replicate incubations at 24,
48, 72, 96, and 120 h. At the end of the incubation, we determined the
3H activities of the H2O (AH2O; includes possible
radio-label incorporation into biomass) and of non-reacted CH4
(ACH4) by liquid scintillation counting. Activities were
corrected for (insubstantial) fractional turnover (∼ 0.1–0.01 %)
in killed controls (addition of 100 µL saturated HgCl2
solution). From these activities, we calculated the fractional turnover of
methane (first-order rate constants; k; Eq. 1):
k=AH2O(AH2O+ACH4)×1t,
where t is incubation time.
rMOx was then calculated from k and water column
[CH4] at the beginning of the incubation (see Sect. 2.4; Eq. 2):
rMOx=k×[CH4].rMOx from incubations with 14C-labelled methane was
determined analogously by measuring the radioactivity of 14CH4,
14CO2 (ACO2), and the remaining radioactivity
(AR), according to Blees et al. (2014) and Steinle et
al. (2016). The use of 14C also allows the assessment of methane
incorporation into biomass (Eq. 3):
Cincorp.=ARACO2+AR.
MOx rates in incubations with adjusted oxygen concentrations.
rMOx determined in incubations of Boknis Eck water (20 m b.s.l.)
with 3H-CH4 in February 2014 (a) and June 2014
(b). Asterisks indicate a p < 0.05 of a
two-tailed, two-sample t test assuming equal variance of the MOx rate
compared to the MOx rate of the lowest oxygen concentration. Corresponding
oxygen concentrations determined at the beginning and the end of incubations
from the February 2014 (c) and the June 2014 sampling (d)
for incubations with oxygen concentration
< 10 µmol L-1. Numbers on the x axis of
(c) and (d) correspond to numbers above the bars in
(a) and (b) and indicate the incubation number. Incubations
were performed in triplicates and standard deviations are indicated. For
oxygen concentrations > 10 µmol L-1, oxygen
concentrations at the end of incubations were 14–40 % (February 2014)
and 3–8 % (June 14) lower than at the beginning (data not shown).
Oxygen manipulation experiments
Oxygen dependency experiments with the addition of 3H-CH4 were
conducted with water from 25 m b.s.l. sampled in February 2014 (in situ
concentrations of [O2] = 443 µmol L-1;
[CH4] = 234 nmol L-1) and from 20 m b.s.l. in June 2014 (in situ
concentrations of [O2] = 161 µmol L-1;
[CH4] = 34 nmol L-1). Until the start of the experiments
(∼ 5 days after sampling), the sampled water was stored headspace free
at 0 ∘C. For the incubations, the water was filled into 160 mL
glass vials, which were closed with gas-tight bromobutyl rubber stoppers
(Helvoet Pharma, Niemann et al., 2015). Before use, the stoppers were boiled
in water and stored under N2 in order to avoid bleeding of oxygen from
the rubber matrix into the vials. The vials were then purged for 30 min with
high-purity N2 gas, transferred to an anoxic glove box (N2
atmosphere), and the N2 headspace that was generated during the purging
was exchanged with N2-purged Boknis Eck water. For final oxygen
concentrations < 15 µmol L-1 (Fig. 3), we injected
0.1–8 mL of Boknis Eck water (in the glove box) that was previously
equilibrated with ambient air. No additional oxygen was added to the
incubation with the lowest oxygen concentration after purging the vials,
resulting in oxygen concentrations < 0.5 µmol L-1.
For the final oxygen concentrations > 15 µmol L-1, 10
ml headspace with a predefined gas mixture of O2/ N2
(5/95–12/88) was added, and the vials were left to equilibrate overnight
at 4 ∘C. Additional vials were used to fill up the headspace the
next day. After the oxygen adjustment, we added 12 µL of anoxic
Boknis Eck water enriched in methane, resulting in a final methane
concentration of ∼ 100 nmol L-1 in the incubation vial. For
rMOx determination, we added 3H-CH4 tracer in
the glove box as described above. Oxygen concentration was measured with a
high-sensitivity (detection limit ca. 0.05 µM) OX-500 microsensor
(Unisense). N2-purged seawater amended with dithionite (final
concentration 9 mmol L-1) was used as a blank. Oxygen concentrations
during incubations were determined by measuring initial and final oxygen
concentration in parallel incubations, which were amended with 6 µL
N2 gas instead of 3H-CH4. Vials were incubated at
20 ∘C in the dark for 6 h ([O2]
> 15 µmol l-1) or 10 h (for
[O2] < 15 µmol L-1). In situ temperatures were
2.7 and 9.8 ∘C in February and June 2014, respectively. Incubation
times differed because of time constraints during sample processing.
rMOx was determined as described above.
Incorporation of biomass at different oxygen concentrations
Incorporation of biomass at different oxygen concentrations was assessed
using 14C-CH4 with water from 5 m b.s.l. sampled in February 2014 (in
situ concentrations of [O2] = 581;
[CH4] = 22 nmol L-1) and June 2014 (in situ concentrations of
[O2] = 301;
[CH4] = 14.5 nmol L-1), from 20 m b.s.l. sampled in
November 2013 (in situ concentrations of
[O2] = 234;
[CH4] = 82 nmol L-1) and June 2014 (in situ concentrations
of [O2] = 161;
[CH4] = 34 nmol L-1), and from 25 m b.s.l. in February 2014 (in
situ concentrations of [O2] = 443;
[CH4] = 234 nmol L-1; see also Table 1). Samples were
prepared as described in Sect. 2.4.1 with the following modifications: we
only performed the 14C-CH4 incubations with two different oxygen
concentrations (< 0.5 and
∼ 220 µmol L-1), and used 220 mL instead of 160 mL
glass vials. We added 10 µL of a 14C-CH4/ N2
gas mixture (∼ 200 kBq, ∼ 80 µmol CH4, American
Radiolabeled Chemicals, USA) to the samples. The vials were incubated for 6 h
at 20 ∘C in the dark.
Temperature dependency experiments
Similar to the determination of rMOx at in situ
temperature, we incubated water column aliquots in triplicates at different
temperatures between 0.5 and 37 ∘C in incubators. Exact temperatures
are provided in Figs. 5 and S2. We determined the temperature dependency of
MOx in samples collected at 5 and 20 m b.s.l. between September 2013 and
September 2014 (Table 1). The MOx temperature optimum is defined here as the
temperature where measured MOx rates were highest (i.e. not as the optimum
for growth).
Areal MOx rates and methane release to the atmosphere
For each sampling date, we interpolated linearly between the measured rates
at different depths, to obtain depth-integrated average rates for the 28 m-deep water column, and to calculate the methane oxidation rate per unit area
(FMOx; in µmol m-2 d-1). Methane flux
(Fatm; in µmol m-2 d-1) from surface
waters to the atmosphere was calculated according to Bange et al. (2010):
Fatm=k600×ScCH4/600-0.5×CH4-[CH4]eq,
where ScCH4 is the Schmidt number for CH4, which is dependent
on temperature and salinity, and is calculated as the ratio of kinematic
viscosity of seawater (Siedler and Peters, 1986) and the diffusion
coefficient of methane in seawater (Jähne et al., 1987). [CH4] is
the measured methane concentration at 1 m b.s.l., [CH4]eq is
the calculated CH4 equilibrium concentration (Wiesenburg and Guinasso,
1979), with respect to average atmospheric pressure at sea level (measured at
the Kiel Lighthouse, data available online on the website of the
Federal Maritime and Hydrographic Agency of Germany; www.bsh.de) and
the atmospheric methane concentration (median between 2012 and 2014) in the
Northern Hemisphere (Mace Head Station; Prinn et al., 2014), and
k600 is the gas transfer coefficient. Following the
recommendation by Raymond and Cole (2001) for coastal systems, we used 3 and
7 cm h-1 as minimum and maximum values for k600. These
k600 values already include wind strength.
To determine the strength of water column stratification, we calculated the
Brunt–Väisälä buoyancy frequency N:
N=-gρ×dρdz,
where g is the gravitational constant, ρ is the potential density, and
z is the geometric height. The average N (in cycles per hour; cph) was
calculated for the depth interval 10–20 m b.s.l.
Statistical analyses
The pairwise linear correlations of different physico-chemical factors with
methane concentrations and MOx rate constants and MOx rates were calculated
in Matlab with the corr(X,Y, “Pearson”, “both”) function to obtain the
Pearson linear correlation coefficient and the corresponding p value. In
the results and discussion section, all presented R2 values are Persons
linear correlation coefficients.
ResultsSeasonal variations of physico-chemical water column properties
Physico-chemical water column properties generally showed large seasonal
variations (Fig. 2). Salinity varied strongly in bottom (18–25 psu) and
surface waters (13–20 psu) with the highest salinities observed in
September–November (Fig. 2a). During winter samplings, water temperatures
were coldest and rather invariant throughout the water column at
1–3 ∘C (March 2013, February 2014; Fig. 2b). They increased from
spring until the end of summer to a maximum of 18 ∘C in the surface
(June 2013, September 2014) and 13 ∘C in bottom waters
(October 2012, September 2014). Dissolved oxygen concentrations in bottom
waters varied from < 1 to 450 µmol L-1 (Fig. 2c),
with the highest concentrations observed during fully mixed conditions (March
2013, February 2014). In March 2013 and February 2013, chlorophyll a
concentrations were comparably high (data not shown, available at
www.bokniseck.de), indicating a phytoplankton bloom during these time
periods. Bottom waters became hypoxic in June (2013, 2014) and reached oxygen
concentrations ≤ 1 µmol L-1 towards the end of the
stratification period (September 2013, 2014). In surface waters, levels of
dissolved oxygen were always high
(> 280 µmol L-1), reaching maximum concentrations
during a phytoplankton bloom in March 2013 and February 2014
(> 450 µmol L-1; Fig. 2c). Dissolved methane
concentrations reached values up to 466 ± 13 nmol L-1
(March 2014) in bottom waters, and were always
> 30 nmol L-1 during the time of our study (Fig. 2d). We
did not observe a clear repeating seasonal pattern of methane concentrations
in the 2 years of our study. Surface-dissolved methane concentrations ranged
between 8 and 27 nmol L-1, corresponding to supersaturation levels of
270–870 % with respect to the atmospheric equilibrium
(2.8–4.3 nmol L-1).
Seasonal variability of MOx
First-order rate constants (k) of MOx were always highest in bottom
waters (0.003–0.084 d-1) with the exception of November 2013 when the
highest k was measured at 15 m b.s.l. (Figs. 2e, S1 in the
Supplement). The same pattern was found for rMOx, which
was always highest in bottom waters (1.0–11.6 nmol L-1 d-1),
again with the exception of November 2013 (Fig. 2f). The highest values for
rMOx were observed in summer (June 2013) or autumn
(October 2012, September 2013, September 2014) when bottom water temperatures
were highest and oxygen concentration were lowest. A correspondence between
maximum rMOx and high/maximum CH4 concentrations
(i.e. in March 2014) was not observed.
Experiments on the influence of oxygen concentrations on MOx activity
In the subsequent presentation of experimental data, hypoxic conditions
(i.e. [O2] < 63 µmol L-1) will be referred to
as “low” and [O2] > 63 µmol L-1 as
“high” oxygen concentrations for the sake of simplicity. During our lab-based
experiments with different oxygen concentrations, rMOx was
always highest in incubations with the lowest oxygen concentration (Tables S1,
S2 in the Supplement, Fig. 3). Rates under nearly saturated oxygen conditions were
significantly lower (50 % in February, 75 % in June;
p<0.05) than the rate measured at the lowest initial oxygen
concentration. However, while we found that rMOx did not
vary strongly at different oxygen concentrations
< 140 µmol L-1 (Fig. 3a) in February 2014, the rates
measured in June 2014 were more variable (Fig. 3b).
All incubations remained oxic during the incubation time, even incubations
with very low initial oxygen concentrations (Tables S1, S2, Fig. 3c, d). In
February 2014, 41–79 % of oxygen was consumed during incubations with
initial [O2] < 15 µmol L-1 (Fig. 3c), and
14–40 % during incubations with initial [O2]
> 15 µmol L-1 (Table S1). In June 2014,
22–73 % of the oxygen was consumed during incubations with initial
[O2] < 15 µmol L-1 (Fig. 3d), and 3–8 %
during incubations with [O2] > 15 µmol L-1
(Table S2).
Similar to incubations with 3H-CH4, k values determined with
14C-CH4 at saturated oxygen concentration were lower than k values
measured in incubations with
[O2] < 0.5 µmol L-1 (32 % lower on
average; Figs. 4a, S2a, b). In contrast, a higher fraction of the
oxidized 14C was incorporated into biomass in incubations at saturated
oxygen concentration than at
[O2] < 0.5 µmol L-1 (between 108 and
3800 % more; Figs. 4b, S2c, d), irrespective of water depth and sampling
season (Fig. S2). Radio-label incorporation at low oxygen levels
([O2] < 0.5 µmol L-1) was generally more
pronounced in bottom (20 m b.s.l.) than in surface waters (5 m b.s.l.).
Methane–carbon assimilation in relation to oxygen concentration.
Methane–carbon assimilation was determined from incubations amended with
14C-CH4 at saturated (∼ 220 µmol L-1, shaded bars) or low oxygen concentrations
(< 0.5 µmol L-1, black bars) of water recovered
in June 2014 at 5 and 20 m b.s.l. Incubations were performed in
triplicates and standard deviations are indicated. (a) First-order rate
constant (k). (b) Fraction of oxidized methane incorporated into biomass.
Asterisks indicate a p value < 0.05 of a two-tailed, two-sample
t test assuming equal variance between the samples at low and high oxygen
concentrations.
Temperature dependence of MOx
In general, k increased with temperature and reached maximum values
at 20–37 ∘C, indicating a mesophilic temperature optimum
(Fig. 5a, c; shown are results from September 2013 and February 2014; Table 1;
Fig. S3). Only in November 2013, maximum MOx was observed at
10–20 ∘C, consistent with a psychrophilic temperature optimum
(Fig. 5b). These patterns were independent of water depth (Figs. 5, S3).
MOx first-order rate constants (k) at different temperatures.
First-order rate constants of MOx were determined with
3H-CH4 amendments in triplicated incubations of
water from 20 m b.s.l. recovered in September 2013 (a), November 2013 (b), and February 2014
(c). Red, dashed lines indicate in situ temperatures.
Water-column methane removal by MOx and methane fluxes to the atmosphere
Depth-integrated rMOx (=FMOx)
varied between 11.7 µmol m-2 d-1 (March 2013) and
82.3 µmol m-2 d-1 (September 2014; Table 2). Estimated
average fluxes of methane to the atmosphere were
3.6–9.2 µmol m-2 d-1 during stratified periods, and
10.0–25.1 µmol m-2 d-1 during mixed periods
(considering a minimum or maximum kw, respectively;
Table 2; Raymond and Cole 2001). According to the buoyancy frequency
N, we grouped the sampling dates into two categories: weakly (i.e.
N < 120 cph) and strongly stratified (i.e.
N > 120 cph). The water column was only weakly stratified in
October 2012, March 2013, and February 2014, and strongly stratified during
all other samplings (Table 2).
Integrated methane oxidation rates (FMOx) and methane
flux into the atmosphere (Fatm) in comparison to stratification
(indicated by the buoyancy frequency N). Fatm was calculated with
a min and max k600-value. N is given as the average N for
10–20 m b.s.l. A water column with N values > 120 is
considered stratified.
SamplingFMOxFatm- min k600Fatm- max k600FMOx/FatmN(µmol m-2 d-1)(µmol m-2 d-1)(µmol m-2 d-1)(cph)Oct 201229.612.431.11.487Mar 201311.710.526.40.666Jun 201327.33.27.94.9247Sep 201333.03.48.55.6229Nov 201328.06.315.82.5211Feb 201414.57.017.61.2114Jun 201412.72.97.42.4200Sep 201482.32.56.219.0227DiscussionSeasonal variations at Boknis Eck Development of seasonal hypoxia
Oxygen concentrations were always close to saturation levels during our
winter samplings (i.e. March 2013, February 2014), when the water column was
poorly stratified and phytoplankton blooms occurred, which is typical for
this time period (Bange et al., 2010). During June samplings, we observed
much lower bottom water oxygen concentrations, indicating the onset of
hypoxia, reaching submicromolar oxygen concentrations below 24 m b.s.l. in
September (2013, 2014). Our observation is in accordance with a previous time
series study (2006–2008) by Bange et al. (2010), who found hypoxic events
starting between May and August and lasting until September or November.
Long-term monitoring at Boknis Eck showed that the frequency and length of
hypoxic events have increased over the last 20 years (Lennartz et al.,
2014), although nutrient inputs into the Baltic Sea were strongly reduced
(HELCOM, 2009). One of the main reasons for the ongoing decrease in oxygen
concentration is the increasing water temperature since the 1960s (Lennartz
et al., 2014). Higher surface water temperatures have led to an extension of
the stratification period (starting earlier in the annual cycle), reducing
the overall exchange between bottom and surface waters (Hoppe et al., 2013;
Lennartz et al., 2014). Furthermore, a general increase in temperature also
enhances mineralization of organic matter in bottom waters and results in a
higher biological oxygen demand (Hoppe et al., 2013; Lennartz et al., 2014).
Seasonal dynamics of methane concentrations and MOx
Methane concentrations at Boknis Eck were in a similar range to other shelf
seas and coastal ecosystems (e.g. Rehder et al., 1998; Bange, 2006;
Upstill–Goddard 2016). We did not observe any clear seasonal methane
concentration patterns as observed for oxygen concentrations and other
physico-chemical parameters (Fig. 2). Our data are consistent with
observations from 2006 to 2008 by Bange et al. (2010), who showed that
methane concentrations did not follow bimodal seasonal variations. Instead,
increases in water column methane followed chlorophyll a
concentrations in surface waters with a 1-month time lag, suggesting that
pulses of elevated organic matter input to the sediments were boosting
benthic methanogenesis.
We did not observe direct links between water column oxygenation and methane
concentrations (R2= 0.007; p= 0.6). However, water column
oxygen concentrations can have indirect and inverse effects on methane
concentrations: low oxygen concentrations combined with high sedimentation
rates of organic matter lead to enhanced burial of “fresh” organic matter
to the sediments, which in turn favours methanogenesis at Boknis Eck (Bange
et al., 2010; Maltby, 2015). Furthermore, water column stratification at
times of water column hypoxia at Boknis Eck hinders exchange between bottom
and surface waters, which further promotes methane accumulation in bottom
waters. Such a modulating effect of oxygen on methane concentrations has also
been found in other hypoxic ecosystems (see review by Naqvi et al., 2010).
Nonetheless, the highest methane concentrations were not always observed during
periods of minimum oxygen concentrations. On the contrary, we found
reduced net methane accumulation in bottom waters at times of hypoxia and
strong water column stratification (summer/autumn 2013, Fig. 2), likely
caused by the comparatively high MOx rates observed during this time period.
We did not observe a direct stimulus of high methane concentrations on the
turnover rate constant k (R2= 0.1; p= 0.6). For
example, we found low methane concentrations in March 2013 co-occurring with
high turnover constants, while high methane concentrations in September 2014
were also accompanied by elevated turnover constants. Previous studies
suggested an inverse relationship between turnover time (i.e. 1/k) and
methane concentrations (Elliott et al., 2011; Nauw et al., 2015; Osudar et
al., 2015; James et al., 2016). Although this relationship may be robust
across different environmental settings, several studies found that on a
smaller, local scale the CH4/k connection does not necessarily apply
(Heintz et al., 2012; Mau et al., 2012; Steinle et al., 2015, 2016).
MOx rates at Boknis Eck were of the same order of magnitude as those measured
in other coastal environments (e.g. Abril and Iversen 2002; Mau et al.,
2013; Osudar et al., 2015). MOx measurements in this study revealed seasonal
dynamics, with lower rates during the winter season when the water column was
mixed and oxygen concentrations were high (March 2013, February 2014), and
highest rates during stratified, hypoxic conditions (June–October). Our data
suggest a negative dependency ofrMOx with oxygen concentration
(R2= 0.49; p= 0.001), whereas this was not the case with
temperature (R2= 0.03; p= 0.82). In order to further
investigate these putative links observed during the time-series study, we
conducted laboratory experiments to specifically assess the effects of oxygen
concentration (Sect. 4.2) and temperature (Sect. 4.3) on MOx.
Aerobic methanotrophy under micro-oxic conditions
We observed the highest MOx rates in September 2013 and September 2014
(Fig. 2f), when bottom water oxygen concentrations were below the detection
limit of the oxygen sensor (i.e. 1–2 µmol L-1). Whether
oxygen concentrations reached true zero levels is unclear. Our measurements
did not reveal hydrogen sulfide concentrations in the water column, and the
absence of any hydrogen sulfide smell points to the fact that traces of
oxygen were probably still present. Anaerobic oxidation of methane (AOM) thus
seems unlikely to account for the observed oxidation rates since anaerobic
methanotrophs cannot persist in the presence of oxygen even at submicromolar
levels (Treude et al., 2005; Knittel and Boetius, 2009). Other recent studies
in lakes reported on the occurrence of aerobic methanotrophy in apparently
anoxic environments (Blees et al., 2014; Milucka et al., 2015; Oswald et al.,
2015). Two of these studies showed that, in the presence of light,
photosynthetic algae create oxic microniches and provide enough oxygen for
MOx to proceed under otherwise anoxic conditions (Milucka et al., 2015;
Oswald et al., 2015). We cannot rule out that in situ MOx in oxygen-depleted
waters of Boknis Eck was, at least to some degree, fuelled by photosynthesis
in bottom waters. However, light intensities deeper than 20 m b.s.l. in the
murky waters at Boknis Eck are likely too low to account for the observed
high rates. Furthermore, in the dark-incubation experiments of this study,
rates were still highest at the lowest oxygen concentration (Tables S1, S2,
Fig. 3), arguing against any significant photosynthetic production of oxygen
to support light-dependent MOx. In another lake study, a large potentially
active MOx community was discovered in the anoxic hypolimnion > 125 m
below the lake surface, where light-dependent MOx can be excluded (Blees et
al., 2014). It was hypothesized that sporadic oxygen inflow was sufficient to
sustain a viable MOx community in anoxic waters, well below the permanent
redoxcline. At Boknis Eck, it is possible that episodic oxygen inputs through
horizontal advection can occur, as has been observed after North Sea water
inflows into the anoxic basins of a Danish fjord (Zopfi et al., 2001) and the
Baltic Sea (Schmale et al., 2016). Although we cannot say without doubt what
the sources of oxygen are that sustain MOx under micro-oxic conditions our
incubation experiments with oxygen concentrations as low as
∼ 0.1 µmol L-1 show that MOx rates remain high at such
low concentration (Figs. 3, 4). This consequently provides evidence that
MOB are well adapted to the seasonally submicromolar oxygen levels in bottom
waters at Boknis Eck, Baltic Sea.
Whereas plausible explanations exist for the presence and activity of MOB
under seemingly oxygen-starved conditions, we still lack an explanation for
the observation that in our incubations MOx rates were highest at the lowest
oxygen levels, independently of the initial oxygenation state of the sampled
water (Fig. 3). The apparent adaptation to low oxygen concentrations may be
part of a strategy to avoid the detrimental effects of methane starvation
under oxic conditions and to escape grazing pressure in more oxygenated
water. For example, grazers were found to control the community size of MOB
in shallow Finnish lakes (Devlin et al., 2015). The ability of MOB to operate
at low oxygen levels apparently enables them to thrive in bottom waters with
only trace amounts of oxygen. Additionally, reduced grazing activity under
hypoxia may allow efficient MOB community growth, which would lead to
elevated MOx activity in these water layers. Indeed, direct links between the
MOB community size and MOx have been demonstrated before (e.g. Steinle et
al., 2015). We did not investigate zooplankton in our ex situ incubations,
and hence, do not know whether limited grazing within the incubations
themselves at low oxygen levels was responsible for the observed trend of
highest MOx rates at low oxygen levels.
Enhancement of MOx rates in incubations at low oxygen levels can also be
explained at the cellular/biochemical level. Aerobic microbes produce
reactive oxygen species (ROS; including superoxide anion radicals, hydrogen
peroxide, and hydroxyl radicals) as by-products during their metabolism, which
can cause oxidative damage to cellular structures. The amount of ROS leaking
from the respiratory chain typically increases at elevated oxygen
concentrations (see review by Baez and Shiloach, 2014). Although we can only
speculate as to how effectively MOB are able to remove ROS (e.g. by catalase),
it seems possible that MOx may be slowed down at high oxygen concentrations.
However, the fraction of 14C incorporated into biomass was markedly
higher at elevated oxygen concentration, even though MOx rates were higher at
low oxygen concentration (Fig. 4), which rather suggests differential
metabolic functioning of MOB at low versus high oxygen concentrations.
Kalyuzhnaya et al. (2013) showed that, under oxygen-deficiency stress
(< 10 µmol L-1), a strain of type I MOB
(Methylomicrobium alcaliphylum 20Z) switched to fermentative
methane utilization, leading to a reduced MOB-biomass synthesis and the
enhanced formation of short-chain carbonic acids (i.e. formate, acetate,
succinate) as metabolic end products. If the Boknis Eck-MOB employed a
similar, energetically less favourable methane utilization pathway, our
results could be explained by an overall higher catabolic activity at the
cost of anabolic investment at low oxygen concentrations. Additional
biochemical investigations are necessary to constrain the metabolic
partitioning of MOB at high versus low oxygen levels further, but also to
test the potential role of ROS in MOx attenuation at elevated oxygen levels.
Finally, we cannot rule out that MOx in our incubations (and at Boknis Eck)
is mediated by a diverse MOB community, of which different members are active
at different oxygen levels. Such a shift may also lead to the observed
discrepancies in the MOx rate and metabolic functioning.
Temperature effects on MOx Mesophilic behaviour of MOx and implications for future warming
With the exception of November 2013 (see Sect. 4.4, below), the MOB community
at Boknis Eck generally showed a mesophilic behaviour, with temperature
optima > 10 and < 37 ∘C, both in bottom
(Fig. 5) and surface waters, respectively (Fig. S3). This is consistent with
temperature optimum ranges observed for most cultured aerobic methanotrophs
(Hanson and Hanson, 1996; Murrell, 2010). Except for November 2013 (see
Sect. 4.3.2), the temperature optimum was ∼ 5–20 ∘C higher
than the in situ temperature (at the time of sampling), which is typical for
many microorganisms (Price and Sowers 2004). The ongoing increase in
atmospheric temperature has led to a global sea surface temperature anomaly
of about 0.5 ∘C (until 2010), and future projections indicate
further warming by up to 2 ∘C until the middle of the 21st century
(IPCC, 2013). A similar warming trend is observed for the Baltic Sea (HELCOM,
2009). It is unclear how exactly surface water warming (and associated
physico-biogeochemical side effects in the upper water column) will influence
bottom water temperatures in the future. Particularly in shallow shelf seas,
however, ocean surface warming is likely to propagate to deeper water layers,
and indeed, such a warming trend has been recorded at Boknis Eck (Lennartz et
al., 2014). Our incubation experiments indicate that the present MOB
community is well adapted to temperature changes of a few degrees Celsius,
and that rMOx will probably increase in the near future.
Indirect evidence for a change of the MOB community by North Sea water
inflow events
Contrary to the general mesophilic MOB community at Boknis Eck, incubations
with water samples from November 2013 (Figs. 5b, S3a) revealed a
psychrophilic behaviour of the MOB with a much lower temperature optimum at
about 10 ∘C. In November 2013, in situ temperatures were 12.0 and
10.6 ∘C at 20 and 5 m b.s.l., respectively. In contrast to all other
sampling dates, the temperature optimum hence corresponded to the in situ
temperature. These differences suggest the presence of another microbial MOB
community at Boknis Eck in November 2013 compared to the other sampling
times. The sampling took place on 8 November 2013, about 1 week after a
larger inflow event that transported oxygen-rich, salty North Sea water into
the Baltic Sea. This input is clearly indicated by salinity anomalies
observed at several hydrographic measurement stations of the Federal Maritime
and Hydrographic Agency of Germany (Nausch et al., 2014), including the
nearby station, Kiel Lighthouse. No continuous salinity measurements were
conducted at Boknis Eck to provide evidence for the saltwater injection
directly at the study site. However, the unusual oxygen profile with a
distinct minimum at 15 m b.s.l. and increasing oxygen concentrations in bottom
waters seems to attest to the October inflow event, during which dense
undercurrents of salt- and oxygen-rich water from the North Sea were wedging
into, and (partly) displacing, the hypoxic deep Eckernförde Bay water
(Fig. S1).
In November 2013, maximum k and rMOx were
detected at 15 m b.s.l., and not in bottom waters, as it was the case during all
the other samplings (Figs. 2, S1). In combination with the observed shift
from a meso- to a psychrophilic community, this suggests that with the
inflowing North Sea water, the local MOB community at Boknis Eck was
displaced. North Sea water is characterized by elevated methane
concentrations (Rehder et al., 1998) and relatively high water column MOx
rates were detected at several sites in the North Sea (Mau et al., 2015;
Osudar et al., 2015; Steinle et al., 2016), so that the inflowing water may
indeed contain relatively high numbers of MOB. However, the inflow and the
transient replacement of hypoxic Eckernförde Bay water (including its
microbial stock) has led to reduced MOx rates by the imported psychrophilic
compared to the autochthonous mesophilic MOB community near the sea floor.
Similarly, current-associated translocation of MOx communities has been found
to constitute an important control on the magnitude of local MOx rates
offshore Svalbard (Steinle et al., 2015). In Eckernförde Bay, further
studies that include molecular work would be needed to investigate the origin
of the seemingly differential MOB communities, their actual cell numbers, and
the effects of sporadic, short-term perturbations on the MOx potential.
Considerable methane removal by MOx
The median methane efflux into the atmosphere calculated from our
measurements (5.1 or 11.9 µmol m-2 d-1, considering
min. and max. values for k, respectively) was very similar to
previous data from a monthly sampling campaign at Boknis Eck between 2006 and
2008 (6.3–14.7 µmol m-2 d-1; Bange et al., 2010).
Average surface saturation (447 % with respect to atmospheric
equilibrium) at Boknis Eck was at the lower end of European estuarine systems
and river plumes, but clearly higher than values determined for European
shelf waters (Upstill-Goddard et al., 2000; Bange, 2006; Schubert et al.,
2006; Grunwald et al., 2009; Ferrón et al., 2010; Schmale et al., 2010;
Osudar et al., 2015; Upstill-Goddard and Barnes, 2016). At Boknis Eck,
methane originates from sedimentary methanogenesis (Whiticar 2002; Treude et
al., 2005; Maltby, 2015), which can enter the water column either by
diffusion or by bubble transport. The amplitudes of methanogenesis and AOM
were found to show strong spatio-temporal heterogeneity, which makes flux
estimates difficult (Treude et al., 2005; Maltby, 2015). However, our data
allow calculating the amount of water column methane oxidation compared to
the fraction of methane that ultimately evades to the atmosphere (i.e.
FMOx/Fatm-avg; possible effects
of advection on methane concentration and MOx are ignored). Our
depth-integrated MOx rates and the average of our minimum and maximum
estimates of methane efflux to the atmosphere imply that 2.4–19 times more
methane is oxidized than is emitted to the atmosphere during stratified
conditions (Table 2), underscoring the high efficiency of the water column
methane filter during summer/autumn, albeit the shallow water depth. In
contrast, almost the same amount of methane is oxidized and emitted (factor
of 0.6–1.4) during mixed conditions in winter/spring. This difference is
mostly due to the lower average Fatm under stratified
conditions, as Fatm correlates negatively with buoyancy
frequency (R2= 0.8; Fig. S4). However, FMOx was
also highest in autumn months (September–November), and lowest in winter/spring
(February–March; Table 2). Under stratified conditions, the combination of a
generally higher (community-driven) MOx potential and the limited exchange
between bottom waters and the upper mixed layer, and hence a lower turbulent
diffusive methane flux, are conducive to efficient methane oxidation and
contribute to the higher MOx filter capacity during summer/autumn. In
conclusion, seasonal water column stratification and, consequently, lower
oxygen concentrations thus not only promote generally higher rates of MOx but
also have a modulating effect on the efficiency of the microbial methane
filter in the water column.
Conclusions and implications
To the best of our knowledge, this is the first long-term
(> 2 years) seasonal study on MOx activity in a seasonally
stratified/hypoxic coastal environment. The results are important for the
understanding of the temporal dynamics and environmental controls on the
efficiency of the MOx methane filter in shallow marine environments. We
demonstrate that methane oxidation at Boknis Eck is strongly affected by
changes of water column stratification, as well as by inflow events from the
North Sea, and the associated episodic displacement of bacterial communities
with different MOx potential. Moreover, we provide evidence that MOB at
Boknis Eck are well adapted to very low oxygen concentrations, with a clear
tendency of the highest MOx rates occurring in the submicromolar range. Although
the exact ecological driving forces, as well as the biochemical mechanisms
behind this adaptation remain uncertain, it seems likely that the capacity to
thrive in low-oxic waters enables MOB to evade grazing pressure in the more
oxygenated parts of the water column.
Our field and laboratory investigations revealed that very low oxygen
concentrations under stratified conditions and at elevated temperatures are
particularly conducive to high MOx rates and efficient methane “removal”
from the water column. Ongoing trends at Boknis Eck (and in many other
coastal ecosystems) predict warmer temperatures in the future, and probably
an earlier onset of seasonal stratification. However, for a future scenario,
it remains unclear as to what extent the low-oxygen adaptation and a
temperature-related enhancement of MOx will counterbalance elevated rates of
methanogenesis in the sediments caused by higher temperatures. Our study
suggests that an extension of the hypoxic period and increasing temperatures
will not necessarily lead to higher methane evasion to the atmosphere.
Ultimately, the oxygen–MOx link will also depend on the potential inhibition
of MOB growth under oxygen-depleted conditions. Our experimental data suggest
that the MOB communities can experience growth restrictions under
oxygen-deficiency stress, but whether the expected spatio-temporal expansion
of hypoxia, and eventually anoxia, may finally hamper MOx has to be
investigated further.
All data presented in this paper are available in the PANGAEA data
repository (10.1594/PANGAEA.871890, Steinle et al., 2017).
The Supplement related to this article is available online at doi:10.5194/bg-14-1631-2017-supplement.
Lea Steinle, Johanna Maltby, Tina Treude, Moritz F. Lehmann, and Helge Niemann designed the
study. Lea Steinle and Johanna Maltby carried out on board sampling. Lea Steinle, Johanna
Maltby, Annette Kock, and Hermann W. Bange conducted further geochemical analyses. Lea Steinle measured microbial rates and performed incubation experiments.
Helge
Niemann helped with incubation experiments. Lea Steinle prepared the
manuscript with contributions from all authors.
The authors declare that they have no conflict of
interest.
Acknowledgements
We thank the captains and crews of R/V Alkor, R/C Littorina and R/B
Polarfuchs, and the staff of the GEOMAR's Technology and Logistics Centre
for the excellent support at sea and onshore. Additional thanks go to G. Schüssler, F. Wulff, P. Wefers, A. Petersen, M. Lange, and F. Evers for
help with the fieldwork. We also thank F. Malien, X. Ma, S. Lennartz and T. Baustian for the regular calibration of the CTD and CH4 analysis. This
work received financial support through a D–A–CH project funded by the
Swiss National Science Foundation and the German Research foundation (grant
no. 200021L_138057, 200020_159878/1), and
through the Cluster of Excellence “The Future Ocean” funded by the German
Research Foundation. Further support was provided through the EU COST Action
PERGAMON (ESSEM 0902).
Edited by: C. P. Slomp
Reviewed by: D. Rush, S. Mau, and one anonymous referee
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