FEMS Microbiology Ecology, 92, 2016, fiw009
doi: 10.1093/femsec/fiw009
Advance Access Publication Date: 19 January 2016
Research Article
RESEARCH ARTICLE
Methane-cycling microorganisms in soils of a
high-alpine altitudinal gradient
Katrin Hofmann1,∗ , Harald Pauli2 , Nadine Praeg1 , Andreas O. Wagner1
and Paul Illmer1
1
Institute of Microbiology, University of Innsbruck, 6020 Innsbruck, Austria and 2 Institute for Interdisciplinary
Mountain Research, Austrian Academy of Sciences and Center for Global Change and Sustainability,
University of Natural Resources and Life Sciences, 1190 Vienna, Austria
∗
Corresponding author: Institute of Microbiology, LFU Innsbruck, Technikerstraße 25d, Innsbruck 6020, Austria. Tel: +43-512-507-51345;
Fax: +43-512-507-2928; E-mail: [email protected]
One sentence summary: Methanogenic archaea and methanotrophic bacteria were discovered in aerated high-alpine soils, indicating their ability to
withstand low temperatures.
Editor: Max Häggblom
ABSTRACT
Methanogens and methanotrophs play unique roles as producers and consumers of the greenhouse gas methane (CH4 ) in
soils, respectively. Here, we aimed to reveal whether and to which extent methane-cyclers occur in high-alpine soils, and to
assess their spatial distribution along an altitudinal gradient (2700–3500 m) in the Austrian Alps at sites located within the
alpine (2700–2900 m), the alpine-nival (3000–3100 m) and the nival belts (3200–3500 m). Methanococcales and Methanocella
spp. were most abundant among all quantified methanogenic guilds, whereas Methanosarcinales were not detected in the
studied soil. The detected methanogens seem to be capable of persisting despite a highly oxic low-temperature
environment. Methanogenic and methanotrophic activities and abundances of methanotrophs, Methanococcales and
Methanocella spp. declined with altitude. Methanogenic and methanotrophic abundances were best explained by mean
annual soil temperature and dissolved organic carbon, respectively. Alpine belt soils harbored significantly more
methane-cyclers than those of the nival belt, indicating some influence of plant cover. Our results show that methanogens
are capable of persisting in high-alpine cold soils and might help to understand future changes of these environments
caused by climate warming.
Keywords: alpine soil; altitudinal gradient; biogeography; methanogenic archaea; methanotrophic bacteria
INTRODUCTION
Methanogenic archaea (methanogens) and methane-oxidizing
bacteria (MOB) are the key players involved in methane-cycling
in soils due to their ability to either produce (methanogens)
or remove (MOB) the greenhouse gas methane (CH4 ), which is
considered as the second most important greenhouse gas in
the Earth’s atmosphere and significantly contributes to climate
warming (Le Mer and Roger 2001). Taking into account direct
and indirect chemical reactions of this gas with aerosols, its
global warming potential (GWP) is estimated to be ∼25 times
higher than the GWP of CO2 (Crutzen and Lelieveld 2001). Increasing abundance of atmospheric CH4 has already contributed
to an increase in mean air temperatures, which in the European
Alps was twice the global average by the end of the 20th century (Böhm et al. 2001). According to predictions stated in the
‘5th Assessment Report of the Intergovernmental Panel on Climate Change’ surface temperatures worldwide will increase by
Received: 30 October 2015; Accepted: 13 January 2016
C FEMS 2016. All rights reserved. For permissions, please e-mail: [email protected]
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FEMS Microbiology Ecology, 2016, Vol. 92, No. 3
1.1◦ C–6.4◦ C by the end of the 21st century (Stocker et al. 2013).
This may strongly affect alpine environments, which are expected to react extremely sensitively to climate change (Diaz,
Grosjean and Graumlich 2003; Schröter et al. 2005).
Methane uptake in (upland) soils is predominately mediated by aerobic methane-oxidizing bacteria, which are the only
known biological sink of CH4 . MOB are capable of using CH4 as
their sole source of carbon and energy by oxidation of CH4 to
the end products carbon dioxide and water (Hanson and Hanson
1996). The gene pmoA encodes for the α-subunit of the enzyme
particulate methane monooxygenase that is responsible for the
initial conversion of CH4 to methanol and can be found in almost all known methanotrophs. Thus, it has been widely used
for molecular studies (Hanson and Hanson 1996; McDonald et
al. 2008). MOB have been regularly detected at the oxic/anoxic
interfaces of various habitats in which they prevent the CH4
produced via methanogenesis from escaping to the atmosphere
(Conrad 1996). These MOB are typically capable of removing CH4
at high concentrations (>100 ppm) and are often referred to as
low-affinity methanotrophs or type 1 methanotrophs (Nazaries
et al. 2013). By contrast, type 2 methanotrophs (high affinity) can
metabolize methane at concentrations below 12 ppm (Singh et
al. 2010). Both type 1 and type 2 MOB are only distantly related
and mainly belong to the γ - and α-Proteobacteria, respectively.
The so far uncultured lineages of MOB capable of utilizing atmospheric CH4 concentrations ≤1.8 ppm are only distantly related to type 1 and 2 MOB and include the two ‘Upland soil clusters’ USCα and USCγ (Bender and Conrad 1992; Knief, Lipski and
Dunfield 2003; Angel and Conrad 2009; Kolb 2009). Other putative methane oxidizing clades have also been detected in tropical soils (‘Tropical upland soil cluster’, TUSC) (Knief et al. 2005)
and in forest soils (Cluster 1) (Kolb et al. 2005). These clades are
primarily responsible for the uptake of atmospheric CH4 in upland soils, which are considered as the sole terrestrial sink and
contribute 5%–15% of the annual uptake (Stocker et al. 2013). Besides these studies, which provided a better understanding of
MOB in low-altitudinal soils, few investigations have considered
the abundance and activity of MOB in high-alpine soils (Nauer
et al. 2012; Wagner et al. 2012; Hofmann, Reitschuler and Illmer
2013; Chiri et al. 2015). Nauer et al. (2012) found substantially different patterns of CH4 uptake in alpine glacier foreland soils depending on the bedrock type (siliceous versus calcareous). In the
foreland of the receding Rotmoos glacier (Austria), CH4 oxidation activity was found to increase significantly with soil age,
but also distinctly increased in autumn at the end of the plant
growing period (Hofmann, Reitschuler and Illmer 2013). Other
studies have observed that both, the soil methane sink, as well
as the abundance of methanotrophic bacteria, increase with soil
age in the forelands of the Damma and the Griessfirn glaciers
(Chiri et al. 2015).
Methane production in soil is due to methanogenic archaea,
which were long assumed to be restricted to highly anoxic environments. This assumption was questioned when Peters and
Conrad (1995) observed that methane could be produced in aerated soils when incubated under anoxic conditions, and subsequent research demonstrated that some methanogenic strains
possess the genetic features to protect themselves against oxidative stress (Takao, Yasui and Oikawa 1991; Brioukhanov et
al. 2000; Shima et al. 2000). Since then, methanogens and
methanogenic activities have been found in other well-aerated
soils such as desert soils (Angel, Matthies and Conrad 2011;
Angel, Claus and Conrad 2012), pasture soil (Nicol, Glover and
Prosser 2003; Prem, Reitschuler and Illmer 2014) and subalpine
fallow soils (Praeg, Wagner and Illmer 2014), which further high-
lights their ability to tolerate oxygen. However, little research
on methanogens in high-alpine soils has been conducted and
hardly any information on their abundances, especially at the
order level, in these cold environments is available. In the soils
of an Alpine glacier foreland, methanogenic activities could already be detected in young, primary soils, but were higher in mature ones (Hofmann, Reitschuler and Illmer 2013). In Himalayan
cold deserts, gene abundance of mcrA encoding for the α-subunit
of the methanogenic methyl coenzyme M reductase was detected to range from 5 × 102 to 1.5 × 104 g−1 dry soil, which indicates cold tolerance of certain methanogens (Aschenbach et al.
2013).
The main objectives of this study were to (i) examine whether
and to which extent methanogenic guilds as well as methanotrophs are present in high-alpine soils, (ii) determine the distribution patterns of their abundances and the correspondent
potential activities engaged in methane cycling along the altitudinal gradient, (iii) assess the ratio between methanogens
and methanotrophs and (iv) relate the observed distributions of
methanogenic and methanotrophic abundances along the gradient to physicochemical soil properties.
MATERIALS AND METHODS
Study area and sampling
This study was conducted at Mount Schrankogel, Eastern Central Alps, Tyrol, Austria (11◦ 05’58”E, 47◦ 02’41”N; 3498 m) in August 2014. The northern and eastern sides of this mountain are
surrounded by receding glaciers and the respective forelands.
Mt Schrankogel is mainly comprised of siliceous bedrocks (Hammer 1929) and typical soil types include leptosols and cambisols.
The altitudinal gradient investigated was located at the southwest facing slope of the mountain and covered altitudes ranging from 2700 to ∼3500 m above sea level (a.s.l; Fig. S1, Supporting Information). Altitudes ranging from 2700 to 2900 m a.s.l are
alpine grasslands dominated by Carex curvula (Gottfried, Pauli
and Grabherr 1998), which is replaced by nival plant species such
as Androsace alpine, Poa laxa and Saxifraga bryoides at 3200 m a.s.l
(Gottfried et al. 1999; Pauli, Gottfried and Grabherr 1999). The
alpine-nival ecotone from 3000 to 3100 m a.s.l represents a transitional area in which alpine grassland and patchy and open nival vegetation cooccur (Gottfried et al. 1999).
In August 2014, nine sites were sampled along the southwestern slope from 2700 to 3500 m, at intervals of 100 m, representing the alpine (2700–2900 m), alpine-nival (3000–3100 m)
and nival belts (3200–3500 m). The slope of the sampling sites
was relatively uniform and ranged between 20◦ and 30◦ (Fig. S1,
Supporting Information). At each site, three replicate sampling
plots of 1 × 1 m were set up. Soil was collected from the first
5 cm below the vegetation cover at three randomly selected
spots per plot and was afterwards merged to a composite sample. Samples were immediately transported to the laboratory,
sieved at 2 mm and stored at 4◦ C for physicochemical analyses as well as determination of microbial activity and biomass.
For DNA extraction, soil samples were stored at −20◦ C. The
sampling plots were located near permanently installed GeoPrecision Mlog5W loggers (GeoPrecision, Germany) and Tinytag
loggers (Gemini Data Loggers, UK) which measured soil temperatures at depths of 10 cm below ground and 1–3 cm above
ground once per hour, respectively (Gottfried, Pauli and Grabherr 1998). On the basis of all data recorded from August 2013–
July 2014, mean annual temperatures (MAT) were calculated
(Table 1).
Hofmann et al.
3
Table 1. Physicochemical characteristics of the high-altitudinal soils sampled along the studied transect on Mount Schrankogel. Data represent
means ± standard deviations (n = 3).
Altitude
(m a.s.l.)
Altitudinal
belt
2700
2800
2900
alpine
3000
3100
alpine/nival
3200
3300
3400
3500
nival
MATa
(◦ C)
NH4 + -N
(μg g−1 dry soil)
NO3 − -N
(μg g−1 dry soil)
12.8 (0.42)
13.8 (1.29)
10.8 (1.09)
3.23 (0.167)
5.47 (0.727)
3.50 (1.487)
0.59 (0.046)
1.95 (1.009)
1.46 (0.716)
22.2 (5.50)
24.4 (1.75)
12.7 (1.37)
11.8 (0.85)
4.10 (2.113)
2.69 (0.361)
1.20 (0.556)
0.74 (0.246)
14.3 (0.41)
20.7 (8.87)
27.2 (20.13)
23.5 (3.27)
11.7 (2.42)
10.4 (1.55)
12.5 (2.51)
6.2 (0.69)
2.61 (0.501)
3.25 (0.314)
3.02 (0.717)
3.91 (0.230)
1.60 (1.961)
0.64 (0.197)
0.43 (0.104)
0.73 (0.033)
pH
WC
(g g−1 )
MWHC
(g g−1 )
OM
(mg g−1 )
DOC
(mg g−1 )
4.2 (0.07)
4.4 (0.06)
4.6 (0.13)
0.24 (0.045)
0.27 (0.018)
0.16 (0.094)
0.73 (0.134)
1.02 (0.144)
0.57 (0.219)
52.2 (7.73)
121.0 (23.56)
48.1 (15.66)
0.9
−0.1
5.0 (0.07)
4.6 (0.19)
0.10 (0.037)
0.13 (0.011)
0.36 (0.085)
0.39 (0.066)
−2.0
−4.6
−3.1
−4.0
4.2 (0.11)
4.5 (0.00)
4.6 (0.56)
5.0 (0.19)
0.06 (0.022)
0.09 (0.011)
0.10 (0.045)
0.09 (0.034)
0.29 (0.006)
0.30 (0.048)
0.30 (0.046)
0.32 (0.009)
4.4b
3.3b
2.1
a
WC, water content; MWHC, maximum water holding capacity; OM, organic matter; DOC, dissolved organic carbon; MAT, mean annual soil temperature (10 cm below
ground).
b
Due to a lack of data loggers at 2700 and 2800 m, the MAT was calculated on the basis of a linear regression model using the data of loggers located from 2900 m to
the summit. This calculation should be valid because of the relatively uniform aspect and slope across the studied gradient.
Soil characteristics
Soil water content (WC) was determined gravimetrically by drying 5 g of sieved soil at 105◦ C overnight. pH was measured in a
1:2.5 (w/v) soil to CaCl2 (0.01 M) mixture. Maximum water holding capacity (MWHC) was determined by weighing 10 g of sieved
soil into glass cylinders with pores at one side. The cylinders
were placed in deionized water for 1 h. After water saturation,
the samples were placed on 10 cm quartz sand for 3 h. The wet
samples were weighed and dried for 2 days at 105◦ C. Subsequent
weighing allowed determination of MWHC. Organic matter (OM)
was measured using the loss on ignition method. Oven-dried
(105◦ C, overnight) soils were incinerated for 4 h at 430◦ C (Schinner et al. 1996). Dissolved organic carbon (DOC) was quantified
on a TOC-L analyser (Shimadzu Co, Japan) after extraction using
soil and distilled water at a mixing ratio of 1:5 (w/v). NH4 + -N and
NO3 − -N were extracted from fresh soil using 2 M KCl and determined by photometry at 660 and 210 nm, respectively (Schinner
et al. 1996).
Methanogenic and methanotrophic activities
To assess potential methane production and oxidation, 5 g of
soil sample (fresh weight) were filled into sterile serum flasks.
Anoxic conditions for the assessment of methanogenic activity were established by flushing the sample with sterile N2 several times. After the last flushing step, the flasks were sealed
with butyl rubber stoppers. During an incubation period of seven
weeks at 25◦ C, CH4 concentrations in the flask’s headspaces
were measured via gas chromatography at regular time intervals
(0, 7, 14, 21, 28, 49 days).
In order to determine the potential activity of methanotrophs, the serum flasks were sealed under oxic conditions with atmospheric CH4 concentrations (∼1.8 ppm) in the
headspace. Incubation time was up to 8 days at 25◦ C. CH4 was
quantified using gas samples which were removed from the
headspace at 0, 2, 4, 24, 28, 48, 72 and 171 h of incubation.
We chose 25◦ C as incubation temperature, because most of
the known methanogens and methanotrophs are mesophilic
(Nazaries et al. 2013). However, this temperature is only seldom found in the investigated soils. Hence, the measured CH4
production and oxidation rates represent potential (not actual)
activities measured under optimal conditions. These measurements are comparable to standard soil microbial activity assays
(e.g. denitrification; see Schinner et al. 1996) and are useful to
compare different soil sites, although the measured rates do not
necessarily display those occurring in situ.
Both potential methane production rates and potential
methane consumption rates were calculated from a linear regression of the measured CH4 concentrations against time
points. The quality of the fitting was assessed on the basis
of the coefficient of determination R2 . CH4 was measured on
a GC-2010 Plus gas chromatograph (Shimadzu Co., Japan) that
was equipped with a flame ionization detector (FID) as well
as with a Shin Carbon TS 100/120 mesh (2 m × 1 mm) column (Restek, USA). The injector temperature was set to 160◦ C,
the column temperature to 140◦ C and the detector temperature to 180◦ C. N2 was used as the mobile phase at a flow rate
of 14.5 ml min−1 .
DNA extraction and quantitative PCR (Q-PCR)
Genomic DNA was extracted from 0.5 g of sieved soil using a
commercially available kit (NucleoSpin Soil, Macherey-Nagel,
Germany). Quality and quantity of the DNA was checked by
UV/VIS spectroscopy using a Nanodrop 2000c (PEQLAB, Germany). Q-PCR was conducted using the SensiMix SYBR no-ROX
kit (Bioline, UK) on a Corbett Life Science (Qiagen, the Netherlands) Rotor-Gene Q system. Determination of methanogenic
16S rRNA gene copy numbers was performed with primers
targeting the following methanogenic guilds: Methanosarcinales
(MSL), Methanococcales (MCC), Methanobacteriales (MBT) (Yu, Lee
and Hwang 2005), Methanomicrobiales (MMB) (Vigneron et al. 2013)
and Methanocella spp. (Angel, Claus and Conrad 2012). Methanotrophic bacteria were quantified using the primer pair 189 F
and mb661 R (Kolb et al. 2003). The reactions (20 μl) contained
10 μl SensiMix SYBR no-ROX kit (Bioline, UK), 0.2 μM (MSL and
MMB), 0.25 μM (MBT and MCC) or 0.15 μM (Methanocella spp.,
MOB) of each primer, 5 mM MgCl2 , 0.04% (v/v) bovine serum albumin and 2–10 ng of DNA template. Q-PCR was preceded by
an initial denaturation step of 10 min at 95◦ C (Table S1). In each
run, we included non-template DNA and non-template controls
(UltraPure DNase/RNase-Free Distilled Water, Invitrogen, USA).
Pure culture DNA for preparation of genomic DNA standards
and construction of the calibration curves were extracted from
Methanosarcina acetivorans (DSM2834) (MSL), Methanothermobacter
wolfei (DSM2970) (MBT), Methanococcus voltae (DSM4254) (MCC),
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FEMS Microbiology Ecology, 2016, Vol. 92, No. 3
Methanoculleus bourgensis (DSM3045) (MMB), Methanocella conradii
(DSM24694) and Methylosinus sporium (DSM17706) (MOB).
Along the altitudinal gradient at Mt Schrankogel, soil WC ( r =
−0.71; P < 0.001), maximum water holding capacity (r = −0.75;
P < 0.001), organic matter content (r = −0.60; P < 0.001) and dissolved organic carbon (r = −0.57; P < 0.01) declined with increasing altitude. Soil pH ranged from 4.1 to 5.2 (Table 1) and exhibited
a slightly positive relationship (r = 0.39; P < 0.05) with altitude.
The pools of NH4 + -N and NO3 − -N did not follow any consistent
trend and remained relatively uniform with values ranging from
0.6 ± 0.05 to 0.7 ± 0.03 μg NH4 + -N g−1 dry soil and from 3.2 ±
0.17 to 3.9 ± 0.23 μg NO3 − -N g−1 dry soil, respectively (Table 1).
Soil temperature data indicated that the altitudinal gradient is
linked (r = −0.97; P < 0.001) to a temperature gradient with mean
annual soil temperatures ranging between 4.4◦ C at 2700 m and
−4.0◦ C at 3500 m (Table 1). Mean annual soil temperature decreased by 1.2◦ C per 100 m of altitudinal increase between 2900
and 3500 m.
Abundance of Methanococcales, Methanobacteriales and methanotrophs was significantly higher in soils sampled at the alpine
belt (2700–2900 m; P < 0.001) and in those sampled at the alpinenival belt (3000–3100 m; P < 0.05) compared to the values measured in soils of the nival altitudinal belt (3200–3500 m)(Figs 1a,
c and e). The abundances of Methanocella spp. were significantly
lower (P < 0.001) in soils of the alpine-nival ecotone compared to
those derived from the alpine belt, but significantly higher (P <
0.001) compared to those derived from the nival belt (Fig. 1b). On
the contrary, we observed no significant difference of the abundance of Methanomicrobiales in soils of the alpine-nival ecotone
compared to those of the nival belt (Fig. 1d).
Methanococcales and Methanocella spp. were the most abundant methanogenic guilds with Log10 abundances ranging from
6.3 ± 0.4 at 2700 m a.s.l to 4.7 ± 0.4 g−1 dry soil at 3500 m a.s.l. and
6.4 ± 0.3 at 2700 m a.s.l. to 4.2 ± 0.4 g−1 dry soil at 3500 m a.s.l.
Log10 abundance of Methanobacteriales ranged from 4.2 ± 0.6 to
4.4 ± 0.8 g−1 dry soil at altitudes ranging from 2700 to 3100 m a.s.l
(corresponding to the alpine altitudinal belt and the alpine-nival
transitional area). At higher locations, Methanobacteriales could
not be detected except for two samples derived from 3400 and
3500 m a.s.l. The abundance of Methanomicrobiales followed similar patterns compared to those of the Methanobacteriales. Log10
abundances of Methanococcales (r = −0.70; P < 0.001), Methanocella
spp. (r = −0.85; P < 0.001), Methanobacteriales (r = −0.67; P <
0.001) and Methanomicrobiales (r = −0.62; P < 0.001) were significantly negatively correlated to altitude, suggesting a pattern of
linear decrease of methanogens along this altitudinal gradient,
which was most pronounced for the abundance of Methanobacteriales and Methanomicrobiales. Log10 pmoA gene abundance of
methanotrophic bacteria ranged from 5.3 ± 0.3 g−1 dry soil in
soils located at 2700 m a.s.l to 3.2 ± 0.7 g−1 dry soil in soils
located at 3500 m a.s.l., and moreover, significantly decreased
(r = −0.74; P < 0.001) with increasing altitude. The Log10 ratio of methanogenic archaea abundance (corresponding to the
sum of all quantified groups) and methanotrophic abundance
remained relatively constant irrespective of the altitude (Fig. 2b).
Simple linear regressions of the abundances in relation to altitude showed that Methanobacteriales (slope β = −5.8 × 10−3 ) and
Methanomicrobiales (slope β = −3.3 × 10−3 ) exhibited a stronger
decline compared with Methanococcales (slope β = −1.7 × 10−3 )
and Methanocella spp. (slope β = −3.0 × 10−3 ).
Multiple linear regressions indicated that mean annual soil
temperature increase led to higher abundances of Methanococcales, Methanocella spp. and Methanobacteriales. Additionally, both
abundance of Methanococcales and Methanocella spp. were positively linked to soil moisture (Table 2). By contrast, no relationship between the abundance of Methanomicrobiales and mean annual soil temperature could be observed. Abundance of Methanomicrobiales was, however, found to be positively linked to
organic matter and dissolved organic carbon contents of the
soils. Variance partitioning pointed to the fact that dissolved organic carbon had a stronger impact on methanotrophic pmoA
gene abundance compared with mean annual soil temperature
(Table 2).
Abundance of methanogens and methanotrophs in
relation to altitude and soil properties
Potential activities of atmospheric methane oxidizers
and methanogens
Although Q-PCR targeting Methanosarcinales was performed, this
methanogenic order could not be detected in any of the samples. Abundances of all quantified methanogenic groups and
methanotrophic bacteria were significantly (P < 0.05) influenced
by the altitudinal belt in which the soil was collected (Fig. 1).
Both potential activities of atmospheric CH4 oxidizers (r = −0.54;
P < 0.01) as well as methanogenic archaea (r = −0.64; P < 0.001)
linearly decreased with increasing altitude along the gradient
with rates ranging between 4.1 ± 1.42 at 2700 m a.s.l. and 0.1 ±
0.14 ng CH4 -C g−1 dry soil d−1 at 3500 m and between 2.8 ± 3.92
Statistical analyses
All statistical analyses were conducted using STATISTICA version 9 (StatSoft Inc., Tulsa, OK, USA). One-way analysis of variance was applied to test for significant impacts of the altitudinal belts (alpine, alpine-nival and nival) on the abundance of
methanogenic archaea and methanotrophic bacteria, but also
on the corresponding potential activities. Because of the unequal numbers of cells per altitudinal zone (alpine = 9; alpinenival = 6; nival = 12), we applied type III-ANOVA as suggested in
Quinn and Keough (2011). Evaluation of significant differences
between the groups was performed using ‘Tukey’s Honestly Significant Difference Test’ for post-hoc analysis. To gain an insight into the spatial distribution of methanogenic and methanotrophic abundance and activities along the altitudinal gradient,
we used correlation analysis based on Pearson’s correlation coefficients. When linearly decreasing patterns were found, we additionally applied regression analysis to estimate the magnitude of
the decrease (represented by the slope β). Multiple linear regression analysis was used to relate the abundances and activities to
possible environmental drivers (abiotic soil properties and mean
annual soil temperature) and to estimate their relative importance by comparing the standardized regression coefficients and
the decomposition of the variance. Abiotic predictor variables
which were strongly autocorrelated and therefore did not meet
the assumption of independence were removed prior to model
selection. Independent variables were fitted to the dependent
variables by using backward selection (Quinn and Keough 2011).
The differences between groups, the correlation coefficients and
the regression models were regarded as significant when P values were below 0.05.
RESULTS
Soil properties and soil temperature
Hofmann et al.
5
Figure 1. 16S rRNA gene abundance of the methanogenic guilds (a) Methanococcales (MCC), (b) Methanocella spp., (c) Methanobacteriales (MBT), (d) Methanomicrobiales
(MMB) and (e) pmoA gene abundance of methanotrophic bacteria in soils of the alpine belt (2700–2900 m; n = 9), the alpine-nival ecotone (3000–3100 m; n = 6) and the
nival altitudinal belt (3200–3500 m; n = 12) at Mount Schrankogel (Eastern Central Alps, Tyrol, Austria). The columns show means ± SE. Significant differences (P <
0.05) between groups are indicated by different letters.
at 2700 m and 0.3 ± 0.11 ng CH4 -C g−1 dry soil d−1 at 3500 m,
respectively.
Potential methane production rates were significantly higher
(P < 0.01) in soils of the alpine altitudinal belt (2700–2900 m) compared to the rates in soils of the nival altitudinal belt (3200–3500
m), whereas the production rates in alpine-nival soils were in-
termediate, and thus, represented a transitional stage (Fig. 3a).
Oxidation of CH4 at atmospheric concentrations by the soils
at Mt Schrankogel was significantly (P < 0.01) depending on
the altitudinal belt. Compared with potential CH4 oxidation
rates determined from alpine and alpine-nival soils, which were
not significantly different from each other, nival soils exhibited
6
FEMS Microbiology Ecology, 2016, Vol. 92, No. 3
Figure 2. Log10 16S rRNA gene abundances (a) and Log10 ratio between the abundance of total methanogenic archaea (sum of 16S rRNA gene copies of the quantified guilds) and the abundance of methanotrophic bacteria (b) in relation to
altitude at Mount Schrankogel (Eastern Central Alps, Tyrol, Austria).
significantly (P < 0.01) reduced oxidation rates (Fig. 3b). Backward model selection led to linear regression models that included mean annual soil temperature as predictor variable for
both potential methane production and potential oxidation of
atmospheric CH4 (Table 3).
DISCUSSION
In the present study, the abundances and potential activities of
methanotrophic bacteria as well as methanogenic archaea were
investigated along an altitudinal gradient which is located on Mt
Schrankogel in the Eastern Central European Alps and is among
the highest peaks in Austria. This gradient includes three vertical altitudinal belts each dominated by a unique community of
plant species i.e. the alpine altitudinal belt (2700–2900 m), the
alpine-nival ecotone (3000–3100 m) and the nival altitudinal belt
(3200–3500 m).
Studying altitudinal gradients provides insights into the distribution of organisms relative to changing environmental conditions occurring over short geographical distances (Körner
2007). Moreover, it also allows estimation of the effects of future
global climatic changes (e.g. temperature increase) on mountain ecosystems, which are expected to react most sensitively
(Diaz, Grosjean and Graumlich 2003). Both Log10 pmoA gene copy
numbers of methanotrophs and 16S rRNA gene copies of all
measured methanogenic clades showed linearly declining patterns along the altitudinal gradient at Mt Schrankogel. Comparison of our finding with other studies is difficult for two reasons. First, studies on microbial abundances along altitudinal
gradients are rare, compared to those targeting plants and animals and led to contradictory results. Second, to our knowledge methanogens and methanotrophs have so far not been investigated along such gradients. For instance, our results were
aligned with archaeal and bacterial abundances, which linearly
decreased along the same gradient (KH, unpublished data), but
contradictory to archaeal and bacterial abundances measured
across Mt Shegyla, which did not follow any consistent pattern
(Wang et al. 2015).
Determination of methanotrophic abundances in highaltitudinal soils has been neglected in past studies. Methanotrophic pmoA gene copy numbers ranged between 3.2 × 103
g−1 dry soil at the summit at 3500 m a.s.l and 2.3 × 105 g−1
dry soil in soils located at 2700 m a.s.l. Apart from the data of
Chiri et al. (2015), who reported similar pmoA gene copy numbers ranging between 2.4 × 103 and 5.5 × 105 g−1 dry soil for
two Swiss glacier forelands located below 2500 m a.s.l., no abundance data of high-alpine non-wetlands are available. Moreover, the values we measured across Mt Schrankogel were at
the lower edge of methanotrophic abundance determined at
low-altitudinal grassland sites (3.8 × 105 −1.9 × 106 g−1 dry soil)
(Shrestha et al. 2012) and lower compared to the abundances determined at beech forest sites (∼106 g−1 dry soil) (Kolb et al. 2005).
Regression models pointed to the fact that mean annual soil
temperatures contributed to the observed decreasing trends of
methanotrophic activity and abundance along the gradient on
Mt Schrankogel, and thus, were partly in agreement with the
observations of Shrestha et al. (2012), who showed that methanotrophic activities in a low-altitudinal meadow increased with
temperature but declined with increasing soil moisture. Although soil moisture was regarded as crucial factor regulating
methane uptake (Czepiel, Crill and Harriss 1995; Schnell and
King 1996; Le Mer and Roger 2001; Shrestha et al. 2012), we could
not detect any significant effect of this parameter on the abundance and activity of methanotrophic bacteria. Still, relatively
high (∼24%) and low (∼9%) moisture contents in soils located
at 2700 and 3500 m a.s.l, respectively, coincided with high or
low abundance and activity. Czepiel, Crill and Harriss (1995)
found that methane uptake increases to a value of soil moisture close to field capacity, and afterward decreases, and found
optimal moisture contents to range between 18% and 33%. It has
been suggested that below the optimal range, methane uptake
is inhibited due to desiccation stress, whereas above this range
substrate supply could be reduced as a consequence of limited
diffusivity.
For long it was not resolved whether methanotrophs involved in atmospheric CH4 uptake (≤1.8 ppm) in uplands are able
to maintain growth by using CH4 alone. West and Schmidt (1998)
discovered higher CH4 consumption rates after application of
acetate to an alpine tundra soil, either pointing to direct stimulation of MOB or to an indirect increase because of higher CH4
production. Recently, it was demonstrated that USCα methanotrophs that were assumed to be adapted to atmospheric CH4
concentrations are able to assimilate acetate and thus can be
seen as facultative methanotrophs (Pratscher, Dumont and Conrad 2011). Partial correlations indicated that dissolved organic
carbon (partial r = 0.57) might play a role for the distribution
of functional pmoA gene abundance along the gradient on Mt
Schrankogel, which is in agreement with recent reports from
Hofmann et al.
7
Table 2. Results of backward selection of multiple linear regression models using methanogenic and methanotrophic gene abundance as
dependent variables and mean annual soil temperature (MAT) as well as physicochemical soil properties as predictor variables. DOC, dissolved
organic carbon; OM, organic matter; WC, soil water content; MWHC, maximum water holding capacity.
Dependent
variable
Methanococcales, Log10 16S rRNA gene abundance
Methanocella spp., Log10 16S rRNA gene abundance
Methanobacteriales, Log10 16S rRNA gene abundance
Methanomicrobiales, Log10 16S rRNA gene abundance
Methanotrophs, Log10 pmoA gene abundance
Predictors
Regression
coefficient ß
Intercept
MAT
WC
MWHC
Intercept
MAT
WC
Intercept
5.7 (0.28)
0.1 (0.04)
6.9 (2.89)
−2.0 (0.91)
4.7 (0.39)
0.2 (0.04)
4.7 (1.49)
2.9 (0.31)
MAT
Intercept
OM
DOC
Intercept
MAT
DOC
0.5 (0.10)
−1.713 (0.93)
18.7 (6.37)
0.3 (0.09)
−18.5 (6.56)
3.8 (1.44)
1518.4 (133.07)
arid environments (Sullivan, Selmants and Hart 2013) and points
to facultative methanotrophy.
Methanogenesis could be activated in each soil sample we
collected along the studied altitudinal gradient. The potential
of well-aerated soils to produce CH4 under favorable conditions was first demonstrated by Peters and Conrad (1995), and
further, research has revealed that even hot as well as cold
desert environments possess this potential (Angel, Matthies and
Conrad 2011; Angel, Claus and Conrad 2012; Aschenbach et al.
2013). Considering that the methane production rates along
Mt Schrankogel were generated using field-moist samples, direct comparisons with these rates, which were obtained from
slurry incubations, may not be justified. Moreover, the release of
CH4 from high-alpine, field moist soil samples without addition
of any external substrate contradicts the findings of West and
Schmidt (2002), who could only induce CH4 formation when they
supplied alpine grasslands with H2 as a precursor, which points
to substrate limitation. Contrarily, no such limitation seems to
occur in the soil samples of Mt Schrankogel. Methane was produced at rates declining from 2.8 ng CH4 -C to 0.3 ng CH4 -C g−1
dry soil d−1 at altitudes between 2700 and 3500 m a.s.l. These
rates were well in line with the production rates of a mature
glacier foreland soil (0.6 ng CH4 -C g−1 dry soil d−1 ) located at 2280
m, but lower compared with the productions rates of a subalpine
fallow soil (74 ng CH4 -C g−1 dry soil d−1 ) located at 1970 m determined under mesophilic incubation conditions (Hofmann, Reitschuler and Illmer 2013; Praeg, Wagner and Illmer 2014). Wellaerated grassland soils located at lower altitudes (500–2000 m
a.s.l.) exhibited higher methanogenic activities with production
rates ranging from 8.7 ng CH4 -C to 27 705 ng CH4 -C g−1 dry soil
d−1 (Hofmann et al. 2015), thus, pointing to temperature limitation of potential CH4 production along the altitudinal gradients.
The occurrence and activity of methanogenic archaea has
already been proved in cold deserts of the Western Himalayas
that experience only 100 mm of annual precipitation (Aschenbach et al. 2013). However, we assumed that the high-altitudinal
soils at Mt Schrankogel may harbor more methanogens due
to higher annual precipitation (1100–1300 mm y−1 ). Indeed, we
found that total methanogenic abundance (as calculated from
the 16S rRNA gene abundances of each quantified clade), which
Regression
coefficient ß (corr.)
0.7 (0.22)
0.9 (0.36)
−0.8 (0.38)
0.6 (0.12)
0.4 (0.12)
0.7 (0.14)
0.4 (0.15)
0.5 (0.15)
0.2 (0.07)
0.8 (0.07)
Sign.
level
P < 0.001
P < 0.01
P < 0.05
P < 0.05
P < 0.001
P < 0.001
P < 0.01
P < 0.001
P < 0.001
P > 0.05
P < 0.01
P < 0.01
P < 0.01
P < 0.05
P < 0.001
Tolerance
0.45
0.16
0.15
0.46
0.46
1.00
0.81
0.81
0.62
0.62
Model
statistics
R2 = 0.55
R2 adj . = 0.50
P < 0.001
R2 = 0.83
R2 adj . = 0.82
P < 0.001
R2 = 0.53
R2 adj . = 0.51
P < 0.001
R2 = 0.58
R2 adj . = 0.55
P < 0.001
R2 = 0.92
R2 adj . = 0.92
P < 0.001
ranged between 2.5 × 106 g−1 dry soil in soils sampled at 2700
m a.s.l. and 4.6 × 104 g−1 dry soil in soils sampled at 3500 m
a.s.l., was higher compared to the values measured at the Himalayan sites (5 × 102 –1.5 × 104 g−1 dry soil) (Aschenbach et al.
2013). Even in subglacial sediment samples methanogenic coenzyme M was detected at concentrations corresponding to ∼3 ×
103 methanogens g−1 sediment (Boyd et al. 2010).
The declining spatial pattern of both potential CH4 production and the abundances of Methanocella spp., Methanococcales
and Methanobacteriales could be, at least partly, explained by
mean annual soil temperature, because the altitudinal gradient
corresponded to a temperature gradient (4.4 to −4.0◦ C from 2700
to 3500 m a.s.l.). Similarly, laboratory incubations of Arctic peat
soil revealed that increasing temperature boosted the CH4 production rates and the relative abundance of methanogens (Hoj,
Olsen and Torsvik 2008) and glacier foreland soils of the Austrian
Central Alps also emitted most CH4 as incubation temperatures
increased (Hofmann, Reitschuler and Illmer 2013). Hence, our
result adds further evidence for temperature limitation of both
potential methane production as well as methanogenic abundance. Subsequently, a temperature increase as predicted for the
Alps might result in an increase of methanogenic abundance
and activity. Additionally, soil moisture seemed to structure
the observed linear decrease of Methanococcales and Methanocella
spp. abundances along the altitudinal gradient on Mt Schrankogel. Relatively high moisture contents (∼24%) of soils located
at 2700 m provided more suitable conditions for the growth of
methanogens compared with the soils located at 3500 m (WC
∼9%), possibly due to the higher number of oxygen-free microniches within the soils at 2700 m (Zausig, Stepniewski and Horn
1991; Peters and Conrad 1995). Hence, CH4 might be produced
in situ along the studied gradient, at least temporarily when the
environmental conditions become favorable, which was previously observed in Canadian grasslands acting as CH4 sources
shortly after submersion (Wang and Bettany 1995) and biological
soil crusts incubated under wet conditions that contained more
methanogenic mcrA transcripts than dry soils (Angel, Matthies
and Conrad 2011).
Despite the fact that the studied high-alpine soils were well
aerated, methanogenic archaea that were long believed to be
8
FEMS Microbiology Ecology, 2016, Vol. 92, No. 3
and Conrad 2012). However, we could not detect Methanosarcinales in the soils sampled along the gradient (2700–3500 m)
on Mt Schrankogel. Soils sampled from 2700–3000 m were instead dominated by Methanocella spp. as well as by the order
Methanococcales. At higher altitudes (3100–3500 m), 16S rRNA
gene abundance of Methanococcales was clearly higher compared
with those of Methanocella spp. Together with the comparably
stronger decline of Methanobacteriales and Methanomicrobiales (as
indicated by a more negative β) this might, on the one hand,
suggest a better adaptability of Methanococcales and Methanocella
spp. to cold climatic conditions and, on the other hand, point to
a clear altitudinal structuring of methanogenic guilds in the European Alps. Additionally, the Log10 ratio of total methanogens
(sum of 16S rRNA gene copies) and methanotrophic bacteria did
not vary with increasing altitude, which indicates a strong association between both functional groups and points to a similar sensitivity toward low temperatures. However, this assumption needs to be verified either by physiological experiments
on methanogenic isolates from these soils, or by monitoring
changes of the entire methanogenic community structure and
diversity relative to different temperatures. Additionally, we observed that potential methane production was positively correlated with both dominant methanogenic groups, Methanocella
spp. (r = 0.53, P < 0.01) and Methanococcales (r = 0.40, P < 0.05),
indicating that these methanogens were activated in our soil incubations and pointing to the suitability of the method and the
fact that methanogenic activities may also play a role under in
situ conditions given that they are facing favorable conditions
(e.g. oxygen-free micro-niches).
CONCLUSIONS
Figure 3. Potential methanogenic (a) and methanotrophic activities (b) in soils of
the alpine altitudinal belt (2700–2900 m; n = 9), the alpine-nival ecotone (3000–
3100 m; n = 6) and the nival altitudinal belt (3200–3500 m; n = 12) at Mount
Schrankogel (Eastern Central Alps, Tyrol, Austria). The columns show means ±
SE. Significant differences (P < 0.05) between groups are indicated by different
letters.
restricted to highly anoxic habitats were present. Their ability to withstand periods of low water availability and aeration
could be due to the detoxification of reactive oxygen species
(ROS) by catalase genes, similar to the process observed in biological soil crusts from arid regions (Angel, Matthies and Conrad 2011). In the European Alps, Methanosarcinales were present
in most of the investigated montane and subalpine grasslands
(Hofmann et al. 2015), which confirms the previous suggestion that these methanogens were autochthonous members of
the methanogenic communities in upland soils (Angel, Claus
According to our knowledge, this is the first study investigating both methanogenic archaea and methanotrophic bacteria
concurrently across an altitudinal gradient in the Alps. Apart
from the frequently detected methanogenic genus Methanocella
spp., our results indicated that high-alpine soils also provide
niches for Methanococcales, and, at least to a limited extent, for
Methanobacteriales and Methanomicrobiales. Thus, methanogens
seem to be also present in high-altitudinal cold soils, in spite of
the prevailing cold and highly oxic conditions within these soils,
which are usually not thicker than 5–10 cm. Moreover, the abundance of methanogens followed a linearly declining trend along
the altitudinal gradient, which seemed to be primarily driven
by soil temperature and water content. Increased air temperatures, due to climate warming, might therefore increase the
methanogenic community and boost their activity, but methanotrophic bacteria should be stimulated too, as the ratio between
these two groups remained quite constant along the gradient
and was not influenced by altitude.
Table 3. Results of backward selection of multiple linear regression models using potential methane production and oxidation as dependent
variables and mean annual soil temperature (MAT) and physicochemical soil properties as predictor variables.
Dependent
variable
Potential methane production
Potential oxidation of atmospheric CH4
Predictors
Regression
coefficient ß
Regression
coefficient ß (corr.)
Sign.
level
Tolerance
Intercept
MAT
1.5 (0.33)
0.3 (0.11)
0.5 (0.17)
P < 0.001
P < 0.01
1.00
Intercept
MAT
2.5 (0.45)
0.4 (0.15)
0.5 (0.17)
P < 0.001
P < 0.01
1.00
Model
statistics
R2 = 0.29
R2 adj . = 0.26
P < 0.01
R2 = 0.25
R2 adj . = 0.22
P < 0.01
Hofmann et al.
SUPPLEMENTARY DATA
Supplementary data are available at FEMSEC online.
ACKNOWLEDGEMENTS
KH thanks Sieglinde Farbmacher (University of Innsbruck) for
laboratory assistance and M. Huber and P. Wischounig for helpful discussions about statistics.
FUNDING
This study was supported by the Austrian Climate Research Program (Project GZ B368633).
Conflict of interest. None declared.
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