Introduction
N2O emissions from soil contribute to climate warming as
N2O is a potent greenhouse gas (IPCC, 2015); it is mainly produced in soils through microbial
nitrification and denitrification (Zumft, 1997). Clarifying nitrification and
denitrification processes and their controlling factors will be beneficial
for understanding the N cycle in terrestrial ecosystems. Previous studies are
mainly focused on bacterial nitrification and denitrification (Hayatsu et
al., 2008; Klotz and Stein, 2008) because the conventional N cycle is thought
to be controlled primarily by bacteria. However, recent studies using novel
molecular techniques have shown that soil fungi are important players in
terrestrial N cycling, including N2O production and
nitrification–denitrification in drylands or soils with high organic carbon
(C) and N (Chen et al., 2015; Huang et al., 2017; Laughlin and Stevens, 2002;
Marusenko et al., 2013; Zhong et al., 2018).
The Tibetan grasslands occupy approximately 40 % of the Tibetan Plateau,
which represents 0.7–1.0 % of total global N storage (Tian et al., 2006)
and is required for sufficient forage production (Zheng et al., 2000). These
grasslands represent one of the most vulnerable regions in the world to
climate change and anthropogenic perturbation (Thompson et al., 1993;
Thompson, 2000; Wang and French, 1994). A much greater than average increase
in the surface temperature has been predicted to occur in this region in the
future (Giorgi et al., 2001) and have profound impacts on soil N cycling in
alpine grasslands. Additionally, the grasslands of the Tibetan Plateau are
generally divided into two grazing seasons, i.e., summer grazing from June to
September and winter grazing from October to May (Cui et al.,
2014), which host about
13.3 million domestic yaks and 50 million sheep, with dramatically increasing
numbers in the future (Yao et al., 2006). Grazing strongly affects soil N
cycling, as well as plant and microbial diversity (Hillebrand, 2008) and the
stability of ecosystems (Klein et al., 2004). Previous studies have
demonstrated losses of N caused by warming (Klein et al., 2004, 2007) and
that overgrazing (Zhou et al., 2005) leads to degradation in alpine
grasslands. The effects of climate warming and grazing on the aboveground
vegetation, soil physicochemical properties, litter mass loss, bacterial
communities and N2O fluxes of Tibetan alpine grasslands have been
extensively investigated (Hu et al., 2010; Li et al., 2016; Luo et al., 2010;
Rui et al., 2012; Wang et al., 2012; Zhu et al., 2015); however, most of
these studies were focused on the effect of summer grazing; little is shown
on the effect of winter grazing on them (Zhu et al., 2015; Che et al., 2018).
On the other hand, many studies of Tibetan alpine grasslands are mainly
focused on bacterial nitrifiers and denitrifiers or their activities, taking
these to be the key factors in N2O emission in alpine grasslands.
However, while many studies have explored N mineralization, nitrification and
even denitrification as well as bacterial nitrifiers and denitrifiers for
better understanding of N2O emission and ecosystem functioning
(Yang et al., 2013; Yue et al., 2015), few studies have been conducted to
distinguish whether bacteria or fungi dominate in N2O emission and
N cycling (Kato et al., 2013), especially under warming and grazing
conditions.
Since optimum environments for fungi and bacteria are different, they may
respond differently to environmental changes. Fungi prefer a lower
temperature (Pietikäinen et al., 2005), higher organic C / N (Chen et al.,
2015) and a more arid soil environment (Marusenko et al., 2013) compared to
bacteria. Climate warming and grazing can change vegetation cover, soil
water and energy balance, alter the quantity and quality of soil organic
matter and mineral N content (Saggar et al., 2004), and thus affect N2O
production (Shi et al., 2017). However, it remains unknown how bacteria and
fungi respond to concurrent warming and grazing and contribute to N2O
production in alpine grasslands.
To clarify whether fungi played the main role in the N2O production
process and its response to warming and winter grazing in alpine grasslands,
we used a warming and grazing experiment over 10 years in an alpine meadow on
the Tibetan Plateau. We measured the gene abundance of soil bacterial and
fungal communities using quantitative PCR, and the potential of N2O
emission from bacterial and fungal nitrification and denitrification through
an incubation experiment to assess the contribution of N2O
production potential from bacteria and fungi. We aimed to test the following
hypotheses: (1) soil fungi were the main contributors to N2O
production because of the low soil temperature and high organic C and N in
the alpine grasslands, and (2) although N2O emission was not
affected by warming and winter grazing at our site (Zhu et al., 2015), the
biotic pathways responsible for N2O would be changed due to the
distinctly preferred soil environments of bacterial and fungal communities.
Materials and methods
Site and sampling
Details of the experimental site and design of the warming and grazing were
described by Wang et al. (2012). The experiment was conducted in an alpine
grassland (37∘37′ N, 101∘12′ E; 3250 m elevation) at
the Haibei Alpine Meadow Ecosystem Research Station of the Chinese Academy of
Sciences. Over the past 25 years, the mean annual temperature was
-2 ∘C, and the mean annual precipitation was 500 mm. In the soil
sampling year and month of August 2015,
mean temperature was 0 and 9.7 ∘C, respectively; total rainfall was
327.2 and 46.6 mm, respectively. Over 80 % of total rainfall falls
during the summer monsoon season (Luo et al., 2010; Zhao and Zhou, 1999). The
soil was classified as Gelic Cambisols (WRB, 1998). The plant community at
the experimental site is dominated by Kobresia humilis,
Festuca ovina, Elymus nutans, Poa pratensis,
Carex scabrirostris, Gentiana straminea, Gentiana farreri, Blysmus sinocompressus, Potentilla nivea and
Dasiphora fruticosa (Luo et al., 2010).
A two-way factorial design (warming and grazing) was used with four
replicates of each of four treatments (Wang et al., 2012), beginning in May
2006, namely no warming with no grazing (C), no warming with winter grazing
(G), warming with no winter grazing (W) and warming with winter grazing
(WG). In total, 16 plots of 3 m diameter were fully randomized throughout
the study site.
For warming treatments, the design of the controlled warming (i.e., a
free-air temperature enhancement (FATE) system with infrared heaters) with a
grazing experiment was described previously by Kimball et al. (2008) and Wang
et al. (2012). Free-air temperature enhancement using infrared heating was
set up to create a warming treatment since May 2006 (Luo et al., 2010). The
differences in canopy temperature at set points between heated plots and the
corresponding reference plots were 1.2 ∘C during the daytime and
1.7 ∘C at night in summer. During winter, from October to April, the
power output of the heaters was manually set at 1500 W per plot to make sure
the increased soil temperature was the same as in summer, as some infrared
thermometers were not working.
For grazing treatments, summer grazing treatments were used to explore the
effects of warming and grazing on ecosystem during the growing season from
2006 to 2010 (Luo et al., 2010; Hu et al., 2010; Wang et al., 2012).
Considering strong disturbance, grazing was stopped during 2011–2015; summer
grazing was replaced by cutting and removing about 50 % of the litter
biomass in October and the following March each year to simulate winter
grazing. Given the importance of winter grazing, winter grazing during the
non-growing seasons was further investigated (Zhu et al., 2015; Che et al.,
2018). Alpine meadows in the region can be divided into two grazing seasons
(i.e., warm-season grazing from June to September and cold-season grazing
from October to May) (Cui et al., 2015). Before the experiment was conducted,
we had examined how clipping simulated the effects of actual grazing before
we established four replicated “actual grazing treatments” compared with
the “simulated grazing treatments”. The soils and plants all showed no
difference between simulated grazing and actual grazing treatments (Klein et
al., 2004, 2007), because the soil is frozen in winter, meaning that the
effect of selective feeding and trampling by sheep would be limited, so the
effect of cutting in winter was similar to winter grazing (Zhu et al., 2015).
Soil sampling
Five soil cores (5 cm in diameter) were randomly collected within each plot
on 15 August 2015 at a depth of 0–20 cm (including the organic layer) and
then mixed to form a composite sample. All soil samples were transported to
the laboratory and sieved through a 2 mm mesh before being stored at -20
or 4 ∘C for further molecular analyses.
Soil properties and gene abundance of bacteria and fungi analysis
Soil moisture content was measured by drying at 105 ∘C for 24 h.
For soil mineral N (NH4+–N and NO3-–N) analyses,
10 g of soil (field-moist) were shaken for 1 h with 50 mL of 1 M KCl and
filtered through filter paper, and determined the NH4+–N and
NO3-–N concentrations by a Skalar flow analyzer (Skalar
Analytical, Breda, the Netherlands). Total C and N contents were measured by
using combustion elemental analyzers (PerkinElmer, EA2400, USA).
Soil DNA was extracted from 0.5 g of frozen soil using a
FastDNA™ Kit for Soil (QBIOgene) based on the instructions and
stored at -20 ∘C. Total bacteria and fungi copies were quantified
by real-time PCR using an iCycler thermal cycler equipped with an optical
module (Bio-Rad, USA)
The real-time PCR mixture contained 5 ng of soil DNA, 2 pmol of primers and
a 10× iQ SYBR Green super mix (Bio-Rad) in a 20 µL reaction
volume. The primers for bacteria were 341F 5′-CCTACGGGAGGCAGCAG-3′ and
534R5′-ATTACCGCGGCTGCTGGCA-3′ (Muyzer et al., 1993). The thermal cycle
conditions were 10 min at 95 ∘C; 35 cycles of PCR were then
performed in the iCycler iQ Real-Time PCR Detection System (BIORAD) as
follows: 20 s at 95 ∘C, 15 s at 55 ∘C and 30 s at
72 ∘C. A final 5 min extension step completed the protocol. The
primers for fungi were FU18S1 5′-GGAAACTCACCAGGTCCAGA-3′ derived from
Nu-SSU-1196 and Nu-SSU-1536 5′-ATTGCAATGCYCTATCCCCA-3′ (Borneman and
Hartin, 2000), and the thermal cycle conditions were one step of 10 min at
95 ∘C. Then 40 cycles of PCR were performed as follows: 20 s at
95 ∘C, 30 s at 62 ∘C and 30 s at 72 ∘C. A final
5 min extension step completed the protocol.
Results (F-value and P-value) from two-way ANOVA for the effects of
warming (W), winter grazing (G) and their interactions (WG) on soil and
microbial characteristics.
W
G
WG
F value
P value
F value
P value
F value
P value
Biomass
0.21
0.65
1.41
0.26
1.21
0.29
Temperature
61.16
< 0.01
4.64
0.05
25.54
< 0.01
Soil moisture
14.87
< 0.01
0.17
0.68
0.13
0.72
TC
2.69
0.12
2.7
0.13
3.95
0.07
TN
1.44
0.25
1.47
0.25
3.02
0.11
NH4+–N
4.57
0.05
1.6
0.23
0.02
0.89
NO3-–N
3.6
0.05
1.42
0.25
0.09
0.81
Bacteria
17.91
< 0.01
11.67
< 0.01
0.11
0.75
Fungi
1.72
0.21
0.70
0.42
2.89
0.12
BNEA
1.01
0.90
3.24
0.35
3.94
0.07
FNEA
4.58
0.05
1.15
0.34
0.37
0.51
TNEA
0.8
0.39
2.23
0.16
0
0.95
BDEA
5.16
0.04
2.45
0.14
4.04
0.07
FDEA
1.52
0.24
0.96
0.34
9.98
< 0.01
TDEA
0.98
0.34
2.33
0.15
0.15
0.70
Bold indicates significance at P < 0.05.
Total fungal and bacterial nitrification enzyme activity, and total
fungal and bacterial potential of <inline-formula><mml:math id="M83" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> production from denitrification
analysis
Fungal (FNEA), bacterial (BNEA) and total nitrification enzyme activity
(TNEA) was determined following the protocol described in Dassonville et
al. (2011). Briefly, moist field soil equivalent to 12 g of dry soil was
weighed into 240 mL specimen bottles (LabServ); 12 mL of NH4–N
solution (50 µg N–(NH4)2SO4 g-1
dry soil) and distilled water were added to achieve a 96 mL total liquid
volume, and the slurry was incubated at 28 ∘C for 10 h with
constant agitation (180 rpm) in an orbital shaker (Lab-Line 3527; Boston,
MA, USA) to mix slurry well and provide an aerobic environment. Three
treatments were imposed: (i) cycloheximide (C15H23NO4, a
fungicide) at 1.5 mg g-1 in solution was used to inhibit the
nitrification activity from soil fungi, (ii) streptomycin
sulfate (C42H84N14O36S3, a
bactericide) at 3.0 mg g-1 in solution was used to inhibit the
nitrification activity from soil bacteria (Castaldi and Smith, 1998; Laughlin
et al., 2009) and (III) a no-inhibitor control was used to show the total
nitrification activity. During incubation, 10 mL of the soil slurry was
sampled with a syringe at 2, 4, 6, 8 and 10 h, and then filtered through
Whatman No. 42 ashless filter paper. Filtered samples were stored at
-20 ∘C until analysis for NO2-+NO3-
concentration on a LACHAT Quickchem Automated Ion Analyzer (Foss 5027
Sampler, TECATOR, Hillerød, Denmark). Linear regression between the
NO2-+NO3- production rate and time was observed, and the
rates of nitrification enzyme activity were determined from the slope of this
linear regression. The nitrification enzyme activity of soil fungi was
estimated by the difference between rates of nitrification enzyme activity
under treatment (III) and treatment (I); the nitrification enzyme activity of
soil bacteria was estimated by the difference between rates of nitrification
enzyme activity under treatment (III) and treatment (II). The total
nitrification enzyme activity was from treatment (III).
Fungal (FDEA), bacterial (BDEA) and total potentials of N2O
production (TDEA) from denitrification were measured in fresh soil from each
plot following the protocol described in Patra et al. (2006) and Marusenko et
al. (2013). Three sub-samples (equivalent to 12 g dry soil) from each soil
sample were placed into 240 mL plasma flasks, and 7 mL of a solution
containing KNO3 (50 µg NO3-N g-1 dry
soil), glucose (0.5 mg C g-1 dry soil) and glutamic acid
(0.5 mg C g-1 dry soil) were added. Additional distilled water was
provided to achieve 100 % water-holding capacity and optimal conditions
for denitrification. Three treatments were imposed: (I) cycloheximide
(C15H23NO4; a fungicide) at 1.5 mg g-1 in solution was
used to inhibit the fungal potential of N2O production from
denitrification, (II) streptomycin sulfate
(C42H84N14O36S3; a bactericide) at 3.0 mg g-1 in
solution was used to inhibit the bacterial potential of N2O
production from denitrification (Castaldi and Smith, 1998; Laughlin and
Stevens, 2002), and (III) a no-inhibitor control was used to show the total
potential of N2O production from denitrification. The headspace air
of the specimen bottles was replaced with N2 to provide anaerobic
conditions. Specimen bottles were then sealed with a lid containing a rubber
septum for gas sample collection. Specimen bottles with the soil slurry were
then incubated at 28 ∘C for 48 h with constant agitation (180 rpm)
in an orbital shaker (Lab-Line 3527; Boston, MA, USA). During incubation,
12 mL gas samples were taken at 0, 24 and 48 h with syringes and injected
into pre-evacuated 6 mL glass vials. The N2O concentration of the
gas samples was analyzed via gas chromatography. The potential of
N2O production from denitrification was calculated from the slope
of the regression using values for 0, 24 and 48 h of incubation. The fungal
potential of N2O production from denitrification was estimated by
the difference between potential production under treatment (III) and
treatment (I). The bacterial potential of N2O production from
denitrification was estimated by the difference between rates of
denitrification enzyme activity under treatment (III) and treatment (II).
Total denitrification enzyme activity was from treatment
(III).
The contribution of bacteria and fungi to total nitrification enzyme activity
was calculated by the ratio of BNEA or FNEA to BNEA + FNEA; the
contribution of bacteria and fungi to the total potential of N2O
production from denitrification was calculated by the ratio of BDEA or FDEA
to BDEA + FDEA.
Statistical analysis
For the controlled experiment, the statistical
significance of the effects of warming, grazing and their interaction on
plant biomass, soil properties, microbial functional genes, and fungal and
bacterial nitrification enzyme activity and potential of N2O production
from denitrification were tested by two-way ANOVA in the PROC GLM procedure
of SAS (version 9, SAS Institute, Cary, NC, USA).
Results
Plant biomass and soil properties
The average plant standing biomass was 343, 345, 301 and 362 g dry matter m-2 in the control, G, W and WG treatments measured at the day of
soil sampling, respectively. Grazing and warming had no effect on plant
biomass (Fig. 1a, Table 1).
Soil temperature varied from 11.8 to 14.0 ∘C. Grazing (P= 0.05) and
warming (P < 0.01) increased soil temperature (Fig. 1b, Table 1). The
average soil moisture varied from 26 % to 34 % (w/w). Grazing had no
effect on soil moisture, which was lower in warming plots (P < 0.01)
(Fig. 1c, Table 1). There was an interactive effect between grazing and
warming on soil temperature (P < 0.01).
Soil total C (TC) was not affected by grazing (P= 0.13) or warming
(P= 0.12) alone, but there was a marginal interaction between grazing and
warming on TC (P= 0.07) (Fig. 2a, Table 1). Similar to TC, soil total N
(TN) also showed no response to grazing or warming (Fig. 2b, Table 1). Soil
NH4+–N content was lower in warming treatments than in
no-warming treatments (P= 0.05) (Fig. 2c, Table 1). Greater soil
NO3–N content occurred under the warming treatments (P= 0.05) than
under the no-warming treatments (Fig. 2d, Table 1).
Plant biomass (a) soil temperature (b) and soil
moisture content (c) in an alpine meadow. C (black bar), control treatment; G (white
bar), winter grazing treatment; W (white-dotted bar), warming treatment; WG
(black-dotted bar), warming combined with the winter grazing treatment.
Values are means ±1 s.e.m. (n= 4).
![]()
Soil total carbon (TC) (a), soil total nitrogen
(TN) (b), soil NH4+–N (c) and
NO3-–N (d) content in an alpine meadow. C (black bar),
control treatment; G (white bar), winter grazing treatment; W (white-dotted
bar), warming treatment; WG (black-dotted bar), warming combined with the
winter grazing treatment. Values are means ±1 s.e.m. (n= 4).
![]()
Microbial functional genes
Bacterial gene abundance varied from 4.71×109 to
5.93×109 copies g-1 dry soil, which was much higher
than fungal gene abundance (Fig. 3). Warming and grazing both increased the
bacterial gene abundance in soil (P < 0.01), but there was no
interaction effect between them on bacterial gene abundance (Table 1). By
comparison, fungal gene abundance showed no difference across all
treatments.
Nitrification enzyme activity and potential of <inline-formula><mml:math id="M147" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> production from
denitrification of bacteria and fungi
TNEA varied from 1.07 to 1.64 µg N g-1 h-1 in all
treatments. BNEA ranged from 0.43 to 0.64 µg N g-1 h-1, which
was lower than the FNEA in soil (0.59–0.66 µg N g-1 h-1)
(P= 0.01) (Fig. 4a–c). FNEA was lower under warming treatments than under
the no-warming treatments (P= 0.05) (Table 1).
Abundance of bacteria (a) and fungi (b) in an alpine meadow; C (black bar),
control treatment; G (white bar), winter grazing treatment; W (white-dotted bar), warming treatment; WG (black-dotted bar), warming combined with the
winter grazing treatment. Values are means
±1 s.e.m. (n= 4).
![]()
Bacterial nitrification enzyme activity (BNEA) (a), fungal
nitrification enzyme activity (FNEA) (b), total nitrification enzyme
activity (TNEA) (c); bacterial potential of N2O production
from denitrification (BDEA) (d), fungal potential of N2O
production from denitrification (FDEA) (e) and total potential of
N2O production from denitrification (TDEA) (f) in an
alpine meadow. C (black bar), control treatment; G (white bar), winter
grazing treatment; W (white-dotted bar), warming treatment; WG (black-dotted
bar), warming combined with the winter grazing treatment. Values are means
±1 s.e.m. (n= 4).
![]()
TDEA was between 1.32 and 1.80 µg N g-1 h-1. FDEA was clearly
the dominant process for TDEA (Fig. 4d–f), because it was higher than BDEA
for all treatments except warming. Warming increased BDEA (P= 0.04).
Warming and grazing had a significant interaction effect on FDEA (P < 0.01) (Table 1).
Contribution of bacteria and fungi to total nitrification enzyme
activity (box with the red and dashed line) and total potential of N2O
production from denitrification (box with the black and solid line) in an
alpine meadow. C (black bar), control treatment; G (white bar), winter grazing
treatment; W (white-dotted bar), warming treatment; WG (black-dotted bar), warming combined with the
winter grazing treatment. Values are means
±1 s.e.m. (n= 4).
![]()
The contribution of bacteria and fungi to potential <inline-formula><mml:math id="M174" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">N</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>
emissions
The contribution of FNEA to TNEA varied from 47±2 % to 56±5 %, and the contribution of FDEA to TDEA varied from 45±3 % to
63±3 % (Fig. 5). Warming significantly decreased the contribution
of FNEA and FDEA to TNEA and TDEA in soils (FNEA: P= 0.02; FDEA: P= 0.04).
Discussion
N2O is mainly produced from microbial nitrification and
denitrification processes, but the contribution of bacteria and fungi to
nitrification and denitrification processes is still unclear. In our results,
fungi contributed 54 % and 63 % of the TNEA and TDEA, respectively,
in control treatments of the alpine grassland studied. Our result of the
fungal contribution to potential of N2O production is much lower
than Laughlin and Stevens (2002) and
Zhong et al. (2018), who reported 89 % and 86 % fungal
contributions from temperate grasslands, but is higher than the 40–51 %
fungal contribution observed across different ecosystems by Chen et
al. (2014). Kato et al. (2013) also showed that N2O emissions from
FDEA were higher than from BDEA in alpine meadows, reinforcing the important
role fungi play in the denitrification process. Our findings support our
first hypothesis and further proved that both nitrification and
denitrification were largely driven by fungal communities in alpine meadow
grasslands. A possible explanation is that fungi prefer the arid, high
organic substrate and low-temperature environment (Pietikäinen et al.,
2005; Chen et al., 2015; Marusenko et al., 2013). In alpine grasslands, the
mean annual temperature is 0 ∘C; even during the sampling day, the
mean temperature was only 11 ∘C. The cold environment could cause
higher activity in fungi than in bacteria. Moreover, the cold environment
decreases the rate of mineralization, leading to greater organic C and N
accumulation (Ineson et al., 1998; Schmidt et al., 2004). In our study, soil
TC and TN concentrations were 72–86 and 6–7 g kg-1, respectively
(Fig. 2a and b), much higher than in temperate grasslands and farmland,
providing a favorable environment for fungi (Bai et al., 2010). These are the
main reasons why soil fungi played the main role in the N2O
production process in the Tibetan alpine grasslands.
Our methodology did not exclude a role for archaea in nitrification and
denitrification. Previous studies on grasslands only focused on fungal and
bacterial process because archaeal-specific inhibitors have not yet been
identified for N cycling processes. However, archaea are widespread in soil,
and are involved in nitrification denitrification (Cabello et al., 2004);
e.g., archaeal ammonia oxidizers are global (Leininger et al., 2006). In our
study, we also found that the TNEA was higher than the sum of NEA from
bacteria and fungi, while TDEA was higher than DEA from bacteria and fungi
(Fig. 4), which showed that archaea also played a role in the N2O
production process in our site. The development of inhibitor-based approaches
may help to show how archaea respond to environmental change (Marusenko et
al., 2013).
Our results supported the second hypothesis that although warming did not
change the total N2O production potential on the Qinghai–Tibetan
Plateau, the biotic pathways responsible for N2O had been changed,
as bacterial contributions to TNEA and TDEA were all higher than fungal,
which suggested higher bacterial N2O production potential under
warming treatment (Fig. 4, Table 1). The increase in bacterial N2O
production potential, coupled with a decrease in fungal N2O
production potential, could be the main reasons why the total N2O
production potential showed no difference between control and warming
treatments. The field data of N2O emission in our site measured in
the years of 2011–2012 also showed no effect of warming on N2O
emission (Zhu et al., 2015). Our results reinforced this and suggested that
bacterial nitrification and the denitrification process alone are unable to
accurately describe the response of N2O to warming.
It is these two reasons that lead to the changes in fungal and bacterial
pathways for the N2O production process by warming. Firstly,
warming significantly increased the soil temperature (Fig. 1b, Table 1); the
increased soil temperature directly reduced fungal activity but increased
bacterial activity, because fungi prefer the cold environment compared with
bacteria (Pietikäinen et al., 2005). Secondly, fungi prefer a higher
organic C / N environment, while bacteria prefer a higher inorganic
C / N environment (Chen et al., 2015). In our site, although the soil
NH4+–N concentration did not change with warming, soil
NO3-–N concentration that was significantly increased showed
that the soil inorganic N was increased (Fig. 2a and b, Table 1); on the
other hand, the soil dissolved organic nitrogen was significantly decreased
from 48 to 41 mg kg-1 (P < 0.04), and the soil labile C
and N were also found to be significantly decreased by warming (Rui et al.,
2012); this showed that the soil organic C and N were decreased in our site.
Therefore, warming indirectly reduced fungal activity but increased bacterial
activity through increased soil inorganic N and decreased soil organic N in
our site. In our site, the FNEA and FDEA were reduced by 16 % and
30 %, respectively, but the BNEA and BDEA were increased by 15 % and
41 %, respectively, by warming. All these changes resulted in fungi
contributing less to nitrification and denitrification than bacteria
(Fig. 5). Although the gene abundance of fungi was not changed by warming,
which showed inconsistencies with the changes in FNEA and FDEA, these
inconsistencies might be explained by the fungal gene abundance not likely
providing information on real-time process rates since such rates are
dependent on environmental conditions: fluctuations in environmental
conditions can cause rapid changes in real-time process rates but not
necessarily affect gene abundance (Zhong et al., 2014). In summary, it indicates that the soil microbial process
was altered by warming, even though the total potential of N2O
production did not change, with a shift in dominance from fungi to bacteria
in the N2O production process after 10 years of warming.
Numerous studies have demonstrated that grazing can impact microbial
processes and induce the loss of N by (1) altering the substrate
concentration for N2O production and reduction in soil through the
deposition of dung and urine (Saggar et al., 2004); (2) reducing vegetation
cover due to changes in soil water content and energy balance (Leriche et
al., 2001); and (3) increasing soil compaction and reducing soil aeration
through animal tramping (Houlbrooke et al., 2008). However, most of these
were focused on grazing in the growing season, and few were focused on the
effect of winter grazing on the N cycle process. In this study fungal and
bacterial potential of N2O production from nitrification and
denitrification all showed little response to winter grazing (Fig. 4,
Table 1). A possible explanation is that neither soil moisture, nor plant
biomass nor organic/inorganic C / N content was affected by winter
grazing (Figs. 1–2, Table 1). Additionally, the soil was frozen in winter,
so that the effect of selective feeding and trampling could be limited by
grazing sheep (Zhu et al., 2015; Krümmelbein et al., 2009; Steffens et
al., 2008). As a result, the same soil environmental conditions for both
winter grazing and control had no effect on soil fungi and bacteria, and thus
on fungal and bacterial nitrification and denitrification. Moreover, the
field data of N2O emission in the years of 2011–2012 also support
the results and suggest that replacing summer grazing by winter grazing could
cause the soil N cycle process to become stable (Zhu et al., 2015).
Overall, we conclude that fungi played the dominant role in the N2O
production process in alpine meadows. Previous studies had proved that the
climate warming did not affect the N2O production in our site (Zhu
et al., 2015), but we found that warming could alter biotic pathways
responsible for the N2O production process on the Tibetan Plateau.
Our study exhibited the effects of a decade of the simulation experiment;
however, a thorough understanding of the long-term impact of warming and
grazing on soil fungal nitrification and denitrification from alpine meadow
grasslands requires further investigation for a multi-decade period.
From this study, due to the different adaptation strategies of fungi and
bacteria, and their different nutrition requirements, future changes in
climate and soil resources are likely to affect biogeochemistry in a way not
currently accounted for in ecosystem models that assume N transformations
are controlled only by bacteria. Accurate predictions for N2O
production and N loss due to environmental change and land use will benefit
from the inclusion of fungi as key mediators of ecological processes in
grasslands.