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Journal of Resources and Ecology >

2019 , Vol. 10 >Issue 1: 69 - 76

DOI: https://doi.org/10.5814/j.issn.1674-764X.2019.01.009

Orginal Article

A Meta-analysis of the Effects of Warming and Elevated CO2 on Soil Microbes

  • FU Gang 1 ,
  • ZHANG Haorui 1, 2 ,
  • LI Shaowei 1 ,
  • SUN Wei , 1, *
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  • 1. Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 2. University of Chinese Academy of Sciences, Beijing 100049, China
*Corresponding author: SUN Wei, E-mail:

Received date: 2018-06-05

  Accepted date: 2018-09-12

  Online published: 2019-01-28

Supported by

National Natural Science Foundation of China (31600432, 41571042)

The National Key Research Projects of China (2017YFA0604801)

The Youth Innovation Research Team Project of Key Laboratory of Ecosystem Network Observation and Modeling (LENOM2016Q0002)

Chinese Academy of Science Western Light Talents Program (Response of livestock carrying capability to climatic change and grazing in the alpine meadow of Northern Tibetan Plateau) and Tibet Science and Technology Major Projects of Pratacultural Industry.

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Abstract

Soil microbes play important roles in terrestrial ecosystem carbon and nitrogen cycling. Climatic warming and elevated CO2 are two aspects of climatic change. In this study, we used a meta-analysis approach to synthesise observations related to the effects of warming and elevated CO2 on soil microbial biomass and community structure. Ecosystem types were mainly grouped into forests and grasslands. Warming methods included open top chambers and infrared radiators. Experimental settings included all-day warming, daytime warming and nighttime warming. Warming increased soil actinomycetes and saprotrophic fungi, while elevated CO2 decreased soil gram-positive bacteria (G+). Mean annual temperature and mean annual precipitation were negatively correlated with warming effects on gram-negative bacteria (G-) and total phospholipid fatty acid (PLFA), respectively. Elevation was positively correlated with the warming effect on total PLFA, bacteria, G+ and G-. Grassland exhibited a positive response of total PLFA and actinomycetes to warming, while forest exhibited a positive response in the ratio of soil fungi to bacteria (F/B ratio) to warming. The open top chamber method increased G-, while the infrared radiator method decreased the F/B ratio. Daytime warming rather than all-day warming increased G-. Our findings indicated that the effects of warming on soil microbes differed with ecosystem types, warming methods, warming times, elevation and local climate conditions.

Key words： ecosystem types; elevated CO2; increased temperature; response ratio; warming methods

Cite this article

FU Gang , ZHANG Haorui , LI Shaowei , SUN Wei . A Meta-analysis of the Effects of Warming and Elevated CO2 on Soil Microbes[J]. Journal of Resources and Ecology, 2019 , 10(1) : 69 -76 . DOI: 10.5814/j.issn.1674-764X.2019.01.009

1 Introduction

Soil microbes play important roles in terrestrial ecosystem carbon and nitrogen cycling (Zhou et al., 2012). There are several major soil microbial taxa, including fungi, gram- positive bacteria (G+), gram-negative bacteria (G-), actinomycetes, arbuscular mycorrhizal fungi (AMF), and saprotrophic fungi (SF). Most soil microbial biomass is composed of fungi and bacteria (Baath and Anderson, 2003). Different soil microbial taxa have different functions (Hu et al., 2001). Human activity has resulted in an increase in the atmospheric carbon dioxide (CO2) concentration and the global surface temperature has increased since the Industrial Revolution (IPCC, 2013). Elevated CO2 and warming will most likely alter soil microbial communities (Kanerva et al., 2008; Rinnan et al., 2007).
Phospholipid fatty acid (PLFA) analysis is one of the most commonly used methods to determine soil microbial community composition. Based on the PLFA analysis, soil fungi, total bacteria, G+, G-, actinomycetes, AMF, SF and other soil taxa can be determined (Bardgett, et al., 1996; Frostegard, et al., 1993). The change of soil total PLFA can reflect changes of soil microbial biomass for soil biota from all taxa (Zhang et al., 2014). The changes in soil fungi, total bacteria, G+, G-, actinomycetes, AMF and SF can be used to reflect the changes in soil microbial biomass for a specific taxon, respectively (Zhang et al., 2014). The changes in soil fungi to bacteria ratio (F/B ratio) and the ratio of G+ to G- (G+/G- ratio) can be used to reflect the changes in soil microbial community structure (Fu and Shen, 2017b). Soil microbial taxa can have inconsistent responses to experimental warming with regard to ecosystem types and climatic conditions. Elevated temperature can either increase (Shen et al., 2014), decrease (Allison and Treseder, 2008; Ma et al., 2011) or have a negligible effect on soil fungi and bacteria (Liu et al., 2014; Schindlbacher et al., 2011). Elevated temperature can also have inconsistent effects on soil G+, G-, actinomycetes and AMF (Li et al., 2013; Rousk et al., 2013). Elevated temperature can increase (Zhang et al., 2004), reduce (Zhang et al., 2014) or have a negligible effect (Gutknecht et al., 2012; Zhang et al., 2013) on soil F/B ratio. Elevated temperature effects on the soil G+/G- ratio have been found to vary with landscape types, including increases in an alpine swamp meadow and forest ecosystem on the Tibetan Plateau, reductions in an alpine meadow and steppe on the Tibetan Plateau and a tundra ecosystem in the Changbai Mountain, and no obvious effect in a subarctic tundra (Rinnan et al., 2007; Wang et al., 2014; Zhang et al., 2014; Zhao et al., 2014).
There are inconsistent results on the relationship between warming duration and warming effects on soil microbial biomass, with either no relationship (Bai et al., 2013; Zhang et al., 2015) or a negative relationship (Blankinship et al., 2011). In addition, findings on the relationships between elevated CO2 duration and elevated CO2 effects on soil microbial biomass were also inconsistent, with either negative (Blankinship et al., 2011) or positive correlations (Ross et al., 2013). Several meta-analyses have indicated that soil microbial biomass in forest soils responded more strongly to warming than the microbial biomass in grassland soils (Bai et al., 2013; Lu et al., 2013), whereas Zhang et al. (2015) have found that microbial biomass in grassland soils responded more strongly to warming than that in forest soils. Therefore, it remains unclear whether treatment durations are related to treatment effects on soil microbes or whether soil microbial biomass in forest soils can respond more strongly to warming than microbial biomass in grassland soils.
To better understand these conflicting results, we compiled the data from 28 published warming and/or elevated CO2 studies related to soil microbial community composition derived from PLFA analyses. All of the 28 studies were based on field experiments. No previous meta-analyses have examined the relationship between the effect of warming on soil microbes and elevation. The main objectives of this study were to: 1) examine the general effects of warming or elevated CO2 on soil microbes; 2) test whether warming duration or warming magnitude can affect responses of soil microbes to warming; 3) check whether elevated CO2 duration or elevated CO2 magnitude can influence responses of soil microbes to elevated CO2; and 4) investigate whether responses of soil microbes to warming can vary with ecosystem types or elevation.

2 Methods

2.1 Data compilation

The relevant articles published prior to 2017 were found using the Web of Science and the China National Knowledge Infrastructure. The compiled database included soil total PLFA, fungi, bacteria, G+, G-, actinomycetes, AMF, SF, the F/B ratio and the G+/G- ratio.
Our criteria for selecting relevant articles or subsets of data from articles included: 1) only field experimental studies were used; 2) for experiments with multiple factors, only the data from warming or elevated CO2 treatments compared to a control were adopted; 3) at least one of the variables considered here was measured; 4) for experiments with multiple observations at different times from the same study site, only the latest results were adopted, considering that the observations included in the meta-analysis should be independent (Hedges et al., 1999); and (5) multiple soil depths, treatment magnitudes or ecosystem types were treated as independent variables.
We extracted the data (means, standard deviations or standard errors, and sample sizes) using the GetData software if the studies provided the data in figures (Fu and Shen, 2017c; Fu et al., 2015). Only one study analyzed the interactive effects of warming and elevated CO2 on the soil microbial community (Andresen et al., 2014). Therefore, we did not analyze the interactive effects of warming and elevated CO2.
All 28 studies were grouped according to ecosystem type, which included forest, grassland, shrubland and tundra ecosystems (Table 1). Experimental durations (i.e., from the beginning of warming or elevated CO2 treatment to the soil sampling time) were calculated in years. The main warming methods included open top chamber and infrared radiator. There were all-day warming, daytime warming and nighttime warming treatments in different studies. Warming magnitudes ranged from 0.1°C to 4°C (including 23 levels) and mean annual temperatures ranged from -7.3°C to 16.3°C. The increased CO2 concentrations ranged from 36 ppm to 360 ppm (including 8 levels). The elevated CO2 methods employed in the experiments included regular FACE techniques, greenhouses and open-top chambers.
Table 1 Basic information for the 28 studies included in the meta-analysis
Authors Year Journal Title MAT
(℃)		 MAP
(mm)		 Elevation (m) Latitude Longitude Vegetation types
Wang et al. 2011 Chinese Journal of Applied and Environmental Biology Microbial communities of alpine meadow soil in the Eastern Qinghai-Tibetan Plateau subjected to experimental warming and grazing 1.1 752.4 3561 32.45 102.37 Grassland
Schindlbacher et al. 2011 Soil Biology & Biochemistry Experimental warming effects on the microbial community of a temperate mountain forest soil 5.7 1480 910 47.58 11.64 Forest
Andresen
et al.		 2014 PLoS ONE Bacteria and fungi respond differently to multifactorial climate change in a temperate heathland, traced with 13C-glycine and FACE CO2 8 600 55.88 11.97 Tundra
Rinnan et al. 2007 Global Change Biology Fifteen years of climate change manipulations alter soil microbial communities in a subarctic heath ecosystem -0.4 245.5 450 68.35 18.82 Tundra
Rousk et al. 2013 Global Change Biology Investigating the long-term legacy of drought and warming on the soil microbial community across five European shrubland ecosystems 56.38 10.95 Shrubland
46.88 19.72 Shrubland
40.60 8.15 Shrubland
52.40 5.92 Shrubland
53.05 -3.47 Shrubland
Zhou et al. 2012 Nature Climate Change Microbial mediation of carbon-cycle feedbacks to climate warming 16.3 914 34.98 -97.52 Grassland
Zhao et al. 2014 Plant and Soil Effects of experimental warming and nitrogen fertilization on soil microbial communities and processes of two subalpine coniferous species in Eastern Tibetan Plateau, China 8.9 919.5 1820 31.68 103.88 Forest
Zhang et al. 2014 PLoS ONE Responses of soil microbial communities to experimental warming in alpine grasslands on the Qinghai-Tibet Plateau -3.8 290.9 4635 34.82 92.93 Grassland
Zhang et al. 2011 Soil Biology & Biochemistry Soil microbial community changes and their linkages with ecosystem carbon exchange under asymmetrically diurnal warming 2.1 383 1324 42.03 116.28 Grassland
Shen et al. 2014 Pedosphere Soil microbial responses to experimental warming and nitrogen addition in a temperate steppe of Northern China 2.1 383 1324 42.03 116.28 Grassland
Zhang et al. 2013 Oecologia Soil microbial responses to warming and increased precipitation and their implications for ecosystem C cycling 2.1 383 1324 42.03 116.28 Grassland
Wang et al. 2014 Acta Ecologica Sinica Effects of warming on soil microbial community structure in Changbai Mountain tundra -7.3 1600 2028 Tundra
Gutknecht et al. 2012 Global Change Biology Microbial communities and their responses to simulated global change fluctuate greatly over multiple years 37.67 -122.37 Grassland
Xu et al. 2015 Soil Biology & Biochemistry Labile, recalcitrant, microbial carbon and nitrogen and the microbial community composition at two Abies faxoniana forest elevations under elevated temperatures 2.7 813 3000 Forest
Maestre
et al.		 2015 Frontiers in Microbiology Warming reduces the cover and diversity of biocrust-forming mosses and lichens, and increases the physiological stress of soil microbial communities in a semi-arid Pinus halepensis plantation 14.6 315 38.54 -49.00 Forest
Zhang et al. 2015 European Journal of Soil Science Depth-related responses of soil microbial communities to experimental warming in an alpine meadow on the Qinghai-Tibet Plateau -3.8 383 4635 34.85 92.93 Grassland
De Long
et al.		 2016 Ecosystems Contrasting responses of soil microbial and nematode communities to warming and plant functional group removal across a post-fire boreal forest successional gradient Forest
Yoshitake
et al.		 2015 Ecological Research Soil microbial response to experimental warming in cool temperate semi-natural grassland in Japan 7.1 2128 36.13 137.42 Grassland
Authors Year Journal Title MAT
(℃)		 MAP
(mm)		 Elevation (m) Latitude Longitude Vegetation types
Kao-Kniffin et al. 2013 Microbial Ecology A microbial link between elevated CO2 and methane emissions that is plant species-specific Grassland
Feng et al. 2010 Global Change Biology Altered microbial community structure and organic matter composition under elevated CO2 and N fertilization in the duke forest 35.97 -79.08 Forest
Kasurinen
et al.		 2005 Global Change Biology Below-ground responses of silver birch trees exposed to elevated CO2 and O3 levels during three growing seasons 307.33 120 62.65 27.05 Forest
Kanerva
et al.		 2008 Soil Biology & Biochemistry Changes in soil microbial community structure under elevated changes in soil microbial community structure under elevated tropospheric O3 and CO2 60.82 23.47 Grassland
Ebersberger et al. 2004 Plant and Soil Effects of long term CO2 enrichment on microbial community structure in calcareous grassland 8.75 900 520 47.55 7.57 Grassland
Janus et al. 2005 Microbial Ecology Elevated atmospheric CO2 alters soil microbial communities associated with trembling aspen (Populus tremuloides) roots 45.57 -84.67 Forest
Hagedorn
et al.		 2013 Soil Biology & Biochemistry Nine years of CO2 enrichment at the alpine treeline stimulates soil respiration but does not alter soil microbial communities 47.47 7.50 Forest
Manninen
et al.		 2010 Soil Biology & Biochemistry Plant and soil microbial biomasses in Agrostis capillaris and Lathyrus pratensis monocultures exposed to elevated O3 and CO2 for three growing seasons 60.82 23.47 Grassland
Chung et al. 2007 Global Change Biology Plant species richness, elevated CO2, and atmospheric nitrogen deposition alter soil microbial community composition and function Grassland
Guenet et al. 2012 Geoderma The impact of long-term CO2 enrichment and moisture levels on soil microbial community structure and enzyme activities Grassland

MAT mean annual temperature; MAP mean annual precipitation.

2.2 Statistical analyses

We used the METAWIN 2.1 software (Sinauer Associates Inc., Sunderland, MA, USA) to perform this meta-analysis. We treated the natural logarithm of the response ratio (R) as the effect size (Hedges et al., 1999).
\[\ln R=\ln \left( \frac{{{{\bar{X}}}_{t}}}{{{{\bar{X}}}_{c}}} \right)=\ln \left( {{{\bar{X}}}_{t}} \right)-\ln \left( {{{\bar{X}}}_{c}} \right)\ (1)\]
where \(\overline{{{X}_{t}}}\) and \(\overline{{{X}_{c}}}\) are the mean values of the treatments and control, respectively.
We used the inverse of the pooled variance (\[1/v\]) as the weighting factor (\(w\)) for each study,
\[v=\frac{S_{t}
{2}}{{{n}_{t}}\overline{X_{t}
{2}}}+\frac{S_{c}
{2}}{{{n}_{c}}\overline{X_{c}
{2}}}\ (2)\]
where \({{n}_{t}}\) and \({{n}_{c}}\) are the sample sizes of the treatments and control, respectively; and \(S_{t}
{2}\) and \(S_{c}
{2}\) are the standard deviations of the treatments and control, respectively.
Then, we obtained the mean effect size (\(\ln \bar{R}\)) derived from all observations,
\[\ln \bar{R}=\frac{\sum\limits_{i=1}
{m}{{{w}_{i}}\ln {{R}_{i}}}}{\sum\limits_{i=1}
{m}{{{w}_{i}}}}\ (3)\]
where \(\ln {{R}_{i}}\] and \({{w}_{i}}\) are \(\text{ln}R\) and \(w\) of the ith observation, respectively.
A fixed effects model was used to examine whether warming or elevated atmospheric CO2 had a significant effect on each variable across all studies. Mean effect sizes were generated and 95% bias-corrected bootstrap confidence intervals (CI) were estimated. If the 95% bias- corrected bootstrap CI did not include zero, the response of the variable to warming or elevated atmospheric CO2 was considered significant (Fu and Shen, 2017a). Both of the common rank correlation tests, Kendall's tau and Spearman Rank-Order correlation, for publication bias were performed, and all the rank correlations were non-significant. The mean effect size of each variable was transformed to the percentage change as \(({{e}
{\overline{\text{Lo}{{\text{g}}_{\text{e}}}R}}}-1)\times 100%\) (Fu and Shen, 2016).
We used a fixed effects model with a grouping variable to compare responses among vegetation types, warming times and warming methods. For a specific group, the mean effect size was calculated using only the data of that group. If the 95% bias-corrected bootstrap CI did not bracket zero for a specific group, the response of that specific variable to warming or elevated atmospheric CO2 was considered significant.
We used a random effects model with a continuous variable (> 15 observations) to test the correlations of the effect sizes of warming or elevated CO2 with experimental duration or magnitude. If the regression coefficient (i.e., slope) was significant, then this independent variable could explain significantly the variation among the effect sizes of the treatments.

3 Results

Different soil microbe taxa may have different sensitivities to elevated temperature and CO2. Warming significantly increased soil actinomycetes by 11.1% and saprotrophic fungi by 13.8%, whereas warming did not significantly change soil total PLFA, fungi, bacteria, G+, G-, AMF, F/B ratio or G+/G- ratio (Fig. 1). Elevated CO2 only significantly decreased soil G+ by 6.6% (Fig. 2).
Fig. 1 Warming effects on soil microbial biomass
Note: G+: gram-positive bacteria, G-: gram-negative bacteria, F/B ratio: the ratio of soil fungi to bacteria, G+/G- ratio: the ratio of G+ to G-, AMF: arbuscular mycorrhizal fungi, SF: saprotrophic fungi. The error bars indicate effect sizes and 95% bootstrap confidence intervals. The sample size for each variable is shown next to the bar.
Fig. 2 Elevated CO2 effects on soil microbial biomass
Note: Related descriptions as shown in Fig. 1.
Warming duration and magnitude were not correlated with warming effects on soil total PLFA, fungi, bacteria, G+, G- or F/B ratio (Table 2). Increased CO2 duration (QM = 1.20, p = 0.274, n = 17) and magnitude (QM = 0.74, p = 0.389, n = 17) were not correlated with elevated CO2 effects on soil total PLFA.
Table 2 Relationships between warming effects on soil microbial biomass and relevant variables
Variables Slope p QM QE QT n
Warming duration
Total PLFA -0.01 0.633 0.23 29.21 29.44 28
Fungi 0.01 0.568 0.33 24.81 25.13 28
Bacteria 0.01 0.394 0.73 29.67 30.39 29
G+ 0.03 0.417 0.66 20.04 20.69 20
G- 0.01 0.849 0.04 18.21 18.25 18
F/B ratio -0.01 0.471 0.52 18.79 19.31 22
Warming magnitude
Total PLFA -0.02 0.819 0.05 27.44 27.49 24
Fungi 0.05 0.517 0.42 22.01 22.43 26
Bacteria 0.01 0.887 0.02 27.36 27.38 26
G+ 0.01 0.904 0.01 22.38 22.39 21
G- 0.03 0.580 0.31 19.21 19.52 19
F/B ratio -0.01 0.815 0.05 16.16 16.21 19
Mean annual air temperature
Total PLFA -0.01 0.451 0.57 18.44 19.00 20
Fungi -0.01 0.366 0.82 14.80 15.62 20
Bacteria -0.01 0.269 1.22 17.68 18.90 21
G+ -0.01 0.166 1.92 22.23 24.16 20
G- -0.02 0.014 6.09 19.75 25.84 18
F/B ratio -0.0021 0.633 0.23 16.55 16.78 19
Mean annual precipitation
Total PLFA -0.0002 0.019 5.54 24.16 29.70 19
Fungi -0.0002 0.077 5.15 19.67 24.82 19
Bacteria -0.0001 0.244 1.36 19.22 20.58 20
G+ -0.0002 0.109 2.57 19.34 21.91 20
G- -0.0002 0.208 1.58 18.43 20.01 18
F/B ratio 0.0000 0.597 0.28 14.33 14.61 18
Elevation
Total PLFA 0.0001 0.031 4.63 16.81 21.45 17
Fungi 0.00 0.366 0.82 15.94 16.76 17
Bacteria 0.0001 0.018 5.63 15.45 21.09 17
G+ 0.0001 0.010 6.63 19.30 25.93 17
G- 0.0001 0.034 4.51 19.65 24.16 16

Note: Slope: regression coefficients; P: the statistical probability; n: the number of the observations used in the meta-analysis; QT: Total heterogeneity of the effect sizes of treatments among all studies; QM: the variation that can be explained by the continuous randomized-effects model; QE: The residual error; A significant slope (P < 0.05) indicates that an independent variable can explain the variation among effect sizes. G+: gram-positive bacteria, G-: gram-negative bacteria, F/B ratio: the ratio of soil fungi to bacteria.

Mean annual air temperature and mean annual precipitation were negatively correlated with warming effect on soil G- and soil total PLFA, respectively (Table 2). Elevation was positively correlated with warming effect on soil total PLFA, bacteria, G+ and G- (Table 2).
Warming increased soil total PLFA by 29.5% and actinomycetes by 19.9% in grasslands, whereas soil total PLFA and actinomycetes in forests did not change under warming (Fig. 3). The OTC method increased G- by 19.3%, while the IR method did not affect G- (Fig. 4). The IR method decreased the F/B ratio by 6.8%, while the OTC method did not affect the F/B ratio (Fig. 4). Daytime warming increased G- by 10.7%, while all-day warming did not affect G- (Fig. 5).
Fig. 3 Warming effects on soil microbial biomass for (a) forest and (b) grassland
Note: Related descriptions as shown in Fig. 1.
Fig. 4 Effects of (a) infrared radiator and (b) open top chamber on soil microbial biomass
Note: Related descriptions as shown in Fig.1
Fig. 5 Effects of (a) all-day, (b) daytime and (c) nighttime warming on soil microbial biomass
Note: Related descriptions as shown in Fig. 1.

4 Discussion

Elevated CO2 may affect the soil microbial community considering the decrease in soil gram-positive bacteria (G+) found in our study, which was likely attributed to the following mechanisms. First, elevated CO2 generally increases ratios of soil carbon to nitrogen and litter carbon to nitrogen (de Graaff et al., 2006; Luo et al., 2006; Yang et al., 2011),while soil gram-positive bacteria decreases with increasing ratios of soil carbon to nitrogen and litter carbon to nitrogen (Huang et al., 2014; Lange et al., 2014). Second, elevated CO2 generally decreases soil nitrogen availability (de Graaff et al., 2006) and soil bacterial growth may be suppressed in nitrogen-limited systems (Hu et al., 2001).
Our findings implied that soil microbes might have stronger responses to warming in colder and drier areas, and the responses of soil microbes to warming increased with increasing elevation. These findings were in line with some previous studies (Chen et al., 2015; Zhang et al., 2015). Therefore, the temperature sensitivity of soil microbes may increase with increasing elevation, and decreasing temperature and water availability. Our findings were also in agreement with a previous meta-analysis which showed that daytime warming had a stronger positive effect on soil microbial abundance than all-day warming (Chen et al., 2015).
Our findings supported a previous study which showed that warming increased soil microbial biomass carbon and nitrogen in alpine grasslands but not in forests on the Tibetan Plateau (Zhang et al., 2015). This phenomenon may be attributed to the following mechanisms. First, the positive effects of warming on soil microbial total PLFA decreased with increasing mean annual precipitation (Table 2) and the grasslands had a lower mean annual precipitation than the forests in our meta-analysis (most <800 mm vs. >800 mm). Second, the positive effects of warming on soil microbial total PLFA increased with increasing elevation (Table 2) and the grasslands had a higher average elevation than the forests in our meta-analysis (3994 m vs. 2535 m). In addition, warming increased the F/B ratio by 16.4% in forests but not in grasslands (Fig.3). Therefore, forest and grassland soil microbes appear to have different sensitivities to elevated temperature.
Our findings also supported recent a meta-analysis which indicated that warming effects on soil microbial biomass varied between the OTC and IR methods (Chen, et al., 2015). The finding that warming effects on the F/B ratio varied between the OTC and IR methods can be attributed to the following mechanisms. First, the F/B ratio decreased with increasing soil nitrogen availability (Zhang et al., 2005), and the increased magnitude of soil nitrogen availability caused by the IR method was greater than that caused by the OTC method (Bai et al., 2013). Second, the IR and OTC methods resulted in different magnitudes of increases in plant belowground biomass and decreases in soil moisture (Lu et al., 2013), which in turn caused different changes in the soil F/B ratios between the IR and OTC methods (Gutknecht et al., 2012).

5 Conclusions

Warming increased soil actinomycetes and saprotrophic fungi, while elevated CO2 decreased soil gram-positive bacteria (G+). Mean annual temperature and mean annual precipitation were negatively correlated with the warming effect on gram-negative bacteria (G-) and total phospholipid fatty acid (PLFA), respectively. Elevation was positively correlated with the warming effect on total PLFA, bacteria, G+ and G-. Grassland exhibited a positive response of total PLFA and actinomycetes to warming, while forest exhibited a positive response in the ratio of soil fungi to bacteria (F/B ratio) to warming. The open top chamber method increased G-, while the infrared radiator method decreased the F/B ratio. Daytime warming, rather than all-day warming, increased G-. Therefore, the sensitivities of soil microbial communities to warming varied with ecosystem types, warming methods and warming times. In colder and drier areas, soil microbial biomass appeared to have a higher temperature sensitivity. The temperature sensitivity of soil microbial biomass also increased with increasing elevation.

The authors have declared that no competing interests exist.

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