RESEARCH ARTICLE

Abundance and community structure of ammonia-oxidizing Archaea and Bacteria in response to fertilization and mowing in a temperate steppe in Inner Mongolia Yong-Liang Chen1,2, Hang-Wei Hu1, Hong-Yan Han3, Yue Du2, Shi-Qiang Wan3, Zhu-Wen Xu4 & Bao-Dong Chen1 1 State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China; 2University of Chinese Academy of Sciences, Beijing, China; 3Key Laboratory of Plant Stress Biology, College of Life Sciences, Henan University, Kaifeng, Henan, China; and 4State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China

Correspondence: Baodong Chen, State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. Tel.: + 86 10 62849068; fax: +86 10 62923549; e-mail: [email protected]

MICROBIOLOGY ECOLOGY

Received 15 January 2014; revised 23 February 2014; accepted 24 March 2014. Final version published online 28 april 2014. DOI: 10.1111/1574-6941.12336 Editor: Riks Laanbroek Keywords ammonia-oxidizing Archaea; ammoniaoxidizing Bacteria; fertilization; land management practices; mowing; nitrification.

Abstract Based on a 6-year field trial in a temperate steppe in Inner Mongolia, we investigated the effects of nitrogen (N) and phosphorus (P) fertilization and mowing on the abundance and community compositions of ammonia-oxidizing Bacteria (AOB) and Archaea (AOA) upon early (May) and peak (August) plant growth using quantitative PCR (qPCR), terminal-restriction fragment length polymorphism (T-RFLP), cloning and sequencing. The results showed that N fertilization changed AOB community composition and increased AOB abundance in both May and August, but significantly decreased AOA abundance in May. By contrast, P fertilization significantly influenced AOB abundance only in August. Mowing significantly decreased AOA abundance and had little effect on AOA community compositions in May, while significantly influencing AOB abundance in both May and August, Moreover, AOA and AOB community structures showed obvious seasonal variations between May and August. Phylogenetic analysis showed that all AOA sequences fell into the Nitrososphaera cluster, and the AOB community was dominated by Nitrosospira Cluster 3. The results suggest that fertilization and mowing play important roles in affecting the abundance and community compositions of AOA and AOB.

Introduction Mowing is one of the most important land-management practices in grassland ecosystems. Much evidence has suggested that mowing or hay harvest could significantly alter aboveground plant species richness (Diaz et al., 2007) and increase plant population and community stability (Yang et al., 2012). Moreover, aboveground biomass removal by mowing can significantly reduce C deposits belowground, resulting in substrate limitation to soil-inhabiting microbes (Wan & Luo, 2003). Apart from mowing, other intensive land management practices such as fertilization can also markedly alter the species richness and community structure of plants, and decrease plant population and community stability (Yang et al., 2012) in grassland ecosystems, particularly in nutrient-limited

FEMS Microbiol Ecol 89 (2014) 67–79

environments (Stevens et al., 2004; Yang et al., 2011). Therefore, these two different land management practices might have divergent impacts in altering resource availability for plant growth and maintaining plant community stability in the grasslands. However, few studies have addressed the influence of land management practices, especially mowing or grazing on soil microbial communities involved in soil N cycling (Patra et al., 2005, 2006). This greatly hampered our ability to predict grassland responses to land-management practices, as the microorganisms are essential for maintaining ecosystem functions and plant nutrient availability by their involvement in key steps of biogeochemical cycling processes. Changes in microbial community compositions can greatly affect the resistance and resilience of grassland functioning to anthropogenic disturbances.

ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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Ammonia oxidation, the conversion from ammonia to nitrite, is thought to be the rate-limiting step of nitrification in terrestrial ecosystems; it is therefore central to the global nitrogen cycle (Kowalchuk & Stephen, 2001). Ammonia-oxidizing Bacteria (AOB) were traditionally considered the dominant contributors to ammonia oxidation. However, recent identification of the functional gene responsible for ammonia oxidation (i.e. ammonia monooxygenase, amoA) in Archaea (Venter et al., 2004) and isolation of Nitrosopumilus maritimus (K€ onneke et al., 2005) demonstrated that Archaea could also be capable of oxidizing ammonia. Nevertheless, comparative genomic analyses indicated that AOA and AOB may differ greatly in their physiology and metabolic pathways (Walker et al., 2010). AOA and AOB strains also exhibit significantly different ammonia oxidation kinetics in liquid batch culture (Martens-Habbena et al., 2009). Both archaeal and bacterial ammonia oxidizers are ubiquitous in terrestrial environments (Leininger et al., 2006; Shen et al., 2008; Chen et al., 2013). However, relative contributions of each group to soil nitrification processes are still being debated. Several recent studies have suggested that AOA play a more important role than AOB in ammonia oxidation in strongly acidic soils (Yao et al., 2011; Zhang et al., 2012). In contrast, AOB were found to control mainly the ammonia oxidation in microcosm studies of nitrogen-rich and agricultural soils (Di et al., 2009; Jia & Conrad, 2009). Various factors influencing the performance of soil ammonia oxidizers have been identified; among the most intensively studied factors are climatic conditions (Tourna et al., 2008; Chen et al., 2013), plant diversity (Malchair et al., 2010) and land managements such as fertilization, mowing and grazing (He et al., 2007; Le Roux et al., 2008; Shen et al., 2008; Di et al., 2009). During a 17-year field experiment, Shen et al. (2008) found that long-term fertilization had a significant impact on abundance and community compositions of AOB but not AOA. However, studies on the effects of P addition on ammonia oxidizers in grasslands are relatively scarce. Grazing has been further shown to induce changes in AOB abundance and community structures in field studies (Patra et al., 2005, 2006). Le Roux et al. (2008) demonstrated that AOB and AOA could respond rapidly to changes in aboveground grazing regime. Zhong et al. (2013) also found that grazing induced a significant increase in AOB abundance in a meadow steppe in northern China. However, aboveground grazing is different from mowing in that grazing is much patchier in terms of space and time (Rook et al., 2004; Klimek et al., 2007) and is accompanied by soil compaction due to grazing livestock, or nitrogen-input via urine and dung application. To date, the influences of mowing on the community ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

compositions of ammonia oxidizers have never been studied under microcosm or field conditions. Furthermore, most field studies have focused on ammonia oxidizers at only a single snapshot (Chen et al., 2011, 2013; Shen et al., 2011) and offer no information about the temporal pattern of ammonia oxidizer communities. It was reported that the ammonia oxidizers showed seasonal variations in their abundance (Sher et al., 2013). Seasonal variations in temperature, precipitation and root exudates may serve as important factors driving the dynamics of ammonia oxidizer communities. Therefore, a systematic investigation of ammonia oxidizers is required. Here, we investigated the effects of fertilization and mowing on the abundance and community structure of ammonia oxidizers at different plant growing seasons in a field experiment established in a temperate steppe in Inner Mongolia. The temperate steppe represents typical vegetation across the Eurasian continent, and has been predicted to experience increasingly intensive anthropogenic land management disturbance (Niu et al., 2010; Yang et al., 2011). Our study hence aimed to test the following two hypotheses: (1) mowing and fertilization would have strong effects on abundance and community structure of ammonia oxidizers; (2) the community of ammonia oxidizers would vary during plant growing seasons.

Materials and methods Field description and experimental design

The experimental field is located in a typical temperate steppe in Duolun County (42o20 N, 116o170 E; 1324 m above sea level), Inner Mongolia. Mean annual precipitation is approximately 380 mm, with > 90% occurring from May to October. Mean annual temperature is 2.1°C, with mean monthly temperature ranging from 17.5°C in January to 18.9°C in July. The soil in this area is classified as chestnut according to the Chinese classification, or Haplic Calcisol according to the FAO classification. The dominant plant species in the area are perennial herbs, such as Artemisia frigida, Stipa krylovii, Cleistogenes squarrosa and Agropyron cristattum. This study was a part of Duolun Global Change Multifactor Experiment (GCME) established in 2005. The whole experimental area was 199 9 265 m. Within this experimental area, eight 92 9 60 m plots were arranged into four rows and two columns with a 5-m-wide buffer zone between the plots. The eight plots were randomly assigned to mowing and non-mowing treatments, and each treatment had four replicates. Each 92 9 60 m2 plot was divided into four 44 9 28 m2 subplots, therefore resulting FEMS Microbiol Ecol 89 (2014) 67–79

69

Effects of N and P fertilization and mowing on AOB and AOA

in a total of 32 subplots with a 1-m-wide buffer zone. The four subplots within each plot were randomly assigned to four treatments of nutrient addition: control (C; no nutrient addition), nitrogen addition (N; 10 g N m2 year1, treated with urea in 2005 and NH4NO3 from 2006 to 2011), phosphorus addition (P; 5 g P2O5 m2 year1, treated with calcium superphosphate), and combined additions of N and P (NP, with the same form and amount of N and P as in the N and P treatments). Fertilizers were applied once a year in mid-July from 2005 to 2011. Mowing was conducted annually in August at the height of 10 cm aboveground using a lawnmower to mimic hay harvesting, and the harvested plant materials were removed immediately after mowing. Soil sampling

Soil samples were collected on 5 May and 22 August in 2011, representing the stage of early and peak plant growth, respectively. One composite soil sample was collected from each of the eight treatments. Five subsamples were randomly collected from the 0–15 cm top-soil to form one composite sample. Plant residues and debris were removed by hand, and each composite sample was homogenized by thorough mixing. All samples were stored in an ice box, and transported to the laboratory. Soil samples were passed through a 2.0-mm sieve, and stored at 4°C for determination of soil chemical properties and potential nitrification rates, and at 80°C before DNA extraction. Determination of soil chemical properties and potential nitrification rate

The soil moisture content was measured by drying fresh soils for 24 h at 105°C, and soil pH was determined with a soil to water ratio of 1 : 2.5. Soil ammonium and nitrate were extracted with 2 M KCl (a soil to water ratio of 1 : 5), and then measured with a continuous flow analyzer (SAN++, Skalar, Breda, Holland). Available soil P, extracted with 0.5 M NaHCO3, was determined by colorimetry according to Murphy & Riley (1962). Potential nitrification rate (PNR) was measured using the chlorate inhibition method (Kurola et al., 2005). Briefly, a 5-g sample of fresh soil was added to a 50-mL centrifuge tube consisting of 20 mL phosphate buffer solution (g L1: NaCl, 8.0; KCl, 0.2; Na2HPO4, 0.2; NaH2PO4, 0.2; pH 7.4), with a final concentration of 1 mM (NH4)2SO4. KClO3 10 mM was added to inhibit nitrite oxidation. The soil slurry was incubated in a dark incubator at 25°C for 24 h, after which nitrite was extracted with 5 mL of 2 M KCl and measured in a continuous flow analyzer. FEMS Microbiol Ecol 89 (2014) 67–79

DNA extraction and quantitative PCR (qPCR) of amoA genes

Soil DNA was extracted from 0.5 g of frozen soil using the FastDNA SPIN Kit for Soil (Q BIOgene Inc., Carlsbad, CA) according to the manufacturer’s instructions. The concentration and purity of the extracted DNA was assessed using a Nanodrop ND-2000 UV-Vis Spectrophotometer (NanoDrop Technologies, Wilmington, DE). The abundance of AOA and AOB amoA genes was determined by qPCR using the primer pairs Arch-amoAF/ArchamoAR (Francis et al., 2005) and amoA1F/amoA2R (Rotthauwe et al., 1997), respectively. The qPCR assays were performed on an iCycler iQ5 Thermocycler (Bio-Rad Laboratories, Hercules, CA). All reactions were performed in 25-lL reaction mixtures, including 12.5-lL SYBR Premix Ex TaqTM (Takara Biotechnology, Dalian, China), 1 lL bovine serum albumin (25 mg mL1), 0.5 lL each primer (10 lM), and 2 lL diluted DNA (1–10 ng) as a template. Amplifications were carried out as follows: 95°C for 1 min, followed by 40 cycles of 10 s at 95°C, 30 s at 55°C for AOB or 53°C for AOA, 1 min at 72°C, and a plate read at 83°C. Each set of qPCR reactions was carried out in triplicate. Product specificity was checked by melt curve analysis at the end of the qPCR runs and visualization by agarose gel electrophoresis. The PCR efficiency of AOA or AOB was 90–100% and r2 was 0.99. T-RFLP analysis

For the T-RFLP analysis, PCR amplification was performed using the primer pairs as the qPCR assays described above, with each forward primer fluorescently labeled with FAM. The thermo-cycling conditions for PCR reactions of AOA and AOB were the same as those for the qPCR assays. PCR products were gel-purified using the Wizard SV Gel and PCR Clean-Up Kit (Promega, San Luis Obispo, CA) and then digested with the restriction enzyme FastDigest MboI at 37°C for 5 min and at 65°C for 15 min. After purification, the digestion products of each sample were mixed with deionized formamide and GeneScanTM 500 ROXTM Size Standard (Applied Biosystems) at 95°C for 3 min and then placed on ice immediately. The DNA fragments were size-separated by capillary electrophoresis using the ABI PRISM 3130XL Genetic Analyzer (Applied Biosystems). Cloning and sequence analysis

One clone library from the CK treatment soils in May was constructed for AOA and AOB respectively using the same primer pairs as in the qPCR assays. The purified PCR products were ligated into the pGEM-T Easy Vector (Promega, ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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Madison, WI) and then transformed into Escherichia coli JM109 (Takara Biotechnology, Dalian, China) according to the manufacturer’s instructions. Fifty positive AOA clones and 30 positive AOB clones were randomly selected from each soil clone library and then sequenced. All the obtained sequences were subjected to homology analysis with the software DNAMAN version 6.0.3.48 (Lynnon Biosoft). Operational taxonomy units (OTUs) were defined as sharing 97% similarity. One representative sequence of each OTU and the related sequences obtained by BLAST were used for constructing the phylogenetic tree. Neighbor-joining tree construction was performed using MEGA version 4.0 (Tamura et al., 2007) by performing 1000 replicates to produce bootstrap replicates. Statistical analyses

The amoA gene copy numbers were log-transformed to provide variance homogeneity. Statistical analyses were performed based on SPSS version 16.0 (SPSS Inc., Chicago, IL). Three-way analysis of variance (ANOVA) was performed to examine the significance of treatment effects and their interactions on the observed parameters. A least-significant difference (LSD) test was applied to examine quantitative differences between treatments. To visualize differences in soil samples, an ordination principal component analysis (PCA) was performed with CANOCO software (Centre for Biometry, Wageningen, Netherlands).

Results Soil physico-chemical properties

N fertilization significantly decreased soil pH but increased soil NH4+-N and NO3-N concentrations in both May and August (Table 1). P fertilization significantly decreased soil pH (P < 0.05) and NO3-N concentrations (P < 0.001) in May (Table 1). As expected, P fertilization also significantly increased available P concentrations in soil in both May and August (P < 0.001, Table 1). Mowing significantly decreased soil water content (P < 0.05, Table 1) but increased soil NH4+-N and available P concentrations in May. However, soil NO3-N concentrations were significantly decreased by mowing in August. Potential nitrification rates (PNR)

The potential nitrification rates ranged from 0.12 to 1.23 mg NO2-N g1 soil h1 in all treatments in May, and ranged from 0.08 to 0.31 mg NO2-N g1 soil h1 in August (Fig. 1). The highest PNR was recorded under N fertilization in May, and was 10 times higher than that ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

Table 1. Soil physico-chemical properties under different treatments of fertilization and mowing (n = 4)

Treatments May* CK N P NP CK + M N+M P+M NP + M Significance of N P M N*P N*M P*M N*P*M August CK N P NP CK + M N+M P+M NP + M Significance of N P M N*P N*M P*M N*P*M

Water content (%)

pH (H2O)

NH4+-N (mg kg1)

NO3-N (mg kg1)

4.74ab 4.86a 4.58ab 4.58ab 4.58ab 4.29ab 3.97b 4.38ab

7.10a 6.27b 6.83a 6.02b 6.96a 6.06b 6.87a 6.06b

5.59c 5.96bc 5.89bc 8.36a 7.63ab 9.39a 7.69ab 9.30a

6.76ab 8.98a 5.20bc 5.60b 6.83ab 8.10a 3.21c 6.68ab

10.50d 8.59d 37.27b 30.66c 9.93d 8.76d 46.42a 43.08ab

0.739 0.198 0.044 0.434 0.991 0.911 0.264

0.000 0.049 0.386 0.738 0.826 0.171 0.800

0.002 0.146 0.000 0.285 0.771 0.139 0.219

0.002 0.000 0.412 0.857 0.313 0.962 0.064

0.036 0.000 0.001 0.254 0.502 0.001 0.671

0.65ab 0.72a 0.49b 0.71a 0.72a 0.67ab 0.73a 0.70a

7.21a 6.35b 7.13a 6.38c 7.16a 6.61bc 7.04a 6.30bc

13.71c 25.31ab 14.40c 27.64a 18.00bc 18.81bc 15.21c 25.88ab

5.79c 32.63a 5.18c 22.96ab 5.79c 11.41bc 4.91c 16.84bc

10.22c 11.04c 30.07b 52.76a 15.75bc 16.49bc 51.87a 47.01a

0.278 0.470 0.178 0.303 0.040 0.242 0.451

0.000 0.065 0.853 0.727 0.203 0.132 0.217

0.000 0.320 0.664 0.123 0.075 0.862 0.264

0.000 0.643 0.033 0.824 0.036 0.236 0.221

0.216 0.000 0.090 0.298 0.083 0.743 0.085

Olsen-P (mg kg1)

*Part of May data from Chen et al. (2014). CK, control; N, fertilization with 10 g N m2 year1; P, fertilization with 5 g P2O5 m2 year1; NP, fertilization with 10 g N m2 year1 and 5 g P2O5 m2 year1; M, mowing. Values in columns with the same letter do not differ significantly (P < 0.05) as determined by the least-significant-difference test. Significant effects (P < 0.05) are highlighted in bold as determined by three-way ANOVA.

under the P fertilization plus mowing treatment. N fertilization significantly increased PNR in May (P < 0.001, Table 2). Significant interactions of N fertilization, P fertilization and mowing on PNR were observed (P < 0.05), as a significant increase caused by mowing was only detected in the NP treatment and not in the CK, N or P treatments. In addition, PNR in May showed significant positive correlations with soil moisture content (P = 0.001, Table 3) and soil NO3-N concentrations (P < 0.001), but a significant negative correlation with pH values (P < 0.05, Table 3). Significant positive correlations were FEMS Microbiol Ecol 89 (2014) 67–79

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Effects of N and P fertilization and mowing on AOB and AOA

also observed between PNR and AOB abundance in May (P < 0.05, Table 3). By contrast, PNR in August showed a significant negative correlation with pH values

Potential nitrification activity (mg NO2–1-N kg–1 soil h–1)

(a)

CK

2.0

N

P

NP

AOA and AOB abundance

May

1.5

1.0

0.5

0.0 Non-mowing

Potential nitrification activity (mg NO2–1-N kg–1 soil h–1)

(b)

0.6

Mowing

August

0.5 0.4 0.3 0.2 0.1 0.0 Non-mowing

Mowing

Fig. 1. Potential nitrification rate (PNR) under different fertilization and mowing treatments in May (a) and August (b). CK, control; N, fertilization with 10 g N m2 year1; P, fertilization with 5 g P2O5 m2 year1; NP, fertilization with 10 g N m2 year1 and 5 g P2O5 m2 year1; M, mowing. See Table 2 for statistical results. Columns represent means of four replicates. Error bars indicate standard deviations. Table 2. Results of a three-way ANOVA for PNR, AOB and AOA amoA copy numbers from different fertilization and mowing treatments (n = 4)

May PNR AOA AOB August PNR AOA AOB

(P < 0.05), but significant positive correlations with soil NH4+-N concentrations (P < 0.01) and NO3-N concentrations (P = 0.001).

N

P

M

N*P

N*M

P*M

N*P*M

0.001 0.015 0.000

0.164 0.588 0.440

0.154 0.001 0.006

0.303 0.121 0.302

0.139 0.714 0.137

0.057 0.562 0.620

0.032 0.964 0.931

0.198 0.482 0.000

0.495 0.612 0.011

0.490 0.138 0.000

0.407 0.163 0.038

0.162 0.873 0.685

0.375 0.575 0.567

0.103 0.538 0.213

CK, control; N, fertilization with 10 g N m2 year1; P, fertilization with 5 g P2O5 m2 year1; NP, fertilization with 10 g N m2 year1 and 5 g P2O5 m2 year1; M, mowing. Significant effects (P < 0.05) are highlighted in bold as determined by three-way ANOVA.

FEMS Microbiol Ecol 89 (2014) 67–79

Archaeal amoA copies ranged from 1.05 9 109 to 2.10 9 109 g1 soil across all treatments (Fig. 2a and b). Three-way ANOVA showed that both N fertilization and mowing significantly decreased AOA abundance in May (P < 0.05 and P < 0.001, respectively). However, no significant differences in AOA abundance were found among all treatments in August (Table 2, Fig. 2b). Generally, AOB abundance was lower than AOA abundance, and ranged from 2.41 9 105 to 7.67 9 107 copies g1 soil (Fig. 3). N fertilization significantly increased AOB abundance both in May and in August (P < 0.001, Table 2). On the other hand, significant effects of P fertilization on AOB abundance were found in August (P < 0.05, Table 2). N and P fertilization interactively influenced AOB abundance (P < 0.05, Table 2) in August, and the NP treatment showed a significant higher AOB abundance compared with that in the N or P treatment, irrespective of the mowing treatment. Furthermore, mowing also significantly influenced AOB abundance both May and in August (P < 0.01 and P < 0.001, respectively; Table 2). AOA abundance in May showed a significant positive correlation with soil pH (P < 0.05) but a negative correlation with soil NH4+-N concentrations (P < 0.001). By contrast, AOB abundance in May showed a significant negative correlation with soil pH (P < 0.001) but a significant positive correlation with soil NH4+-N concentrations (P < 0.01). Similarly, AOB abundance in August also showed a significant negative correlation with soil pH values (P < 0.001) but significant positive correlations with soil NH4+-N (P < 0.001) concentrations and NO3N concentrations (P < 0.001). Community structures of AOA and AOB

PCA analysis showed that AOA community compositions in May (Fig. 4a) and August (Fig. 4b) remained unchanged with respect to fertilization and mowing treatments. Subtle alternations were detected between the mowing treatments and the non-mowing controls. For example, the P treatment was clearly separated from the P plus mowing treatment (Fig. 4a). PCA analysis showed that AOB community compositions were highly different among treatments both in May (Fig. 5a) and in August (Fig. 5b). Additionally, the N-fertilized treatments were clearly separated from the non-N-fertilized controls especially in May (Fig. 5a). However, both AOA and AOB ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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Table 3. Correlations of soil properties, PNR and abundances of AOA and AOB in May and August

May PNR AOA AOB August PNR AOA AOB

Soil moisture

pH

NH4+-N

NO3-N

Olsen-P

AOA

AOB

0.480(0.001) 0.055(0.317) 0.037(0.840)

0.335(0.049) 0.136(0.019) 0.960(0.000)

0.043(0.350) 0.055(0.000) 0.152(0.002)

0.137(0.000) 0.008(0.556) 0.078(0.078)

0.006(0.266) 0.001(0.547) 0.001(0.825)

0.405(0.446) – –

0.327(0.034) – –

0.258(0.155) 0.264(0.462) 0.738(0.518)

0.137(0.021) 0.076(0.516) 1.857(0.000)

0.010(0.003) 0.003(0.644) 0.089(0.000)

0.007(0.001) 0.000(0.996) 0.045(0.000)

0.001(0.595) 0.000(0.961) 0.009(0.250)

0.126(0.193) – –

0.052(0.086) – –

N

NP

Significant effects (P < 0.05) are highlighted in bold.

CK

10

N

P

NP

AOA-May

(a)

Log number of bacterial amoA copies g–1 dry soil

Log number of archaeal amoA copies g–1 dry soil

(a)

9

8

7

P

AOB-May

8

7

6

5

Mowing

Non-mowing

(b)

AOA-August

Log number of bacterial amoA copies g–1 dry soil

Log number of archaeal amoA copies g–1 dry soil

10

CK

4

Non-mowing

(b)

9

9

8

7 Non-mowing

Mowing

Fig. 2. AOA amoA gene copies under different fertilization and mowing treatments in May (a) and August (b). CK, control; N, fertilization with 10 g N m2 year1; P, fertilization with 5 g P2O5 m2 year1; NP, fertilization with 10 g N m2 year1 and 5 g P2O5 m2 year1; M, mowing. See Table 2 for statistical results. Columns represent means of four replicates, error bars indicate standard deviations.

communities did differ remarkably between May (Fig. 6a) and August (Fig. 6b). Phylogeny of AOA and AOB

To characterize the diversity of amoA genes, 50 randomly selected AOA amoA gene clones and 30 randomly selected ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

9

Mowing

AOB-August

8

7

6

5

4 Non-mowing

Mowing

Fig. 3. AOB amoA copies under different fertilization and mowing treatments in May (a) and August (b). CK, control; N, fertilization with 10 g N m2 year1; P, fertilization with 5 g P2O5 m2 year1; NP, fertilization with 10 g N m2 year1 and 5 g P2O5 m2 year1; M, mowing. See Table 2 for statistical results. Columns represent means of four replicates, error bars indicate standard deviations.

AOB amoA gene clones from soils of the control treatment were sequenced (Figs 7 and 8). Phylogenetic analysis showed that all the AOA sequences belonged to the Nitrososphaera cluster (Fig. 7). Similarly, the AOB amoA gene sequences obtained in the soil belonged to the Nitrosospira cluster 3a and cluster 9 (Fig. 8). FEMS Microbiol Ecol 89 (2014) 67–79

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Effects of N and P fertilization and mowing on AOB and AOA

(a)

(a)

(b)

(b)

Fig. 5. AOB compositions under different fertilization and mowing treatments as assessed by principal component analysis of T-RFLP data in May (a) and August (b). CK, control; N, N fertilization; P, P fertilization; NP, combined N and P fertilization; CK+M, control with mowing; N+M, N fertilization with mowing; P+M, P fertilization with mowing; NP+M, combined N and P fertilization with mowing.

Fig. 4. AOA compositions under different fertilization and mowing treatments as assessed by principal component analysis of T-RFLP data in May (a) and August (b). CK, control; N, N fertilization; P, P fertilization; NP, combined N and P fertilization; CK+M, control with mowing; N+M, N fertilization with mowing; P+M, P fertilization with mowing; NP+M, combined N and P fertilization with mowing.

Discussion Effects of fertilization and mowing on PNR and abundance of AOA and AOB

As expected, N addition significantly increased the soil NH4+-N concentrations in both May and August (Table 1), and the higher NH4+-N concentrations in soil increased PNR. Mowing, a common land management practice, did not affect PNR, although it did significantly increase soil NH4+-N concentrations in May (Table 1). FEMS Microbiol Ecol 89 (2014) 67–79

Interestingly, PNR and AOB abundance were significantly higher in May than in August. This is consistent with the findings in the study of Sher et al. (2013) that PNR was higher during the winter than during the summer. This may be explained by the relatively high soil water contents in May; the increased soil moisture at this time might have accelerated soil mineralization rates and NH4+-N availability (Stark & Firestone, 1995), thus supporting higher PNR and AOB abundance. It has been suggested that the ammonia oxidizers are sensitive to water stress, which affects their activity through both dehydration and substrate limitation (Stark & Firestone, 1995). Field studies also confirmed the significant positive effects of precipitation increment on AOB abundance in a temperate steppe in Inner Mongolia (Chen et al., 2013). PNR was significantly correlated with the abundance of AOB but not that of AOA, suggesting that nitrification ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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(a)

the observed predominance of AOA over AOB in a variety of agricultural and grassland soils (Leininger et al., 2006; Shen et al., 2008; Chen et al., 2013). There appears to be a general trend of greater AOA abundance in a large number of soils. However, there is still great uncertainty about the physiology and habitat preferences of AOA. It appears that archaeal ammonia monooxygenase (AMO) has a higher affinity for substrate than does bacterial AMO (Martens-Habbena et al., 2009). The differences in substrate affinities may allow AOA and AOB to inhabit distinct ecological niches shaped by substrate availability. The significantly lower AOA abundance in the N-fertilized soils in May support this premise, as the N fertilization significantly increased the soil NH4+-N concentrations in the two growing seasons, particularly in August. The high NH4+-N concentrations in the soil might therefore have provided an unfavorable environment for AOA growth. Similar studies also demonstrated that AOA prefer low ammonia substrate (Di et al., 2010), and AOA growth was even depressed by high ammonium amendments (Verhamme et al., 2011). There is also evidence that AOA may be more metabolically versatile and may be heterotrophs or mixotrophs, as they can also use organic carbon. Walker et al. (2010) found that the genome of Nitrosopumilus maritimus contains genes encoding for the complete oxidative tricarboxylic acid cycle (TCA) and transporters for amino acids. A stimulated growth of Nitrososphaera viennensis by small additions of pyruvate (Tourna et al., 2011) also supported mixotrophic growth by AOA. The significantly lower AOA abundance in the mowing plots compared with the controls without mowing may support a heterotrophic or mixotrophic life of AOA, as mowing can significantly reduce organic carbon of root exudates into soil, limiting substrate to soil microorganisms (Wan & Luo, 2003). Highly labile soil organic matter, such as straw and root exudates, may stimulate growth of AOA (Chen et al., 2008; Wessen et al., 2010; Ai et al., 2013). However, it does not appear that AOA in this study are limited by C resources, as there were no significant differences in soil total C and organic matter among all treatments in May (data not shown). By contrast, AOB was found to prefer to use high ammonia substrate (Di et al., 2010), and the ammonia concentration contributes to the definition of distinct AOA and AOB in soil microcosms (Verhamme et al., 2011). The N-amended plots showed significantly increased NH4+-N concentrations in both May and August, which may have contributed to a higher AOB abundance in the present study. A number of studies have demonstrated similar results in that only AOB abundance increased in response to high levels of N fertilizers (Shen et al., 2008; Di et al., 2009; Verhamme et al., 2011; Chen et al., 2013).

(b)

Fig. 6. AOA (a) and AOB (b) community compositions in May and August. CK, control; N, N fertilization; P, P fertilization; NP, combined N and P fertilization; CK+M, control with mowing; N+M, N fertilization with mowing; P+M, P fertilization with mowing; NP+M, combined N and P fertilization with mowing.

might be driven principally by AOB in the examined grassland soils. In a series of microcosms with low soil ammonia concentrations and incubated without external nitrogen, AOA was found to be mainly responsible for the ammonia oxidation (Offre et al., 2009; Gubry-Rangin et al., 2010; Zhang et al., 2010, 2012). By contrast, AOB was thought primarily to control the ammonia oxidation in soils supplied with nitrogen fertilizers (Di et al., 2009, 2010; Jia & Conrad, 2009). The correlation between AOB and PNR in this study was therefore supposed to be attributed largely to the ammonia substrate availability. In this study, AOA were much more abundant than AOB in both May and August, which is consistent with ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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Effects of N and P fertilization and mowing on AOB and AOA

Fig. 7. Neighbor-joining phylogenetic tree of AOA amoA gene sequences retrieved from the clone library of our soil and the NCBI gene bank. Filled triangles indicate the sequences retrieved from the soil samples. Bootstrap values (> 50) are indicated at branch points.

Interestingly, mowing also significantly affected the AOB abundance in May and August. As a common land-management practice, mowing might result in a decrease in available N concentrations in soil. In this study, the soil NO3-N concentrations were significantly decreased by mowing in August. Thus, a possible explanation for the effect of mowing on AOB abundance in August could be the obvious N losses from soil after mowing. However, the AOB abundance under mowing treatments in May was significantly higher than those in the non-mowing controls. The significant increase in NH4+-N concentrations in soil by mowing in May might favor the growth the AOB. In addition, NP fertilization significantly increased AOB abundance compared with only N or P fertilization in August, showing the interaction of P and N fertilization in affecting AOB abundance. FEMS Microbiol Ecol 89 (2014) 67–79

AOA and AOB community structures in response to land-management and the seasonal variations

Fertilization seemed to have no influence on AOA communities in May and August, whereas mowing seemed to induce small alternations in AOA community compositions in May. For example, AOA community compositions under the P treatment were highly different from the composition under the P plus mowing treatment (Fig. 4a). In contrast, N fertilizer strongly shifted AOB community compositions, especially in May, whereas mowing had no obvious effect on AOB communities. These results indicate that N fertilization and mowing played different roles in affecting community compositions of ammonia oxidizers. ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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Fig. 8. Neighbor-joining phylogenetic tree of AOB amoA gene sequences retrieved from the clone library of our soil and the NCBI gene bank. Filled triangles indicate the sequences retrieved from the soil samples. Bootstrap values (> 50) are indicated at branch points.

N availability might be directly linked to the AOB community compositions (Hynes & Germida, 2012). Long-term N fertilization significantly changed AOB community compositions but had marginal effects on AOA communities in alkaline agricultural soils (Chu et al., 2008; Shen et al., 2008) and neutral grassland soils (Chen et al., 2013). However, a large number of molecular evidences demonstrated that AOA were more sensitive than AOB to different fertilization treatments in various acidic soils (He et al., 2007; Chen et al., 2011). Thus, the changes in community compositions of ammonia oxidizers in response to fertilization may depend on the soil pH and soil types. We did not observe an obvious P effect on ammonia oxidizer communities, despite the significant effect of P fertilizer on AOB abundance. By contrast, Chu et al. (2007) found differences in denaturing gradient gel electrophoresis (DGGE) banding patterns of the amoA gene between control and PK (phosphorus and potassium)enriched plots in agricultural soils after fertilization for 16 years. Non-changes in ammonia oxidizer communities under P-fertilized plots do not exclude the possibility of interactions of P with N. As previously stated, AOB abundance responded primarily to N addition and was additionally stimulated by the NP addition, indicating secondary P limitation. Thus, we can still expect an ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

obvious effect of P fertilizer on ammonia oxidizer communities in long-term observations. However, little is known about the direct influences of P fertilization on ammonia oxidizers, which still needs further investigation. Interestingly, AOA and AOB communities showed obvious differences between May and August, which could be possibly explained by several mechanisms. One possibility is that exudates from plant roots play an important role in affecting the community compositions of AOA and AOB. Chen et al. (2008) reported that oxygen and carbon dioxide released by rice roots into the rhizosphere were the major factors determining the changes in AOA and AOB community structures in a paddy soil. Ai et al. (2013) also reported obvious differences in AOA community compositions between reproductive stages of wheat (in early May) and maize (in late August) in a calcareous fluvo-aquic soil. The quality and quantity of root exudation might be significantly different between May and August, as there were no plants growing in early May in our plots. Additionally, seasonal factors (temperature and water) are also important in determining the community compositions of ammonia oxidizers. It should be noted that the mean temperatures in May and August are significantly different (Niu et al., 2010). These differences in FEMS Microbiol Ecol 89 (2014) 67–79

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May and August may lead to distinct optimal growth rate of different AOA lineages. The impact of different temperatures on ammonia oxidizers was examined in field and microcosm experiments. Tourna et al. (2008) studied the influence of temperature on AOA and AOB in soil microcosms at temperatures in the range of 10–30 °C, and they found profound changes in AOA community structures. Stres et al. (2008) also found that soil AOA, but not AOB, community structures were more dynamic and were strongly influenced by temperature in soil microcosms. Thus, we speculate that temperature could be an important factor contributing to this temporal variability. It should also be mentioned that the soil moisture content in May is significantly higher than in August (Table 1). Chen et al. (2013) reported that long-term precipitation increment markedly changed the AOB but not the AOA community composition. Similarly, AOA and AOB community structures were observed to be highly responsive to changes in soil water availability (Gleeson et al., 2010). Therefore, soil water content is another factor potentially influencing the temporal variability of ammonia oxidizer communities. All AOA sequences were grouped within the Nitrososphaera cluster in this study, suggesting that AOA in this temperate steppe do not share a similar origin with marine sequences. Dominance of Nitrososphaera cluster in AOA were observed in agricultural (He et al., 2007; Shen et al., 2008) and grassland (Di et al., 2009; Chen et al., 2013) soils. Phylogenetic analysis of AOB amoA gene sequences showed that soil AOB was affiliated within Nitrosospira sequences, and AOB was dominated by Nitrosospira 3a. Similar results were found in agricultural soils (He et al., 2007; Shen et al., 2008) and high N environments (Di et al., 2009; Chen et al., 2013). The high N deposition rate in this area (Liu et al., 2011) may have resulted in preferable growth of Nitrosospira species. Finally, we have to admit that archaeal amoA primers used in the present study were somehow outdated and might not cover the known diversity of AOA. In particular, a series of species such as Nitrosocaldus yellowstonii, Nitrosopumilus maritimus and Cenarchaeum symbiosum might have been underestimated. However, two comprehensive studies showed that the abundances of AOA clusters Nitrosocaldus and Nitrosopumilus were usually very low in the surveyed soils (Gubry-Rangin et al., 2011; Hu et al., 2013). Therefore, our results may be largely reliable in reflecting ammonia oxidizer communities. Moreover, although the bacterial amoA primers used in this study did not amplify all existing AOB (Stephen et al., 1999), they were selected for compatibility reasons with other studies. In conclusion, to our knowledge this study is the first to examine the mowing effects on abundance and FEMS Microbiol Ecol 89 (2014) 67–79

community composition of ammonia oxidizers in a grassland ecosystem. We clearly demonstrated that mowing played an important role in shaping ammonia oxidizer communities in the temperate steppe. The significant changes in the abundance of ammonia oxidizers and the subtle changes in AOA community compositions after mowing indicate the importance of protecting the grassland from intensive mowing or grazing, which may lead to significant grassland degradation and changes in the community compositions of N-cycling microorganisms. On the other hand, fertilization practices, especially N fertilization increased the AOB abundance and also led to changes in AOB community structures. The high sensitivity of AOB rather than AOA community compositions to N fertilizer and the significant correlations between PNR and AOB abundance suggest that the ammonia oxidation might be mainly driven by AOB in this grassland ecosystem, with the functions of AOA in soil N cycling remain unresolved. Additionally, we found obvious seasonal variations of AOA and AOB communities between May and August, highlighting the importance of taking temporal variability into account when performing field experiments, lest the background variation overwhelm the treatment effects. The present study has led to a better understanding of the community dynamics of the ammonia oxidizers under land-management practices in the temperate grassland ecosystems, and therefore has implications for the protection of the grasslands from anthropogenic disturbances.

Acknowledgements The study was financially supported by Knowledge Innovation Program of the Chinese Academy of Sciences (Project KZCX2-YW-BR-17), State Key Laboratory of Urban and Regional Ecology (SKLURE2008-1-03) and The Ministry of Science and Technology of China (2013CB956300).

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