Effects of Different Nitrogen Additions on Soil Microbial Communities In

Effects of different nitrogen additions on soil microbial communities in different seasons in a boreal forest 1,2 1,3 1 2 1 1 GUOYONG YAN, YAJUAN XING, LIJIAN XU, JIANYU WANG, XIONGDE DONG, WENJUN SHAN, 1 1,2, LIANG GUO, AND QINGGUI WANG

1College of Agricultural Resource and Environment, Heilongjiang University, 74 Xuefu Road, Harbin 150080 China 2School of Forestry, Northeast Forestry University, 26 Hexing Road, Harbin 150040 China 3Institute of Forestry Science of Heilongjiang Province, 134 Haping Road, Harbin 150081 China

Citation: Yan, G., Y. Xing, L. Xu, J. Wang, X. Dong, W. Shan, L. Guo, and Q. Wang. 2017. Effects of different nitrogen additions on soil microbial communities in different seasons in a boreal forest. Ecosphere 8(7):e01879. 10.1002/ecs2.1879

Abstract. In the global change scenario, nitrogen (N) deposition has the potential to affect the soil microbial communities that play critical roles in ecosystem functioning. Although the impacts of N deposition on soil microbial communities have been reasonably well studied, microorganism responses to the N addition combined with the seasonal change have rarely been reported. This study was conducted to evaluate the effects of different levels of N addition (0, 2.5, 5.0, and 7.5 g Nm 2yr 1) on soil microbial communities in different seasons (spring, summer, and autumn) in a boreal forest. Our results showed that the soil physical–chemical properties were found to be changed by N addition and seasonal changes were correlated with microbial community structure. The N addition and seasonal changes significantly affect the diversity and abundance of the microbial community, while their interactions only affect the bacterial abundance and the fungal diversity. In addition, our results also provided clear evidence for specific responses of microorganisms to the different N additions and each season. Our findings suggest that the microbial community response to N deposition could be the seasonal change and will strongly correlate with environmental change.

Key words: boreal forest; nitrogen deposition; seasonal changes; soil microbial communities.

Received 15 April 2017; accepted 24 May 2017; ﬁnal version received 14 June 2017. Corresponding Editor: Michael F. Allen. Copyright: © 2017 Yan et al. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. E-mail: [email protected]

INTRODUCTION deposition has increased by 8 kg N/hm2 compared with the 1980s (Liu et al. 2013). Increased Atmospheric nitrogen (N) deposition from N deposition can have dramatic impacts on the anthropogenic sources is currently estimated to structure and function of terrestrial ecosystem. be 30–50% greater than that from natural terres- Although attention has been paid to the effect of trial sources (Canﬁeld et al. 2010) and has N deposition on ecosystem functioning, most increased approximately fourfold over the past studies focused on the response of the above- century (IPCC 2013). It is predicted that the rate ground portion, such as aboveground plant pro- of N deposition will continuously increase, and duction, plant community composition, plant by 2050, it may double (Phoenix et al. 2011). diversity, and lignin in the leaf litter (Galloway Especially in China, with the rapid economic et al. 2008, Xia and Wan 2008, Bleeker et al. 2011, growth, the average annual bulk deposition of N Phoenix et al. 2011, Frey et al. 2014). The effects increased to 21.1 kg N/hm2 in the 2000s from of N deposition on the soil microbial communi- 13.2 kg N/hm2 in the 1990s and atmospheric N ties and their related ecological processes remain

❖ www.esajournals.org 1 July 2017 ❖ Volume 8(7) ❖ Article e01879 YAN ET AL. unclear, although they are also important in glo- microorganisms will respond to environmental bal change ecology (Hoover et al. 2012, Li et al. change in the future. 2013a, b, Yao et al. 2014, Zhao et al. 2014, Xiong In addition to N deposition, soil microorgan- et al. 2016). isms also have to face the seasonal variations in Soil microbial communities are directly related environmental conditions such as temperature to soil biogeochemical processes, and they play an and moisture (Lopez-Mondejar et al. 2015). These important role in the soil carbon cycle and soil N seasonal variations result in the seasonal change turnover (Bardgett et al. 2008, Xiong et al. 2014a, in microbial community (Aponte et al. 2010, Kai- b, Zeng et al. 2016). The soil microorganisms can ser et al. 2010, Landesman and Dighton 2011, affect plant growth, soil organic matter decompo- Kuffner et al. 2012, Zhang et al. 2013, Zhou et al. sition and mineralization, nutrient cycling, and 2013, Vorıskova et al. 2014, Siles et al. 2016). Thus, soil degradation (Klaubauf et al. 2010, Li et al. interaction between seasonal change and N depo- 2012, Graham et al. 2016). However, the commu- sition might have an impact on microbial community structure is considered to be a key determi- nities. However, previous studies on the response nant of the functions: Direct change in microbial of microbial communities to the N deposition community structure may alter microbial func- have rarely focused on the seasonal changes. tions and soil N and C dynamics (Fierer et al. Therefore, we designed an experiment to study 2012, Chen et al. 2014, Matulich and Martiny the responses of the soil microbial community to 2014, Leff et al. 2015, Mannisto et al. 2016). There- N addition and seasonal changes. The average fore, the shifts in the structure and composition of annual N deposition in China increased to the microbial communities are strong indicators 3.5 g Nm 2yr 1 in 2012 from 1.3 g Nm 2yr 1 of soil biochemical processes and essential ecosys- in 1980 due to the increased anthropogenic activi- tem functions (Edmeades 2003, Liu et al. 2006, ties and excessive application of fertilizer, and the Pardo et al. 2011). current N deposition rate is 2.5 g Nm 2yr 1 in Nitrogen deposition can affect structure and northern China (Liu et al. 2013). Therefore, we composition of soil microbial communities (Tre- investigated the soil microbial community in a seder 2008, Klaubauf et al. 2010, Tian and Niu controlled experiment plot that has received N 2015, Shi et al. 2016). Many previous experi- addition at four different levels (0, 2.5, 5.0, and ments (including field and laboratory) have also 7.5 g Nm 2yr 1) for 4 yr in a boreal forest, identified the major shifts in the microbial com- northern China. The objective of this study was to munity structure under N addition treatments examine the effects of N additions, seasonal (Ramirez et al. 2010a, b, Fierer et al. 2012, changes, and their interaction on soil microbial Ramirez et al. 2012, Koyama et al. 2014, Leff community composition and diversity. We et al. 2015). Moreover, several meta-analyses hypothesized that (1) N addition, seasonal have demonstrated that the responses of soil changes, and their interaction will cause a change microbial communities to experimental N in the microbial community structure; (2) this manipulations might alter soil ecosystem func- change will be via modifying the soil properties tions (Treseder 2008, Janssens et al. 2010, Zhou and underground micro-environmental factors. et al. 2014, Carey et al. 2016). Although previous The Illumina MiSeq sequencing analysis was used studies suggested that N availability was an to determine the taxa of soil bacteria and fungi. important determinant for the dominant life strategy of the soil microbial community (Fierer MATERIALS AND METHODS et al. 2012, Chen et al. 2014, Leff et al. 2015), the relationships between the different microbial Site description taxa and N addition level are variable (Williams Our experiment was conducted in a boreal for- et al. 2013, Zhong et al. 2015), and the mecha- est that is located in Nanwenghe National Natu- nisms underlying the soil microbial feedback in ral Reserve (51°050–51°390 N, 125°070–125°500 E) response to N deposition remain elusive (Zeng in the Greater Khingan Mountains, China. The et al. 2016). Understanding the effect of N depo- climate of the station is a typical cold temper- sition on soil microbial communities is beneficial ate continental climate with a long, cold winter in the prediction of the manner in which soil and a short, warm summer. Mean annual

❖ www.esajournals.org 2 July 2017 ❖ Volume 8(7) ❖ Article e01879 YAN ET AL. temperature is 2.4°C, ranging from 26.3°Cin two sub-samples: One of them was immediately ° January to 18.6 C in July. The mean annual pre- frozen in liquid N2, put into the box containing cipitation is about 489 mm, mainly falling during dry ice, taken back to the laboratory, and stored short summer (July and August). The soil type of at 80°C for nucleic acid extraction, and the the studied areas is mainly stony to sandy loam, other one was packed in an icebox and trans- and the mean soil depth is 20 cm. The dominant ported to the laboratory for nutrient analysis. and principal tree species is Larix gmelinii with a mean stand density of 2852 99 trees/hm2 and Soil physicochemical properties ° a mean diameter at breast height (1.3 m height, The soil temperature (T5cm, C) and the soil 3 dbh) of 8.98 0.32 cm. moisture (W5cm, volumetric water content, m / m3) at the 5 cm depth were simultaneously mon- Experimental design itored by using a soil temperature probe (EM50; To investigate the effects of N deposition, the N Decagon Devices, Pullman, Washington, USA) addition experiment was established in May 2011. and the soil moisture probe (EC-5; Decagon This design was replicated in three random exper- Devices). The soil pH was measured by using a imental blocks, each consisting of four plots mea- pH meter (Sartorius PB-10, Gottingen, Germany) suring 20 9 20 m each, and the plots were with a 1:2.5 (soil:water, dry weight/volume) ratio separated by 10 m wide buffer strips to avoid dis- of soil to water following shaking for 30 min. turbing nearby plots. In total, 12 plots were estab- The soil total carbon and total N (TN) were mea- lished. According to the current N deposition rate sured by using a Multi N/C 3100 Analyzer (Ana- (2.5 g Nm 2yr 1) in northern China (Liu et al. lytik Jena, Thuringia, Germany). Dissolved 2013), three N addition treatments—low level of organic carbon (DOC) and dissolved total N N(LN,2.5gNm 2yr 1), medium level of N (DTN) were extracted from 10 g soil using (MN, 5 g Nm 2yr 1), high level of N (HN, 2 mol/L KCl extraction procedures. Dissolved 7.5 g Nm 2yr 1)—and a control treatment (C, total N and DOC were determined by using a no N addition) were conducted randomly in four Multi N/C 3100 Analyzer (Analytik Jena AG, plots of each block. NH4NO3 was applied in this Thuringia, Germany). study as a form of N addition from May 2011 and was evenly distributed on five occasions during DNA extraction and PCR amplification each growing season (from May to September) of Microbial DNA in each sample was extracted local forests. The NH4NO3 was weighed (571.4, from 0.5 g soil using the E.Z.N.A. Soil DNA Kit 1142.9, and 1714.3 g NH4NO3 for LN, MN, and (Omega Bio-Tek, Norcross, Georgia, USA) accord- HN in each plot in the 10th of each month, respec- ing to the manufacturer’s protocol. The protocol is tively) according to the N addition rate, mixed available online (http://omegabiotek.com/store/ with 32 L of water. Then, a solution of NH4NO3 wp-content/uploads/2013/04/D5625-Soil-DNA-Kit- was sprayed evenly onto the forest floor of each Combo-Omega.pdf). The 16S ribosomal RNA plot by using a backpack sprayer. Each control gene was amplified by using a barcoded primer plot received 32 L of N-free water. set 338F (5ʹ-TGCTGCCTCCCGTAGGAGT-3ʹ)/ 806R (5ʹ-GGACTACHVGGGTWTCTAAT-3ʹ), and Soil sampling the fungal 18S ribosomal RNA genes were ampli- To determine the effect of seasonal changes, fied by using the primer set ITS1F (5ʹ-CTTG soil samples were collected in spring (21st May), GTCATTTAGAGGAAGTAA-3ʹ)/2043R (5ʹ-GCTG summer (23rd July), and autumn (27th Septem- CGTTCTTCATCGATGC-3ʹ). Three replicates of ber) of 2015. Six soil columns (depth = 0–10 cm) polymerase chain reaction were performed for were obtained at six random points on each plot each soil sample, and the products were pooled using a stainless soil corer (5 cm inner diameter prior to purification. Amplicons were extracted and 10 cm long). The six soil columns were then from 2% agarose gels and purified using the Axy- mixed to form a composite sample. All of the Prep DNA Gel Extraction Kit (Axygen Biosciences, samples were sieved through a 2-mm soil sieve, Union City, California, USA) according to the and the roots, stones, and other debris were manufacturer’s instructions and quantified with removed. Each sample was then divided into QuantiFluor-ST (Promega, Madison, Wisconsin,

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USA). Then, the purified amplicons were pooled (LDA) effect size (LEfSe) method (http://hutten in equimolar concentrations and then sequenced hower.sph.harvard.edu/lefse/) for biomarker dis- on an Illumina MiSeq platform. The Illumina covery. The LEfSe emphasizes both statistical MiSeq sequencing was performed at Shanghai significance and biological relevance (Segata Majorbio Bio-Pharm Technology, Shanghai, et al. 2011). When the N addition treatments China. The Illumina MiSeq sequencing was were used as the classes of the LEfSe analysis, described in detail by Zhong et al. (2015). the seasonal changes were used as subclasses of Raw FASTQ files were used in the processing the LEfSe analysis, and vice versa. Both the sig- of the sequencing data. The raw FASTQ files were nificance alphas for the factorial Kruskal–Wallis demultiplexed and quality-filtered using QIIME test and the pairwise Wilcoxon test between sub- (version 1.17, http://qiime.org). Operational taxo- classes were 0.05 and an effect size threshold for nomic units were clustered with a 97% similarity the logarithmic LDA score was 2 for all of the cutoff using UPARSE (version 7.1, http://drive5. biomarkers evaluated in this study. com/uparse/), and the chimeric sequences were The redundancy analysis (RDA, post hoc per- identified and removed using UCHIME (version mutation tests with 999 permutations) was used 4.2.40, http://drive5.com/usearch/manual/uchime_ as the statistical criterion to assess multivariate algo.html). The phylogenetic affiliation of each changes in microbial community composition 16S rRNA gene sequence was analyzed by the among treatments using the vegan package in R Ribosomal Database Project Classifier (version version 3.3.1, which is a multivariate direct gra- 2.2, http://sourceforge.net/projects/rdp-classifier/) dient analysis method, was further implemented against the SILVA (SSU117/119, https://www.arb- to test for significant associations between the silva.de/) 16S rRNA and 18S rRNA database soil microbial community and soil properties in using a confidence threshold of 70% (Amato et al. the different treatments of N addition and sea- 2013, Zhong et al. 2015). On average, 28,411 quali- sonal changes. fied 16S rRNA sequences and 30,334 qualified 18S The principal component analysis (PCA) based rRNA sequences were obtained per sample. The on the distance matrix was used to elucidate MOTHUR software (version 1.30.1, http:// changes in soil microbial communities due to www.mothur.org/wiki/Schloss_SOP#Alpha_diver different treatments, and PERMANOVA was sity) was used to calculate alpha diversity and performed as described for the unweighted richness indexes. The calculation of diversity UniFrac distances. All statistical analyses were indexes included the Shannon index (http:// performed using the vegan package in R software www.mothur.org/wiki/Shannon), and that of rich- version 3.3.1. ness indexes included the Chao1 estimator (http:// www.mothur.org/wiki/Chao). RESULTS

Statistical analyses Effects of N addition and seasonal changes on soil The soil factors in each sample were analyzed properties ’ by analysis of variance (ANOVA) with Tukey s Whereas the values of T5cm, VWC5cm, DOC, honestly significant difference (HSD) test to inves- DTN, and TN were not significantly different tigate differences in response to simulated N among the different N addition treatments, the deposition, seasonal changes, and their interaction soil pH and the C:N ratios were significantly dif- using R version 3.3.1 (R Development Core Team ferent among the different N addition treatments 2016, http://www.r-project.org). Moreover, gen- (Tables 1, 2). And in different seasons, the effects eral linear model and multivariate ANOVA with of N addition on pH and C:N ratios were differ- Tukey’s HSD test were used to examine the main ent (Tables 1, 2). In the spring, a significant and interactive effects of N addition and seasonal decrease in pH was observed in MN and HN changes on the richness and Shannon indexes for treatments, whereas no significant differences bacteria and fungi. in soil pH were observed in control and LN The characterization of microbial community treatments. In the summer, a significant decrease under N addition and seasonal changes was in soil pH was observed among the different described using the linear discriminant analysis N addition treatments. In the autumn, no

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Table 1. Effects of nitrogen (N) addition on abiotic soil variables in different seasons (mean SD).

° 3 3 Treatments pH T5cm( C) VWC5cm(m /m ) DOC (mg/kg) DTN (mg/kg) TN (mg/g) C:N Spring C 4.63 (0.03) a 6.46 (0.58) a 0.48 (0.02) a 0.55 (0.02) a 0.033 (0.002) a 0.96 (0.14) a 16.48 (1.18) a LN 4.64 (0.02) a 5.49 (0.42) a 0.41 (0.05) a 0.56 (0.02) a 0.035 (0.001) a 0.86 (0.03) a 15.77 (0.83) b MN 4.39 (0.02) b 5.58 (0.90) a 0.41 (0.06) a 0.55 (0.02) a 0.035 (0.002) a 0.82 (0.13) a 15.73 (5.70) b HN 4.20 (0.03) b 7.07 (0.46) a 0.57 (0.11) a 0.56 (0.02) a 0.036 (0.002) a 0.90 (0.03) a 15.80 (1.23) c Summer C 5.37 (0.04) a 14.11 (0.074) a 0.51 (0.07) a 0.72 (0.04) a 0.041 (0.001) a 1.27 (0.46) a 15.83 (1.19) a LN 5.07 (0.04) b 13.58 (0.57) a 0.42 (0.04) a 1.03 (0.33) a 0.046 (0.003) a 0.94 (0.09) a 16.61 (1.30) a MN 4.88 (0.05) c 13.91 (0.63) a 0.52 (0.07) a 0.99 (0.20) a 0.046 (0.003) a 1.29 (0.01) a 21.29 (0.58) b HN 5.06 (0.03) bd 13.58 (0.35) a 0.45 (0.01) a 0.93 (0.10) a 0.046 (0.002) a 0.81 (0.07) a 26.55 (1.92) a Autumn C 4.04 (0.03) b 12.37 (0.44) a 0.42 (0.02) a 0.43 (0.02) a 0.032 (0.000) ab 0.93 (0.11) a 13.06 (1.20) a LN 4.21 (0.01) a 12.37 (0.46) a 0.38 (0.10) a 0.41 (0.02) a 0.031 (0.001) b 1.11 (0.34) a 11.64 (1.84) a MN 3.98 (0.05) b 12.50 (0.46) a 0.38 (0.05) a 0.39 (0.02) a 0.033 (0.001) a 0.79 (0.03) a 12.12 (3.36) a HN 4.05 (0.04) b 12.57 (0.44) a 0.49 (0.03) a 0.36 (0.02) a 0.031 (0.000) b 1.05 (0.12) a 13.69 (1.44) a Notes: HN, high level of N; LN, low level of N; MN, medium level of N. The treatments C, LN, MN, and HN represent no N 2 1 2 1 2 1 addition, 2.5 g N m yr N addition, 5 g N m yr N addition, and 7.5 g N m yr N addition, respectively. T5cmrepre- sents soil temperature at 5 cm soil depth; VWC5cmrepresents soil volume water content at 5 cm soil depth; DOC represents soil dissolved organic carbon; DTN represents soil dissolved total nitrogen; TN represents soil total nitrogen; C:N represents the ratio of soil dissolved carbon to soil dissolved nitrogen. The values in brackets represent standard deviation (N = 3). Lower- case letters for a given variable indicate significant difference (P < 0.05) among different N addition treatments in same season based on one-way ANOVA, followed by Tukey’s HSD test. significant differences were observed among the Responses of soil microbial diversity and richness treatments for soil pH, except LN treatments. to N addition and seasonal changes Nevertheless, responses of the C:N ratios to the Nadditionhadasignificantly different impact N addition treatments were only significantly on microbial (bacteria and fungi) richness and different in spring, and soil C:N ratios signifi- diversity in different seasons (Fig. 1). For bacteria, cantly decreased with the increase in N addition. in spring, the Shannon index and the Chao index In contrast to N addition treatments, seasonal in the LN and MN treatments significantly changes had significantly affected most of the increased compared with the control, while those fi measured soil properties, such as pH, T5cm, DOC, signi cantly decreased in the HN treatment DTN, and C:N ratios (Tables 1, 2). The changes in (P < 0.05). The Shannon index and the Chao1 soil properties caused by seasonal changes had index were found to be significantly decreased consistent patterns, and their values were highest (P < 0.05) in the HN treatment compared with in summer compared with the spring and autumn control in autumn. For fungi, the Chao1 index sig- and significantly different among the seasons nificantly increased in the LN and MN treatments (P < 0.05). In addition, statistically significant and significantly decreased (P < 0.05) in the HN interactions between N addition and seasonal treatment compared with the control treatment. fl fi changes in uencing soil pH and T5cmwere found Additionally, the Shannon index signi cantly in our study (Tables 1, 2). increased among N addition treatments in the

Table 2. The effects of nitrogen (N) addition, season, and their interaction on abiotic soil variables.

° 3 3 Parameters pH T5cm( C) VWC5cm(m /m ) DOC (mg/kg) DTN (mg/kg) TN (mg/g) C:N N addition *** 0.110 0.336 0.762 0.177 0.349 ** Season *** *** 0.256 *** *** 0.842 * N addition 9 Season *** ** 0.639 0.802 0.701 0.403 0.325

Notes: DOC, dissolved organic carbon; DTN, dissolved total nitrogen; VWC5cm, volumetric water content. Two-way ANOVA was applied to indicate signiﬁcant difference among variances. P < 0.05; P < 0.01; P < 0.001.

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Fig. 1. Effects of N addition and season on alpha diversities of bacteria and fungi. Chaol index (A) and Shan- non index (B) of bacteria, Chaol index (C) and Shannon index (D) of fungi. spring and significantly increased (P < 0.05) in abundance of the microbial community, while the MN treatment and significantly decreased in their interactions only affected bacterial abun- HN treatment in autumn. Moreover, in summer, dance and fungal diversity (Table 3). the Shannon index significantly increased < (P 0.05) with the increase in N addition. Table 3. Results of mixed model evaluating effects of In addition to N addition treatments, seasonal fi N treatments (N) and season (S) and their interaction changes also signi cantly affected diversity and on alpha diversities of bacteria and fungi. richness of bacteria and fungi (Table 3). The diversity and richness of bacteria and fungi NSN9 S showed a different response to the seasonal Variables FPFPFP changes (Fig. 1). The Chao1 index of bacteria fi Bacteria and fungi signi cantly increased in summer Chaol index 12.89 *** 16.19 *** 3.08 * compared with the spring and autumn, but the Shannon index 7.06 ** 8.03 ** 1.03 0.373 Shannon index of bacteria and fungi had no sig- Fungi nificant difference (P < 0.05) among different Chaol index 15.90 *** 8.78 *** 1.65 0.178 seasons. In general, the N addition and seasonal Shannon index 13.74 *** 18.82 *** 8.06 *** changes significantly affected diversity and P < 0.05; P < 0.01; P < 0.001.

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Effect of N addition on soil microbial community and Ascomycota were the dominant taxa in all the structure in different seasons treatments, and Basidiomycota increased under N The simulated N deposition altered the relative addition in spring and decreased in summer; how- abundance of bacteria and fungi at the phylum ever, the change in trend of Ascomycota was oppo- level as shown in Fig. 2. For fungi, Basidiomycota site to that of Basidiomycota in spring and summer

Fig. 2. The average of relative abundance (%) of fungal taxa (A) and bacterial taxa (B) at the phylum level (n = 3).

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(Fig. 2A). For bacteria, Proteobacteria, Acidobacte- Clostridium-sensu-stricto-13, Clostridiaceae-1, Gem- ria, Actinobacteria, and Chloroflexi were the domi- matimonas, Gemmatimonadaceae, Geobacter, and nant taxa in all the treatments. The Proteobacteria Geobacteraceae primarily changed in summer. increased under the N addition treatments in There was no significant bacterial biomarker that spring and autumn, but decreased in summer, and could be used for autumn. With regard to fungi, the change in trend of Chloroflexi was opposite to the significant change in taxa was primarily that of Proteobacteria among all seasons. found in autumn (Paraphaeosphaeria, Stachybotrys, Effects of different N addition treatments in and hygrophorus) and summer (Xenopolyscytalum, different seasons on soil bacterial and fungal Sarocladium, Cystofilobasidium, Guehomyces, and community were evaluated by principal compo- Xanthophyllomyces). In addition, Cystofilobasidi- nent analysis (PCA). For bacteria, the first princi- aceae, Cystofilobasidiales, and Agricales were also pal component (PC1) accounted for 31.31% and used as biomarkers for the summer. These micro- the second component (PC2) for 18.17% of the bial species changes due to seasonal changes variation in the profiles (Fig. 3A). Under the same could be used as biomarkers for identifying N addition level, the bacterial community struc- different states of soils. ture in summer was significantly different from those of the spring and autumn (P < 0.05). For Relationships between the microbial community fungi, we also analyzed the first and second PCs, structure and soil properties which explained 78.32% and 8.33% of variance in Redundancy analysis showed the relationship fungal community composition, respectively between soil properties and microbial (bacterial (Fig. 3B). The fungal community composition or fungal) community structure (Table 4). Accord- was significantly different between summer and ing to the post hoc permutation test, the soil bac- autumn (P < 0.05). In addition, the N addition terial community composition was significantly treatments also moderately altered the composi- correlated with DOC (R2 = 0.34, P < 0.001), DTN tion of the fungal and bacterial community. In (R2 = 0.39, P < 0.001), TN (R2 = 0.18, P < 0.028), general, seasonal variation, N deposition, and C:N (R2 = 0.32, P = 0.002), and pH (R2 = 0.18, fi = their interaction had signi cant effects on micro- P 0.047), but not T5cmor VWC5cm. The change bial community composition (P < 0.05). in DOC explained 73.29% of the total variability Linear discriminant analysis effect size analyses of the bacterial community composition. The soil were used to identify the statistical significance of fungal community was only marginally corre- 2 = = differentially abundant taxa of bacteria and fungi lated with VWC5cm (R 0.31, P 0.006) and in all of the treatments. The results of the LEfSe explained 29.23% of the total variability of the analyses for N addition and seasonal changes are fungal community composition. The soil property shown in Figs. 4, 5, respectively. The LEfSe results indices explained 31.94% of the variation in the at the genus level showed that Pseudolabrys (for bacterial community and 29.11% of the variation LN), OM27-clade and Elstera (for MN), and Ram- in the fungal community. In general, seasonally libacter (HN) could be used as bacterial biomark- induced variability in microbial community com- ers for the N addition. And Leptodontidium (for position was larger than N treatment-induced control treatments), Cystodendron (for LN), and variability. Wilcoxina (for MN) could be used as fungal biomarkers for the N addition at genus level. DISCUSSION Besides those genera, Thelephoraceae, Thelephorales, Pyronemataceae, Pezlzales,andPezlzomycetes could Changes in soil bacterial community composi- be fungal biomarkers for MN. Our results suggest tion associated with changes in quantity and that these microbial taxa could potentially be used quality of soil organic matter are likely to subse- as biomarkers for detecting different levels of N quently influence soil C storage (Cusack et al. deposition in boreal forest soil. 2011, Zeng et al. 2016), and changes in soil fun- By using the LEfSe analysis to identify bacte- gal community composition associated with rial changes caused by seasonal changes, we changes in decomposers of organic matter and found that Microbacterium and Epilithonimonas symbiosis of plants are likely to affect ecosystem primarily changed in the spring, whereas C and N cycles (Allen et al. 2010, Pardo et al.

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Fig. 3. Principal component analysis of microbial community data by permutation-based analysis of variance

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(Fig. 3. Continued) illustrating signiﬁcant separation of the microbial community in N addition and season treatments. CC1, CC2, and CC3 represent control treatments; CL1, CL2, and CL3 represent low level of N (LN) treatments; CM1, CM2, and CM3 represent medium level of N (MN) treatments; CH1, CH2, and CH3 represent high level of N (HN) treatments; XC1, XC2, and XC3 represent control treatments; XL1, XL2, and XL3 represent LN treatments; XM1, XM2, and XM3 represent MN treatments; XH1, XH2, and XH3 represent HN treatments; QC1, QC2, and QC3 represent control treatments; QL1, QL2, and QL3 represent LN treatments; QM1, QM2, and QM3 represent MN treatments; QH1, QH2, and QH3 represent HN treatments.

2011, Fernandez-Fueyo et al. 2012, Schneider (Freedman et al. 2015, Zeng et al. 2016). Our et al. 2012, Morrison et al. 2016). In addition, the results showed that the HN addition resulted in loss of bacterial and fungal species diversity fol- the decrease in microbial diversity in spring and lowing N enrichment may threaten ecosystem autumn. It is consistent with other previous stud- stability (Tilman et al. 2006). Therefore, in study- ies that showed a decline in microbial diversity ing effects of N deposition on forest ecosystem following HN addition treatments (Burke et al. functions, it is important to take into account 2006, Campbell et al. 2010, Janssens et al. 2010, shifts of soil microbial community composition Ramirez et al. 2010a, b, Freedman et al. 2015, and diversity. The soil microbial community Zeng et al. 2016). This result suggested that the composition should be more copiotrophic in HN addition might have reached or exceeded microcosms with higher soil N concentrations the critical value of soil N for microorganisms. and stronger seasonal fluctuations (Mannisto According to the related references, we summa- et al. 2016). However, the studies of effects of N rized three potential mechanisms that have been addition on soil bacterial and fungal communi- proposed to clarify the HN-induced decline of ties have rarely focused on seasonal changes, microbial diversity: (1) N accumulation caused a neglecting interactions between N deposition decline in biodiversity by the expansion of nitro- and seasonal variation. In this study, we demon- philous species and competitive exclusion of strated that N addition and seasonal changes others (Bobbink et al. 2010); (2) microbial caused fundamental changes in the diversity and responses to N addition were plant species speci- community composition of soil bacteria and fic, and direct changes in plant composition due fungi in a boreal forest. In addition, we found to HN addition may affect microbial diversity by that seasonal changes might mediate effects of N altering the quality of plant-derived C (Sagova- addition on soil microbial communities by affect- Mareckova et al. 2011, Zeng et al. 2016); and (3) ing soil properties. the decrease in microbial diversity may be due to changes in soil properties (i.e., soil water and P Effects of seasonal changes on soil microbial status) caused by the N addition (Geisseler and diversity response to N addition Scow 2014, Zhong et al. 2015, Zeng et al. 2016). Boreal forests are generally N-limited. There- For example, a HN addition can induce soil acid- fore, the soil microorganisms in boreal forests ification, exerting deleterious effects on microbial might be N-limited as well (Tamm 1991, Sistla growth (Vitousek et al. 1997, Wei et al. 2013). In et al. 2012, Koyama et al. 2013, Stark et al. 2014). our study, the soil pH also showed a significant Previous studies have shown that low-level addi- decrease in HN treatments, and decrease in soil tion of N can stimulate soil microbial growth pH usually could significantly reduce the micro- (Zhang et al. 2008, Bai et al. 2010), which is bial diversity with N addition (Feng et al. 2014, consistent with our results in LN and MN treat- Liu et al. 2014, Zhou et al. 2016). In addition, ments in spring and autumn. This suggests that Allen et al. (2010) found that at high levels of N N might be a limiting factor for soil microbial application, plants rejected ectomycorrhizal growth in our study site, and a LN addition fungi, thereby setting the stage for water and P improved soil microbial activity and increased limits to growth, which might result in a microbial diversity. Nevertheless, the HN decrease in fungal diversity. Thus, N has not just addition might inhibit soil microorganisms a direct impact on soil microbes, but also an

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Fig. 4. A linear discriminant analysis effect size method identiﬁes the signiﬁcantly different abundant taxa of

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(Fig. 4. Continued) bacteria (A) and fungi (B) in all of the N treatments. The taxa with significantly different abundance among treatments are represented by colored dots, and from the center outward, they represent the kingdom, phylum, class, order, family, and genus levels. The colored shadows represent trends of the significantly differed taxa. Only taxa meeting an linear discriminant analysis significance threshold of >2 are shown. The treatments C, low level of N (LN), medium level of N (MN), and high level of N (HN) represent no N addition, 2.5 g Nm 2yr 1 N addition, 5gNm 2yr 1 N addition, and 7.5 g Nm 2yr 1 N addition, respectively. All the season treatments were included in this analysis. indirect impact mediated through the plant ecosystem functions they mediate (Allison et al. responses. Although we did not measure plant 2013). Therefore, the mechanisms that affect physiological data, we found that fine root bio- microbial communities can be critical for under- mass significantly decreased in the high levels of standing how ecosystem processes respond to N treatment (Yan et al. 2017); therefore, we also environmental changes (Freedman et al. 2015). think that a HN treatment may change the In our study, N addition and seasonal changes microbial community by indirectly mediating significantly altered soil bacterial and fungal the response of plants. community composition (Fig. 3), consistent with Vorıskova et al. (2014) found that the fungal our hypothesis. Many previous studies also have community experiences significant seasonal demonstrated that shifts in soil bacterial and fun- changes in activity, biomass content, composition, gal community composition might occur as a and relative abundance of different groups, which result of N addition (Clegg et al. 2006, Singh is consistent with our results. However, the effects et al. 2010, Li et al. 2013a, b, Morrison et al. of N addition on soil microbial diversity were 2016). However, in contrast, some studies also weak in summer compared with spring and found that N addition did not alter microbial autumn in our site. It seems that the microbial community composition (Frey et al. 2004, 2008, response to N deposition might be seasonally or Bradford et al. 2008, Contosta et al. 2015). These temporally dependent (Freedman et al. 2015). In different results suggest that effects of N addition addition, many previous studies also suggest that on soil microbial composition could depend on both bacterial and fungal communities exhibit sea- the length of treatments and the type of N addi- sonal community dynamics (Lipson and Schmidt tion (Dong et al. 2014, Contosta et al. 2015). In 2004, Bevivino et al. 2014, Vorıskova et al. 2014, addition, other studies have reported that sea- Matulich et al. 2015). In our results, seasonal varia- sonal variation in microbial community may be tions significantly changed soil moisture, soil tem- driven by shifts in climate and resource availabil- perature, DOC, and DTN, consistent with another ity (Bohlen et al. 2001, Waldrop and Firestone previous report (Zhang et al. 2015). Moreover, we 2006, Vorıskova et al. 2014), which is consistent speculated that soil microbial diversity responses with our results. to N deposition might be modified by seasonal The LEfSe analyses found that microbial taxa changes that altered soil properties (including soil (Pseudolabrys, OM27-clade, Elstera, Ramlibacter, temperature, soil moisture, and soil nutrients; Leptodontidium, Cystodendron, and Wilcoxina) Zhang and Han 2012, Freedman et al. 2015). To might be used as biomarkers of microbial achieve a deeper understanding of the microbial response to N addition (Fig. 4). These results response to future rates of N deposition, we must indicate that different levels of N addition had a gain a greater understanding of the seasonal and significant effect on certain microbial species. temporal robustness of soil microbial response to Ramlibacter belongs to Proteobacteria, and field this pervasive agent of climate change. experiments have shown increased abundance of Proteobacteria in N addition plots (Ramirez et al. Responses of soil microbial community 2010a, b, Koyama et al. 2014), which is consistent composition to N addition and seasonal changes with our results in spring (Fig. 2). Elstera and The changes in soil microbial community com- Pseudolabrys also belong to Proteobacteria. In con- position are often associated with changes in the trast to what we observed in this experiment,

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Fig. 5. A linear discriminant analysis effect size method identifies the significantly different abundant taxa of bacteria (A) and fungi (B) in all of the season changes. The taxa with significantly different abundance among

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(Fig. 5. Continued) treatments are represented by colored dots, and from the center outward, they represent the kingdom, phylum, class, order, family, and genus levels. The colored shadows represent trends of the signiﬁcantly differed taxa. Only taxa meeting an linear discriminant analysis signiﬁcance threshold of >2 are shown. The treatments SP, SM, and AU represent spring season, summer season, and autumn season, respectively. All the treatments of N addition treatments were included in this analysis.

Mannisto et al. (2016) have shown decreased significantly changed. The significant change in abundance of Alphaproteobacteria in N addition bacterial and fungal taxa predicted by the LEfSe plots, which is consistent with our results in analysis was primarily observed in summer, summer and autumn (Fig. 2). These different which may indicate that changes in bacterial and results suggest that the season may modulate the fungal taxa in different seasons correlate with response of Proteobacteria to N addition. More- ecosystem functions and processes. For example, over, we found that the relative abundance of one previous study suggested that the fungal Ascomycota significantly increased in control, LN, biomass increased approximately threefold from and MN treatments, respectively. Increase in its spring to summer, which corresponded to the abundance may be improving the rates of soil C expected increase in photosynthate allocation decomposition in low-level N treatments (LN below the ground (Vorıskova et al. 2014). How- and MN). However, Wang et al. (2015) found ever, N treatments and seasonal changes caused that members of the Ascomycota are particularly a significant increase or decrease in the commu- vulnerable to high nutrient levels and explained nities of specific microbial groups (Dong et al. why there is no change in the HN treatment. The 2014). Our results suggest that these microbial shift in the relative abundance of Ascomycota species could potentially be used as biomarkers may in turn dramatically affect the soil C decom- for detecting different levels of N and for identi- position (Xiong et al. 2014a, b). By using the fying seasonal responses of microorganisms in LEfSe analysis to identify microbial changes boreal forests. caused by seasonal changes (Fig. 5), we found The RDA illustrated that these changes in that specific bacterial taxa (Microbacterium and microbial community composition were corre- Epilithonimonas, spring; Clostridium-sensu-stricto- lated with soil chemical properties (Table 4). Bac- 13, Clostridiaceae-1, Gemmatimonas, Gemmatimon- terial community composition was found to be adaceae, Geobacter, and Geobacteraceae, summer) significantly correlated with DTN and TN. Our and fungal taxa (Paraphaeosphaeria, Stachybotrys, result is consistent with those of Fontaine and and hygrophorus, autumn; Xenopolyscytalum, Saro- Barot (2005) and Fierer et al. (2007), who showed cladium, Cystofilobasidium, Guehomyces, and Xan- that the shift in dominant life-history strategies thophyllomyces, summer) were found to be may be a result of the increase in N availability. Li

Table 4. The redundancy analysis used to explore the relationships between microbial community and selected soil properties for bacteria and fungi.

Bacteria Fungi Variables %Var R2 P Cum% %Var R2 P Cum%

T5cm 4.03 0.07 0.304 4.03 5.07 0.18 0.058 5.07 VWC5cm 4.50 0.14 0.083 8.53 8.51 0.31 ** 13.58 DOC 5.04 0.34 *** 13.57 2.57 0.03 0.613 16.15 DTN 5.72 0.39 *** 19.29 6.59 0.08 0.263 22.74 TN 4.28 0.18 ** 23.57 2.91 0.01 0.924 25.65 C:N 4.70 0.32 ** 28.27 2.07 0.03 0.595 27.72 pH 3.67 0.18 * 31.94 1.39 0.01 0.868 29.11 Notes: DOC, dissolved organic carbon; DTN, dissolved total nitrogen. %Var represents percentage variance in our data explained by that variable; Cum% represents the sum percentage of variance explained. P < 0.05; P < 0.01; P < 0.001.

❖ www.esajournals.org 14 July 2017 ❖ Volume 8(7) ❖ Article e01879 YAN ET AL. et al. (2014) also reported that soil TN had a great China (2016YFA0600800), National Natural Science impact on the microbial community structure. Foundation of China (41575137, 31370494, 31170421, The DOC and pH were also related to bacterial 31070406), and the Key Projects of Heilongjiang Pro- distribution in our study. Few studies focused on vince Natural Science Foundation (ZD201406). G. Yan the relationship between DOC and bacterial com- and Y. Xing contributed equally to this work. munity composition, but Sul et al. (2013) reported LITERATURE CITED that SOC (soil organic carbon) was the most important factor explaining the differences in soil bacterial community structure. Moreover, soil pH Allen, M. F., E. B. Allen, J. L. Lansing, K. S. Pregitzer, R. L. Hendrick, R. W. Ruess, and S. L. Collins. is a major factor influencing the structure of the 2010. Responses to chronic N fertilization of ecto- soil microbial community (Nilsson et al. 2007, mycorrhizal pinon but not arbuscular mycorrhizal Lauber et al. 2009, Feng et al. 2014, Liu et al. juniper in a pinon-juniper woodland. Journal of 2014, Zhong et al. 2015). Soil pH has been shown Arid Environments 74:1170–1176. to decrease with N addition (Zhong et al. 2015), Allison, S. D., Y. Lu, C. Weihe, M. L. Goulden, A. C. which is consistent with our results. And Martiny, K. K. Treseder, and J. B. Martiny. 2013. decreased pH caused a shift in the soil microbial Microbial abundance and composition influence community (Feng et al. 2014, Liu et al. 2014). In litter decomposition response to environmental – addition, the results of the RDA also implied that change. Ecology 94:714 725. fungi are more resistant to environmental changes Amato, K. R., C. J. Yeoman, A. Kent, N. Righini, than bacteria (Hawkes et al. 2011, Jin et al. 2011), F. Carbonero, A. Estrad, H. R. Gaskins, R. M. Stumpf, S. Yildirim, and M. Torralba. 2013. Habitat and fungal community composition only corre- degradation impacts black howler monkey (Alo- lated with VWC5cmin our study. Previous stud- uatta pigra) gastrointestinal microbiomes. ISME ies show evidence that the soil microbial Journal 7:1344–1353. fi community is signi cantly correlated with soil Aponte, C., L. V. Garcıa, T. Maranon, and M. Gardes. moisture (Bi et al. 2012, Zhang et al. 2013). 2010. Indirect host effect on ectomycorrhizal fungi: Leaf fall and litter quality explain changes in fun- CONCLUSION gal communities on the roots of co-occurring Mediterranean oaks. Soil Biology and Biochemistry – After a four-year experiment in a boreal forest, 42:788 796. N addition resulted in significant changes in soil Bai, Y. F., J. G. Wu, C. M. Clark, S. Naeem, Q. M. Pan, bacterial and fungal community composition and J. H. Huang, L. X. Zhang, and X. G. Han. 2010. Tradeoffs and thresholds in the effects of nitrogen these changes exhibited significant differences in addition on biodiversity and ecosystem function- spring, summer, and autumn, respectively, in a fi ing: evidence from inner Mongolia Grasslands. boreal forest. Moreover, some of speci cmicrobial Global Change Biology 16:358–372. taxa could be used as biomarkers for microbial Bardgett, R. D., C. Freeman, and N. J. Ostle. 2008. responses to the N addition and seasonal changes. Microbial contributions to climate change through The VWC5cm, DOC, DTN, TN, and pH contents carbon cycle feedbacks. International Society for were obviously correlated with the soil microbial Microbial Ecology Journal 2:805–814. community composition. It indicated that they Bevivino, A., et al. 2014. Soil bacterial community were the key variables for maintaining the soil response to differences in agricultural management microbial community. In addition, we found that along with seasonal changes in a Mediterranean seasonal changes might change the effects of N region. PLoS ONE 9:e105515. Bi, J., N. L. Zhang, Y. Liang, L. Cai, and K. P. Ma. 2012. addition on soil microbial communities by affect- Impacts of increased N use and precipitation on ing soil properties. Taken together, the responses fi microbial C utilization potential in the semiarid of microbial responses to N addition are signi - grassland of Inner Mongolia. Chinese Journal of cantly different in different seasons. Eco-Agriculture 20:1586–1593. Bleeker, A., W. Hicks, F. Dentener, J. Galloway, and ACKNOWLEDGMENTS J. Erisman. 2011. N deposition as a threat to the World’s protected areas under the Convention on This research was supported by grants from the Biological Diversity. Environmental Pollution 159: National Key Research and Development Program of 2280–2288.

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