Microbial Community Assembly and Metabolic Function During Wheat Straw Decomposition Under Different Nitrogen Fertilization Treatments

Biology and Fertility of Soils https://doi.org/10.1007/s00374-020-01438-z

ORIGINAL PAPER

Microbial community assembly and metabolic function during wheat straw decomposition under different nitrogen fertilization treatments

Yangquanwei Zhong1 & Jin Liu2 & Xiaoyu Jia2 & Zhouping Shangguan2 & Ruiwu Wang1 & Weiming Yan2,3

Received: 8 July 2019 /Revised: 22 January 2020 /Accepted: 27 January 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020

Abstract In-depth microbial community characterization, a community-level metabolic function analysis, and biogeochemical assess- ments of residues were performed to understand the principles governing microbial community assembly in wheat straw during decomposition with different N fertilization rates in soil. We identified a suite of decomposition-associated bacterial and fungal groups in straw that contribute to C and N cycling. The decomposition-associated microbial community in straw is likely mainly derived from the original straw, and the bacterial and fungal communities showed different patterns along with the decomposition. Overall, the microbial community composition and function were not substantially affected by the N fertilization rate, but N fertilization significantly increased the straw microbial assembly speed and had significant effects on the abundances of certain taxa and C- and N-related genes, leading to different decomposition rates of straw under different N fertilization rates. Furthermore, the straw quality, especially dissolved organic C (DOC) and lignin, accounted for most observed effects on microbial community development and decomposition. The results provide new insight into the roles of the microbial community in straw during crop residue decomposition for nutrient cycling in farmland ecosystems.

Keywords Microbial community . Metabolic function . Nitrogen fertilization . Crop residue . Decomposition

Introduction been lost to the atmosphere due to intensive agricultural production (Lal 2004). The enhancement of C sequestration by agricul- Soil represents the largest sink of terrestrial C, i.e., 2500 Gt at a tural soils has significant implications for the reduction of atmo- depth of 1 m, and approximately 25% of agricultural soil C has spheric CO2 and alleviation of soil degradation (Banerjee et al. 2016). In addition, approximately 3.8 billion tons of crop residues are produced annually worldwide (Lal 2005),andsuchcrop Electronic supplementary material The online version of this article residues could be returned to the soil to replenish the soil nutri- (https://doi.org/10.1007/s00374-020-01438-z) contains supplementary material, which is available to authorized users. ents and are important sources of organic matter for improving the physical, chemical, and biological properties of soil (Kumar * Ruiwu Wang and Goh 2000, 2003). The decomposition of crop residues in soil [email protected] is a complex process involving the mineralization and transfor- * Weiming Yan mation of organic matter induced by microbes (Dilly et al. 2004; [email protected] Marschner et al. 2011;Patersonetal.2008). Given the importance of straw decomposition in soil C sequestration, there has 1 School of Ecology and Environment, Northwestern Polytechnical been continued interest in elucidating the dynamic changes in ’ ’ University, Xi an 710072, People sRepublicofChina microbial communities occurring during residue decomposition 2 State Key Laboratory of Soil Erosion and Dryland Farming on the and the associated regulatory factors. Loess Plateau, Northwest A&F University, When crop residues are returned to the soil, the specific Yangling 712100, Shaanxi, People’sRepublicofChina microbial taxa established on the surface of straw act as de- 3 Institute of Soil and Water Conservation, Chinese Academy of composers (Bastian et al. 2009; Marschner et al. 2011). Sciences, Xinong Rd. 26, Yangling 712100, Shaanxi, People’s Republic of China During the decomposition of crop residues, the changes in Biol Fertil Soils microbial and biochemical activity result in a series of decom- accompanied by a succession of microbial decomposers with position stages associated with microbial succession (Gao various catabolic capabilities involved in the decomposition et al. 2016). Previous studies have provided evidences de- process (Bastian et al. 2009; Guo et al. 2018; Osono 2006). In scribing the structural and functional changes in microbial addition, the primary factors associated with the residue chem- communities during residue decomposition in different ways. istry characteristics affecting the changes in microbial com- These studies focused on the effects of environmental factors munities and metabolic function under different N fertilization (temperature and soil type) (Sun et al. 2013;Zhouetal.2016a, rates have been poorly studied. 2016b), experimental duration (Marschner et al. 2011; Sun To address these issues, we investigated wheat straw de- et al. 2013), straw quality (Marschner et al. 2011;Zhouetal. composition in a field subjected to long-term N application 2016b), or the return of straw (Banerjee et al. 2016;Chenetal. under three N fertilization rates. We examined the dynamic 2017) on the abundance and composition of soil microbial patterns of the straw microbial community composition and communities. However, few studies have concentrated pri- metabolic functions and the chemical characteristics of the marily on evaluating the changes in the abundance and com- straw and its decomposition. Specifically, we aimed to (1) position of both bacterial and fungal communities in straw determine the dynamic process of the establishment of micro- along with its decomposition. Both bacteria and fungi on litter bial communities (both bacterial and fungal) on straw along play key roles in residue decomposition (Pankratov et al. with the decomposition of straw and determine the primary 2011; Štursová et al. 2012; Voriskova and Baldrian 2013); source of the microbes driving straw decomposition, (2) ex- however, a comprehensive understanding of the microbial plore the effect of N fertilization on straw decomposition and community on straw during decomposition is lacking. microbial community composition and function, and (3) un- In the farmland ecosystem, N fertilization is the most com- derstand the factors affecting microbial community establish- mon agricultural practice, and different N fertilization rates ment and functional dynamics. have varied effects on plant nutrients and soil microbial communities (Zhong et al. 2015a). Thus, the effects of N fertilization on crop residue decomposition is variable and depends on Materials and methods the nutrient content in residues and soil, the microbial community composition, etc. (Hobbie et al. 2012;Lietal.2017; Experimental site and climatic conditions Potthoff et al. 2005). Compared to plants grown in rich nutrient soil, soil N deficits can result in a low leaf N concentration, This study was conducted in an experimental field at the lower decomposition rates, and higher C/N ratios (Wang et al. Institute of Soil and Water Conservation, Yangling, Shaanxi 2012). In addition, soil N availability can lead to increased or (34°17′56″ N, 108°04′7″ E) located in the southern boundary decreased microbial diversity and activity (Treseder 2008; of the Loess Plateau. The region experiences a temperate, Zhong et al. 2015a, 2017), which can further influence residue semihumid climate with a mean annual temperature of decomposition. Thus, due to the direct and indirect effects of 13 °C, a mean annual precipitation of 632 mm, and approxi- N application on straw decomposition, a comprehensive study mately 60% of the precipitation occurring between July and considering the straw quality and microbial communities September. The soil type is Lou soil (Eum-Orthic Anthrosol). could enhance our understanding of nutrient cycling, microbial succession, and residue decomposition under N fertilization. In addition, previous studies have reported that the de- Experimental plot design composition process begins before litter enters the soil (Stone 1987) and that the establishment of microbiota on the surface This study adopted a randomized block design involving three of litter from soil is a dynamic process (Voriskova and N fertilization rates, and each treatment included three repli- Baldrian 2013). However, whether the microbes that drive cates. N was applied at the following rates: 0, 180, and 360 kg residue decomposition are derived primarily from the straw Nha−1 (hereafter termed N0, N180, and N360, respectively). before it is buried or are associated with the soil remains Winter wheat (Triticum aestivum L. cv., Changhan No. 58) unclear. was cultivated. Each plot had an area of 2 × 3 m and contained The decomposition of crop residue is governed by both the 20 rows of wheat spaced 15 cm apart, and each plot was sown quantity and quality of the residue (Jensen et al. 2005; with 90 plants. N was applied in the form of urea, while phos- Johnson et al. 2007;Yuetal.2015), climatic conditions (such phate (P) was applied in the form of super P (33 kg P ha−1), as temperature and moisture) (Sun et al. 2013; Zhong et al. and the applications were performed the same across all treat- 2017), and soil properties (Frouz et al. 2015; Zhong et al. ments each year before sowing. No potassium or 2017). Both the residue quality and activity of litter- micronutrients were applied in this study. Furthermore, no associated microorganisms change throughout the decompo- manual irrigation was performed, and weeds were regularly sition process (Dilly et al. 2001). These changes are removed throughout the study. Biol Fertil Soils

Soil and wheat straw sampling and decomposition Kjeldahl method. The concentrations of cellulose, hemicellu- experiment lose, and lignin in the wheat straw were determined using a modified version of the method proposed by Van Soest (Gao During the harvesting stage (June 9, 2017), nine soil samples et al. 2016; Van Soest and Wine 1967). Briefly, the first step of were collected from the 0–20 cm layer along the diagonals of the sequential extraction procedure involved the removal of each plot using a soil drilling sampler (5 cm inner diameter) and the neutral detergent-extractable fraction (NDF) at 100 °C for mixed. All samples were sieved through a 2 mm screen to re- 60 min to obtain the cell wall fractions, which primarily com- move the roots and other debris, and a portion of each soil sample prise hemicellulose, cellulose, and lignin. The second step was collected in a 50-mL centrifuge tube, placed in an icebox, involved acid detergent extraction using 2 M HCl to remove and transferred to the laboratory. The tubes were stored at − hemicellulose, followed by strong acid (H2SO4,72%)extrac- 80 °C until the soil DNA extraction. The remaining soil was used tion to remove cellulose. The non-extractable residue was as- for the measurements of the physicochemical properties. sumed to be primarily composed of lignin and insoluble pro- Mature wheat straw was collected from each plot with ster- teins. All solid fractions obtained after each extraction were ile gloves. The straw samples from each plot were combined oven dried at 80 °C, and the residual organic matter content into a sample and cut into 1-cm debris under aseptic condi- was estimated based on the loss upon ignition at 550 °C for tions. A portion of the sample was collected in a 50 mL cen- 4 h. The results were calculated as percentages of the volatile trifuge tube and stored at − 80 °C until the DNA extraction solids. All soil physicochemical analyses were performed in from the straw surface. The remaining straw sample was used duplicate. for the decomposition experiment and the determination of the physicochemical properties. DNA extraction, Illumina HiSeq 2500 sequencing In the decomposition experiment, 5 g of wheat straw were and data processing placed in separate bags (10 × 10 cm, 100 μm nylon mesh bags) for the detection of soil microbial colonization and de- Microbial DNA was extracted from 1 g straw samples (or composition effects. In each plot, 48 bags were buried in a 5- 0.5 g soil samples) using an E.Z.N.A. Soil DNA kit (Omega to 10 cm soil layer, and 3 plot replicates were used for each N Bio-tek, Norcross, GA, USA) according to the manufacturer’s fertilization treatment. No crops were grown after harvest, and protocol. The DNA preparation and sequencing library weeds were regularly removed. Twelve bags were collected preparation were performed following the opinions from each plot on days 20, 50, 77, and 110, and three repli- described by Scholer et al. (2017) and Vestergaard et al. cates (two bags mixed per replicate) were collected in a cen- (2017). The V3-V4 region of the bacterial 16S rRNA gene trifuge tube, which was placed in an icebox, transferred to the and the ITS1 region of the fungal rRNA gene were PCR laboratory, and stored at − 80 °C until the DNA extraction amplified (95 °C for 2 min, followed by 27 cycles of 95 °C from the straw surface. The other samples, which were also for 30 s, 55 °C for 30 s, and 72 °C for 45 s, with a final mixed with two bags per replicate, were dried in an oven at extension at 72 °C for 10 min) using the primers 341F (5′- 60 °C to a constant weight to calculate the decomposition rate barcode-CCTAYGGGRBGCASCAG-3′) and 806R (5′- and measure the physicochemical properties. GGACTACNNGGGTATCTAAT-3′) (Caporaso et al. 2012) for the 16S rRNA gene and the primers ITS1F (5′-barcode- Measurements of the physicochemical properties CTTGGTCATTTAGAGGAAGTAA-3′)andITS2R(5′- of wheat straw GCTGCGTTCTTCATCGATGC-3′) (Gardes and Bruns 1993) for the ITS1 region, including an eight-base barcode The organic C content of straw was determined using the sequence unique to each sample. The PCR amplification standard potassium dichromate oxidation-outer heating meth- was performed in triplicate in 20-μL mixtures, and each mix- od (Nelson and Sommers 1982). Briefly, 0.1~0.2 g of straw ture contained 4 μL of 5× FastPfu Buffer, 2 μLof2.5mM were added to test tubes with 0.1~0.3 g silica sand and accu- deoxynucleotide triphosphates (dNTPs), 0.8 μLofeachprim- rately mixed with 5 mL of potassium dichromate (1 mol L−1 1/ er (5 μM), 0.4 μL of FastPfu polymerase, and 10 ng of tem-

6K2Cr2O7); then, 5 mL of concentrated H2SO4 was added. plate DNA. The relative abundances of the bacterial and fun- The tube was heated in an oil bath at 170~180 °C for 5 min, gal rRNA gene copies were quantified using a previously cooled to room temperature, and then titrated with 0.2 mol L−1 described method (Fierer et al. 2005). The amplicons were ferrous sulfate. The total N content was assayed using the extracted from 2% agarose gels, purified using an AxyPrep Kjeldahl method (Bremner and Mulvaney 1982). The straw DNA Gel Extraction kit (Axygen Biosciences, Union City, dissolved organic C (DOC) and N (DON) were extracted by CA, USA) according to the manufacturer’s instructions, and shaking 200 mg of litter with 30 mL of deionized water for quantified using a QuantiFluor-ST instrument (Promega, 24 h in the dark at 25 °C and subsequently analyzed with a USA). The purified amplicons were pooled in equimolar con- total C analyzer (Shimadzu, TOC-Vwp, Japan) and the centrations and then paired-end sequenced (2 × 250) on an Biol Fertil Soils

Illumina HiSeq 2500 platform (Illumina Int., San Diego, CA, using the “Shannon” method in the R package Vegan USA) according to standard protocols. (Oksanen et al. 2016). The similarities among the samples in The raw FASTQ files were demultiplexed and quality fil- terms of microbial taxa (bacterial and fungal) and relative tered using QIIME (version 1.17). The operational taxonomic abundance profiles of gene families were determined using units (OTUs) were clustered with a 97% similarity cutoff the unweighted UniFrac distance calculated by the OTUs phy- using UPARSE (version 7.1 http://drive5.com/uparse/), and logenetic relationships using QIIME (Version 1.9.1) and the the chimeric sequences were identified and removed using Bray-Curtis dissimilarity index for the OTUs, and the gene the UCHIME algorithm. The phylogenetic affiliation of each families were calculated using the vegan package in R. Both rRNA gene sequence was determined using the Ribosomal the microbial taxa and the gene family profiles were compared Database Project (RDP) Classifier (http://rdp.cme.msu.edu/) using a principal coordinate analysis (PCoA) based on the against the SILVA (SSU117/119) database for the 16S rRNA dissimilarity distance. A canonical correlation analysis gene and the UNITE database for the ITS1 rRNA region with (CCA) was performed to elucidate the relationships between a confidence threshold of 80% (Wang et al. 2007). On aver- the composition of the bacteria and fungi microbial commu- age, 64,478 high-quality 16S rRNA gene sequences and nities and straw chemical properties. A variance partial analy- 79,127 high-quality ITS region sequences were obtained per sis (VPA) was performed using the vegan package to deter- sample (Supplementary Table S1). The bacterial 16S rRNA mine the contributions of environment factors to the variation gene sequencing data were uploaded to the NCBI SRA data- in the bacterial and fungal community composition. We used a base under accession number PRJNA514198. To assess the linear regression to examine the relationship between the tem- microbial diversity among the samples in a comparable man- poral distance among the samples and similarity (Bray-Curtis ner, a normalized dataset was used for the subsequent analy- distance) in the microbial composition, which can indicate the ses. To normalize the data, a subset of the lowest number of microbial assembly speed (Liang et al. 2015). The Bray-Curtis sequences across all samples was randomly selected from distance data point is the average distance between each sam- each sample using the mothur software package. The ple and the 110-day sample. Shannon diversity index, which is a measure of species diver- To obtain the best discriminant performance of the taxa sity, was calculated using QIIME (Version1.9.1) and visual- across the straw decomposition time in the field, we regressed ized using R (Version 2.15.3). the relative abundances of the bacterial and fungal taxa at the order level against the decomposition time in the field using Microbial function prediction the default parameters of an R-implemented algorithm (R package ‘randomForest’, ntree = 1000, using a default mtry TheFAPROTAX(Loucaetal.2016) and PICRUSt of p/3, where p is the number of taxa in the class) (Breiman (Phylogenetic Investigation of Communities by et al. 2003). The random forest approach is among the most Reconstruction of Unobserved States) (Langille et al. 2013) robust ensemble machine learning methods used for classifi- approaches were used to evaluate the functional potentials of cation and regression. Lists of taxa ranked by random forests the microbial communities by following the prescribed guide- in order of feature importance were determined over 100 iter- lines. FAPROTAX is a prokaryotic environmental function da- ations. The number of marker taxa was determined using 10- tabase that provides annotation of the amplicon of a given spe- fold cross-validation implemented with the ‘rfcv’ function in cies based on the existing literature. In addition, PICRUSt was the R package “randomForest” with five repeats. used to predict the microbial metabolic functions. First, we built an OTU tree based on the genetic information provided in the Greengene database, reconstructed the ancestral states in the Results reference tree, and then predicted the gene function spectrum of tips that lack sequenced genomes by identifying the nearest Straw microbiota abundance and composition varies corresponding ancestral state reconstruction. Subsequently, the over time during decomposition in the field full spectrum of the fungal and bacterial domains from the KEGG Orthology gene function was identified, and the se- Both the bacterial and fungal Shannon indices in soil were quenced microbial composition was “mapped” onto the data- higher than those in wheat straw (Fig. 1). During the decom- base to predict the metabolic functions. position process, the bacterial Shannon index in straw exhibited gradually increasing trends, whereas fungi exhibited no Calculations and statistical analyses such trends during decomposition. After 110 days of decomposition, the bacterial diversity was similar to that in the soil, All statistical analyses were performed using the R software but the fungal diversity index in straw was only half of that in package (version 3.5) (R Core Team 2014). The α-diversity the soil. The PCoA of the unweighted UniFrac distances and measurements were calculated by the functional diversity Bray-Curtis distances of OTUs of all samples showed that the Biol Fertil Soils

decreased in an N fertilization-dependent manner. The N360 treatment resulted in the steepest slope in both bacteria and fungi, while the N0 treatment resulted in a gentle slope, and bacteria exhibited a higher slope than fungi with the same N treatment.

Specific taxon dynamics and biomarkers of straw microbiota during decomposition in the field

As decomposition progressed, the specific taxon dynamics exhibited time-dependent trends (Fig. 4; Supplementary Fig. S1). The initial microbiota abundance and composition in straw significantly differed from that observed in soil and gradually shifted as the decomposition time increased. Regarding bacteria, the class Betaproteobacteria was the dominant taxon during the initial stages, especially in N0 and N180, and then, the abundance decreased with decomposition, and the primary bacterial taxa observed during decomposition was the phylum Bacteroidetes and classes Gammaproteobacteria and Alphaproteobacteria. Dothideomycetes was the dominant fungal taxon on the straw, and its abundance also decreased with decomposition. The class Sordariomycetes and the phyla Glomeromycota and V4 were the primary fungi taxa observed during decomposition, but the abundances of Sordariomycetes and V4 were low before the burial of the straw in soil. To determine the correlation between the bacterial and fungal taxonomic biomarkers and straw decomposition time in the field, we regressed the relative abundances of bacteria and fungi at the order level using a random forest regression. The model (taxon abundance~decomposition days) explained a b Fig. 1 Boxplot of the Shannon indices of the bacterial ( ) and fungal ( ) 91.4% and 76.75% of the microbial variance associated with communities during the decomposition of straw and in soil under different nitrogen fertilization rates decomposition in bacteria and fungi, respectively. To identify the important classes correlated with the decomposition time in the field, we performed 10-fold cross-validation with five decomposition time, not the soil N content, was the primary repeats to evaluate the importance of the microbial class. The factor influencing the composition of both the bacterial and minimum number of orders against the cross-validation error fungal communities (Fig. 2). The microbes associated with the curve stabilized when 18 orders of bacteria and 26 orders of soil and the initial straw clustered together and those from the fungi were used. Thus, we defined these taxa as biomarker initial straw samples shifted far across the decomposition time taxa in the model as shown in Fig. 5 in order of time- in the field and developmental stages on the first and second discriminatory importance. coordinate axes. The Bray-Curtis distance between the straw microbiota of Changes in the metabolic function of microbiota the samples collected at each time point and those collected on during decomposition day 110 decreased as the decomposition time in the field increased in both bacteria and fungi (Fig. 3). We used a linear Shifts in microbial taxa are associated with large shifts in func- regression to examine the straw microbial colonization speed tional gene abundances as predicted by the 16S rRNA gene data during the decomposition process (Liang et al. 2015), and analysis via PICRUSt (phylogenetic investigation of communi- each data point represents the average distance between the ties by reconstruction of unobserved states) (Fig. 6a). The micro- decomposition days and three replications of day 110. These bial functions of straw significantly differed from those in soil results show that the abundance and composition of both bac- and shifted with the decomposition time, but there were no sig- teria and fungi are linearly related to the decomposition time nificant differences among the N treatments (Fig. 6a). The results and that the slope of the Bray-Curtis distance significantly also identified the Kyoto Encyclopedia of Genes and Genomes Biol Fertil Soils

Fig. 2 Principal coordinate analysis (PCoA) plot of the first two principal components based on the bacterial (a and c) and fungal (b and d)community compositions during decomposition and in soil according to the unweighted UniFrac distance (a and b) and Bray-Curtis distance (c and d)analyses

(KEGG) orthology group “metabolism” (Fig. 6b)asthemajor Major factors influencing straw microbial community functional group, which slightly increased throughout the de- assembly and changes in metabolic function composition process. Furthermore, we analyzed the genes associated with C degradation and N cycling using the FAPROTAX During straw decomposition, the chemical properties of straw package, and the abundances of the genes associated with continually change, and shifts occur in the microbial commu- cellulolysis, chitinolysis, and aromatic compound degradation nity composition and function (Supplementary Table S2 and in the C cycle were significantly altered (Fig. 6c). The abun- Table S3). As expected, weight loss increased as the decom- dances of these genes immediately increased upon the onset of position time increased, and the N application treatments en- straw degradation and exhibited a similar trend under both the hanced weight loss after 110 days of decomposition. The total N0 and N180 treatments. However, under the N360 treatment, C content in straw showed no significant change after decom- significantly increased abundances of cellulolysis-associated position, whereas the total N content in straw was enriched genes were observed on day 20, and increases in chitinolysis- after decomposition. The wheat straw DOC concentration and aromatic compound degradation-associated genes were ob- continually decreased during decomposition, whereas the served on day 50. The abundances of N-related genes, such as DON concentration first decreased and then slightly increased those associated with nitrate reduction and N respiration, also after 77 days. Interestingly, the hemicellulose and cellulose increased significantly on day 20 and then gradually decreased. contents first decreased during the early stage (20 days), However, the abundances of the N fixation-associated genes whereas the proportion of lignin increased after 20 days of continually increased during decomposition (Fig. 6c). These N- decomposition and then decreased. Our CCA results showed related genes exhibited similar trends under the three N that the changes in the chemical properties of wheat straw treatments. could partially account for the changes in the bacterial and Biol Fertil Soils

fungal communities (Fig. 7a, b). The DOC, lignin, N, DON, and hemicellulose levels were closely associated with the abundance and composition of both bacterial and fungal communities (p < 0.05) (Table S4), and the straw DOC and lignin contents made the greatest contributions to the bacteria and fungi community abundance and composition changes based on the VPA analysis of the four most significant factors (Fig. 7c, d).

Discussion

The decomposition of crop residue inputs is the dominant source of organic matter in agricultural ecosystems and involves the activities of microbes (Banerjee et al. 2016;Gao et al. 2016). The results of the present study provide important insight into both straw decomposition and the associated microbial succession. We observed a rapid increase in the bacterial and fungal diversity in straw during the first 20 days, which could be a result of invasion by new colonizers from the soil (Bastian et al. 2009; Voriskova and Baldrian 2013). The soil bacterial and fungal community diversities were not significantly affected by the N treatments, which is inconsis- tent with previous work (Janssens et al. 2010; Treseder 2008) reporting that N application, especially high N application treatment, reduces the soil microbial biomass, soil microbial diversity, and respiration. These results indicated that N appli- Fig. 3 Regression analysis of the decomposition time and bacterial (a) and fungal (b) taxa based on the Bray-Curtis distances between the straw cation has different effects on microbial diversity between surface microbiota at each time point and the last collected samples under straw and soil, which could be due to the short time period three nitrogen fertilization treatments of microbial assembly during decomposition or the C source in straw plays a more important role in microbial communities

N0 N180 N360 100 a 100 bc100 Phylum/Class c__Alphaproteobacteria c__Betaproteobacteria 75 75 75 c__Deltaproteobacteria c__Gammaproteobacteria Low Abundance 50 50 50 p__Acidobacteria p__Actinobacteria p__Bacteroidetes

Bacteria p__Gemmatimonadetes 25 25 25 p__Saccharibacteria

Relativev abundance % 0 0 0 d 100 100 e 100 f

% Phylum/Class c__Dothideomycetes 75 c__Eurotiomycetes 75 75 c__Leotiomycetes c__Sordariomycetes Low Abundance p__Basidiomycota 50 50 50 p__Glomeromycota

Fungi p__unidentified p__Zygomycota p__V4 25 25 25

Relativev abundance 0 0 0 0 20 50 77 110 0 20 50 77 110 0 20 50 77 110

Straw decomposition days Soil Straw decomposition daysSoil Straw decomposition days Soil Fig. 4 Changes in the bacterial and fungal phyla with the top 10 relative straw surface microbiota over the decomposition time. a–c Bacterial abundances (bacteria of the phylum Proteobacteria and fungi of the taxa under the 0, 180, and 360 kg ha−1 N treatments, respectively. d–f phylum Ascomycota phylum are shown at the class level) in soil and Fungal taxa under the 0, 180, and 360 kg ha−1 N treatments, respectively Biol Fertil Soils

Fig. 5 Bacterial (a) and fungal (b) taxonomic biomarkers of wheat descending order of importance to the accuracy of the model. The insert residence time in fields. The top 18 bacterial orders and top 26 fungal panel represents the 10-fold cross-validation error as a function of the orders were identified by applying a random forest regression of their number of input classes used for the regression against the straw decom- relative abundances in the straw surface against the straw position time in the field in order of variable importance decomposition time in the field. Biomarker taxa are ranked in than that in soil. In addition, we observed that the Shannon environmental conditions between soil and straw. The micro- diversity indices of bacteria and fungi exhibited different pat- bial community composition in straw gradually shifted along terns during the decomposition process as the bacterial diver- with decomposition, and the microbial community composi- sity in straw reached levels similar to those observed in soil tion during the early stage (before 50 days) significantly dif- after 110 days of decomposition. In contrast, the fungal diver- fered from that during the late stage (after 70 days) in both sity in straw was only half of the soil fungal diversity (Fig. 1), bacteria and fungi (Fig. 2a, d). These results are consistent which could be due to the invasion of bacteria that usually with those reported by Bastian et al. (2009) as microbial suc- dominate during the initial phases, whereas fungi showed a cession on fresh organic residue is dominated by copiotrophs higher abundance during the later stages of straw decomposi- (r-strategists) during the early stages of decomposition due to tion (Marschner et al. 2011; Paterson et al. 2008). the rich nutrient conditions with oligotrophs (K-strategists) As expected, the microbial community composition and increasing in relative abundance as the substrate quantity function in straw significantly differed from those observed and/or quality declines. These time-dependent trends in mi- in soil, which could be the result of different C sources and crobial colonization were also reported in the decomposition Biol Fertil Soils

a c

Fig. 6 Changes in microbial metabolic function during straw Kyoto Encyclopedia of Genes and Genomes (KEGG) database. c decomposition. a PCoA plot of the first two principal components Significantly altered metabolic functions in the carbon and nitrogen cy- based on the microbial metabolic function during decomposition. b cles at different nitrogen fertilization rates Different functional categories of microbial community based on the of different types of crops residues, including those of maize dynamics during the decomposition process. These results (Sun et al. 2013; Wei et al. 2018) and rice (Chen et al. 2018; may be useful for identifying the most closely related bacterial Guo et al. 2018;Wangetal.2019;Xuetal.2018). Our results and fungal taxa during the wheat straw decomposition pro- show that specific taxa (e.g., Alphaproteobacteria and cess. Real bioindicators in soil need to follow several criteria Gammaproteobacteria) were common and dominant during as reported by Schloter et al. (2018), but whether these marker residue decomposition, which is consistent with the results of taxa chosen by the random forest method in this study could studies investigating other crops (Sun et al. 2013;Zhouetal. be real bioindicators remains worthy of further study. 2016b). However, the observed abundances of other taxa The crop residue quality, particularly the N, lignin and (e.g., Actinobacteria and Bacteroidetes) differed from those polyphenol contents, can alter the decomposition dynamics reported in other studies. For example, Bacteroidetes was a (Finn et al. 2015;Jensenetal.2005; Rivas et al. 2014). In dominant taxon during decomposition in our study but not in our previous study, we observed that N treatments had signif- other studies investigating wheat straw decomposition (Zhou icant effects on the crop nutrient content (Zhong et al. 2015b), et al. 2016b). In the fungi community, the class and the initial physicochemical properties of straw also signif- Dothideomycetes was dominant during the early stage, where- icantly differed among the N treatments (Supplementary as Sordariomycetes and the phyla Glomeromycota and V4 Table S2, S3). Additionally, the composition of the soil mi- were dominant during the later stage, and these fungal taxa crobial communities differed across the different N fertiliza- showed large variations among the N treatments. These tion treatments (Zhong et al. 2015a), which may have consid- changes in fungal community composition differed from those erable effects on straw microbiota. Thus, we hypothesized that observed in other wheat straw decomposition studies (Bastian the N fertilization rates could affect crop residue decomposi- et al. 2009), which may be due to the different environmental tion by influencing the composition and function of straw and soil conditions applied or different fungal marker genes microbial communities. Although the PCoA results showed and databases used (Xue et al. 2019). Due to the strong asso- that the N fertilization rates had a weaker effect on the micro- ciations between the decomposition time and microbial com- bial composition and function in terms of the decomposition munities, we further identified changes in 18 bacterial orders time, N fertilization did affect the abundances of specific mi- and 26 fungal orders as indicators of microbial community crobial taxa during decomposition (Fig. 4), such as the fungal Biol Fertil Soils

Fig. 7 Relationships between environmental factors and straw microbial the Bray-Curtis distance. The arrows in a and b indicate the lengths, and communities. Ordination plots of the results of the CCA used to explore the angles between the explanatory and response variables reflect corre- the relationships among the microbial communities, soil properties, and lations. C indicates straw organic C, N indicates straw total N, DOC meteorological factors of bacteria (a) and fungi (b). Variance partition indicates straw dissolved C, and DON indicates straw dissolved N. The analysis (VPA) showing the relative contributions of the straw chemical r2 and p values of each factor are shown in Supplementary Table S3 properties to the bacteria (c)andfungi(d) community variations based on class Sordariomycetes, the fungal phylum Glomeromycota, Ascomycota, which were shown to be prevalent in live and and the bacterial class Gammaproteobacteria. These results senescent leaves, accounted for more than 88.5% of the fungal indicate that these taxa were highly sensitive to N application. abundance during litter decomposition. In addition, these re- The N fertilization rate is not a key factor driving the shifts in sults indicate that the major taxa observed during decomposi- microbial community composition during decomposition, al- tion may be primarily derived from the original taxa present in though it significantly affected the speed of microbial coloni- the straw rather than the soil, although this possibility requires zation during decomposition (Fig. 3). Upon N application, further investigation using isotope labeling technology. microbes could rapidly colonize straw due to the higher N The straw nutrients, including the levels of DOC, DON, availability and lower ratio of lignin to N (Table S2), which lignin, cellulose, and hemicellulose, significantly changed might lead to a higher colonization speed than that observed during decomposition (Table S2). These changes correlated under the N0 treatment. with the microbial metabolic functions, which exhibited sig- To identify the potential sources of the decomposition- nificant time-dependent dynamic changes (Fig. 6a) and grad- associated straw microbial communities, we compared the ually increased as the decomposition time increased (Fig. 6b). major taxa in straw during decomposition with those present The rapid response of genes associated with C and N cycling in soil. The phyla Proteobacteria, Bacteroidetes,and during the first 20 days indicates that microbiota could rapidly Actinobacteria dominated the initial straw and accounted for adjust metabolic functions to adapt to the habitat. The genes over 90% of the bacterial community on day 110, while the associated with C cycling showed the highest abundance on major fungal taxa Ascomycota and Basidiomycota accounted day 20 and then decreased with decomposition. Biochemical for over 70% of the fungal community after 110 days of de- decomposition is a sequential process that initially involves composition. These results could also indicate that straw de- the loss of less recalcitrant components (e.g., water-soluble composition may occur before burial in soil as Voriskova and constituents and unprotected cellulose, oligosaccharides, Baldrian (2013) reported that members of the phylum hemicellulose, and cellulose), followed by the degradation of Biol Fertil Soils recalcitrant compounds (e.g., lignin or suberin) (Klotzbucher decomposition, and these changes in the chemical composi- et al. 2011; Voriskova and Baldrian 2013; Zhong et al. 2017), tion of plant litter (including straw) regulate the composition all of which are accompanied by changes in litter-associated of the microbial communities involved in litter decomposition microorganisms (Dilly 2001). The relatively higher cellulolyt- (Melillo et al. 1989). The depletion of soluble substances in ic gene abundance caused the rapid decomposition of cellu- straw residues (Table S2) could restrict microbial growth and lose during the first 20 days (Supplementary Table S2), which reduce the decomposition rate of the residues (Rivas et al. is consistent with the observed prevalence of the phylum 2014). In our study, the changes in the straw chemical com- Ascomycota among the detected fungi, and members of these position could explain 55.27 and 29.83% of the observed fungi are generally known to decompose cellulose over lignin changes in the compositions of the bacterial and fungal com- (Schneider et al. 2012). With the decline of easily accessible munities, respectively, based on the CCA analysis (Fig. 7; polysaccharides, such as cellulose and hemicellulose Table S4). In addition, both the labile components (hemicel- (Table S2) (Zhou et al. 2016b), the rate of mass loss along lulose, DOC, and DON) and recalcitrant components (lignin with the abundances of related genes gradually decreased and N) were strongly related to the straw bacterial and fungal (Fig. 6c). Our results revealed consistent changes in microbial communities. These results could be explained by the increas- gene abundance with decomposition, which is consistent with ing lignin-to-carbohydrate ratio due to the loss of hemicellu- the results of many other studies (Marschner et al. 2011; lose decreasing the decomposition rate (Voriskova and Zhong et al. 2018;Zhouetal.2016b). Although N fertilization Baldrian 2013), and DOC and lignin are factors that could has relatively few effects on microbial community functions account for most of the observed microbial community com- overall (based on the KEGG database analysis) (Fig. 6a), it position changes (Fig. 7c, d). influenced the abundances of genes associated with the C and Ncycles(Fig.6c). This result was especially notable under the N360 treatment, which resulted in a higher abundance of genes associated with C degradation and lower abundance Conclusions of genes associated with N fixation. This difference may be a reason for the higher decomposition rate observed under the In this study, we investigated the changes in straw micro- N360 treatment (Supplementary Table S2). Our results pro- bial community assembly and metabolic function during vide insight into the microbial-associated mechanisms driving wheat straw decomposition under different N fertilization wheat straw decomposition under different N treatments. treatments. Our results demonstrate that bacterial and fun- However, the metabolic functions were based on 16S rRNA gal communities exhibit different patterns during decom- gene predictions, which may not fully represent the abun- position; the bacterial diversity in straw during later de- dances of genes in the straw microbial community. Thus, fur- composition stages is almost as high as that observed in ther metagenomic analyses should be performed to more com- soil, whereas fungal diversity is only half that observed in prehensively assess the changes in gene abundance. In addi- soil. Furthermore, the decomposition time, not the N fer- tion, the detection of functional genes does not indicate that tilization rate, had a stronger effect on the changes in the such genes were really expressed; thus, the absolute abun- microbial community composition and function. dances of microbial communities and expression of genes However, the N fertilization treatment promoted a higher should be considered in future studies (Nannipieri et al. 2019). microbial assembly speed and had significant effects on In this study, we primarily focused on investigating the the abundances of specific microbial taxa and C- and N- rapid dynamic stage of straw decomposition, and approxi- related genes, leading to different decomposition rates at mately 50% of the total mass was lost within 110 days. different N fertilization rates. Furthermore, the bacterial These results are consistent with those described by Gao and fungal taxa that dominate the decomposition- et al. (2016), who reported that 54.8% of mass loss could associated community may be derived primarily from occur within a 4-month period with subsequent decomposi- the initial straw rather than soil. In addition, the continual tion occurring very slowly. The trend of mass loss of wheat changes in the straw chemical properties were significant- straw in our study was also similar to that observed in previous ly correlated with the microbial metabolic functions, es- studies investigating crop straw and other plant litters (Gao pecially the DOC and lignin levels. Taken together, our et al. 2016; Melillo et al. 1989;Wuetal.2009). Cellulose results provide insight into the processes of microbial and hemicellulose are labile components in plant litter, where- community establishment and decomposition of straw as lignin, which is a complex polymer of aromatic rings, is a and the microbial mechanism of straw decomposition in stable component that resists degradation (Neher et al. 2003). the field under N fertilization. However, the specific role The release of labile components provides nutrients and ener- of bioindicators and absolute abundances of microbial gy for microbial growth and decomposition of crop residues communities and expression of genes should be consid- as feedback, whereas recalcitrant components exhibit slower ered in future studies for the accurate prediction of the Biol Fertil Soils microbial community composition shift during straw PCR assays. Appl Environ Microbiol 71:4117–4120. https://doi.org/ decomposition. 10.1128/AEM.71.7.4117-4120.2005 Finn D, Page K, Catton K, Strounina E, Kienzle M, Robertson F, Armstrong R, Dalal R (2015) Effect of added nitrogen on plant litter Funding information This study was funded by the National Science decomposition depends on initial soil carbon and nitrogen stoichi- Foundation of China (41701336 and 41807323), the National ometry. Soil Biol Biochem 91:160–168. https://doi.org/10.1016/j. Postdoctoral Program for Innovative Talents (BX201700200 and soilbio.2015.09.001 BX201700198), the NSFC-Yunnan United fund (U1302267), the Frouz J, Spaldonova A, Lhotakova Z, Cajthaml T (2015) Major mecha- National Science Fund for Distinguished Young Scholars (31325005), nisms contributing to the macrofauna-mediated slow down of litter the National Postdoctoral Program of China (2018M631185), and the decomposition. Soil Biol Biochem 91:23–31. https://doi.org/10. Top International University Visiting Program for Outstanding Young 1016/j.soilbio.2015.08.024 scholars of Northwestern Polytechnical University. Gao HJ, Chen X, Wei JL, Zhang YJ, Zhang LG, Chang J, Thompson ML (2016) Decomposition dynamics and changes in chemical composition of wheat straw residue under anaerobic and aerobic conditions. PLoS One 11:e0158172. https://doi.org/10.1371/journal. pone.0158172 Gardes M, Bruns TD (1993) ITS primers with enhanced specificity for basidiomycetes-application to the identification of mycorrhizae and References rusts. Mol Ecol 2:113–118. https://doi.org/10.1111/j.1365-294X. 1993.tb00005.x Banerjee S, Kirkby CA, Schmutter D, Bissett A, Kirkegaard JA, Guo TF, Zhang Q, Ai C, Liang GQ, He P, Zhou W (2018) Nitrogen Richardson AE (2016) Network analysis reveals functional redun- enrichment regulates straw decomposition and its associated micro- dancy and keystone taxa amongst bacterial and fungal communities bial community in a double-rice cropping system. Sci Rep-UK 8: during organic matter decomposition in an arable soil. Soil Biol 1847. https://doi.org/10.1038/s41598-018-20293-5 Biochem 97:188–198. https://doi.org/10.1016/j.soilbio.2016.03.017 Hobbie SE, Eddy WC, Buyarski CR, Adair EC, Ogdahl ML, Weisenhorn Bastian F, Bouziri L, Nicolardot B, Ranjard L (2009) Impact of wheat P (2012) Response of decomposing litter and its microbial commu- straw decomposition on successional patterns of soil microbial com- nity to multiple forms of nitrogen enrichment. Ecol Monogr 82:389– munity structure. Soil Biol Biochem 41:262–275. https://doi.org/10. 405. https://doi.org/10.1890/11-1600.1 1016/j.soilbio.2008.10.024 Janssens IA, Dieleman W, Luyssaert S, Subke JA, Reichstein M, Breiman L, Last M, Rice J (2003) Random forests: finding quasars. Ceulemans R, Ciais P, Dolman AJ, Grace J, Matteucci G, Papale Statistical Challenges in Astronomy. Springer, New York, NY, pp D, Piao SL, Schulze ED, Tang J, Law BE (2010) Reduction of forest 243–254 soil respiration in response to nitrogen deposition. Nat Geosci 3: Bremner J, Mulvaney C (1982) Nitrogen-total methods of soil analysis. 315–322. https://doi.org/10.1038/ngeo844 In: Page AL, Miller RH, Keeney DR (Eds) methods of soils analy- Jensen LS, Salo T, Palmason F, Breland TA, Henriksen TM, Stenberg B, sis. Part 2, chemical and microbiological properties, 2nd edition. Pedersen A, Lundstrom C, Esala M (2005) Influence of biochemical American Society of Agronomy, Madison, pp. 595-624 quality on C and N mineralisation from a broad variety of plant Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer materials in soil. Plant Soil 273:307–326. https://doi.org/10.1007/ N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, s11104-004-8128-y Smith G, Knight R (2012) Ultra-high-throughput microbial commu- Johnson JMF, Barbour NW, Weyers SL (2007) Chemical composition of nity analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6: crop biomass impacts its decomposition. Soil Sci Soc Am J 71:155– 1621–1624. https://doi.org/10.1038/ismej.2012.8 162. https://doi.org/10.2136/sssaj2005.0419 Chen ZM, Wang HY, Liu XW, Zhao XL, Lu DJ, Zhou JM, Li CZ (2017) Klotzbucher T, Kaiser K, Guggenberger G, Gatzek C, Kalbitz K (2011) A Changes in soil microbial community and organic carbon fractions new conceptual model for the fate of lignin in decomposing plant under short-term straw return in a rice-wheat cropping system. Soil litter. Ecology 92:1052–1062. https://doi.org/10.1890/10-1307.1 Tillage Res 165:121–127. https://doi.org/10.1016/j.still.2016.07. Kumar K, Goh KM (2000) Crop residues and management practices: 018 effects on soil quality, soil nitrogen dynamics, crop yield, and nitro- Chen X, Xia Y,Hu Y,Gunina A, Ge T, Zhang Z, Wu J, Su Y (2018) Effect gen recovery. Adv Agron 68:197–319. https://doi.org/10.1016/ of nitrogen fertilization on the fate of rice residue-C in paddy soil S0065-2113(08)60846-9 depending on depth: 13C amino sugar analysis. Biol Fertil Soils 54: Kumar K, Goh KM (2003) Nitrogen release from crop residues and 523–531. https://doi.org/10.1007/s00374-018-1278-5 organic amendments as affected by biochemical composition. Core Team R (2014) R: a language and environment for statistical com- Commun Soil Sci Plan 34:2441–2460. https://doi.org/10.1081/ puting. R Foundation for Statistical Computing, Vienna, p 2014 Css-120024778 Dilly O (2001) Microbial respiratory quotient during basal metabolism Lal R (2004) Soil carbon sequestration impacts on global climate change and after glucose amendment in soils and litter. Soil Biol Biochem and food security. Science 304:1623–1627. https://doi.org/10.1126/ 33:117–127. https://doi.org/10.1016/S0038-0717(00)00123-1 science.1097396 Dilly O, Bartsch S, Rosenbrock P, Buscot F, Munch JC (2001) Shifts in Lal R (2005) World crop residues production and implications of its use physiological capabilities of the microbiota during the decomposi- as a biofuel. Environ Int 31:575–584. https://doi.org/10.1016/j. tion of leaf litter in a black alder (Alnus glutinosa (Gaertn.) L.) forest. envint.2004.09.005 Soil Biol Biochem 33:921–930. https://doi.org/10.1016/S0038- Langille MGI, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes 0717(00)00239-X JA, Clemente JC, Burkepile DE, Thurber VRL, Knight R, Beiko Dilly O, Bloem J, Vos A, Munch JC (2004) Bacterial diversity in agri- RG, Huttenhower BC (2013) Predictive functional profiling of mi- cultural soils during litter decomposition. Appl Environ Microbiol crobial communities using 16S rRNA marker gene sequences. Nat 70:468–474. https://doi.org/10.1128/Aem.70.1.468-474.2004 Biotechnol 31:814–821. https://doi.org/10.1038/nbt.2676 Fierer N, Jackson JA, Vilgalys R, Jackson RB (2005) Assessment of soil Li XG, Jia B, Lv JT, Ma QJ, Kuzyakov Y, Li FM (2017) Nitrogen fertil- microbial community structure by use of taxon-specific quantitative ization decreases the decomposition of soil organic matter and plant Biol Fertil Soils

residues in planted soils. Soil Biol Biochem 112:47–55. https://doi. Stone JK (1987) Initiation and development of latent infections by org/10.1016/j.soilbio.2017.04.018 Rhabdocline-Parkeri on Douglas-fir. Can J Bot 65:2614–2621. Liang YT, Jiang Y, Wang F, Wen C, Deng Y, Xue K, Qin Y, Yang Y, Wu https://doi.org/10.1139/B87-352 L, Zhou J, Sun B (2015) Long-term soil transplant simulating cli- Štursová M, Žifčáková L, Leigh MB, Burgess R, Baldrian P (2012) mate change with latitude significantly alters microbial temporal Cellulose utilization in forest litter and soil: identification of bacte- turnover. ISME J 9:2561–2572. https://doi.org/10.1038/ismej. rial and fungal decomposers. FEMS Microbiol Ecol 80:735–746. 2015.78 https://doi.org/10.1111/j.1574-6941.2012.01343.x Louca S, Parfrey LW, Doebeli M (2016) Decoupling function and taxon- Sun B, Wang XY, Wang F, Jiang YJ, Zhang XX (2013) Assessing the omy in the global ocean microbiome. Science 353:1272–1277. relative effects of geographic location and soil type on microbial https://doi.org/10.1126/science.aaf4507 communities associated with straw decomposition. Appl Environ Marschner P, Umar S, Baumann K (2011) The microbial community Microbiol 79:3327–3335. https://doi.org/10.1128/Aem.00083-13 composition changes rapidly in the early stages of decomposition Treseder KK (2008) Nitrogen additions and microbial biomass: a meta- of wheat residue. Soil Biol Biochem 43:445–451. https://doi.org/10. analysis of ecosystem studies. Ecol Lett 11:1111–1120. https://doi. 1016/j.soilbio.2010.11.015 org/10.1111/j.1461-0248.2008.01230.x Melillo JM, Aber JD, Linkins AE, Ricca A, Fry B, Nadelhoffer KJ (1989) Van Soest PJ, Wine RH (1967) Use of Detergents in Analysis of Fibrous Carbon and nitrogen dynamics along the decay continuum - plant Feeds .4. Determination of Plant Cell-Wall Constituents. J Assoc Off – litter to soil organic-matter. Plant Soil 115:189–198. https://doi.org/ Agric Chem 50:119 128 10.1007/Bf02202587 Vestergaard G, Schulz S, Schöler A, Schloter M (2017) making big data — Nannipieri P, Penton CR, Purahong W, Schloter M, van Elsas JD (2019) smart how to use metagenomics to understand soil quality. Biol – Recommendations for soil microbiome analyses. Biol Fertil Soils Fertil Soils 53:479 484. https://doi.org/10.1007/s00374-017-1191- 55:765–766. https://doi.org/10.1007/s00374-019-01409-z 3 Neher D, Barbercheck M, El-Allaf S, Anas O (2003) Effects of distur- Voriskova J, Baldrian P (2013) Fungal community on decomposing leaf – bance and ecosystem on decomposition. Appl Soil Ecol 23:165– litter undergoes rapid successional changes. ISME J 7:477 486. 179. https://doi.org/10.1016/S0929-1393(03)00043-X https://doi.org/10.1038/ismej.2012.116 Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classi- Nelson D, Sommers LE (1982) Total carbon, organic carbon, and organic fier for rapid assignment of rRNA sequences into the new bacterial matter methods of soil analysis part 2 chemical and microbiological taxonomy. Appl Environ Microbiol 73:5261–5267. https://doi.org/ properties. Soil Science Society of America, Madison, pp 539–579 10.1128/AEM.00062-07 Oksanen J, Blanchet FG, Kindt R, Legendre P, O’Hara RB, Simpson GL, Wang XY, Sun B, Mao JD, Sui YY, Cao XY (2012) Structural conver- Solymos P, Stevens MHH, Wagner H (2016) Vegan: community gence of maize and wheat straw during two-year decomposition ecology package. R package version 2:3–4 under different climate conditions. Environ Sci Technol 46:7159– Osono T (2006) Role of phyllosphere fungi of forest trees in the devel- 7165. https://doi.org/10.1021/es300522x opment of decomposer fungal communities and decomposition pro- Wang DD, Zhu Z, Shahbaz M, Chen L, Liu S, Inbushi K, Wu J, Ge T cesses of leaf litter. Can J Microbiol 52:701–716. https://doi.org/10. (2019) Split N and P addition decreases straw mineralization and the 1139/W06-023 priming effect of a paddy soil: a 100-day incubation experiment. Pankratov TA, Ivanova AO, Dedysh SN, Liesack W (2011) Bacterial Biol Fertil Soils 55:835–835. https://doi.org/10.1007/s00374-019- populations and environmental factors controlling cellulose degra- 01395-2 – dation in an acidic Sphagnum peat. Environ Microbiol 13:1800 Wei HW, Wang LH, Hassan M, Xie B (2018) Succession of the functional 1814 microbial communities and the metabolic functions in maize straw Paterson E, Osler G, Dawson LA, Gebbing T, Sim A, Ord B (2008) composting process. Bioresour Technol 256:333–341. https://doi. Labile and recalcitrant plant fractions are utilised by distinct micro- org/10.1016/j.biortech.2018.02.050 bial communities in soil: independent of the presence of roots and Wu WX, Lu HH, Liu W, Devare M, Thies JE, Chen YX (2009) – mycorrhizal fungi. Soil Biol Biochem 40:1103 1113. https://doi. Decomposition of bacillus thuringiensis (Bt) transgenic rice residues org/10.1016/j.soilbio.2007.12.003 (straw and roots) in paddy fields. J Soils Sediments 9:457–467. Potthoff M, Dyckmans J, Flessa H, Muhs A, Beese F, Joergensen RG https://doi.org/10.1007/s11368-009-0106-9 (2005) Dynamics of maize (Zea mays L.) leaf straw mineralization Xu QC, Dai R, Ruan Y,Rensing C, Liu M, Guo S, Ling N, Shen Q (2018) as affected by the presence of soil and the availability of nitrogen. Probing active microbes involved in Bt-containing rice straw de- – Soil Biol Biochem 37:1259 1266. https://doi.org/10.1016/j.soilbio. composition. Appl Microbiol Biotechnol 102:10273–10284. 2004.11.022 https://doi.org/10.1007/s00253-018-9394-6 Rivas FA, Tabatabai MA, Olk DC, Thompson ML (2014) Kinetics of Xue C, Hao Y, Pu X, Penton CR, Wang Q, Zhao M, Zhang B, Ran W, short-term carbon mineralization in roots of biofuel crops in soils. Huang Q, Shen Q, Tiedje JM (2019) Effect of LSU and ITS genetic Biol Fertil Soils 50:527–535. https://doi.org/10.1007/s00374-013- markers and reference databases on analyses of fungal communities. 0870-y Biol Fertil Soils 55:79–88. https://doi.org/10.1007/s00374-018- Schloter M, Nannipieri P, Sorensen SJ, van Elsas JD (2018) Microbial 1331-4 indicators for soil quality. Biol Fertil Soils 54:1–10. https://doi.org/ Yu Z, Huang Z, Wang M, Liu R, Zheng L, Wan X, Hu Z, Davis MR, Lin 10.1007/s00374-017-1248-3 TC (2015) Nitrogen addition enhances home-field advantage during Schneider T, Keiblinger KM, Schmid E, Sterflinger-gleixner K, litter decomposition in subtropical forest plantations. Soil Biol Ellersdorfer G, Roschitzki B, Richter A, Eberl L, Zechmeister- Biochem 90:188–196. https://doi.org/10.1016/j.soilbio.2015.07.026 Boltenstern S, Riedel K (2012) Who is who in litter decomposition? Zhong YQ, Yan WM, Zhouping SG (2015a) Impact of long-term N Metaproteomics reveals major microbial players and their biogeo- additions upon coupling between soil microbial community struc- chemical functions. ISME J 6:1749–1762. https://doi.org/10.1038/ ture and activity, and nutrient-use efficiencies. Soil Biol Biochem ismej.2012.11 91:151–159. https://doi.org/10.1016/j.soilbio.2015.08.030 Scholer A, Jacquiod S, Vestergaard G, Schulz S, Schloter M (2017) Zhong YQW, Yan WM, Xu XB, Shangguan ZP (2015b) Influence of Analysis of soil microbial communities based on amplicon sequenc- nitrogen fertilization on wheat, and soil carbon, nitrogen and phos- ing of marker genes. Biol Fertil Soils 53:485–489. https://doi.org/ phorus stoichiometry characteristics. Int J Agric Biol 17:1179–1185. 10.1007/s00374-017-1205-1 https://doi.org/10.17957/Ijab/15.0042 Biol Fertil Soils

Zhong YQW, Yan WM, Wang RW, Shangguan ZP (2017) Differential composition associated with straw decomposition. Pedosphere 26: responses of litter decomposition to nutrient addition and soil water 386–398. https://doi.org/10.1016/S1002-0160(15)60051-0 availability with long-term vegetation recovery. Biol Fertil Soils 53: Zhou GX, Zhang J, Zhang C, Feng Y, Chen L, Yu Z, Xin X, Zhao B 939–949. https://doi.org/10.1007/s00374-017-1242-9 (2016b) Effects of changes in straw chemical properties and alkaline Zhong YQW, Yan WM, Wang RW, Wang W, Shangguan ZP (2018) soils on bacterial communities engaged in straw decomposition at Decreased occurrence of carbon cycle functions in microbial com- different temperatures. Sci Rep-UK 6:22186. https://doi.org/10. munities along with long-term secondary succession. Soil Biol 1038/srep22186 Biochem 123:207–217. https://doi.org/10.1016/j.soilbio.2018.05. 017 Publisher’snoteSpringer Nature remains neutral with regard to jurisdic- Zhou GX, Zhang JB, Chen L, Zhang CZ, Yu ZH (2016a) Temperature tional claims in published maps and institutional affiliations. and straw quality regulate the microbial phospholipid fatty acid