Effects of reduced inorganic fertilization and rice straw recovery on soil enzyme activities and bacterial community in double-rice paddy soils

European Journal of Soil Biology 94 (2019) 103116

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European Journal of Soil Biology journal homepage: www.elsevier.com/locate/ejsobi

Effects of reduced inorganic fertilization and rice straw recovery on soil enzyme activities and bacterial community in double-rice paddy soils

T

Jian Zhua,b, Hua Penga,b, Xionghui Jib, Changjun Lib, Shengnan Lib,* a b

Longping Branch of Graduate School of Central South University, 892 Second Yuanda Road, Furong District, Changsha, 410125, China Hunan Institute of Agro-Environment and Ecology, Hunan Academy of Agricultural Sciences, 560 Second Yuanda Road, Furong District, Changsha, 410125, China

A R T I C LE I N FO

A B S T R A C T

Handling editor: Christoph Tebbe

To decrease nutrient losses in paddy soils, use of reduced inorganic fertilization and crop straw return has gained interest in recent years. However, there is limited understanding about the complex responses of soil microbial communities to chemical fertilizers and straw return, especially in the double-rice cropping system. In this study, we report the responses of soil enzyme activities and the bacterial community structure in a double-rice cropping system in southern China after nine years of fertilizer application. Treatments included conventional high inputs of inorganic fertilization, optimum fertilization with reduced inorganic fertilizers (OPT), the combination of inorganic and organic fertilization with rice straw to partially substitute the inorganic fertilizers and keep the inputs of pure N, P, and K the same as OPT (OPT + S), and a no-fertilization control. The soil bacterial communities were examined using Miseq sequencing. The fertilization after nine years significantly increased the soil N, P, K and organic matter contents, but showed little effect on soil pH. The soil enzyme activities were also largely enhanced by fertilization, which were mostly the highest in the OPT + S treatment. The results of Miseq sequencing indicated that the bacterial diversity and community composition were not significantly changed among different fertilization treatments. Nevertheless, they selectively enriched and inhibited the growth of certain bacterial taxa. The OPT + S treatment enriched the highest number of operational taxonomic units (OTUs), most of which were from the phyla Proteobacteria, Acidobacteria, Chlorobi and Bacteroidetes. Correlation analyses suggested that the available potassium, available phosphorus and soil organic matter emerged as the major determinants of the bacterial community composition. Overall, the OPT + S treatment can be more efficient in improving soil nutrient availability without excessive chemical fertilization.

Keywords: Fertilization Rice straw Double-rice paddy soil Bacterial community Miseq sequencing Influential OTUs

1. Introduction Fertilization is an important method of improving soil fertility and crop yields [1]. However, the immoderate increase of inorganic fertilizers does not always translate into a proportional increase in crop yield [2], but instead leads to extra costs and efforts. In China, it has been reported that the synthetic fertilizer application rates are usually far greater than crop demand [3]. For instance, in a winter wheatsummer maize rotation field, the annual application rate of synthetic N (550–600 kg N ha−1) was nearly three times higher than the minimum application rate (about 180 kg N ha−1) needed to achieve maximum grain yields and N uptake [4,5]. Consequently, a large amount of the applied nutrients, especially N and P, were lost to the environment. Over the past few decades, excessive application of inorganic fertilizers with declining nutrient use efficiency in intensive agricultural areas of

China has led to serious environmental problems, including soil acidification, eutrophication of surface waters, and nitrate pollution of groundwater [3,6]. Leaching losses are the primary pathway of N and P losses from paddy fields [7,8], which usually increase with rising application rates. Knowledge-based optimum fertilization reduces fertilizer application rates through the use of the regional mean optimal N application rate in crop systems and in-season N management based on the soil mineral N test in crop systems [9,10]. It is considered an effective management practice to decrease nutrient losses without a decrease in crop yields [3]. Besides, crop straw return is also widely used in agricultural fields for sustainable agriculture, as it increases the inputs of nutrients and organic carbon and has great potential for enhancing soil fertility, the build-up of soil organic matter (SOM), and support of an active microbial community [11,12]. Recent studies have demonstrated that

* Corresponding author. Hunan Institute of Agro-Environment and Ecology, Hunan Academy of Agricultural Sciences, 560 Second Yuanda Road, Furong District, Changsha, 410125, Hunan, China. E-mail address: [email protected] (S. Li).

https://doi.org/10.1016/j.ejsobi.2019.103116 Received 16 May 2019; Received in revised form 6 August 2019; Accepted 6 August 2019 1164-5563/ © 2019 Elsevier Masson SAS. All rights reserved.

European Journal of Soil Biology 94 (2019) 103116

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crop straw return is also effective in reducing N and P leaching losses from intensively managed paddy fields [13,14]. Thus, knowledge-based optimum reduced fertilization and crop straw return are gaining increasing interest to decrease nutrient losses and offset the negative impacts of over-application of synthetic inorganic fertilizers. Soil microorganisms play critical roles in soil functions and productivity through their involvement in nutrients cycling and organic matter turnover [15,16]. Continuous fertilization and crop straw incorporation can contribute to changes in soil conditions, including soil pH, SOM, and nutrient contents, thus, altering the soil microbial community structure which may in turn influence soil N and P losses [17]. Understanding how soil microorganisms respond to synthetic fertilizers and organic matter inputs can be important for the assessment of soil quality and crop nutrient use efficiency [18]. A wide range of studies have addressed how long-term fertilization practices and straw return shift the soil microbiome [12,19,20]. It has been reported that the entire soil microbiome was usually more responsive to inputs of organic fertilizers than chemical fertilizers [20]. Organic fertilizers can facilitate soil microbial diversity and activity, whereas, compared with organic fertilizers, chemical fertilizers were generally less effective [21,22]. Nevertheless, contrasting results were also obtained. A recent study concerning the diazotroph community suggested that regular use of crop residues as well as inorganic fertilizers showed little influence on diazotroph composition, whereas application increasing soil pH by fertilizer plus lime or pig manure reduced the abundance and diversity of diazotrophs [23]. Hence, the type and quantity of fertilizers influence soil microbial communities. In fact, most of the previous studies regarding straw recovery are usually focused on the responses of the total soil microbial biomass and community composition, less is known about their diversity are strongly influenced. In addition, the soil microbiomes also differ among crop species and rotation systems, and their responses to fertilizer practices can vary. The double-rice cropping system is an important rice planting system in China, where low utilization of rice straw and excessive fertilization are common and have induced severe environmental degradation. A long-term experiment was established in April 2007 in the south of China, one of the major rice-producing regions, to investigate the effects of reduced fertilization, rice straw recovery, and their combination on the losses of N and P nutrients. Specifically, we used an advanced practice of rice straw recovery, which further reduced the application rate of chemical fertilizers and substituted with adequate rice straw containing equivalent pure N, P, and K content. The results of prior monitoring had shown significant decrease in nutrient runoff losses without a remarkable rice yield loss [14]. However, the mechanism by which reduced fertilization and straw return affect soil microbial communities in the double-rice cropping system remained unclear. In the present study, combined with 16S rRNA gene-based Miseq high-throughput sequencing, soil samples were analyzed to illustrate the effects of reduced fertilization and partial substitution of synthetic inorganic fertilizers by rice straw on the soil bacterial community in a double-rice cropping system in southern China. Soil bacteria are the most abundant microbial groups and they possess the highest metabolic diversity. The objectives of this study were to: a) verify the influences of different fertilization regimes on soil properties, enzyme activities, and the bacterial diversity and community structure; b) identify the taxa substantially affected by the fertilization regimes; and c) identify the influencing factors best explaining the variations in the bacterial community.

Table 1 The initial soil physiochemical properties. pH

TN (g kg−1)

TP (g kg−1)

TK (g kg−1)

AN (mg kg−1)

AP (mg kg−1)

AK (mg kg−1)

SOM (g kg−1)

5.2

1.99

0.63

8.1

177

23.5

126

30.3

TN: total nitrogen; TP: total phosphorus; TK: total potassium; AN: alkali-hydrolysable nitrogen; AP: available phosphorus; AK: available potassium; SOM: soil organic matter.

region experiences a humid subtropical monsoon climate, with an average annual temperature and precipitation of 17.1 °C and 1500 mm, respectively. The soil is a typical red soil, originally developed from Quaternary red clay, with the characteristics of low pH and poor fertility. The initial soil physiochemical properties are listed in Table 1. The field experiments were arranged as three replicates of four treatments in a randomized block design, where each plot measured 24 m2 (4 m × 6 m) and was separated by a concrete wall reaching 60 cm in to the soil. The treatments comprised CON: conventional fertilization practices of the local farmers with high inputs of inorganic fertilizers; OPT: optimum reduced fertilization using regional mean optimal N application rate and in-season N management based on the soil mineral N test in crop systems; OPT + S: the inputs of inorganic fertilizers were further reduced with adequate rice straw to keep the inputs of pure N, P, and K the same as the OPT treatment; and CK: an unfertilized control. The amount of nutrients applied to the early and late rice in each treatment are listed in Table 2. NH4HCO3 (N 17%) and urea (N 46%) were applied as 70% and 30%, respectively, as the inorganic N fertilizers; superphosphate (P2O5 12%) and potash (K2O 60%) were applied as inorganic P and K fertilizers, respectively. They were used as basal fertilizers and applied one day before transplanting. Urea was used as topdressing and applied 10 days after transplanting. Rice straw was smashed and evenly spread onto the soil surface by hand and immediately tilled into the plowed soil prior to sowing. The N, P, and K characteristics of rice straw were as follows: TN 11.6 g kg−1, P2O5 3.07 g kg−1, K2O 12.8 g kg−1. The field management followed local farmers’ practices. 2.2. Soil sampling and analysis The soil samples were collected in October 2016 after the harvest of late rice. Ten soil cores (1.5 cm diameter, 0–20 cm depth) were randomly collected from each plot and combined to form one composite sample per plot. After visible stones and plant residues were removed, the soil samples were gently broken apart and passed through a sieve (mesh size 8 mm) for the measurement of available nutrients. All Table 2 Fertilization regimes among different treatments. Treatments

CK CON OPT OPT + S

2. Materials and methods

Stage

Early rice Late rice Early rice Late rice Early rice Late rice Early rice Late rice

Inorganic fertilizers (kg/ha) N

P2O5

K2 O

0 0 150 180 105 135 78.9 82.8

0 0 90 90 67.5 36 60.6 22.2

0 0 90 135 90 135 61.2 77.4

Rice straw (kg/ha)

0 0 0 0 0 0 2250 4500

CK: no-fertilization control; CON: conventional high inputs of inorganic fertilization; OPT: optimum reduced fertilization; OPT + S: the inorganic N, P, and K fertilizers were partially substituted with adequate rice straw to keep the inputs of pure N, P, and K the same as the OPT treatment. The rice straw N, P, and K contents were as follows: TN 11.6 g kg−1, P2O5 3.07 g kg−1, K2O 12.8 g kg−1.

2.1. Experimental design A long-term fertilization field experiment was established in 2007 at Changsha County in Hunan Province (28°08′18″ N, 113°12′0″ E), which is an important double cropping rice producing area in China. This 2

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to define OTUs using the cluster_otus algorithm at a sequence identity level of 97% threshold. A total of 1544 OTUs were defined after removing OTUs with just one read. The most abundant read for each OTU was selected as each OTU's representative sequence and taxonomic annotations were assigned to each representative sequence against the Greengenes database. On average, 277,897 qualified sequences were obtained per sample, with an average of 455 bp read lengths.

samples were thoroughly mixed before dividing into two parts: one part was used for soil physiochemical properties analysis, and the other part was sieved through a 2 mm mesh, to increase homogeneity, and then immediately stored at −80 °C for subsequent DNA extraction and molecular analysis. The soils used for physiochemical properties analysis were air-dried to determine soil organic matter (SOM), total nitrogen (TN), total phosphors (TP), total potassium (TK), available phosphorus (AP), and available potassium (AK) and pH. SOM was measured using the potassium dichromate method. TN was determined by Kjeldahl digestion. TP was measured by sodium hydroxide fusion followed by colorimetric analysis. AP was extracted with 0.5 mol L−1 NaHCO3 (pH 8.5) and measured colorimetrically. TK was determined by flame photometry after sodium hydroxide fusion, and the available K was extracted with NH4OAc and determined by flame photometry. Soil pH was determined using a glass electrode in a 1:2.5 soil/water suspension. Fresh soils sieved to < 2 mm were used for enzyme activity analysis. The activities of soil catalase, urease, acid phosphatase, cellulase, and protease were determined as described elsewhere [24]. Briefly, potassium permanganate titration was used to determine soil catalase activity, which was expressed as mL 0.1 mol L−1 KMnO4 (g soil 30 min)−1. Urease was measured colorimetrically using the indophenol blue method and expressed as mg NH4+-N (g soil h)−1. Acid phosphatase was determined through the disodium phenyl phosphate colorimetric method and expressed as mg phenol (100 g soil h)−1. Cellulase and protease activities were measured at 37 °C and expressed as mg (g soil h)−1· and μg tyrosine (g soil h)−1, respectively.

2.5. Statistical analysis Statistical analyses and visualizations were implemented in the R environment (version 3.5.3, http://cran.r-project.org). One-way analysis of variance (ANOVA) was conducted to compare the treatment means of soil physiochemical characteristics and enzyme activities. Diversity indices, including OTU richness and Shannon and Simpson diversity, were estimated after a random resampling to the minimum sample size using the ‘estimate_richness’ function in the ‘phyloseq’ package. The effect size and significance of different fertilization regimes on the bacterial community was quantified using a permutational multivariate analysis of variance (PERMANOVA) performed using the function ‘adonis’ based on the Bray-Curtis distance metrics. Nonmetric multidimensional scaling (NMDS) ordination analyses based on the Bray-Curtis dissimilarities were also conducted using the function ‘metaMDS’. Correlations between soil physiochemical properties and bacterial community composition were calculated using a Mantel test and the subset of environmental variables with significant correlations with the bacterial community dissimilarities was further identified using the function ‘envfit’. All of the above analyses were conducted using the R package ‘vegan’. The R package ‘edgeR’ was used to calculate the differential abundance of OTUs (i.e log2-fold change in the relative abundance of each OTU) for each fertilized treatment as compared to CK. Differential abundance analysis was performed by fitting a generalized linear model with a negative binomial distribution to the normalized value for each OTU [30]. The false discovery rate (FDR) calculations based on the Benjamini-Hochberg method were employed to adjust P-values. We selected an FDR of 5% to denote statistical significances. Enriched OTUs (eOTUs) and depleted OTUs (dOTUs) were defined as OTUs with absolute differential abundance > 1.0 and adjusted P < 0.05. Venn diagrams showing the shared and specific eOTUs/dOTUs in each fertilized treatment were drawn using the ‘VennDiagram’ package. Spearman correlation between the eOTUs/ dOTUs and the soil environmental variables was calculated using the ‘corr.test’ function in the ‘psych’ package.

2.3. DNA extraction, PCR and Miseq sequencing DNA was extracted from soil samples from the triplicate field plots of each treatment using the FastDNA Spin Kit for Soil (MP Biomedicals, Santa Ana, CA, USA) following the manufacturer's instructions. The extracted DNAs were purified using the PowerClean DNA Clean-up Kit (Mobio, CA, USA). DNA quality and quantity were examined using a UV–vis light spectrophotometer (ND-1000, NanoBrop Technologies, Wilmington, DE, USA). The universal prokaryote primers 341F (5′-CCTACGGGAGGCAG CAG-3′) [25] and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) [26] were used to amplify the V3–V4 region of the 16S rRNA gene from the purified soil DNA. PCRs were performed with a final volume of 50 μL containing 250 mM dNTPs, 25 μL rTaq DNA polymerase (Takara Biotech, Co., Ltd., Dalian, China), 1.5 mM MgCl2, 1.0 μM of each primer, and 120 ng template DNA. The amplification conditions included the following steps: 5 min at 95 °C, 35 cycles of 30 s at 95 °C, 30 s at 55 °C, and 45 s at 72 °C, and a final extension at 72 °C for 7 min. The PCR products were purified using a PCR cleanup kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer's instructions. Amplicons were then subjected to paired-end sequencing on the Illumina MiSeq platform at Berry Genomics Co., Ltd (Beijing, China). The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive [27] in BIG Data Center [28], Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under accession number CRA001569 that are publicly accessible at http://bigd.big. ac.cn/gsa.

3. Results 3.1. Soil physiochemical properties The soil physicochemical properties of the treatments are presented in Table 3. The soil pH, TP, and TK showed no significant differences among all treatments (P > 0.05). Interestingly, the OPT + S and CON treatments exhibited similar soil physiochemical properties. The concentrations of TN, AP, and SOM were significantly higher in the treatments of CON compared to those in CK (P < 0.05). However, the soil properties in the OPT treatments, compared to CK, showed no differences (P > 0.05). Higher inorganic nutrients (TN, AP, and AK) and SOM were observed in OPT + S than in OPT.

2.4. Sequence processing and bioinformatic analysis

3.2. Soil enzyme activities

Usearch (Version: v8.1.1756_i86linux32, http://drive5.com/ usearch/) was used for the sequence cleaning and clustering of operational taxonomic units (OTUs). The paired reads from each sample were first merged using fastq_mergepair. All merged reads were then cleaned and filtered against the following quality criteria: (i) a minimum sequence length of 300 bp, (ii) expected number of errors < 3, (iii) no Ns, and (iv) no chimeras (checked with UCHIME) [29]. The qualified reads from different samples were pooled, dereplicated, and clustered

Compared with CK, all the fertilized treatments showed their potential to increase enzyme activities. The activities of the measured enzymes were the highest either in the CON or OPT + S treatments, followed by that in the OPT treatment (Fig. 1). Except cellulase and phosphatase activities, the other measured enzyme activities did not differ significantly between the OPT + S and CON treatments 3

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Table 3 Soil properties after nine years application of different fertilization regimes.

pH TN (g kg−1) TP (g kg−1) TK (g kg−1) AP (mg kg−1) AK (mg kg−1) SOM (g kg−1)

CK

CON

OPT

OPT + S

5.36 ± 0.07 a 2.23 ± 0.13 b 0.69 ± 0.04 a 10.46 ± 0.04 a 11.41 ± 1.29 b 51.39 ± 5.44 b 39.20 ± 2.19 b

5.32 ± 0.14 a 2.41 ± 0.07 a 0.95 ± 0.11 a 10.42 ± 0.07 a 35.22 ± 12.59 a 72.47 ± 16.85 ab 43.86 ± 0.41 a

5.30 ± 0.09 a 2.21 ± 0.12 b 0.88 ± 0.10 a 10.59 ± 0.24 a 25.26 ± 6.09 ab 64.73 ± 2.89 ab 40.50 ± 2.12 b

5.30 ± 0.09 a 2.36 ± 0.11 ab 0.89 ± 0.15 a 10.35 ± 0.26 a 27.88 ± 15.45 a 84.00 ± 27.60 a 42.62 ± 1.09 a

Values represent means ± standard deviations (n = 3). Analysis of variance (ANOVA) was performed. Data within the same row followed by the same letters are not significantly different at P < 0.05. TN: total nitrogen; TP: total phosphorus; TK: total potassium; AP: available phosphorus; AK: available potassium; SOM: soil organic matter.

Chlorobi, Bacteroidetes, Chlamydiae, Cyanobacteria, Planctomycetes, Gemmatimonadetes, and Actinobacteria. Only a small portion of Archaea sequences were also retrieved across the treatments (0.15–1.67%). These were mainly affiliated with Crenarchaeota and Euryarchaeota. 3.4. Bacterial community structure among treatments and their determinants The structure of the bacterial community was very similar at the phylum level with small variations of the relative abundances of some phyla across treatments (Fig. 3a). More distinct patterns emerged at the OTU level. The PERMANOVA analysis indicated that the community composition was significantly affected by the fertilization treatments (R2 = 0.440, P = 0.005). The NMDS profile by Bray-Curtis dissimilarities also illustrated that samples from different treatments were much more separated; nevertheless, the two treatments, OPT and OPT + S, were closer together (Fig. 3b). The Mantel test suggested a significant but low correlation between the soil environmental properties and bacterial community composition (R = 0.3328, P = 0.012). P, SOM, and AK turned out to be the most important variables explaining best the variations of the bacterial community composition according to the results of ‘envfit’ analysis (Fig. 3b). Significant correlations were also found between AP and SOM and the relative abundances of some dominant OTUs, e.g. AP was positively related with OTU1 (Bacillaceae; R = 0.589, P = 0.044), while negatively related to OTU8 (Nitrospiraceae; R = −0.624, P = 0.030); SOM was positively related to OTU18 (Desulfobacteraceae; R = 0.510, P = 0.090) and OTU12 (Syntrophobacteraceae; R = 0.636, P = 0.026).

Fig. 1. Radar chart illustrating the relative responses of enzyme activities to different fertilization treatments. Analysis of variance (ANOVA) was performed. Datapoints on the same perpendicular line followed by the same letters are not significantly different at P < 0.05.

(P > 0.05). The OPT + S treatment significantly enhanced the cellulase activities (P < 0.05), which displayed no apparent differences among the CON, OPT, and CK treatments (P > 0.05). The phosphatase activities were relative to CK significantly increased by 173.3%, 127.3%, and 108.9% in the CON, OPT + S, and OPT treatments, respectively.

3.5. Enriched and depleted OTUs after long-term fertilization 3.3. Diversity and composition of the bacterial community Differential abundances analysis was performed to identify OTUs that were strongly affected by different fertilization regimes. We used the relative abundances of OTUs from the unfertilized soil (CK) as control and an adjusted P-value cutoff of 0.05. ‘Enriched OTUs (eOTUs)’ and ‘depleted OTUs (dOTUs)’ respectively represented OTUs that increased and decreased significantly in relative abundance by more than double in response to long term fertilization. There were 43, 80, and 97 eOTUs, and 60, 61, and 61 dOTUs identified in CON, OPT, and OPT + S, respectively (Fig. 4a). The number of dOTUs was almost the same among all the fertilized treatments, whereas the number of eOTUs varied greatly. The OPT + S treatment enriched the most OTUs, almost half of which (41 OTUs) were uniquely enriched in this treatment (Fig. 4b). Furthermore, the OTUs enriched only in the CON (14 OTUs) or OPT (19 OTUs) treatment were distinctly less than those in the OPT + S treatment. In addition, there were 20 dOTUs and 18 eOTUs shared by all the treatments (Fig. 4b). Most of the phyla contained both enriched and depleted OTUs (Fig. 4c). Nevertheless, the influential OTUs identified in the phyla Deltaproteobacteria, Bacteroidetes, Chlamydiae, and Chlorobi were more

The diversity of the soil bacterial community was assessed using the Miseq high-throughput sequencing of the 16S rRNA gene. After filtering the low-quality reads and removing chimeras and singletons, a total of 3,334,764 qualified reads were retained and grouped into 1544 OTUs. The number of OTUs in each sample averaged 1543 (1541–1544). Over 99.9% (1535) of the OTUs were shared in all the 12 samples. Each sample was re-sampled and normalized to the minimum sample size (192,601 reads) to avoid the effect of different sampling depth. The richness (estimated as the observed OTU numbers) and diversity indices (Shannon and Simpson) showed no significant differences among all treatments (Fig. 2, P > 0.05). The compositions of the bacterial community across treatments were further studied. The bacterial sequences were mainly affiliated with 13 phyla (Fig. 3a). Proteobacteria (33–37%), especially Deltaproteobacteria (16–20%), was the most abundant phylum across all samples. Besides, Nitrospirae, Acidobacteria, Chloroflexi, Firmicutes, and Verrucomicrobia were also dominant in the samples and together accounted for 45–49% of the total sequences. Other bacterial phyla detected in the samples with relative abundances over 1% included 4

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Fig. 2. Diversity of the microbial community among different fertilization regimes. Different letters above each bar indicate significant differences between different fertilization treatments (P < 0.05).

more negatively correlated with TP, AP, AK, and SOM (Fig. 4d).

often enriched than depleted. The 41 OTUs enriched only in the OPT + S were mainly from the phyla Proteobacteria (13 OTUs), Acidobacteria (8 OTUs), Chlorobi (6 OTUs), and Bacteroidetes (4 OTUs) (Supplementary Table 1). In contrast, most of the influential OTUs in the phyla Nitrospirae, Planctomycetes, Verrucomicrobia, and Chloroflexi were depleted (Fig. 4c). Since AP, AK, and SOM were the most important variables driving the variations of the bacterial community composition in the present study, they would show great associations with the specific OTUs influenced by long term fertilization. Thus, the correlation of enriched and depleted OTUs with each environmental parameter was further examined to gain insights into the range of environmental preferences of the strongly affected organisms. Both the enriched and depleted OTUs showed a narrow range of correlation with each environmental factor. Close correlations between the influential OTUs and AP, AK, as well as SOM were observed. Specifically, the enriched OTUs exhibited strong positive correlations with AK, whereas the depleted OTUs were

4. Discussion 4.1. Effects of reduced fertilization and rice straw recovery on soil properties The fertilization treatments after a period of nine years in the present study did not significantly change the bulk soil pH in the doublerice cropping system. However, an acidifying effect of urea and ammonia fertilizers in agricultural fields is well known [6]. The acidity generated by fertilization is mainly a result of nitrification, which produces concomitantly to the formation of nitrite and nitrate protons [31]. However, the rate of nitrification as well as denitrification varies greatly among different cropping systems because of differences in climate, soils, and management practices. It has been reported that denitrification was the primary N loss pathways in the waterlogged rice/upland wheat cropping system in the south of China [3], which

Fig. 3. (a) Relative abundances of the major phyla in each treatment. The relative abundance is expressed as the percentage in the total number of sequences in each treatment. Phyla with relative abundances < 1% are summed as “Others”. (b) Non-metric multidimensional scaling (NMDS) plots based on Bray-Curtis dissimilarities calculated from relative abundances of operational taxonomic units (OTUs). The environmental variables having maximum correlation with the NMDS ordination were projected on the plot. 5

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Fig. 4. Differential abundance analysis exhibiting operational taxonomic units (OTUs) strongly influenced by the fertilized treatments. Enriched and depleted OTUs respectively represented OTUs that significantly increased and decreased, respectively, in relative abundance in the treatments by more than double compared to CK. (a) Heatmap of the enriched and depleted OTUs in the CON, OPT, and OPT + S treatments compared to CK. The numbers of enriched or depleted OTUs in each treatment are also displayed in the graph. (b) Venn diagram showing the numbers of enriched and depleted OTUs unique to and shared among treatments. (c) Numbers of the enriched and depleted OTUs in each phylum. Red indicates phyla with more enriched OTUs, and green represents phyla with more depleted OTUs. (d) Box plots showing the range of Spearman correlations of the enriched and depleted OTUs with each soil environmental parameter. The points of significant correlations were colored red (p < 0.05). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

indicated a high denitrification rate in waterlogged paddy fields. Thus, the high rate of denitrification may largely alleviate the progress of acidification induced by nitrification, and the nine years of fertilization of the present study may be too short a period to exert significant impacts on the soil pH. Consistent with previous results [32,33], the soil N, P, and K and organic matter increased considerably in the fertilized treatments, especially in the CON and OPT + S treatments, compared to the unfertilized treatment. Although the application rates of N, P, and K in the OPT and OPT + S treatments were the same, the SOM, TN, and AK contents after nine years of fertilization were slightly higher in the OPT + S treatment than in the OPT treatment. The results indicates a better fertilizer efficiency with the partial substitution of inorganic fertilizers with returned organic rice straw in the OPT + S treatment compared to that of pure inorganic fertilization in the OPT treatment. Generally, crop straw provides an important source of organic C for soil microorganisms in agro-ecosystems [34], which can significantly increase the soil organic matter contents [35]. It has been widely recommended as an environmentally friendly practice to balance the C loss owing to mineralization and improve soil fertility in agricultural soil [36,37].

4.2. Effects of reduced fertilization and rice straw recovery on enzyme activities Enzymes are important for the cycling of nutrients in soils and most soil enzymes are of microbial origin [38]. It has been reported that mineral fertilizer may decrease the C-, N-, and P-related hydrolytic enzyme activities [39–41]. In contrast, the present study suggests that fertilization can stimulate most of the enzyme activities in the doublerice cropping system. This can be linked to the increase in soil organic carbon and microbial biomass after fertilization [31], since significant increases in microbial biomass C, N, and P were observed in all the fertilized treatments compared to CK in the present study (Supplementary Table 2). Previous studies also illustrated stimulations of enzyme activities after N fertilization as well as straw return [12,42]. Nevertheless, the extent of increment in enzyme activities seemed to be linked with both fertilizer forms and application rates. That the highest enzyme activities were observed in CON, followed by OPT and CK in the present study, suggests a positive correlation between enzyme activities and application rates. However, the enzyme activities were apparently higher in the OPT + S treatment than that in the OPT treatment, even though both treatments shared the same N, P, and K application rates. This phenomenon implied that organic fertilization (in this case, rice straw) was more efficient in stimulating soil enzyme 6

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oxidization and play a key role in the global nitrogen cycle by releasing fixed nitrogen back to the atmosphere as N2 [52,53]. Members of Nitrospirae are known important nitrifying bacteria, which oxidize nitrite to nitrate. Recently, complete ammonia oxidizers were also discovered within the Nitrospira genus that are capable of converting ammonia to nitrate in a single organism (Comammox) [54,55]. Besides, a nitriteoxidizing bacterium was also recognized within the phylum Chloroflexi [56]. The nitrification related microbial groups discussed above are important as they were the leading causes of nitrogen runoff loss in fertilized soils. In contrast, compared to the treatments with only inorganic fertilizers, the OPT + S treatment enriched an apparently higher number of OTUs. Furthermore, several OTUs were only enriched in the OPT + S treatment, most of which were from the phyla Proteobacteria, Acidobacteria, Chlorobi, and Bacteroidetes. Members of Proteobacteria are known as straw or plant residue degrading organisms [57] and have often been considered as copiotrophs with fast growth rates, which are favored in carbon rich environments [58]. Although Acidobacteria are thought to be oligotrophs, some Acidobacteria OTUs were largely enriched by the OPT + S treatment in our study. This was consistent with previous findings that Acidobacteria Gp4 and Gp6 were present in higher abundances in the nutrient-enriched plots than Acidobacteria Gp1 and Gp7 [59]. Bacteroidetes can be adjusted to the gastrointestinal tract, but they are also among the most abundant bacterial groups in the rhizosphere [60]. It has been reported that many Bacteroidetes can degrade complex plant polysaccharides such as starch, cellulose, xylans, and pectin. Besides, some Bacteroides spp. also have a potential to utilize urea as a nitrogen source [61]. Thus, many enriched OTUs in the OPT + S treatment were possibly involved in the decomposition of complex organic matters, and thus, can be beneficial for plant growth by improving nutrient availability. The influential OTUs were closely related with soil AP, AK, as well as SOM. Particularly, the enriched OTUs exhibited positive correlations with AK, which corresponded to the greatly enhanced AK content in the fertilized treatments compared to CK. Furthermore, even in the OPT + S treatment with the highest AK content (84.00 mg kg−1), the AK content was still considerably lower than that of the original value (126.00 mg kg−1) in 2007, which implied AK limiting in the studied paddy soil. Thus, the results indicate the importance of AK in shaping the microbial community. Besides, we also found that all the influential OTUs exhibit a narrow range of positive or negative correlations with the environmental parameters suggesting their preference to specific ecological niches and therefore putatively different physiological capabilities.

activity. This was in agreement with previous results, where compared with organic fertilizers, inorganic fertilizers had a weaker effect on soil enzyme activities [43–45]. In addition, the significant increase in cellulase activity in the OPT + S treatment relative to other treatments can be linked to the input of extra organic matter owing to straw application. The improved cellulase activity can promote the decomposition of cellulose in straw, thus providing C as a nutrient and energy source to the microorganisms [34,35]. 4.3. Effects of reduced fertilization and rice straw recovery on soil bacterial diversity and community composition Deep 16S rRNA gene Miseq sequencing was used to investigate the bacterial community structure in paddy soil. Across all treatments, they were dominated by Proteobacteria, Nitrospirae, Acidobacteria, Chloroflexi, Firmicutes, and Verrucomicrobia, which corresponds at the phylum-level to the results of previous studies in similar red soils [46]. The various fertilization regimes tested in the present study showed negligible effects on all the alpha diversity indices, indicating that bacterial diversity levels were stable under different fertilization regimes. Furthermore, the differences in the bacterial community composition at the phylum level were also minor among all the treatments in the paddy soils. Similar results were reported previously, where statistically significant bacterial community differences were not detectable among treatments with various fertilization regimes [46–48]. On the contrary, several studies have reported significant shifts in soil bacterial diversity and community composition after long-term fertilizer applications [19,47,49]. This can be partially attributed to differences in the experimental systems, management practices, and even the sequencing techniques [50]. Furthermore, a meta-analysis based on 107 datasets from 64 long-term trials worldwide revealed that fertilization application leading to a significant effect on soil microorganisms in agricultural systems was pH dependent [31]. However, when N fertilization decreases the soil pH, soil microbial biomass, their activity and community composition are indeed affected [31]. Consistent with these findings, the soil pH exhibited little variance among all treatments in the present study and relatively stable microbial diversity and community composition was observed, especially when focusing on only the higher taxonomic level. Besides, a recent study also highlighted the importance of seasonal changes on the soil microbial community composition and suggested that the fertilization effect was generally significant in June but not as much in October [20]. The high temperature and precipitation during the summer late rice growing season may cause a substantial shift in the soil microbiome, which may override the effects of fertilization treatments. This can also partially explain the relatively weak effect of fertilization on microbial diversity and community structure in the present study considering the sampling date was in October.

5. Conclusions In summary, the present study indicated a limited effect of fertilization on soil pH and bacterial communities in the double-rice cropping systems, whereas it highlighted the priority of using rice straw recovery in combination with optimum reduced fertilization to decrease nutrient losses in paddy soils. Compared with pure inorganic fertilizers, partial substitution of chemical fertilizers by rice straw was not only more efficient in stimulating soil enzyme activity, but also enriched bacterial taxa which were possibly involved in the decomposition of complex organic matters and thus soil nutrient mobilization. Therefore, the optimum reduced chemical fertilization combined with rice straw recovery can be more efficient in improving soil nutrient availability without excessive chemical fertilization.

4.4. Influential OTUs after long-term fertilization and their determinants Despite that little variance of the community composition were found at the phylum level, more significant differences were observed at the OTU level. Differential abundance analysis was conducted to select OTUs that were responsible for the community differences detected between the fertilized and unfertilized treatments. All the fertilized treatments depleted nearly the same number of OTUs, which encompassed diverse taxonomic groups. Specifically, OTUs in the Nitrospirae, Planctomycetes, Verrucomicrobia, and Chloroflexi phyla were primarily depleted by long term fertilization. The depleted Verrucomicrobia OTUs were all from the order Pedosphaerales, which have been shown to be important members of soil bacterial communities in the tallgrass prairie [51], but little is known about their functioning. Coincidently, members of Nitrospirae, Planctomycetes, and Chloroflexi have all been reported to be involved in the process of nitrogen oxidization. Planctomycetes can initiate anaerobic ammonium

Disclosure statement Declarations of interest: none.

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Acknowledgments [23]

This research was supported by the National Key Research and Development Program of China (2018YFD0800501) and the Young Scientists Fund of the National Natural Science Foundation of China (31800388).

[24]

Appendix A. Supplementary data

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Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ejsobi.2019.103116.

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