硅肥如何提高水稻土中氮磷养分有效性？

How silicon fertilizer improves nitrogen and phosphorus nutrient availability in paddy soil? 硅肥如何提高水稻土中氮磷养分有效性？ 1 2 first-author 1 2 corresp Min LIAO, liaomin@zju.edu.cn Min LIAO, liaomin@zju.edu.cn liaomin@zju.edu.cn https://orcid.org/0000-0001-9078-204X 1 2 1 2 1 3 corresp corresp Min LIAO, liaomin@zju.edu.cn Min LIAO, liaomin@zju.edu.cn Xiaomei XIE, xiexiaomei@zju.edu.cn Xiaomei XIE, xiexiaomei@zju.edu.cn xiexiaomei@zju.edu.cn https://orcid.org/0000-0003-1112-4386 4 College of Environmental and Resource Science, Zhejiang University, Hangzhou310058, China College of Environmental and Resource Science, Zhejiang University, Hangzhou310058, China Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Hangzhou310058, China Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Hangzhou310058, China National Demonstration Center for Experimental Environmental and Resources Education, Zhejiang University, Hangzhou310058, China National Demonstration Center for Experimental Environmental and Resources Education, Zhejiang University, Hangzhou310058, China Institute of Soil & Fertilizer and Resource & Environment, Jiangxi Academy of Agricultural Sciences, Nanchang330200, China Institute of Soil & Fertilizer and Resource & Environment, Jiangxi Academy of Agricultural Sciences, Nanchang330200, China In order to reveal the mechanism of silicon (Si) fertilizer in improving nitrogen (N) and phosphorus (P) nutrient availability in paddy soil, we designed a series of soil culture experiments by combining application of varying Si fertilizer concentrations with fixed N and P fertilizer concentrations. Following the recommendations of fertilizer manufacturers and local farmers, we applied Si in concentrations of 0, 5.2, 10.4, 15.6, and 20.8 μg/kg. At each concentration of added Si, the availability of soil N and P nutrients, soil microbial activity, numbers of ammonia-oxidizing bacteria and P-decomposing bacteria which means that the organic P is decomposed into inorganic nutrients which can be absorbed and utilized by plants, and urease and phosphatase activity first increased, and then decreased, as Si was added to the soil. These indicators reached their highest levels with a Si application rate of 15.6 μg/kg, showing values respectively 19.78%, 105.09%, 8.34%, 73.12%, 130.36%, 28.12%, and 20.15% higher than those of the controls. Appropriate Si application (10.4 to 15.6 µg/kg) could significantly increase the richness of the soil microbial community involved in cycling of N and P nutrients in the soil. When the Si application rate was 15.6 μg/kg, parameters for characterizing microbial abundance such as sequence numbers, operational taxonomic unit (OTU) number, and correlation indices of microbial community richness such as Chao1 index, the adaptive coherence estimator (ACE) index, Shannon index, and Simpson index all reached maximum values, with amounts increased by 14.46%, 10.01%, 23.80%, 30.54%, 0.18%, and 2.64%, respectively, compared with the control group. There is also a good correlation between N and P mineralization and addition of Si fertilizer. The correlation coefficients between the ratio of available P/total P (AP/TP) and the number of ammonia-oxidizing bacteria, AP/TP and acid phosphatase activity (AcPA), AP/TP and the Shannon index, the ratio of available N/total amount of N (AN/TN) and the number of ammoniated bacteria, and AN/TN and AcPA were 0.9290, 0.9508, 0.9202, 0.9140, and 0.9366, respectively. In summary, these results revealed that enhancement of soil microbial community structure diversity and soil microbial activity by appropriate application of Si is the key ecological mechanism by which application of Si fertilizer improves N and P nutrient availability. 目的 2 揭示适量硅养分的添加对促进水稻土中氮（N）和磷（P）养分有效性增加的作用及其生态机制。 创新点 2 发现添加适量的硅养分可有效地提高稻田土壤N和P养分的有效性，其核心生态机制是由于适量硅养分的添加可显著增加稻田土壤的土壤微生物活性、氨化细菌和解磷菌的数量、脲酶和磷酸酶的活性以及与N和P养分循环有关的微生物群落群落，进而促进土壤N和P养分土壤养分矿化。 方法 2 设计了一系列不同硅肥浓度和固定氮磷肥配合施用的土培试验，施硅设置为五个梯度：0、5.2、10.4、15.6和20.8 µg/kg。在25°C培养一个月，分析收获后土壤有效态N和P的含量、土壤微生物活性、氨化细菌和解磷菌的数量、脲酶和磷酸酶的活性以及与土壤微生物群落结构多样性，最后统计分析硅的添加对水稻土N和P养分有效性、土壤微生物活性、氨化细菌和解磷菌的数量、脲酶和磷酸酶的活性以及与土壤微生物群落结构多样性的影响及其相互关系。 结论 2 适量硅养分的添加可显著增加稻田土壤的土壤微生物活性、氨化细菌和解磷菌的数量、脲酶和磷酸酶的活性以及与N和P养分循环有关的微生物群落群落，进而促进N和P养分土壤养分矿化。当硅施用量为15.6µg/kg时，土壤N和P养分的有效性达到最大值，同时土壤微生物活性、氨化细菌和解磷菌的数量、脲酶和磷酸酶的活性以及与N和P养分循环有关的微生物群落群落也均达到最高水平。另外，土壤速效磷比例（有效磷/总磷（AP/TP））与氨化细菌数、AP/TP和酸性磷酸酶活性、AP/TP和Shannon指数、速效氮比例（有效氮/总氮（AN/TN））与氨化细菌数、AN/TN与酸性磷酸酶活性的相关系数分别为0.9290、0.9508、0.9202、0.9140、0.9366。综上所述，适当补充硅养分可提高稻田土壤N和P养分有效性，有助于提高稻田土壤N和P养分的水稻利用效率。 Silicon Paddy soil Nitrogen and phosphorus nutrient availability Microbial community structure nutrient 硅 水稻土 氮磷养分有效性 微生物群落结构 1 Introduction 1 Numerous studies have shown that silicon (Si) has a positive effect on soil nutrient utilization ( Eneji et al., 2008 Eneji et al., 2008 ; Mehrabanjoubani et al., 2015 Mehrabanjoubani et al., 2015 ; Pati et al., 2016 Pati et al., 2016 ; Schaller et al., 2016 Schaller et al., 2016 ). In recent years, many studies have confirmed that the application of Si improves the utilization of soil nutrients by both plants and microbes. For example, Neu et al. (2017) Neu et al. (2017) have shown that Si application at concentrations of 10.4–15.6 μg/kg can effectively increase grain yield and fertilizer utilization rate, while excessive Si application (concentrations higher than 20.8 μg/kg) has adverse effects on plant growth. Schaller et al. (2012) Schaller et al. (2012) have also found that Si application can affect the growth of reeds. Other researchers have pointed out that Si not only improves the efficiency of nitrogen (N)-utilization, but also participates in the process of phosphorus (P)-metabolism in plants ( Saudy and Mubarak, 2015 Saudy and Mubarak, 2015 ; Neu et al., 2017 Neu et al., 2017 ; Liao et al., 2020 Liao et al., 2020 ). With regard to the underlying mechanisms Si-driven mobilization of P from soil minerals, recent research has shown that silicic acid competes with P for binding soil minerals and that increasing Si availability leads to strong mobilization of P from soil minerals ( Schaller et al., 2019 Schaller et al., 2019 ; Hömberg et al., 2020 Hömberg et al., 2020 ). It can be concluded that application of Si plays an important role in improving soil nutrient availability. However, the specific mechanisms underlying the effects of Si in soil-nutrient dynamics are still poorly misunderstood. As the main driving force of nutrient-cycle in the soil‒plant system, soil microorganisms not only drive the transformation and cycling of soil organic matter and inorganic nutrients, but also serve as a nutrient reservoir. As important contributors to the decomposition and synthesis of organic matter (an important source of soil nutrient reserves), soil microorganisms participate in the transformation and cycling of soil nutrients. In terms of metabolism, microorganisms are one of the most active involvements in the decomposition of soil organic matter. Biogeochemical cycling of mineral nutrients is the foundation of soil nutrient cycling (carbon (C), N, P, etc.) ( Zhong et al., 2010 Zhong et al., 2010 ; Chen et al., 2015 Chen et al., 2015 ; Wang et al., 2015 Wang et al., 2015 ). Organic fertilizer is first decomposed, then dissolved, and finally transformed into soil by microorganisms. Some organic compounds are nutrients for microbial activities, while others are absorbed and utilized by plants ( Wang et al., 2015 Wang et al., 2015 ). According to recent research, different types of fertilizers and methods of fertilization can affect soil nutrient status and plant growth, with consequences for floristic abundance (abundance of microbial flora), community structure, and biological functioning of soil microorganisms ( Wei et al., 2013 Wei et al., 2013 ). Conversely, the floristic abundance, community structure, and biological function of soil microorganisms can also affect soil nutrient status and plant growth ( He et al., 2008 He et al., 2008 ; Shen et al., 2010 Shen et al., 2010 ). Previous studies also indicated that application of N and P can affect the dominant microbial community in soil, transforming the microbial community from fungus-dominated to bacteria-dominated ( Waldrop et al., 2004 Waldrop et al., 2004 ; Cusack et al., 2011 Cusack et al., 2011 ). Soil microbial biomass, community structure diversity, and activity of metabolic enzymes are known to be important indicators of soil quality and soil ecosystem health; researchers have found that a combination of P fertilizer and organic fertilizer promotes soil microbial activity and functional diversity, and improves soil microbial community structure, thereby improving biological functioning and productivity of soil ( Chen et al., 2015 Chen et al., 2015 ). P is an important factor in controlling soil microbial biomass and microbial diversity ( He et al., 2008 He et al., 2008 ; Zhong et al., 2010 Zhong et al., 2010 ). Application of N can significantly reduce the ratio of fungi to bacteria in soil microorganisms, increase soil microbial enzyme activity, and enhance decomposition activity in some microorganisms ( Su et al., 2014 Su et al., 2014 ). Other studies have also shown that different fertilizers can affect the activity of soil enzymes; for instance, application of N significantly increases cellulase and phenoloxidase activity in soil ( Waldrop et al., 2004 Waldrop et al., 2004 ; Zhong et al., 2010 Zhong et al., 2010 ; Li et al., 2012 Li et al., 2012 ). As key members of the plant soil ecosystem, soil microorganisms participate in all aspects of plant‒soil interactions, including mineral nutrient cycling, soil-structure optimization, plant pest control, and plant growth and development ( Mendes et al., 2011 Mendes et al., 2011 ; Schnitzer et al., 2011 Schnitzer et al., 2011 ; Schneider et al., 2012 Schneider et al., 2012 ; Meng et al., 2017 Meng et al., 2017 ). It can be seen that different application modes of N fertilizer and P fertilizer affect soil fertility and productivity by affecting microbial community structure and soil enzyme activity in soil ecosystems. However, up to now, few studies have reported changes in soil microbial community structure and soil ecosystem after the combined application of Si fertilizer and N and P fertilizers, as well as the ecological mechanisms underlying the enhanced soil available nutrient content and utilization efficiency of N fertilizer and P fertilizer arising from the application of N fertilizer and P fertilizer in combination with Si fertilizer. Therefore, we hypothesize that the mechanism of Si-driven improvement of soil nutrient availability may be related to microbial action in soil. A series of soil culture experiments were designed to study the effects of application of different levels of Si and a particular concentration of N and P fertilizers on soil microbial activity, soil microbial quantity, soil microbial community structure, and the activity of important metabolic enzymes related to soil N and P metabolisms, and quantify soil available N and P proportions, in order to explore the mechanism of Si improvement of soil nutrient availability and the correlation between Si and microbial activity in paddy soil. 2 Materials and methods 1 2.1 Soil 2 The paddy soils used in this research were sampled from rice fields in Zengjia Village, Sixi Town, Shanggao County, Yichun City, Jiangxi Province, China (E 115°07′04.41″, N 28°16′15.79″). This area belongs to a typical subtropical monsoon climate, with an average annual temperature of 17.6 ℃, an average annual precipitation of 1718.4 mm, and an average frost-free period of 276 d. It includes a rice planting area in the middle and lower reaches of the Yangtze River. Its native materials consist mainly of Quaternary red soil and river and lake sediments. In the field, the study area was divided into 16 plots, each with an area of 16 m 2 (4 m×4 m) and a 0.2-m distance between adjacent plots. A total of 5 kg soil samples were taken from each plot. The random sampling method was used to collect mixed soil samples at depths of 0–20 cm; some of these soil samples were dried naturally to determine their basic physicochemical properties. Other samples were for pre-incubation. The basic physicochemical properties of the soil are shown in Table 1 Table 1 . Properties Value Total nitrogen (g/kg) 3.41 Alkali-hydrolyzable nitrogen (mg/kg) 235.08 Total phosphorus (mg/kg) 662.15 Available phosphorus (mg/kg) 67.51 Available potassium (mg/kg) 192.61 Organic material (g/kg) 47.55 pH 4.97 2.2 Soil treatments and incubation conditions 2 For pre-incubation, we placed the soil samples (equivalent to 150 g dry air weight apiece) into a series of 250 mL beakers, then adjusted the soil samples to equivalent moisture levels according to flooding conditions, simulating flooding in rice planting, and covered each sample with plastic film. To mimic flooded-paddy conditions, we added water to each beaker until the water was 2 cm above the surface of the soil; we then incubated the beakers at 25 ℃ for two weeks. Humidity was kept constant throughout the entire process by adding distilled and sterilized water regularly. After pre-incubation, a total of 75 pre-incubated beakers (5 treatments×3 replicates×5 stages) were prepared to adapt to different nutrient treatments. The N fertilizer was urea, with N content of 46.4% (Shanxi Tianze Coal Chemical Industry Group Co., Ltd., China). As phosphate fertilizer, we used superphosphate produced with P 2 O 5 content of 16.3% (Hunan Yonghe Phosphate Fertilizer Factory Co., Ltd., China). For potassium (K) fertilizer, we used potassium chloride (KCl) with K 2 O content of 60.2% (Sinochem Chemical fertilizer Co., Ltd., China). The Si fertilizer tested in this experiment was a broad-spectrum type, with Si content of 26.4% (Wuhan Tuli Fertilizer Industry Co., Ltd., China). The standard application concentrations of N, P, and K for each beaker were 106.40, 39.18, and 51.05 μg/kg, respectively. Each treatment was repeated three times. In addition, an appropriate amount of Si fertilizer was added as the experimental group. With the non-Si fertilizer group as control, five different concentrations of pure Si were designed and calculated based on the recommendations of fertilizer manufacturers and local farmers and the content of pure Si in fertilizer: control check (CK, without additional Si), S1 (Si, 5.2 μg/kg), S2 (Si, 10.4 μg/kg), S3 (Si, 15.6 μg/kg), and S4 (Si, 20.8 μg/kg). All soils (including the control) were adjusted to replicate the same flooding conditions (water level 2 cm higher than the soil water interface). Next, all beakers were covered with plastic plates with small holes and incubated in the dark at 25 ℃ for 30 d. The water was kept constant by adding distilled water regularly throughout the culture process. After 30 d, soil samples were taken out and analyzed for various parameters. All results were the average values of three repeated determinations, expressed as oven soil weight (105 ℃, 24 h). 2.3 Soil assay 2 The basic physical and chemical properties and N and P contents of soil samples were determined using standard soil agrochemical analysis methods ( Bao, 2011 Bao, 2011 ). Urease content in soil was determined by the indophenol blue colorimetric method and P content was determined by the p -nitrobenzene phosphate method ( Guan, 1986 Guan, 1986 ). The numbers of ammonifying bacteria and phosphatolytic bacteria were determined by the dilution plate counting method ( Li et al., 1996 Li et al., 1996 ). The activity of soil microorganisms was determined by the fluorescein diacetate (FDA) hydrolysis method ( Liu et al., 2009 Liu et al., 2009 ). The community structure of soil microbes was determined with high-throughput sequencing ( Shannon, 1948a Shannon, 1948a , 1948b 1948b ; Simpson, 1949 Simpson, 1949 ; Chao, 1984 Chao, 1984 ; Chao and Yang, 1993 Chao and Yang, 1993 ; Blaxter et al., 2005 Blaxter et al., 2005 ). Total microbion DNA was extracted with a DNA extraction kit (Axygen Company, Hangzhou, China). The quality of DNA extraction was detected by 0.8% agarose gel electrophoresis. DNA was quantified using an ultraviolet (UV) spectrophotometer. Soil bacteria amplified the target fragment with common primers of the v3‒v4 region of the 16S ribosomal RNA (rRNA) gene. The amplification product was detected by 2% agarose gel electrophoresis; the target fragment was cut and recovered using a gel recovery (Axygen). Fluorescence quantitative analysis was performed on the recovered products of polymerase chain reaction (PCR) amplification with fluorescence quantitative instrument. The X-ray fluorescence intensity of the sample was determined and compared with that of the standard sample; samples were mixed in proportion according to the quantitative fluorescence results and the quantities required for sequencing each sample. An TruSeq Nano DNA LT Library Prep kit (Illumina Company, Shanghai, China) was used to prepare the sequence library. The amplification product was first repaired at the end and the self-connecting fragments of the joint were then removed by magnetic bead screening. Following the library system after the addition of the joint, the sequencing library template was enriched and purified. First, an Agilent High Sensitivity DNA kit (Axygen) was used for quality inspection of the library, followed by quantitative analysis of the library using a Quant-iT TM PicoGreen TM dsDNA Assay Kit (Axygen), with a concentration of 2.5 nmol/L. The qualified sequencing libraries were diluted in gradient, mixed in proportion according to the quantities required for sequencing, denatured by NaOH to a single strand, and then sequenced. 2.4 Statistical analyses 2 Microsoft Excel was used for statistical collation of the test data, and IBM SPSS Statistics 20 analysis software was used for analysis of variance (ANOVA) and correlation analysis. The least significant difference (LSD) method was used for comparison and the significant difference level was 5%. 3 Results 1 3.1 Effects of Si on N and P nutrient mineralization in paddy soil 2 The ratio of soil available nutrients to total nutrients is often used to evaluate soil nutrient status. Organic nutrients are transformed into available nutrients for plants to absorb and utilize through the mineralization process. Using the most representative N-P nutrients as examples, Table 2 Table 2 shows the effects of different Si dosages on nutrient mineralization in paddy soil, and that added Si significantly increased the ratio of available nutrients to total nutrients in soil compared with the control group. At a Si application rate of 15.6 μg/kg, the ratios of available N/total amount of N (AN/TN) and available P/total amount of P (AP/TP) in soil reached the maximum values. AN/TN and AP/TP increased by 19.78% and 105.09%, respectively, compared with the control group, indicating that the appropriate Si dosage (about 15.6 μg/kg) could increase the rate of mineralization of soil nutrients, significantly increase the content of mineralized nutrients in paddy soil, reduce the fixation of soil nutrient, and thus increase the content of nutrients that could be absorbed and utilized by rice in paddy soil. Appropriate supply of Si not only affects the Si cycle in soil‒plant ecosystems, but also affects the N and P cycles in these ecosystems, so that Si can be used as a soil conditioner in agricultural soil to improve nutrient utilization rate and nutrient content of paddy soil. Data are expressed as mean±standard deviation (SD), n =6. Different letters in column indicate significant differences between treatments at P < 0.05. AN/TN: available nitrogen/total nitrogen; AP/TP: available phosphorus/total phosphorus; CK: control check; S1: Si, 5.2 μg/kg; S2: Si, 10.4 μg/kg; S3: Si, 15.6 μg/kg; S4: Si, 20.8 μg/kg. Level of Si treatment AN/TN (%) AP/TP (%) CK 9.81±0.14 b 8.25±0.47 d S1 10.33±0.44 b 12.32±1.17 c S2 11.34±0.66 a 14.97±0.58 b S3 11.75±0.40 a 16.92±1.20 a S4 10.95±0.35 b 13.45±3.21 bc 3.2 Influence of Si content on microbial activity in paddy soil 2 About 95% of the energy required in the process of organic matter turnover in the soil environment comes from biodegradation by soil microorganisms. Therefore, soil microbial activity reflects microbial biochemical processes in soil nutrient cycles in a manner, and can be used as an index to evaluate the transformation of organic matter in soil crop ecosystem. Because FDA hydrolase is a good indicator of microbial activity and transformation of organic matter in soil ecosystems, it is considered as a useful biological index of soil health. An increase in FDA hydrolase activity could indicate that soil microorganisms are more active in nutrient transformation. Table 3 Table 3 shows the effects of different Si concentrations on microbial activity in paddy soil; as increasing amounts of Si are added, microbial activity in soil initially increases and then decreases. At a Si dosage of 15.6 μg/kg, activity of FDA hydrolase reached its maximum value (102.53 μg/g), about 7.96% higher than that of the control group. In conclusion, appropriate application (about 15.6 μg/kg) of Si fertilizer can substantially improve soil microbial activity to some extent and enhance recycling and utilization of nutrients in soil ecosystem. The values for FDA hydrolase activity are expressed as mean±standard deviation (SD), n =6. Different letters in column indicate significant differences between treatments at P < 0.05. FDA: fluorescein diacetate; CK: control check; S1: Si, 5.2 μg/kg; S2: Si, 10.4 μg/kg; S3: Si, 15.6 μg/kg; S4: Si, 20.8 μg/kg. Level of Si treatment FDA hydrolase activity (μg/g) Amplitude (%) CK 94.97±0.51 d S1 97.97±1.08 bc 3.16 S2 99.55±1.42 b 4.82 S3 102.53±0.84 a 7.96 S4 96.60±0.60 cd 1.72 3.3 Influence of Si dosage on the numbers of functional microorganisms of N and P nutrient metabolism in paddy soil 2 As the driving force of soil nutrient cycling, the change in soil microbe numbers can sensitively reflect changes in nutrient content of its environment. Phosphate-solubilizing bacteria can dissociate the soluble and insoluble P in soil through their own metabolic activities, and form a P-supply region in the crop rhizosphere, thus promoting the absorption and utilization of P by crop plants. Ammonia-oxidizing bacteria are important players in the decomposition of N-containing organic matter, and they play a decisive role in ammonization. An increase in numbers of these two types of bacteria helps to enhance mineralization of organic nutrients in soil, thus providing greater concentrations of small molecular nutrients for plants to absorb and use. Table 4 Table 4 shows the effects of different Si dosages on the number of functional microorganisms involved in N and P nutrient metabolism in paddy soil, from which we learn that with an increase of added Si, the numbers of P-solubilizing bacteria and ammoniated bacteria in soil initially increase and then decrease. At a dosage of Si of 15.6 μg/kg, the numbers of P-solubilizing bacteria and ammoniated bacteria reached a maximum (8.13×10 2 colony forming units (CFU)/g and 15.00×10 2 CFU/g, respectively), representing an increase of 125.94% and 92.31%, respectively, compared with the control group. In conclusion, appropriate application of Si fertilizer can significantly increase the number of functional microorganisms in soil, especially with respect to P-solubilizing bacteria and ammoniated bacteria. Thus, Si fertilizer can promote the activation of soil nutrients and improve the availability of nutrients available for crop use in soil. The numbers of P-solubilizing bacteria and ammoniated bacteria are expressed as mean±standard deviation (SD), n =6. Different letters in column indicate significant differences between treatments at P < 0.05. CFU: colony forming units; CK: control check; S1: Si, 5.2 μg/kg; S2: Si, 10.4 μg/kg; S3: Si, 15.6 μg/kg; S4: Si, 20.8 μg/kg. 2 Level of Si treatment 2 P-solubilizing bacteria 2 Ammoniated bacteria Number (×10 2 CFU/g) Amplitude (%) Number (×10 2 CFU/g) Amplitude (%) CK 3.60±0.87 c 7.80±1.22 d S1 4.67±0.81 bc 29.61 10.60±2.20 c 35.90 S2 5.87±0.64 b 62.94 12.40±1.11 c 58.97 S3 8.13±0.50 a 125.94 15.00±1.06 a 92.31 S4 5.47±0.95 b 51.83 13.07±1.10 bc 67.51 3.4 Influence of Si dosage on the activity of important N and P nutrient metabolic enzymes in paddy soil 2 Soil enzymes come mainly from soil microorganisms, and their biological activity represents the exuberant degree of potential nutrient components activating metabolism in soil, and to some extent reflects the absorption and utilization of nutrients by crops; they are also important indicators of soil fertility ( Frankenberger and Dick, 1983 Frankenberger and Dick, 1983 ; Nannipieri, 1994 Nannipieri, 1994 ). For example, phosphatase can hydrolyze organic P compounds in the soil into available P, which can be absorbed and utilized by crops. Urease can catalyze the hydrolysis of urea in soil into ammonia, water, and CO 2 , which can be absorbed and utilized by crops. Table 5 Table 5 shows the effects of different amounts of Si on the activity of important N and P nutrient-metabolizing enzymes in soil, showing that with increased Si, acid phosphatase activity (AcPA) and urease activity in soil initially increase and then decrease. At Si dosage of 15.6 μg/kg, AcPA and urease activity reached maximum values of 7.29 mg/g and 1.46 mg/g, respectively, 14.80% and 28.07% higher than those of the control group. These results indicate that appropriate applications (about 15.6 μg/kg) of Si fertilizer can significantly improve the activity of metabolic enzymes related to N and P metabolism in paddy soil, thereby promoting the metabolism of N and P nutrients in soil and improving the ability of soil to supply available nutrients to crops like rice. The data of AcPA and Urease activity are expressed as mean±standard deviation (SD), n =6. Different letters in column indicate significant differences between treatments at P < 0.05. AcPA: acid phosphatase activity; CK: control check; S1: Si, 5.2 μg/kg; S2: Si, 10.4 μg/kg; S3: Si, 15.6 μg/kg; S4: Si, 20.8 μg/kg. 2 Level of Si treatment 2 AcPA 2 Urease activity Activity (mg/g) Amplitude (%) Activity (mg/g) Amplitude (%) CK 6.35±0.32 c 1.14±0.03 d S1 6.67±0.09 bc 5.04 1.24±0.01 bc 8.77 S2 6.90±0.12 b 8.66 1.27±0.02 b 11.40 S3 7.29±0.21 a 14.80 1.46±0.03 a 28.07 S4 6.86±0.26 b 8.03 1.21±0.02 c 6.14 3.5 Effect of Si dosage on microbial abundance in paddy soil 2 An operational taxonomic unit (OTU) usually refers to the merging of sequences from one or more samples according to a certain artificial sequence similarity threshold; those sequences whose similarity is higher than the threshold will be merged into one OTU ( Blaxter et al., 2005 Blaxter et al., 2005 ). At present, most 16S rRNA gene-based bacterial structural diversity studies take 97% sequence similarity as the OTU threshold. OTU numbers can serve as a useful estimate of microbial diversity. An increase in OTU may indicate that the community structure of soil microorganism becomes more abundant. Table 6 Table 6 is a statistical table of sequencing and OTU quantities of soil samples under different applications of Si in paddy soil. From Table 6 Table 6 , it can be seen that within the five gradients set by the experiment, the sequencing quantity and OTU number of soil samples initially increased, and then decreased with the increased Si dosages. At Si dosage of 15.6 μg/kg, the sample sequencing and OTU were 56 720 and 4035, respectively, which represent increases of 14.09% and 9.35% compared with the control group. The above results showed that proper application of Si fertilizer (about 15.6 μg/kg) could significantly improve the species richness of soil microbial community structure. OUT: operational taxonomic unit; CK: control check; S1: Si, 5.2 μg/kg; S2: Si, 10.4 μg/kg; S3: Si, 15.6 μg/kg; S4: Si, 20.8 μg/kg. Level of Si treatment Sample sequencing quantity Number of OTU CK 44 222 3690 S1 45 590 3782 S2 48 455 3870 S3 50 455 4035 S4 43 789 3655 Fig. 1 Fig. 1 shows a Venn diagram analysis of OTUs in soil samples. It is also clear that the number of unique OTUs among groups in soil samples was highest when the dosage of Si was 15.6 μg/kg, indicating that the soil microbial community was richest in diversity when the application amount of Si was 15.6 μg/kg. However, when treated with S4 (i.‍e., Si dosage of 20.8 μg/kg), the number of specific OTUs between groups in the samples decreased significantly, which indicated that the more Si applied, the less beneficial it was to the richness of soil microbial community structure. In conclusion, proper application of Si fertilizer (about 15.6 μg/kg) can effectively improve the richness of microbial community structure in paddy soil. 4 Discussion 1 Many studies have come to the conclusion that proper Si nutrient supply can improve the nutrient utilization efficiency of plants and improve the efficiency of soil nutrient mineralization. Under normal base fertilizer conditions, the addition of Si nutrient below a certain threshold has a positive effect on the growth of plants and utilization of soil nutrients. When the threshold is exceeded, however, the high levels of Si nutrient may lead to a stress response with negative effects on plant growth and utilization of soil nutrients. However, research on the ecological mechanisms underlying Si promotion of plants growth and nutrient utilization is still scarce. In this project, we studied the ecological mechanism by which Si induces microorganisms, and the main driving force of nutrient cycling in the soil-plant ecosystem, to activate and absorb nutrients in soil. Through microbial metabolism, organic matter in soil can be transformed and recycled so that plants can absorb the required nutrients. 4.1 Effects of different Si dosages on α diversity of soil microorganisms in paddy soil 2 Alpha diversity refers to diversity in a specific region or ecosystem and is a comprehensive indicator of richness and evenness. It depends mainly on two factors. One is the number of species, that is, species richness. The other is diversity and uniformity of distribution of individuals in the community. Indices of community richness mainly include the Chao1 index and ACE index. The indices of community diversity include the Shannon index and Simpson index ( Shannon, 1948a Shannon, 1948a , 1948b 1948b ; Simpson, 1949 Simpson, 1949 ; Chao, 1984 Chao, 1984 ; Chao and Yang, 1993 Chao and Yang, 1993 ). The Chao1 index estimates the number of OTUs in the community using the Chao1 algorithm. It is often used in ecology to estimate the total number of species. The larger the value, the more the total number of species. The ACE index is used to estimate the number of OTUs in the community. By default, OTUs with sequence numbers less than 10 are included to estimate the actual number of species in the community. The higher the ACE index, the higher the richness of the community. The Shannon index considers the richness and evenness of the community. The higher the value of the Shannon index, the higher the diversity of community. The Simpson index is one of the indices used to estimate microbial diversity in samples. In ecology, it is often used to quantitatively describe the biodiversity of an area. The higher the Simpson index, the lower the diversity of the community. Table 7 Table 7 is a statistical table of α diversity, which shows that appropriate Si application in soil can improve the Chao1 index, ACE index, Shannon index, and Simpson index of soil microorganisms in paddy soil in a manner, while excessive Si application can reduce the above index. At a Si application rate of 15.6 μg/kg, the above indices of soil microorganisms reached their maximum values, showing increases of 37.05%, 47.45%, 0.14%, and 2.40%, respectively, compared with the control group, indicating that an appropriate application of Si can effectively improve the Chao1 index and ACE index of soil microorganisms in paddy soil but has no significant effect on the Shannon index or Simpson index. This analysis indicates that application of appropriate Si dosages can significantly increase the richness of soil microbial communities, and also to some extent improve the diversity of soil microbial communities. CK: control check; S1: Si, 5.2 μg/kg; S2: Si, 10.4 μg/kg; S3: Si, 15.6 μg/kg; S4: Si, 20.8 μg/kg. Level of Si treatment Chao1 ACE Simpson Shannon CK 3581.24 3721.55 0.9964 10.43 S1 4915.32 4930.81 0.9974 10.56 S2 5024.16 5239.17 0.9974 10.66 S3 5278.29 5487.54 0.9978 10.68 S4 3536.52 3583.19 0.9978 10.65 4.2 Effects of different Si contents on β diversity of microorganisms in paddy soil 2 Beta diversity is often used to compare the diversity of different ecosystems, that is, differences between samples collected from different places. This index uses the evolutionary relationship and abundance information of each sample sequence to calculate the distance between samples and reflect the differences in microbial communities among samples. The main methods of β diversity are principal component analysis (PCA), multi-dimensional scaling (MDS), and clustering analysis to analyze the similarity of community structure among different samples. PCA is a visual method to study the similarity or difference of data. With the idea of dimensionality reduction, PCA can find the most important coordinates in the distance matrix. After sorting the complex data with a series of eigenvalues and eigenvectors, the first few eigenvalues are selected to represent the relationship between samples. MDS is a statistical research method that classifies samples or variables according to their similarity or non-similarity. In an MDS map, space and distance are used to reflect the relationship between each point to judge the distribution of each point in the network and the density of the network. Fig. 2 Fig. 2 is the PCA of microbial communities under different Si application rates in paddy soil; the principal components of microbial community in soil samples are extracted by PCA, and the differences of soil microbial community structure under different Si treatments are analyzed. It also shows that there are obvious differences between soil microbial community structure under CK treatment and soil microbial community structure after Si treatment. The S1, S2, and S4 treatments distribute on the positive axis of principal component 2 (PC2) axis, and CK and S3 distribute on the negative axis of PC2 axis. These results show that the difference in microbial community structure between CK treatment and S1, S2 and S4 treatments is caused mainly by PC2 (20.18%), while the difference of microbial community structure between S1, S2 treatments and S3, S4 treatments is mainly caused by PC1 (50.87%). This result indicates that different Si application rates might cause significant differences in microbial community structure in paddy soil. 4.3 Effects of different Si dosages on microbial community composition in paddy soil 2 The heat map presents the data in a two-dimensional matrix or table using color change as an indicator. It can intuitively depict the data value by the defined color depth. According to the needs of species or sample richness similarity clustering, the clustering data are represented on the heat map, and high-abundance and low-abundance species can be clustered in blocks. The similarities and differences in community composition of multiple samples at different classification levels can be reflected by color gradients and degrees of similarity. The community composition heat map at genus level combined with cluster analysis is presented by clustering and sorting the community composition data of each classification level according to abundance distribution of classification units or degrees of similarity between samples, and then reflecting the similarity in community composition between samples by color gradient. Fig. 3 Fig. 3 is a thermal map of genus-level community composition of soil combined with cluster analysis of top 50 genera. Analysis of Fig. 3 Fig. 3 shows that different Si dosages lead to changes in the dominant microorganisms in the soil microbial community. The dominant microorganisms in the control group include Acidibacter ( Proteus ) and Pesudolabrys ( Yellow bacteria ). The dominant microorganisms in soil treated with S1 are Acidothermus ( Thermophila ), Thermoan , Aebaculum ( Thermophilic anaerobic bacterium ), Syntrophorhabdus , and others; the dominant soil microorganisms in S2 treatment include Sphingomonas ( Sphingosinol monocytes ), Dyella , Fulvimonas ( Yellow rot bacteria ), Soil-bacterium-WF55 , and Bacillus , among others; the dominant soil microorganisms in S3 treatment included Nocardia , Lysobacter ( Lysobacteria ), Sigulisphaera , and Isospera . The dominant soil microorganisms in S4 were Pelomonas , Ralstonia , Streptacidiphilus , Kitasatospora , and Minicystis . These results show that Si application can promote the transformation of dominant microorganisms in paddy soil, such as Bacillus , Cyclolipidicus , Candidatus-soilbacter , Candidatus-koribacter , Thermophilic bacteria, Zooplankton , and slow-growing Rhizobium ( Yu et al., 2016 Yu et al., 2016 ). That is to say, Si application can promote the transformation of soil microorganisms towards the efficient use of soil organic nutrients, thus enhancing soil nutrient recycling and utilization. Earlier research's data showed that soil microorganisms are abundant, with the number of soil microorganisms approximated at 1029 orders of magnitude. However, because the growth of soil microorganisms is closely related to the soil temperature, nutrient content, soil acidity and alkalinity, and interactions between microorganisms, the simple artificial simulated environment of the laboratory cannot replicate the real growth patterns of microorganisms in natural conditions. Compared with the environment, the amount of soil microorganisms in laboratory culture is less than 1% of the total amount of soil microorganisms ( Pace, 1997 Pace, 1997 ). For this reason, we studied the effect of Si application on soil microbial community structure using high-throughput sequencing technology. The results of α diversity analysis showed that appropriate Si dosages could significantly increase the richness of soil microbial communities, and at the same time improve the diversity of soil microbial community to a certain extent. PCA of β diversity showed that there were significant differences in microbial community composition caused by Si fertilizer application in acidic soils. Si can also improve soil pH, increase soil concentrations of basic ions, promote the formation of aggregate structure, and promote the decomposition of organic matter, so as to regulate soil structure and increase the number of soil microorganisms effectively ( Du et al., 2016 Du et al., 2016 ; Cai, 2017 Cai, 2017 ). This means that Si fertilizer can effectively improve the microbial community structure of acidic soil both as a basic fertilizer and soil amendment, which is consistent with the results of this study. 4.4 Relationship between the above microbial indicators and N and P nutrient mineralization in paddy soil 2 Previous experiments have shown that increasing the use of Si fertilize can improve the activity, quantity, and abundance of functional microorganisms in soil and that activity of corresponding enzymes can also be enhanced. Moreover, Si helps to promote the mineralization of soil nutrients, so that the soil can provide more effective nutrients. An analysis of the correlation between some representative indicators in previous experiments and nutrient mineralization indicators is shown in Table 8 Table 8 . * indicates a significant correlation at P < 0.05 and ** indicates a significant correlation at P < 0.01. AP/TP: available phosphorus/total phosphorus; AN/TN: available nitrogen/total nitrogen; FDA: fluorescein diacetate; AcPA: acid phosphatase activity. Factor FDA hydrolase activity P-solubilizing bacteria Ammoniated bacteria AcPA Urease activity Shannon Shannon 0.5730 0.7109 0.9290 ** 0.8363 0.5088 AP/TP 0.8290 0.8818 * 0.9290 ** 0.9508 ** 0.7640 0.9202 ** AN/TN 0.7690 0.8982 * 0.9140 * 0.9366 ** 0.7197 0.8914 * The Shannon index was selected to represent microbial community structure, and AN/TN and AP/TP were used to characterize nutrient mineralization in paddy soil. Table 8 Table 8 shows that the number of ammoniated bacteria and AcPA are strongly correlated with nutrient mineralization and community structure, indicating that the numbers of functional soil microbes and the activity of related enzymes are related to nutrient mineralization and microbial community structure. The Shannon index also shows good correlation with AN/TN and AP/TP, indicating that microbial community structure is closely related to nutrient mineralization. The ecological mechanism of Si improvement in N and P nutrient availability in paddy soil is due mainly to its role in increase of soil microbial community structure diversity and soil microbial activity, resulting in increased mineralization of soil N and P nutrients, which indicates that appropriate concentration of Si soil supplements (about 15.6 μg/kg) not only affects the Si cycle in soil-plant ecosystem, but also affects the N and P cycles in these systems. 5 Conclusions 1 Proper application of Si can effectively increase the number of functional microorganisms involved in the N and P cycles in paddy soils. At Si application rate of 15.6 μg/kg, the numbers of ammoniated bacteria and phosphate-solubilizing bacteria, rates of urease activity, and AcPA in paddy soil reached maximum values, showing respective increases of 73.12%, 130.36%, 28.12%, and 20.15% compared with the control group. The correlation coefficients between soil microbial activity, the number of ammoniated bacteria, urease activity, and AN/TN ratios were 0.764–0.929, and the correlation coefficients of microbial activity, the number of phosphate-solubilizing bacteria, AcPA, and AP/TP were between 0.719–0.937, which further proved that the changes of soil microorganisms and their metabolism-related enzyme activity caused by Si application increased the activity of functional microorganisms and important metabolic enzymes related to N and P cycles in soil, thus promoting the mineralizations of N and P and improving the availability of N and P nutrients. The proper application of Si could effectively improve soil microbial community structure and microbial biodiversity. In particular, appropriate amounts of Si fertilizer could increase the microbial community diversity related to soil C, N, and P cycles, including increases in bacterial taxa such as Bacillus cyclamatus , Thermophilic thermophilus , Rhodiola , Candidatus-soilbacter , Candidatus-koribacter , Bradyrhizobium , and others. At Si dosage of 15.6 μg/kg, sequence number, OTU number, Chao1 index, ACE index, Shannon index, and Simpson index of soil microorganism in paddy fields all reached maximum values, showing increases of 14.46%, 10.01%, 23.80%, 30.54%, 0.18%, and 2.64%, respectively, compared with the control group. References Bao SD , 2011 . Analytical Methods of Agricultural Soil Chemistry . Chinese Agricultured Science and Technology Press , Beijing, China , p. 39 - 61 , 264 - 268 (in Chinese) . Analytical Methods of Agricultural Soil Chemistry Blaxter M , Mann J , Chapman T , et al. , 2005 . Defining operational taxonomic units using DNA barcode data . Philos Trans Roy Soc B Biol Sci , 360 ( 1462 ): 1935 - 1943 . https://doi.org/10.1098/rstb.2005.1725 https://doi.org/10.1098/rstb.2005.1725 Defining operational taxonomic units using DNA barcode data Cai DL , 2017 . Research and application development of silicon fertilizer at home and abroad . Phos Comp Fert , 32 ( 1 ): 37 - 39 (in Chinese) . https://doi.org/10.3969/j.issn.1007-6220.2017.01.014 https://doi.org/10.3969/j.issn.1007-6220.2017.01.014 Research and application development of silicon fertilizer at home and abroad Chao AN , 1984 . Nonparametric estimation of the number of classes in a population . Scand J Stat , 11 ( 4 ): 265 - 270 . Nonparametric estimation of the number of classes in a population Chao AN , Yang MCK , 1993 . Stopping rules and estimation for recapture debugging with unequal failure rates . Biometrika , 80 ( 1 ): 193 - 201 . https://doi.org/10.1093/biomet/80.1.193 https://doi.org/10.1093/biomet/80.1.193 . Stopping rules and estimation for recapture debugging with unequal failure rates Chen XF , Li ZP , Liu M , et al. , 2015 . Effect of long-term fertilizations on microbial community structure and functional diversity in paddy soil of subtropical China . Chin J Ecol , 34 ( 7 ): 1815 - 1822 (in Chinese) . https://doi.org/10.13292/j.1000-4890.20150615.001 https://doi.org/10.13292/j.1000-4890.20150615.001 Effect of long-term fertilizations on microbial community structure and functional diversity in paddy soil of subtropical China Cusack DF , Silver WL , Torn MS , et al. , 2011 . Changes in microbial community characteristics and soil organic matter with nitrogen additions in two tropical forests . Ecology , 92 ( 3 ): 621 - 632 . https://doi.org/10.1890/10-0459.1 https://doi.org/10.1890/10-0459.1 Changes in microbial community characteristics and soil organic matter with nitrogen additions in two tropical forests Du YF , Lv LF , He ZQ , et al. , 2016 . Effect of mineral conditioners on improvement of acid red soil . J Soil Water Conserv , 30 ( 3 ): 351 - 354 (in Chinese) . https://doi.org/10.13870/j.cnki.stbcxb.2016.03.059 https://doi.org/10.13870/j.cnki.stbcxb.2016.03.059 Effect of mineral conditioners on improvement of acid red soil Eneji AE , Inanaga S , Muranaka S , et al. , 2008 . Growth and nutrient use in four grasses under drought stress as mediated by silicon fertilizers . J Plant Nutr , 31 ( 2 ): 355 - 365 . https://doi.org/10.1080/01904160801894913 https://doi.org/10.1080/01904160801894913 Growth and nutrient use in four grasses under drought stress as mediated by silicon fertilizers Frankenberger WT , Dick WA , 1983 . Relationships between enzyme activities and microbial growth and activity indices in soil . Soil Sci Soc Am J , 47 ( 5 ): 945 - 951 . https://doi.org/10.2136/sssaj1983.03615995004700050021x https://doi.org/10.2136/sssaj1983.03615995004700050021x Relationships between enzyme activities and microbial growth and activity indices in soil Guan SY , 1986 . Soil Enzymes and Their Research Methods . Agricultural Press , Beijing, China (in Chinese) . Soil Enzymes and Their Research Methods He JZ , Zheng Y , Chen CR , et al. , 2008 . Microbial composition and diversity of an upland red soil under long-term fertilization treatments as revealed by culture-dependent and culture-independent approaches . J Soils Sed , 8 ( 5 ): 349 - 358 . https://doi.org/10.1007/s11368-008-0025-1 https://doi.org/10.1007/s11368-008-0025-1 Microbial composition and diversity of an upland red soil under long-term fertilization treatments as revealed by culture-dependent and culture-independent approaches Hömberg A , Obst M , Knorr KH , et al. , 2020 . Increased silicon concentration in fen peat leads to a release of iron and phosphate and changes in the composition of dissolved organic matter . Geoderma , 374 : 114422 . https://doi.org/10.1016/j.geoderma.2020.114422 https://doi.org/10.1016/j.geoderma.2020.114422 Increased silicon concentration in fen peat leads to a release of iron and phosphate and changes in the composition of dissolved organic matter Li CH , Jia ZJ , Tang LS , et al. , 2012 . Effect of model of fertilization on microbial abundance and enzyme activity in oasis farmland soil . Acta Pedol Sin , 49 ( 3 ): 567 - 574 (in Chinese) . https://doi.org/10.11766/trxb201101070011 https://doi.org/10.11766/trxb201101070011 Effect of model of fertilization on microbial abundance and enzyme activity in oasis farmland soil Li FD , Yu ZN , He SJ , 1996 . Agricultural Microbiology Experimental Technology . China Agricultural Press , Beijing, China (in Chinese) . Agricultural Microbiology Experimental Technology Liao M , Fang ZP , Liang YQ , et al. , 2020 . Effects of supplying silicon nutrient on utilization rate of nitrogen and phosphorus nutrients by rice and its soil ecological mechanism in a hybrid rice double-cropping system . J Zhejiang Univ-Sci B (Biomed & Biotechnol) , 21 ( 6 ): 474 - 484 . https://doi.org/10.1631/jzus.B1900516 https://doi.org/10.1631/jzus.B1900516 Effects of supplying silicon nutrient on utilization rate of nitrogen and phosphorus nutrients by rice and its soil ecological mechanism in a hybrid rice double-cropping system Liu HF , Ma JH , Jin L , et al. , 2009 . Determination of activity of FDA hydrolysis in paddy soils and its application in Taihu Lake region . Acta Pedol Sin , 46 ( 2 ): 365 - 367 (in Chinese) . https://doi.org/10.3321/j.issn:0564-3929.2009.02.026 https://doi.org/10.3321/j.issn:0564-3929.2009.02.026 Determination of activity of FDA hydrolysis in paddy soils and its application in Taihu Lake region Mehrabanjoubani P , Abdolzadeh A , Sadeghipour HR , et al. , 2015 . Impacts of silicon nutrition on growth and nutrient status of rice plants grown under varying zinc regimes . Theor Exp Plant Physiol , 27 ( 1 ): 19 - 29 . https://doi.org/10.1007/s40626-014-0028-9 https://doi.org/10.1007/s40626-014-0028-9 Impacts of silicon nutrition on growth and nutrient status of rice plants grown under varying zinc regimes Mendes R , Kruijt M , de Bruijn I , et al. , 2011 . Deciphering the rhizosphere microbiome for disease-suppressive bacteria . Science , 332 ( 6033 ): 1097 - 1100 . https://doi.org/10.1126/science.1203980 https://doi.org/10.1126/science.1203980 Deciphering the rhizosphere microbiome for disease-suppressive bacteria Meng FQ , Qiao YH , Wu WL , et al. , 2017 . Environmental impacts and production performances of organic agriculture in China: a monetary valuation . J Environ Manage , 188 : 49 - 57 . https://doi.org/10.1016/j.jenvman.2016.11.080 https://doi.org/10.1016/j.jenvman.2016.11.080 Environmental impacts and production performances of organic agriculture in China: a monetary valuation Nannipieri P , 1994 . The potential use of soil enzymes as indicators of productivity, sustainability and pollution . In: Pankhurst CE, Double BM, Gupta VVSR, et al. (Eds.), Soil Biota: Management in Sustainable Farming Systems . CSIRO , East Melbourne , p. 238 - 244 . https://doi.org/10.1007/978-3-642-14225-3_16 https://doi.org/10.1007/978-3-642-14225-3_16 The potential use of soil enzymes as indicators of productivity, sustainability and pollution Neu S , Schaller J , Dudel GE , 2017 . Silicon availability modifies nutrient use efficiency and content, C:N:P stoichiometry, and productivity of winter wheat ( Triticum aestivum L .). Sci Rep , 7 : 40829 . https://doi.org/10.1038/srep40829 https://doi.org/10.1038/srep40829 Silicon availability modifies nutrient use efficiency and content, C:N:P stoichiometry, and productivity of winter wheat (Triticum aestivum L Pace NR , 1997 . A molecular view of microbial diversity and the biosphere . Science , 276 ( 5313 ): 734 - 740 . https://doi.org/10.1126/science.276.5313.734 https://doi.org/10.1126/science.276.5313.734 A molecular view of microbial diversity and the biosphere Pati S , Pal B , Badole S , et al. , 2016 . Effect of silicon fertilization on growth, yield, and nutrient uptake of rice . Commun Soil Sci Plant Anal , 47 ( 3 ): 284 - 290 . https://doi.org/10.1080/00103624.2015.1122797 https://doi.org/10.1080/00103624.2015.1122797 Effect of silicon fertilization on growth, yield, and nutrient uptake of rice Saudy HS , Mubarak M , 2015 . Mitigating the detrimental impacts of nitrogen deficit and fenoxaprop- p -ethyl herbicide on wheat using silicon . Commun Soil Sci Plant Anal , 46 ( 7 ): 897 - 907 . https://doi.org/10.1080/00103624.2015.1011753 https://doi.org/10.1080/00103624.2015.1011753 Mitigating the detrimental impacts of nitrogen deficit and fenoxaprop-p-ethyl herbicide on wheat using silicon Schaller J , Brackhage C , Gessner MO , et al. , 2012 . Silicon supply modifies C:N:P stoichiometry and growth of Phragmites australis . Plant Biol , 14 ( 2 ): 392 - 396 . https://doi.org/10.1111/j.1438-8677.2011.00537.x https://doi.org/10.1111/j.1438-8677.2011.00537.x Silicon supply modifies C:N:P stoichiometry and growth of Phragmites australis Schaller J , Schoelynck J , Struyf E , et al. , 2016 . Silicon affects nutrient content and ratios of wetland plants . Silicon , 8 ( 4 ): 479 - 485 . https://doi.org/10.1007/s12633-015-9302-y https://doi.org/10.1007/s12633-015-9302-y Silicon affects nutrient content and ratios of wetland plants Schaller J , Faucherre S , Joss H , et al. , 2019 . Silicon increases the phosphorus availability of Arctic soils . Sci Rep , 9 : 449 . https://doi.org/10.1038/s41598-018-37104-6 https://doi.org/10.1038/s41598-018-37104-6 Silicon increases the phosphorus availability of Arctic soils Schneider T , Keiblinger KM , Schmid E , et al. , 2012 . Who is who in litter decomposition? Metaproteomics reveals major microbial players and their biogeochemical functions . ISME J , 6 ( 9 ): 1749 - 1762 . https://doi.org/10.1038/ismej.2012.11 https://doi.org/10.1038/ismej.2012.11 Who is who in litter decomposition? Metaproteomics reveals major microbial players and their biogeochemical functions Schnitzer SA , Klironomos JN , HilleRisLambers J , et al. , 2011 . Soil microbes drive the classic plant diversity-productivity pattern . Ecology , 92 ( 2 ): 296 - 303 . https://doi.org/10.1890/10-0773.1 https://doi.org/10.1890/10-0773.1 Soil microbes drive the classic plant diversity-productivity pattern Shannon CE , 1948a . A mathematical theory of communication . Bell Syst Tech J , 27 ( 3 ): 379 - 423 . A mathematical theory of communication Shannon CE , 1948b . A mathematical theory of communication . Bell Syst Tech J , 27 ( 4 ): 623 - 656 . A mathematical theory of communication Shen JP , Zhang LM , Guo JF , et al. , 2010 . Impact of long-term fertilization practices on the abundance and composition of soil bacterial communities in Northeast China . Appl Soil Ecol , 46 ( 1 ): 119 - 124 . https://doi.org/10.1016/j.apsoil.2010.06.015 https://doi.org/10.1016/j.apsoil.2010.06.015 Impact of long-term fertilization practices on the abundance and composition of soil bacterial communities in Northeast China Simpson EH , 1949 . Measurement of diversity . Nature , 163 ( 4148 ): 688 . https://doi.org/10.1038/163688a0 https://doi.org/10.1038/163688a0 Measurement of diversity Su D , Zhang K , Chen FL , et al. , 2014 . Effects of nitrogen application on soil microbial community structure and function of eucalyptus forests with different organic carbon levels . Ecol Environ Sci , 23 ( 3 ): 423 - 429 (in Chinese) . https://doi.org/10.3969/j.issn.1674-5906.2014.03.009 https://doi.org/10.3969/j.issn.1674-5906.2014.03.009 Effects of nitrogen application on soil microbial community structure and function of eucalyptus forests with different organic carbon levels Waldrop MP , Zak DR , Sinsabaugh RL , 2004 . Microbial community response to nitrogen deposition in northern forest ecosystems . Soil Biol Biochem , 36 ( 9 ): 1443 - 1451 . https://doi.org/10.1016/j.soilbio.2004.04.023 https://doi.org/10.1016/j.soilbio.2004.04.023 Microbial community response to nitrogen deposition in northern forest ecosystems Wang F , Yuan T , Gu SK , et al. , 2015 . Effects of organic and inorganic slow-release compound fertilizer on different soils microbial community structure . Environ Sci , 36 ( 4 ): 1461 - 1467 (in Chinese) . https://doi.org/10.13227/j.hjkx.2015.04.045 https://doi.org/10.13227/j.hjkx.2015.04.045 Effects of organic and inorganic slow-release compound fertilizer on different soils microbial community structure Wei W , Xu YL , Zhu L , et al. , 2013 . Effect of long-term fertilization on soil microbial community in black soil farmland . Acta Pedol Sin , 50 ( 2 ): 372 - 380 (in Chinese) . https://10.11766/trxb201202290053 https://10.11766/trxb201202290053 Effect of long-term fertilization on soil microbial community in black soil farmland Yu ZH , Li YS , Wang GH , et al. , 2016 . Effectiveness of elevated CO 2 mediating bacterial communities in the soybean rhizosphere depends on genotypes . Agric Ecosyst Environ , 231 : 229 - 232 . https://doi.org/10.1016/j.agee.2016.06.043 https://doi.org/10.1016/j.agee.2016.06.043 Effectiveness of elevated CO2 mediating bacterial communities in the soybean rhizosphere depends on genotypes Zhong WH , Gu T , Wang W , et al. , 2010 . The effects of mineral fertilizer and organic manure on soil microbial community and diversity . Plant Soil , 326 ( 1-2 ): 511 - 522 . https://doi.org/10.1007/s11104-009-9988-y https://doi.org/10.1007/s11104-009-9988-y The effects of mineral fertilizer and organic manure on soil microbial community and diversity Yuqi LIANG contributed to data analysis and writing of the manuscript. Min LIAO and Xiaomei XIE contributed to study design, data analysis, and writing and editing of the manuscript. Yuqi LIANG, Zhiping FANG, Jiawen GUO, Xiaomei XIE, and Changxu XU carried out the experimental work. All authors have read and approved the final manuscript and, therefore, have full access to all the data in the study and take responsibility for the integrity and security of the data. We gratefully acknowledge support for this research from the National Key Research and Development Project of China (No. 2016YFD0200800) and the National Natural Science Foundation of China (No. 41571226). 10.1631/jzus.B2000708 1673-1581（2021）07-0521-12 2020-11-02 2021-01-03 2021-07-15 2022-05-09 2021-05-14 © Zhejiang University Press 2021 Yuqi LIANG, Min LIAO, Zhiping FANG, Jiawen GUO, Xiaomei XIE, and Changxu XU declare that they have no conflict of interest. This article does not contain any studies with human or animal subjects performed by any of the authors. Compliance with ethics guidelines 浙江大学学报（英文版）（B辑：生物医学和生物技术） 7 22