Effects of Fungicide Iprodione and Nitrification Inhibitor

Effects of Fungicide Iprodione and Nitrification Inhibitor Effects of fungicide iprodione and nitrification inhibitor 3, 4-dimethylpyrazole phosphate on soil enzyme and bacterial properties Manyun Zhang a, b, à ¯Ã‚ Ã¢â‚¬ ºÃƒ ¯Ã¢â€š ¬Ã‚ ªÃƒ ¯Ã‚ Ã‚ , Weijin Wang a, c, Yaling Zhang a, Ying Teng b, à ¯Ã‚ Ã¢â‚¬ ºÃƒ ¯Ã¢â€š ¬Ã‚ ªÃƒ ¯Ã‚ Ã‚ , Zhihong Xu a, à ¯Ã‚ Ã¢â‚¬ ºÃƒ ¯Ã¢â€š ¬Ã‚ ªÃƒ ¯Ã‚ Ã‚  a Environmental Futures Research Institute, School of Natural Sciences, Griffith University, Brisbane, Queensland 4111, Australia b Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China c Department of Science, Information Technology and Innovation, Dutton Park, Queensland 4102, Australia Abstract Agrochemical applications may have unintended detrimental effects on soil bacteria and soil health. However, limited studies have been conducted to evaluate the effects of repeated fungicide applications and interactive effects of different agrochemical applications on soil bacteria. In this study, an incubation experiment was established to evaluate the potential influences of fungicide iprodione and nitrification inhibitor 3, 4-dimethylpyrazole phosphate (DMPP) on soil enzyme and bacterial properties. Weekly iprodione applications decreased the activities of all enzymes tested, and single DMPP addition inhibited soil ÃŽ ²-glucosidase and urease activities. Compared with the blank control, bacterial 16S rRNA gene abundance significantly decreased following repeated iprodione applications, but increased after DMPP application. After 28 days of incubation, the treatment of iprodione and DMPP applications had higher bacterial 16S rRNA gene abundance than the counterpart with i prodione applications alone, and the similar trends were also observed in the Shannon index. Repeated iprodione applications significantlyincreased the relative abundance of Proteobacteria, but decreased the relative abundances of Chloroflexi and Acidobacteria. The combined applications of iprodione and DMPP increased the number of members of Gaiellaceae, Microbacteriaceae, Nocardioidaceae and Methylobacteriaceae. Simultaneously, bacterial community structure was significantly changed by repeated iprodione applications, alone or together with the DMPP. These results showed that repeated iprodione applications exerted negative effects on soil enzyme activities, bacterial biomass and community diversity. Moreover, relative to iprodione applications alone, extra DMPP application had the potential to alleviate the toxic effects of iprodione on soil bacterial biomass and community diversity. Keywords: agrochemicals; soil enzyme; 16S rRNA gene; bacterial community diversity and structure Introduction Fungicides play important roles in ensuring the crop quality and yield in modern agriculture (Maltby et al., 2009; Sabatier et al., 2014). The infections and phytopathies caused by fungi are the major problems and threats in agricultural production, which leads to the intensification in applications of fungicidal agrochemicals (OMaille, 2015). Previous research has shown that in some developing countries, fungicide application dosages were as high as 8 kg ha-1 y-1 (Liu et al., 2015). Iprodione, as a broad-spectrum fungicide, has been widely used in the intensive agriculture to control phytopathies of cash crops, and iprodione residuals have already been detected in water (Goewie et al., 1985; Sauret et al., 2006), soils (Leistra and Arrià «nne, 2004) and vegetable and fruit (Picà ³ et al., 2004; Juanà ¢Ã¢â€š ¬Ã‚ Garcà ­a et al., 2005; Angioni et al., 2012). According to a report of the Pesticide Data Program, U.S. Department of Agriculture (2014), the detected amount of iprodion e was the highest among all agrochemicals, and iprodione was the only fungicide detected in baby food. Besides the crop phytopathies caused by fungal pathogens, the lower utilization efficiency of nitrogen (N) fertilizer and nitrous oxide (N2O) emission are also worldwide problems in agricultural production (Clough et al., 2007; Menà ©ndez et al., 2012). As a result, nitrification inhibitors are sometimes applied to enhance the utilization efficiency of N fertilizer. The most widely used nitrification inhibitor in recent years is 3, 4-dimethylpyrazole phosphate (DMPP) (Menà ©ndez et al., 2012; Florio et al., 2014). The fungicide iprodione and nitrification inhibitor DMPP may be simultaneously applied into soils in some circumstances. Fungicides are designed to control fungal pathogens, but their lethal effects are not constrained to fungi only (Duah-Yentumi and Johnson, 1986; Muà ±oz-Leoz et al., 2011; Schnug et al., 2015). Once entering into agricultural soil, fungicides and their degradation metabolites may have detrimental effects on soil bacteria and, hence, the overall soil environment. There have been increasing research interests in the impacts of iprodione on environmental safety (Leistra and Matser, 2004; Verdenelli et al., 2012; Morales et al., 2013), because the iprodione is widely applied into agricultural soils at high dosages. Previous studies generally focused on the impacts of a single iprodione application, whereas few studies paid attention to the effects of repeated iprodione applications which occurs in intensively managed cropping systems. Furthermore, iprodione and other agrochemicals (such as DMPP) may be applied into agriculture soils simultaneously. To the best of our knowledge, few stud ies have been conducted to evaluate the interactive effects of different agrochemicals. Researches are, therefore, required to better understand the effects of combined iprodione and DMPP applications on soil bacterial properties. In this study, the iprodione and DMPP were applied into an agricultural soil. Soil enzyme activity, bacterial 16S rRNA gene abundance and bacterial community structure were determined. The main objectives were to (1) assess the effects of iprodione and DMPP on soil enzyme activities; (2) evaluate the impacts of agrochemicals on soil bacterial biomass via determining bacterial 16S rRNA gene abundance; (3) reveal the responses of soil bacteria at different taxa to the agrochemical applications; and (4) compare the potential impacts of iprodione and DMPP applications on soil bacterial community structure. This study will improve our current understanding of the ecological risks of iprodione and DMPP applications, alone or together, on soil nutrient cycling and bacterial properties. 2. Materials and methods 2.1. The chemicals and soil samples A commercial wettable powder formulation of iprodione (Bayer Crop Science, Hangzhou, China) and a chemical reagent DMPP (purity > 97.0%; CIVI-CHEM, Shanghai, China) were used for soil treatments. Soil samples were taken from a farmland (36.78†² N, 118.67†² E) located in Shandong Province, China. The surface soil (0-20 cm) was collected, air-dried at room temperature, mixed thoroughly and sieved (< 2 mm) prior to use. The selected physical and chemical properties of the soil were as follows: sand (50-2000 ÃŽ ¼m), 31.4  ± 1.4%; silt (2-50 ÃŽ ¼m), 36.9  ± 0.8%;   clay (< 2 ÃŽ ¼m), 31.7  ± 0.6%; soil pH (in water), 7.19  ± 0.05; organic carbon (C) content, 10.0  ± 0.1 g kg-1; total N content, 0.93  ± 0.01 g kg-1; Olsen-P, 28.8  ± 0.2 mg kg-1;   NH4OAc-K, 69.9  ± 1.5 mg kg-1; cationic exchange capacity,   16.9  ± 0.4 cmol kg-1. All treatments were added with urea at 200 mg N kg-1 dry soil before the iprodione or DMPP application so that enough substrate ( NH4+-N) was available for soil nitrification (DMPP is generally applied with the urea in agriculture). 2.2. Experimental design Four treatments were used in this study: Treatment 1 (CK), without any iprodione or DMPP applications; Treatment 2 (IPR), weekly iprodione applications at 1.5 mg kg-1 dry soil (the frequency followed the instructions); Treatment 3 (DAA), nitrification inhibitor DMPP application at 2 mg kg-1 dry soil (equivalent to 1% of applied urea-N) at commencement; and Treatment 4 (I+D), weekly iprodione and initial DMPP applications as described in treatments 2 and 3. Each treatment was prepared in triplicates. The chemicals were dissolved in double distilled H2O (ddH2O) and then applied into the test soil. Sixty glass bottles (4 treatments 5 sampling time 3 replications) were filled with the treated soil at 150 g dry weight per bottle. Soil moisture was adjusted to 60% of the water holding capacity and was maintained by the additions of ddH2O. The soil samples were then incubated at 28  °C in the dark, and after 0, 7, 14, 21 and 28 days of incubation, soil samples were collected after mixin g thoroughly in each bottle for analyses of soil enzyme and bacterial properties. 2.3. Soil enzyme activity and geometric mean of assayed enzymes activities Soil ÃŽ ²-glucosidase activity was determined using a soil enzyme assay kit (Catalogue No. HK000218, Toyongbio Company, Shanhai, China). The analytical method was based on that soil ÃŽ ²-glucosidase can hydrolyze p-nitrophenyl-ÃŽ ²-D-glucoside to generate p-nitrophenol. The determination method followed the manufacturers protocol, after treated with toluene, soil samples were incubated with the p-nitrophenyl-ÃŽ ²-d-glucoside and citrate-phosphate buffer (pH = 6.0) for 1 h at 37  °C. The reaction product (p-nitrophenol) concentration was determined with a spectrophotometer at 410 nm, and the results were expressed as ÃŽ ¼g p-nitrophenol g-1 dry soil d-1. Soil urease and phosphatase (acid phosphatase and alkaline phosphatase) activities were determined with the commercially available quantitative analytical kits (Jiancheng Bioengineering Institute, Nanjing, China). In the analytical kit of soil urease (Catalogue No. T017), urea was used as the substrate that can be hydrolyzed by soil urease to generate NH 4+-N. Prior to the urease determination, the test soils were treated with the toluene, and then they were incubation with the urea and citrate buffer (pH = 6.7) for 24 h at 37  °C. The concentration of NH4+-N generated from urea hydrolysis was determined via the indophenol blue method, and soil urease activity was expressed as ÃŽ ¼g NH 4+-N g-1 dry soil d-1. Soil phosphatase activity was determined with disodium phenyl phosphate as the enzyme reaction substrate. Soil phosphatase could hydrolyze the disodium phenyl phosphate at different pH conditions, and in the analytical kits of soil phosphatase and alkaline phosphatase (Catalogue No. T008 and T009), the buffers were acetate buffer (pH = 5) and borate buffer (pH = 9.4), respectively.   After 24 h of incubation at 37  °C, enzyme actions were terminated, and released phenol was determined at 660 nm. Soil phosphatase activities were expressed as ÃŽ ¼g phenol g-1 dry soil d-1. Soil arylsulphatase activity was determined according to the method of Floch et al. (2009) with minor modifications. P-nitrophenyl-sulfate was used as the reaction substrate, and the buffer was 0.5 M acetate (pH = 5.8). After 1 h of incubation, the reaction was halted by the additions of 0.5 M CaCl2 and 1 M NaOH, and the p-nitrophenol concentration was measured with a spectrophotometer at 410 nm. The soil arylsulphatase activity was expressed as ÃŽ ¼g p-nitrophenol g-1 dry soil d-1. The geometric mean of assayed enzymes activities (GMEA) was calculated to integrate data from variables that have different units and variation range. The calculations were made by following Hinojosa et al. (2004). where Glu, Ure, AcP, AlP and Ary were soil ÃŽ ²-glucosidase, urease, acid phosphatase, alkaline phosphatase and arylsulfatase activities, respectively. 2.4. Soil DNA extraction and real time quantitative PCR (qPCR) The genomic DNA of soil samples was extracted from approximately 0.5 g of soil with a Fast DNA SPIN Kit for Soil (MP Biomedicals, Cleveland, OH, USA). Soil bacterial biomass was revealed via determining bacterial 16S rRNA gene abundance, and qPCR was performed to assess bacterial 16S rRNA gene abundance with the universal primers 515F (5-GTGCCAGCMGCCGCGG-3) and 907R (5-CCGTCAATTCMTTTRAGTTT-3). The standard curve of qPCR was obtained by performing serial dilutions of the plasmid containing bacterial 16S rRNA gene. Each qPCR reaction was prepared in a 20.0 ÃŽ ¼L of solution consisting of 10.0 ÃŽ ¼L of SYBR ® Premix Ex Taqâ„ ¢ (TaKaRa Biotech, Dalian, China), 7.6 ÃŽ ¼L of sterile ddH2O, 2.0 ÃŽ ¼L of soil template DNA and 0.4 ÃŽ ¼L of universal primers. The thermocycling conditions were as follows: 95  °C for 3 min, followed by 45 cycles at 95  °C for 10 s, 56  °C for 30 s, 72  °C for 30 s, and then plate reading. The melting curve analyses were conducted by gradually heatin g the PCR mixtures from 65  °C to 95  °C with the determination of SYBR green signal. Negative control was run with sterile ddH2O as the template. After testing the diluted soil DNA suspension, there were no inhibitions detected for the qPCR, and the amplification efficiency of the target gene was 114.52%, with R2 > 0.995. 2.5. The Illumina MiSeq and sequenced data analysis At the end of incubation, soil bacterial community was also analyzed with the Illumina MiSeq platform. After amplifying the V4 region of bacterial 16S rRNA gene with the primers 515F/907R, the PCR products were purified and then subjected to the Illumina Miseq platform (Majorbio Bio-Pharm Technology Co., Ltd., Shanghai, China) to sequence nucleic acid bases of PCR products. The raw reads were de-multiplexed and filtered via the QIIME (version 1.17) with reference to the following standards: (1) The approximately 300 bp reads were truncated at the end side, receiving an average quality score of < 20 over a 10 bp sliding window, and shorter sequence reads (truncated length < 50 bp) were discarded; (2) raw reads with vague bases were discarded; and (3) only sequences with > 10 bp overlap were assembled with reference to the overlapped sequences, and the unassembled reads were unwanted. Operational taxonomic units (OTUs) were clustered within a 0.03 difference via the UPARSE (version 7.1 http://drive5.com/uparse/) for assessing community richness (Ace and Chao1 richness estimators) and community diversity (Shannon and Simpson indices). The richness estimators Ace and Chao1 were nonparametric and abundance-based estimators, which could predict the true value of taxa based on the proportion of rare taxa in a sample and were suitable for community richness ana lysis (Sogin et al., 2006; Gihring et al., 2012). The Shannon and Simpson indices were used for heterogeneity assessment, and the main difference between them was in the calculation method of taxa abundance. 2.6. Statistical analysis Two-way analysis of variance was conducted to detect significant differences among treatments, sampling times and their interactions, and Duncans multiple range test was used to compare statistical significances (P < 0.05) of the means among different treatments at each sampling time and among different incubation time in a specific treatment. Linear discriminant analysis effect size (LEfSe) method (http://huttenhower.sph.harvard.edu/galaxy/root) was employed to reveal biomarkers of soil bacteria among the treatments. The sequencing data were further processed to assess similarities and discrepancies of the whole bacterial community structure among different treatments using the principal coordinate analysis (PCoA) and the unweighted pair group method with arithmetic mean (UPGMA). 3. Results 3.1. Soil enzyme activities and GMEA Soil enzyme activities were significantly affected by the treatments, but the interactions between treatments and sampling time were not significant for the ÃŽ ²-glucosidase and alkaline phosphatase activities (Table S1). The ÃŽ ²-glucosidase, urease and arylsulfatase activities in the CK treatment increased significantly during the first 7 days of incubation (P < 0.05, Fig. 1). By the end of the incubation, the soil enzyme activity in the CK treatment rose from 1004  ± 51 to 1278  ± 133 ÃŽ ¼g p-nitrophenol g-1 dry soil d-1 for ÃŽ ²-glucosidase, from 60.9  ± 4.9 to 323.0  ± 19.6 ÃŽ ¼g NH4+-N g-1 dry soil d-1 for urease, from 698  ± 129 to 802    ± 76 ÃŽ ¼g phenol g-1 dry soil d-1 for acid phosphatase, from 2.21  ± 0.12 to 2.23  ± 0.13 ÃŽ ¼g phenol g-1 dry soil d-1 for alkaline phosphatase, and   from 20.9  ± 2.7 to 28.8  ± 2.3 ÃŽ ¼g p-nitrophenol g-1 dry soil h-1 for sulphatase. After 7 days of incubation, there were no significant differences in soil enzyme a ctivities between IPR and CK treatments, with the exception of acid phosphatase activity. However, soil enzyme activities in the IPR treatment decreased after repeated iprodione applications. DMPP application had no significant effects on phosphatase and arylsulphatase activities during the whole incubation period, but ÃŽ ²-glucosidase and urease activities were consistently inhibited by the DMPP application (89.8% and 76.5% % of the control after 28 days of incubation, respectively). It is interesting to note that, after 28 days of incubation, the activities of soil enzymes in the I+D treatment tended to be higher than those in the IPR treatment (Fig. 1). As shown in Table 1, the GMEA in the CK treatment increased significantly during the first week and remained relatively stable during the following three weeks of incubation. However, compared with the CK treatment, the GMEA was negatively affected by repeated iprodione applications, and the GMEA in the DAA treatment also tended to be lower than their counterparts from 7 days to the end of the incubation (88.9% of the control after 28 days of incubation). Consistent with the trend presented in Fig.1, the GMEA in the I+D treatment was significantly higher than its IPR counterpart after 28 days of incubation (P < 0.05). 3.2. Soil bacterial 16S rRNA gene abundances Both the treatments and sampling time could significantly affect soil bacterial 16S rRNA gene abundances (Table S1). The gene abundances in the CK treatment increased from 3.89-109 to 1.64-1010 copies g-1 during the 28 days of incubation (Fig. 2). A single iprodione application generated negligible effect on soil bacterial 16S rRNA gene abundance after 7 days, but repeated iprodione applications significantly (P < 0.05) decreased soil bacterial 16S rRNA gene abundance, relative to the CK treatment. At the end of the experiment, the bacterial 16S rRNA gene abundance in the IPR treatment was 6.55-109 copies g-1 dry soil, which was the lowest of the four treatments. The gene abundances in the DAA treatment tended to be higher than those in the CK treatment, especially from 14 days onwards. Relative to the iprodione applications alone, extra DMPP application at the commencement increased the gene abundances, after 28 days of incubation, bacterial 16S rRNA gene abundance in the I+D treatm ent was significantly (P < 0.05) higher than that from the IPR treatment. 3.3. Soil bacterial community diversity A total of 624067 raw sequences (> 200 bp) was obtained from the four treatments, and the average length of valid sequences was 396.71. The similarities and differences among OTUs of the four treatments were demonstrated in a four-set Venn diagram (Fig. 3). The unique OTUs were 12, 16, 13 and 22 for the CK, IPR, DAA and I+D treatments, respectively, and the four treatments shared 1653 OTUs. After 28 days of incubation, the Ace and Chao1 estimators, and Shannon index of the CK treatments were 1863  ± 37, 1853  ± 24 and 5.55  ± 0.15, respectively (Table 2). The IPR treatment had the lowest estimator Chao1 (1772  ± 17) and Shannon index (5.40  ± 0.05) among the four treatments, while the I+D had the highest estimator Chao1 and Shannon index. The Simpson index showed no significant differences among the four treatments. Relative to the CK treatment, DMPP application did not exert adverse effects on richness estimators and diversity indices, and DMPP applications had the potential to increase the Shannon indices. 3.4. Soil bacterial community structure The OTUs could be assigned into 11 predominant phyla which were in the following ranking orders: Proteobacteria, Actinobacteria, Gemmatimonadetes, Chloroflexi, Firmicutes, Acidobacteria, Bacteroidetes, Planctomycetes, Nitrospirae, Saccharibacteria and Verrucomicrobia, and the relative abundances of these phyla varied among the different treatments (Fig. 4A). The phylum Proteobacteria was the most abundant, comprising approximately 37.2%, 45.9%, 36.4% and 39.8% OTUs for the CK, IPR, DAA and I+D treatments, respectively. The phylum Actinobacteria was the second most abundant, and the proportions varied from 14.5% to 21.9%. There were no significant differences of relative abundances across all the predominant phyla between the CK and DAA treatments (Fig. 4B). However, compared with the CK treatment, repeated iprodione applications significantly (P < 0.05) increased the relative abundance of phylum Proteobacteria, but decreased the relative abundances of Chloroflexi and Acidobacteria. A t the genus level, the genera Micromonospora, Gemmatimonas, Haliangium and Bacillus accounted for large proportions in the twelve soil samples (Fig. 5). 3.5. Comparison of bacterial community structure LEfSe analysis demonstrated that there were significant associations among predominant bacterial taxa in the four treatments (Fig. 6). The predominant bacterial taxa were the Opitutaceae and Xanthomonadales families in the CK treatment, the Xanthomonadaceae, Erythrobacteraceae, Sphingomonadaceae Sphingomonadales and Rhodocyclaceae families in the IPR treatment, the Streptomycetales Order and the Gemmatimonaceae and Cytophagaceae families in the DAA treatment and the Gaiellaceae, Microbacteriaceae, Nocardioidaceae, and Methylobacteriaceae families in the I+D treatment. The results of LEfSe analysis further revealed that, consistent with the relative abundances shown in Fig. 4, the phylum Protebacteria increased following iprodione applications. A two-dimensional PCoA plot of bacterial community structure explained 68.2% of the total variance, with the PCoA1 having a greater power of separation (accounting for 57.7%). The two-dimensional PCoA demonstrated that the treatments without iprodione applications (CK and DAA treatments) resulted in a shift to the left along PCoA1 (Fig. 7A). There was no significant difference in the PCoA values (both PCoA1 and PCoA2) between the CK and DAA treatments, and this suggested that soil bacterial community structure was not significantly altered by the DMPP application. However, iprodione applications alone (IPR) or together with the DMPP (I+D), shifted the bacterial community to the right side along PCoA1. The IPR and I+D treatments were located in the opposite directions of the origin, with the I+D treatment having lower PCoA2 values. Consistent with the trends presented in the PCoA plot, four clusters could be grouped for these twelve soil samples (Fig. 7B): Cluster 1 contained the samp les of the DAA treatment, CK_1 and CK_2, but the CK_3 sample alone was classified into Cluster 2; Cluster 3 consisted of the samples of I+D treatment, and the samples of IPR treatment were all grouped in Cluster 4. 4. Discussion 4.1. Effects of iprodione applications on soil enzyme and bacteria As a soil xenobiotic, the fungicide iprodione displayed toxicity to soil bacteria on various aspects including the activity, biomass and community diversity (Duah-Yentumi and Johnson, 1986; Verdenelli et al., 2012). Previous researches have also revealed that the principal degradation metabolite 3, 5-dichloroanniline is more biologically toxic and stable than its parent compound iprodione (Athiel et al., 1995). Consequently, both the fungicide and its degradation metabolites have the potential to inhibit the non-target bacteria. On the other hand, the broad-spectrum fungicide could inhibit the flourish of fungi, which can also exhibit the indirect impacts on soil bacteria community (Muà ±oz-Leoz et al., 2011; Verdenelli et al., 2012). The ÃŽ ²-glucosidase, urease, phosphatase, and arylsulfatase are essential in the cycling of C, N, P and S in soil, respectively (Muà ±oz-Leoz et al., 2011). The activities of these enzymes tended to decline after repeated iprodione applications, highlighting the severe impacts of repeated iprodione applications and perhaps the accumulations of its metabolites on soil nutrient cycling. The fungicides could negatively affect soil enzyme activities as a result of: (1) directly reducing the biomass of soil microbes that produce enzymes, (2) competing for the active sites of enzymes with substrates, (3) decreasing the substrate bio-availability through the reaction with substrates, and (4) reacting with the enzyme-substrate complexes (Wang et al., 2009). In the IPR treatment, soil enzyme activities and bacterial 16S rRNA gene abundances decreased concurrently. We postulated that the declines of soil bacterial biomass caused by iprodione applications might have resulted in the decreases of soil enzyme activity. Soil bacterial 16S rRNA gene (both the abundance and community diversity) has been used as an important ecophysiological index for assessing soil contamination (Sipilà ¤ et al., 2008; Bell et al., 2014). In this study, soil bacterial 16S rRNA gene abundance was not significantly affected by the first iprodione application, but decreased with repeated iprodione applications (Fig. 2). The result was consistent with earlier finding of Duah-Yentumi and Johnson (1986) that the impacts of iprodione on soil microbial biomass differed between single and repeated applications. The reasons for these phenomena might be that accumulations of the fungicides and perhaps their degradation products following repeated application increased its eco-toxicity (Trabue et al., 2001; Zhang et al., 2016). Direct measurement of soil bacterial community could reveal shifts in the diversity due to fungicide applications, which might not be detectable by measuring overall bacterial activities and biomass (Lupwayi et al., 2009). Repeated iprodione applications resulted in consistent reductions in the values of bacterial alpha diversity (Table 2). The result was in agreement with the finding of Verdenelli et al. (2012) that iprodione application had significantly negative impacts on microbial community diversity in both agricultural and grassland soils. Moreover, repeated iprodione applications led to declines in the relative abundances of phyla Chloroflexi and Acidobacteria (Fig. 4). The Chloroflexi is associated with the second step of soil nitrification and plays key roles in soil N cycling (Sorokin et al., 2012). As decomposers in soil environment, Acidobacteria could degrade torganic matters derived from plants and soil animals, maintaining soil nutrient cycling and energy flow (Ward e t al., 2009). These changes in the relative abundances of functional bacteria indicated that iprodione applications might slow down soil organic matter turnover and soil nitrification.In this study, we found that repeated iprodione applications, alone or together with the DMPP, caused significant changes in the soil bacterial community structure. In contrast, Wang et al. (2004) showed that a single iprodione application at lower dosage was not detrimental to the soil bacterial community. Given that iprodione was often repeatedly applied at high dosages in intensive agricultural systems, shifts in bacterial community as observed in this study could lead to a series of alternations in soil microbial communities and soil C and nutrient cycling. Therefore, more attention should be paid to the long-term ecotoxic effects caused by repeated applications. 4.2. Effects of DMPP application on soil enzyme activities and bacteria Compared with the CK treatment, DMPP application resulted in significantly lower soil urease activity, (Fig. 1), which was largely responsible for the decline in GMEA in the DAA treatment. It is interesting to note that soil ÃŽ ²-glucosidase, as a proxy for soil organic matter mineralization capacity, was also negatively affected by the DMPP application. Maienza et al. (2014) revealed that DMPP application had adverse impacts on the growth of soil heterotrophic bacteria and fungi. All these results suggested that DMPP might have the potential to slow down soil organic matter decompositions, and this could get supports from previous research results that DMPP could reduce soil carbon dioxide (CO2) and methane (CH4) emissions (Weiske et al., 2001; Maris et al., 2015). The LEfSe analysis revealed that Gemmatimonadetes and Cytophagia families increased following DMPP application (Fig. 6). The Gemmatimonadetes containing photosynthesis genes could assimilate CO2 into organic material via phototrophic pathway and transform solar radiation into metabolic energy, which plays an important role in the increase of soil organic matter content (Zeng et al., 2014). Some strains of the Cytophagaceae family have the nifH gene and have the potential to increase soil N content by biological N fixation (Xu et al., 2014). Dong et al. (2013b) also reported that DMPP application could significantly increase soil nifH gene abundances. These results indicated that apart from inhibiting soil nitrification, DMPP application might have the potential to improve soil C and N contents via (1) decreasing CO2, CH4 andNOX emission;(2) slowing down soil organic matter decompositions; (3) promoting the flourish of some functional microorganisms; and (4) promoting activity of N-fixing bacteria. Consequently, although soil urease and ÃŽ ²-glucosidase were inhibited, the whole soil bacterial biomass increased following DMPP application (Fig. 2), and this is also one of the positive effects generate d by DMPP application. An increase in soil bacterial biomass is commonly found in parallel with increases in community diversity (Weinbauer et al., 2007; Torstensson et al., 2015). Based on the data presented in Table 2, we found that DMPP application promoted, rather than decreased, soil bacterial community diversity, which is consisted with the result of Dong et al. (2013a). Furthermore, both the PCoA and UPMGA indicated that a large proportion of soil bacterial community in the DAA treatment overlapped with that in the C