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Effects of fungicide iprodione and nitrification inhibitor 3, 4-dimethylpyrazole phosphate on soil enzyme and bacterial properties
Science of the Total Environment 599–600 (2017) 254–263
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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv
Effects of fungicide iprodione and nitrification inhibitor 3, 4-dimethylpyrazole phosphate on soil enzyme and bacterial properties Manyun Zhang a,b,⁎, Weijin Wang a,c, Yaling Zhang a, Ying Teng b,⁎⁎, Zhihong Xu a,⁎⁎ a b c
Environmental Futures Research Institute, School of Natural Sciences, Griffith University, Brisbane, Queensland 4111, Australia Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China Department of Science, Information Technology and Innovation, Dutton Park, Queensland 4102, Australia
H I G H L I G H T S
G R A P H I C A L
A B S T R A C T
• Iprodione applications decreased soil enzyme activities and bacterial biomass. • Iprodione applications increased the relative abundance of Proteobacteria. • DMPP application inhibited activities of urease, but increased bacterial biomass. • Iprodione, alone or together with DMPP, changed bacterial community structure.
Repeated iprodione applications decreased soil enzyme activities, bacterial biomass and community diversity. DMPP application increased soil bacterial biomass, and relative to iprodione applications alone, extra DMPP application alleviated the toxic effects of iprodione applications on soil bacterial biomass and community diversity. Moreover, bacterial community structure was changed by repeated iprodione applications, alone or together with the DMPP.
a r t i c l e
i n f o
Article history: Received 8 January 2017 Received in revised form 1 May 2017 Accepted 1 May 2017 Available online xxxx Editor: D. Barcelo Keywords: Agrochemicals Soil enzyme 16S rRNA gene Bacterial community diversity and structure
a b s t r a c t Agrochemical applications may have unintended detrimental effects on soil microorganisms 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 microorganisms. In this study, an incubation experiment was established to evaluate the potential influences of the fungicide iprodione and the nitrification inhibitor 3, 4-dimethylpyrazole phosphate (DMPP) on soil enzyme activities and bacterial properties. Weekly iprodione applications decreased the activities of all enzymes tested, and DMPP application inhibited soil urease activity. Compared with the blank control, bacterial 16S rRNA gene abundance decreased following repeated iprodione applications, but increased after DMPP application. After 28 days of incubation, the treatment receiving both iprodione and DMPP application had higher bacterial 16S rRNA gene abundance and Shannon diversity index than the treatment with iprodione applications alone. Repeated iprodione applications significantly increased the relative abundance of Proteobacteria, but decreased the relative abundances of Chloroflexi and Acidobacteria. Simultaneously, bacterial community structure was changed by repeated iprodione applications, alone or together with DMPP. These results showed that repeated iprodione applications exerted negative effects on soil enzyme activities, bacterial biomass and community diversity. Moreover, relative to iprodione
⁎ Correpondence to: M Zhang Environmental Futures Research Institute, School of Natural Sciences, Griffith University, Brisbane, Queensland 4111, Australia. ⁎⁎ Corresponding authors. E-mail addresses: [email protected] (M. Zhang), [email protected] (Y. Teng), zhihong.xu@griffith.edu.au (Z. Xu).
http://dx.doi.org/10.1016/j.scitotenv.2017.05.011 0048-9697/© 2017 Elsevier B.V. All rights reserved.
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applications alone, additional DMPP application could alleviate the toxic effects of iprodione applications on bacterial biomass and community diversity. © 2017 Elsevier B.V. All rights reserved.
1. Introduction Fungicides play important roles in protecting 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 intensified fungicide applications in recent decades (O'Maille, 2015). Previous research has shown that in some developing countries, fungicide application rate was as high as 8 kg ha− 1 y−1 (Liu et al., 2015). Iprodione, as a broad-spectrum fungicide, has been widely used in intensive agriculture to control the phytopathies of crops, and iprodione residues have already been detected in water (Goewie and Hogendoorn, 1985; Sauret et al., 2006), soil (Leistra and Matser, 2004) and farm products (Picó et al., 2004; Juan-García et al., 2005; Angioni et al., 2012). According to a report by U.S. Department of Agriculture (2014), the iprodione was the most frequently detected agrochemical in the imported fruit, and it was even detected in baby food. Besides the crop phytopathies, low utilization efficiency of nitrogen (N) fertilizer and nitrous oxide (N2O) emission are also worldwide problems in agricultural production (Clough et al., 2007; Menéndez et al., 2012). As a result, nitrification inhibitors are increasingly applied to reduce fertilizer N loss, and one the most widely used nitrification inhibitors in recent years is 3, 4-dimethylpyrazole phosphate (DMPP) (Menéndez et al., 2012; Florio et al., 2014). Fungicides are designed to control fungal pathogens, but their lethal effects are not constrained to the fungi only (Muñoz-Leoz et al., 2013; Schnug et al., 2015; Fang et al., 2016). Once entering into agricultural soils, 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, because of its wide and repeated applications in agricultures (Leistra and Matser, 2004; Verdenelli et al., 2012; Morales et al., 2013). 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 occur in intensively managed cropping systems. Furthermore, the iprodione and other agrochemicals (such as DMPP) may be applied into agriculture soils simultaneously. To the best of our knowledge, few studies have been conducted to evaluate the interactive effects of these different agrochemicals. Researches are, therefore, required to better understand the effects of combined iprodione and DMPP applications on soil enzyme and bacterial properties. In this study, the iprodione and DMPP were applied into an agricultural soil. Soil enzyme activity, bacterial 16S rRNA gene abundance and community structure were determined. The objectives of this study were to (1) assess the effects of iprodione and DMPP applications on soil enzyme activities; (2) evaluate the impacts of these two agrochemicals on soil bacterial biomass (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 would improve our current understandings of the ecological risks of iprodione and DMPP applications, alone or together, to soil nutrient cycling and bacterial population. 2. Materials and methods 2.1. The agrochemicals and test soil A commercial wettable powder formulation of iprodione (Bayer Crop Science, Hangzhou, China) and a chemical reagent DMPP (purity
N97.0%; CIVI-CHEM, Shanghai, China) were used for soil treatments. Soil samples were taken from a vegetable farmland (36.78′ N, 118.67′ E) located in Shandong Province, China. The surface soils (0–20 cm) were collected, air-dried, mixed thoroughly and ground to pass through a 2 mm sieve. Selected physical and chemical properties of the soil were as follows: sand (50–2000 μm), 31.4 ± 1.4%; silt (2–50 μm), 36.9 ± 0.8%; clay (b 2 μm), 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; and 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 (NH+ 4 -N) was available for soil nitrification. 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 and each application at 1.5 mg kg− 1 dry soil (the frequency followed the instruction); 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 the Treatments 2 and 3. Each treatment was prepared in triplicates. The iprodione and DMPP were dissolved in double distilled H2O (ddH2O) and then applied into the test soils. Sixty glass jars (4 treatments × 5 sampling time × 3 replications) were filled with the treated soils at 150 g dry weight equivalent per bottle. Soil water content was adjusted to 60% waterholding capacity and was maintained with ddH2O addition. The treated soils were then incubated at 28 °C in darkness. After 0, 7, 14, 21 and 28 days of incubation, three jars per treatment were sampled for the analyses of soil enzyme and bacterial properties. 2.3. Determinations of soil enzyme activities Soil β-glucosidase activity was determined using a soil enzyme assay kit (Catalogue No. HK000218, Toyongbio Company, Shanghai, China), and the procedure followed manufacturer's protocol. The soil samples were treated with toluene and then incubated with the p-nitrophenylβ-d-glucoside and citrate-phosphate buffer (pH = 6.0) for 1 h at 37 °C. Concentrations of the reaction product (p-nitrophenol) were determined with a spectrophotometer at 410 nm, and the β-glucosidase activity was expressed as μg p-nitrophenol g− 1 dry soil d− 1. Potential urease, acid phosphatase and alkaline phosphatase activities were determined with the commercially available quantitative analytical kits supplied by the Jiancheng Bioengineering Institute (Nanjing, China). Soil samples were previously treated with the toluene to avoid microbial proliferation during enzyme assays. Urease activity assay (Catalogue No. T017) consisted of a 24 h incubation of test soil at 37 °C in the presence of urea (100 g L− 1) and citrate buffer (pH = 6.7). The formed NH+ 4 -N was quantified by the indophenol blue method, and the urease −1 dry soil d−1. The determinaactivity was expressed as μg NH + 4 -N g tions of soil acid and alkaline phosphatases followed the analytical kits (Catalogue No. T008 and T009). Hydrolyses of disodium phenyl phosphate were performed at pH = 5.0 (acetate buffer) and pH = 9.4 (borate buffer) for 24 h at 37 °C to determine the activities of acid and alkaline phosphatases, respectively. The formed phenol was determined at 660 nm, and the phosphate activity was expressed as μg phenol g−1 dry soil d−1.
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Soil arylsulphatase activity was determined according to the method of Floch et al. (2009) with minor modifications. Soil samples were incubated with p-nitrophenyl sulfate (reaction substrate) and 0.5 M acetate buffer (pH = 5.8). The reaction was halted by the additions of 0.5 M CaCl2 and 1 M NaOH after 1 h of incubation. The p-nitrophenol concentrations were measured with a spectrophotometer at 410 nm, and soil arylsulphatase activity was expressed as μg p-nitrophenol g−1 dry soil d−1.
The geometric means of enzyme activities (GMEA) were calculated to integrate data from variables that have different units and variation ranges. The calculation was made according to the method of Hinojosa et al. (2004).
1=5
GMEA ¼ ðGlu Ure Acp Alp AryÞ
ð1Þ
Fig. 1. Effects of iprodione and DMPP applications on soil enzyme activities: (A) β-glucosidase, (B) urease, (C) acid phosphatase, (D) alkaline phosphatase and (E) arylsulphatase. CK, without iprodione or DMPP applications; IPR, weekly iprodione applications; DAA, nitrification inhibitor DMPP application at commencement; and I + D, weekly iprodione applications and DMPP application at commencement. Different lower case letters indicate significant differences (P b 0.05) among treatments for a particular incubation time, and different capital letters indicate significant differences (P b 0.05) among different incubation times for a particular treatment.
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where Glu, Ure, AcP, AlP and Ary were soil β-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 sample was extracted from approximately 0.5 g of soil with a Fast DNA SPIN Kit for Soil (MP Biomedicals). Soil bacterial biomass was estimated by bacterial 16S rRNA gene abundance, which was quantified using the qPCR with the universal primers 515F (5′-GTGCCAGCMGCCGCGG-3′) and 907R (5′-CCGTCAATT CMTTTRAGTTT-3′). The standard curve of qPCR was obtained by performing serial dilutions of the plasmid with bacterial 16S rRNA gene. Each qPCR reaction was prepared in a 20.0 μL of solution consisting of 10.0 μL of SYBR® Premix Ex Taq™ (TaKaRa, Dalian, China), 7.6 μL of sterile ddH2O, 2.0 μL of soil template DNA and 0.4 μL of universal primers (Zhang et al., 2016). 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. A melting curve step was added to check the specificity of amplification product. Negative control was run with sterile ddH2O as the template. Testing of the diluted DNA suspension indicated that there were no detectable inhibitions for the qPCR, and the amplification efficiencies in this study were 110.0%–114.5%, with R2 N 0.995. 2.5. The Illumina MiSeq and sequenced data analysis At the end of incubation, soil bacterial community was also analyzed. 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) approximately 300 bp reads were truncated at the end side, receiving an average quality score of b20 over a 10 bp sliding window, and shorter reads (truncated length b 50 bp) were discarded; (2) raw reads with vague bases were discarded; and (3) only sequences with N 10 bp overlap were assembled with reference to the overlapped sequences, and the unassembled reads were discarded (Wang et al., 2016). Operational taxonomic units (OTUs) were clustered at 97% identity via the UPARSE (version 7.1) for assessing community richness (Ace and Chao1 richness estimators) and community diversity (Shannon and Simpson diversity indices). The Ace and Chao1 richness estimators were nonparametric and abundance-based estimators, which could predict the true value of taxa based on the proportion of rare taxa in a sample (Sogin et al., 2006; Gihring et al., 2012). The Shannon and Simpson diversity indices were used for heterogeneity assessments, and the main difference between them was in the calculation method of taxa abundance. The phylogenetic affiliations of bacterial 16S rRNA gene sequences were analyzed with the SILVA database. 2.6. Statistical analysis Two-way analysis of variance was employed to assess the effects of agrochemical applications, incubation times and their interactions on
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enzyme activities and bacterial 16S rRNA gene abundances. Duncan's multiple range test was further employed to compare statistically significant differences (P b 0.05) of the means among different treatments for each sampling time and among different incubation times for a specific treatment. Linear discriminant analysis effect size (LEfSe) method (http://huttenhower.sph.harvard.edu/galaxy/root) was used to identify the 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) clustering analysis. 3. Results 3.1. Soil enzyme activities and GMEA The soil enzyme activities were significantly affected by the treatments, but the interactions between treatments and sampling times were not significant for the β-glucosidase and alkaline phosphatase activities (Table S1). The activities of soil β-glucosidase, urease and arylsulfatase in the CK treatment significantly (P b 0.05) increased during the first 7 days of incubation (Fig. 1). By the end of the incubation, soil enzyme activities in the CK treatment changed from 1004 ± 51 to 1278 ± 133 μg p-nitrophenol g−1 dry soil d−1 for the β-glucosidase, −1 dry soil d−1 for the urefrom 60.9 ± 4.9 to 323.0 ± 19.6 μg NH+ 4 -N g −1 ase, from 698 ± 129 to 802 ± 76 μg phenol g dry soil d−1 for the acid phosphatase, from 208.4 ± 11.8 to 210.5 ± 12.0 μg phenol g−1 dry soil d−1 for the alkaline phosphatase, and from 502.1 ± 64.8 to 690.5 ± 55.2 μg p-nitrophenol g−1 dry soil d−1 for the sulphatase. After 7 days of incubation, there were no significant differences in soil enzyme activities between the 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 did not exert significantly negative effects on soil phosphatase or arylsulphatase activities during the whole incubation period, but soil urease activity was consistently inhibited by the DMPP application (76.5% of the CK treatment after 28 days of incubation). 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 (P b 0.05) during the first 7 days and remained relatively stable during the following 21 days of incubation. 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 CK counterparts from 7 days onwards. Consistent with the trend presented in Fig. 1, the GMEA in the I + D treatment was significantly (P b 0.05) higher than its IPR counterpart after 28 days of incubation. 3.2. Soil bacterial 16S rRNA gene abundances Both the treatments and sampling times 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 dry soil during the 28 days of incubation (Fig. 2). A single
Table 1 The geometric means of enzyme activities of the four treatments. Treatments
0 day
CK IPR DAA I+ D
337.45 ± 349.61 ± 342.58 ± 346.81 ±
7 day 4.54 aB 27.2 aD 7.51 aB 6.81 aD
547.01 ± 489.02 ± 498.44 ± 519.77 ±
14 day 36.34 aA 13.26 bA 21.68 bA 13.73 abA
509.86 ± 413.68 ± 481.28 ± 463.85 ±
21 day 27.15 aA 16.04 cB 14.44 abA 6.94 bC
506.94 ± 403.18 ± 481.59 ± 466.85 ±
28 day 25.32 aA 31.82 bBC 12.32 aA 16.6 aC
544.35 ± 364.46 ± 484.35 ± 488.14 ±
25.24 aA 12.23 cCD 28.34 b A 7.16 bB
Values represent mean ± standard deviation of triplicate measurements. Different lower case letters in the same column indicate significant differences (P b 0.05) among treatments at a particular incubation time, and different capital letters in the same row indicate significant differences (P b 0.05) among different incubation times in a particular treatment. Treatment abbreviations and explanations are the same as those in Fig. 1.
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Fig. 2. Effects of iprodione and DMPP applications on soil bacterial 16S rRNA gene abundances. Treatment abbreviations and explanations are the same as those in Fig. 1. Different lower case letters indicate significant differences (P b 0.05) among treatments at a particular incubation time, and different capital letters indicate significant differences (P b 0.05) among different incubation times for a particular treatment.
iprodione application generated a negligible effect on soil bacterial 16S rRNA gene abundance after 7 days of incubation, but repeated iprodione applications significantly (P b 0.05) decreased soil bacterial 16S rRNA gene abundances, 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. At the end of incubation, bacterial 16S rRNA gene abundance in the I + D treatment was significantly (P b 0.05) higher than that in the IPR treatment.
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 richness estimators, and Shannon diversity index for the CK treatment were 1863 ± 37, 1853 ± 24 and 5.55 ± 0.15, respectively (Table 2). The IPR treatment had the lowest richness estimators and Shannon diversity index among the four treatments, while the I + D treatment had the highest richness estimators and Shannon diversity index. The Simpson index showed no significant differences among the four treatments. Relative to the CK treatment, DMPP application did not exert significantly adverse effects on the richness estimators and diversity indices.
3.3. Soil bacterial community diversity 3.4. Soil bacterial community structure A total of 624,067 raw sequences (N 200 bp) were obtained from the four treatments, and the average length of valid sequences was 396.7. The similarities and differences among OTUs of the four treatments were demonstrated in a four-set Venn diagram (Fig. 3). The unique
The OTUs could be assigned into 11 predominant phyla in the following orders: Proteobacteria, Actinobacteria, Gemmatimonadetes, Chloroflexi, Firmicutes, Acidobacteria, Bacteroidetes, Planctomycetes, Nitrospirae, Saccharibacteria and Verrucomicrobia (Fig. 4A). The relative abundances of these phyla varied among the different treatments. The phylum Proteobacteria was the most abundant, and the relative abundances were 37.2%, 45.9%, 36.4% and 39.8% for the CK, IPR, DAA and I + D treatments, respectively. There were no significant differences in relative abundances of the predominant phyla between the CK and DAA treatments. However, compared with the CK treatment, repeated iprodione applications significantly (P b 0.05) increased the relative abundance of phylum Proteobacteria, but decreased the relative Table 2 The richness estimators and diversity indices of the four treatments at the end of incubation. Treatments
CK IPR DAA I+ D Fig. 3. A Venn diagram demonstrating the unique and common bacterial OTUs among the different treatments. Treatment abbreviations and explanations are the same as those in Fig. 1.
Richness estimators
Diversity indices
Ace
Shannon
Simpson
5.55 ± 0.15 ab 5.40 ± 0.05 b 5.56 ± 0.12 ab 5.64 ± 0.10 a
0.018 ± 0.008 a 0.017 ± 0.001 a 0.015 ± 0.003 a 0.013 ± 0.001 a
1863 ± 1804 ± 1831 ± 1878 ±
Chao 1 37 a 14 b 20 ab 34 a
1853 ± 1772 ± 1811 ± 1888 ±
24 ab 17 c 46 bc 54 a
Values represent mean ± standard deviation of triplicate measurements. Different lower case letters in the same column indicate significant differences (P b 0.05) among treatments. Treatment abbreviations and explanations are the same as those in Fig. 1.
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Fig. 4. Soil bacterial taxonomic distribution at the phylum level: (A) the predominant phyla and (B) the phyla with significantly different abundances among the four treatments. Treatment abbreviations and explanations are the same as those in Fig. 1.
abundances of phyla Chloroflexi and Acidobacteria (Fig. 4B). At the genus level, the genera Micromonospora, Gemmatimonas, Haliangium and Bacillus accounted for large proportions in the twelve soil samples (Fig. S1). 3.5. Comparison of bacterial community structure LEfSe analysis demonstrated that there were significant associations among predominant bacterial taxa in the four treatments (Fig. 5). The predominant bacterial taxa were the families Opitutaceae and Xanthomonadales in the CK treatment, the families Xanthomonadaceae, Erythrobacteraceae, Sphingomonadaceae, Sphingomonadales and Rhodocyclaceae in the IPR treatment, the families Gemmatimonaceae and Cytophagaceae in the DAA treatment, and the families Gaiellaceae, Microbacteriaceae, Nocardioidaceae, and Methylobacteriaceae in the I + D treatment. The result of LEfSe analysis further revealed that, consistent with the results shown in Fig. 4, the relative abundance of Proteobacteria increased following repeated 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%). There was no significant difference in the PCoA values (both PCoA1 and PCoA2) between the
CK and DAA treatments (Fig. 6A). This suggested that soil bacterial community structure was not significantly altered by the DMPP application. However, relative to the CK treatment, 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 trend presented in the two-dimensional PCoA plot, four clusters could be grouped for these twelve soil samples (Fig. 6B): Cluster 1 contained samples of the DAA treatment, CK_1 and CK_2; the CK_3 sample alone was classified into Cluster 2; Cluster 3 consisted of three samples of the 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 toxicities to soil bacteria on various aspects including the biomass and community diversity (Duah-Yentumi and Johnson, 1986; Verdenelli et al., 2012). Previous study revealed that the principal degradation metabolite of iprodione (3,5-dichloroanniline) was more biologically toxic and stable
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Fig. 5. The taxa of bacteria with significantly different abundance in the treatments identified with the linear discriminant analysis effect size method. Treatment abbreviations and explanations are the same as those in Fig. 1.
than its parent compound (Athiel et al., 1995). Consequently, both the iprodione and its degradation metabolites have the potential to inhibit the non-target bacteria. On the other hand, the broad-spectrum fungicides could inhibit fungal proliferation, which could further exhibit the indirect impacts on soil bacterial community (Muñoz-Leoz et al., 2011; Verdenelli et al., 2012). The β-glucosidase, urease, phosphatase and arylsulfatase are essential in the cycling of C, N, phosphorus (P) and sulfur (S) in soils, respectively (Muñoz-Leoz et al., 2011). The activities of these enzymes tended to decline after repeated iprodione applications (Fig. 1), 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-availabilities 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 decline of soil bacterial biomass caused by iprodione applications might be a reason of the decreases of soil enzyme activities in the IPR treatment. Soil bacterial 16S rRNA gene (both the abundance and community diversity) has been used as an important eco-physiological index for assessing soil contamination (Sipilä 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 an earlier finding of Duah-Yentumi and Johnson (1986) that the impacts of iprodione applications 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
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Fig. 6. The (A) principal coordinate analysis and (B) unweighted pair group method with arithmetic mean clustering analysis of soil bacterial community. Treatment abbreviations and explanations are the same as those in Fig. 1.
degradation products following repeated fungicide applications increased the eco-toxicities (Trabue et al., 2001; Zhang et al., 2016). Direct measurement of soil bacterial community could reveal some shifts in the community 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 reductions in the values of richness estimators and Shannon diversity index (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 a key role in soil N cycling (Sorokin et al., 2012). As decomposers in soil environment, the Acidobacteria could degrade organic matters derived from plants and soil animals, maintaining soil nutrient cycling and energy flow (Ward et 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 soil bacterial community structure (Fig. 6). In contrast, Wang et al. (2004) showed that a single iprodione application was not detrimental to the soil bacterial community. Given that the iprodione was often repeatedly applied at high dosages in intensive agriculture, shifts in the bacterial community as observed in this study could lead to a series of alternations in soil microbial community and nutrient cycling. Therefore, more attention should be paid to the long-term eco-toxic effects caused by repeated iprodione applications. 4.2. Effects of DMPP application on soil enzyme and bacteria Compared with the CK treatment, DMPP application resulted in significantly lower soil urease activity (Fig. 1), which was largely responsible for declines in the GMEA of the DAA treatment (Table 1). It is interesting to note that soil β-glucosidase, as a proxy for soil organic matter mineralization capacity, tended to be negatively affected by DMPP application. Maienza et al. (2014) revealed that DMPP application had adverse impacts on the growths of soil heterotrophic bacteria and fungi. These results suggested that DMPP might have the potential to slow down soil organic matter decomposition. This was in agreement with the previous research results that DMPP application could reduce soil carbon dioxide (CO2) and methane (CH4) emissions (Weiske et al., 2001; Maris et al., 2015). The LEfSe analysis further revealed that in
the DAA treatment, the families Gemmatimonadetes and Cytophagia played key functional roles in soil bacterial community (Fig. 5). The Gemmatimonadetes containing photosynthesis gene can assimilate CO2 into organic material via a phototrophic pathway and transform solar radiation into metabolic energy, which contributes to the increase of soil organic matter content (Zeng et al., 2014). Some strains of the family Cytophagaceae have the nifH gene and can 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 abundance. 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 and N2O emissions; (2) slowing down soil organic matter decompositions; (3) promoting the proliferations of some functional microorganisms; and (4) promoting the activities of N-fixing bacteria (Weiske et al., 2001; Dong et al., 2013b; Maris et al., 2015). Consequently, although soil urease and β-glucosidase were inhibited, the whole soil bacterial biomass increased following DMPP application (Fig. 2), which is also one of the positive effects generated by DMPP application. Based on the data presented in Table 2, we found that DMPP application did not adversely affect soil bacterial community diversity. The result was in agreement with the finding 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 CK treatment, which indicated that DMPP application generated negligible negative effect on soil bacterial community. The result might be regarded as a biosafety evidence of DMPP. Taken together the results of bacterial biomass and community structure, it can be concluded that DMPP application at the recommended dosage is not detrimental to soil bacterial community. This conclusion is also supported by a previous study that DMPP application promoted a relatively active soil bacterial community (Dong et al., 2013a). 4.3. Interactive effects of iprodione and DMPP applications on soil enzyme and bacteria Soil microorganisms were usually considered to be N-limited, and extra N addition could result in shifts in the predominant microbial strategies, favoring a more active microbial community (Fierer et al., 2012). As mentioned above, DMPP application had the potential to improve soil C and N contents, which might have a bio-stimulation effect similar to that of organic N fertilizer application (Muñoz-Leoz et al., 2012). Consequently, extra DMPP application had the potential to reduce the negative effects of repeated iprodione applications on soil
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bacterial biomass (Fig. 2). Moreover, relative to the IPR treatment, extra DMPP application increased bacterial community diversity and positively stimulated the families Gaiellaceae, Microbacteriaceae, Nocardioidaceae and Methylobacteriaceae (Fig. 5). These microorganisms tended to be increased by organic matter additions and were capable of degrading a series of organic pollutants (Stevens et al., 2007; Tsiamis et al., 2012; Albuquerque and Costa, 2014). These results further indicated that DMPP application could stimulate the activities and relative abundances of biodegrading bacteria in soils contaminated with organic pollutants, alleviating the toxicities of iprodione applications. We here, based on soil enzyme activities, bacterial 16S rRNA abundance and community diversity, showed that the detrimental effects of repeated iprodione applications on bacterial population could be largely offset by the extra DMPP application. Despite the wellacknowledged functions of bacteria in soil nutrient cycling and pollutant decomposition, the assessments on combined effects of fungicides and other agrochemicals on soil bacteria are still in their nascent stages. Moreover, the impacts of applied agrochemicals on soil microorganisms also depend on soil properties and environmental conditions. Further studies are, therefore, required to evaluate how the soil types and environmental factors influence the effects of different agrochemicals on soil bacteria. 5. Conclusion Repeated iprodione applications exerted negative effects on the activities of soil enzymes associated with the cycling of C, N, P and S, bacterial biomass, and relative abundances of functional bacteria Chloroflexi and Acidobacteria. DMPP application inhibited soil urease activity, but increased soil bacterial biomass. Moreover, DMPP application at the recommended dosage was not detrimental to soil bacterial community, and relative to iprodione applications alone, extra DMPP application had the potential to alleviate the toxic effects of iprodione applications on soil bacterial population. Given that the iprodione is widely and repeatedly applied in intensive agriculture, more attentions should be paid to iprodione residues and their negative effects on soil environmental quality. Further field studies are also needed to evaluate how environmental factors influence the effects of these agrochemicals on soil microorganisms. Acknowledgements This work was financially supported by the Griffith University Ph.D. scholarships and operating fund and the Outstanding Youth Fund of Jiangsu Province (No. BK20150049). Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2017.05.011. References Albuquerque, L., Costa, M.S., 2014. The family gaiellaceae. In: Rosenberg, E., DeLong, E.F., Lory, S., Stackebrandt, E., Thompson, F. (Eds.), The prokaryotes: Actinobacteria. Springer, Heidelberg, pp. 357–360. Angioni, A., Porcu, L., Dedola, F., 2012. Determination of famoxadone, fenamidone, fenhexamid and iprodione residues in greenhouse tomatoes. Pest Manag. Sci. 68, 543–547. Athiel, P., Mercadier, C., Vega, D., Bastide, J., Davet, P., Brunel, B., Cleyet-Marel, J., 1995. Degradation of iprodione by a soil Arthrobacter-like strain. Appl. Environ. Microbiol. 61, 3216–3220. Bell, T.H., Hassan, S.E.D., Lauron-Moreau, A., Al-Otaibi, F., Hijri, M., Yergeau, E., St-Arnaud, M., 2014. Linkage between bacterial and fungal rhizosphere communities in hydrocarbon-contaminated soils is related to plant phylogeny. ISME J. 8, 331–343. Clough, T.J., Buckthought, L.E., Kelliher, F.M., Sherlock, R.R., 2007. Diurnal fluctuations of dissolved nitrous oxide (N2O) concentrations and estimates of N2O emissions from a spring-fed river: implications for IPCC methodology. Glob. Chang. Biol. 13, 1016–1027.
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Contents lists available at ScienceDirect
Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv
Effects of fungicide iprodione and nitrification inhibitor 3, 4-dimethylpyrazole phosphate on soil enzyme and bacterial properties Manyun Zhang a,b,⁎, Weijin Wang a,c, Yaling Zhang a, Ying Teng b,⁎⁎, Zhihong Xu a,⁎⁎ a b c
Environmental Futures Research Institute, School of Natural Sciences, Griffith University, Brisbane, Queensland 4111, Australia Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China Department of Science, Information Technology and Innovation, Dutton Park, Queensland 4102, Australia
H I G H L I G H T S
G R A P H I C A L
A B S T R A C T
• Iprodione applications decreased soil enzyme activities and bacterial biomass. • Iprodione applications increased the relative abundance of Proteobacteria. • DMPP application inhibited activities of urease, but increased bacterial biomass. • Iprodione, alone or together with DMPP, changed bacterial community structure.
Repeated iprodione applications decreased soil enzyme activities, bacterial biomass and community diversity. DMPP application increased soil bacterial biomass, and relative to iprodione applications alone, extra DMPP application alleviated the toxic effects of iprodione applications on soil bacterial biomass and community diversity. Moreover, bacterial community structure was changed by repeated iprodione applications, alone or together with the DMPP.
a r t i c l e
i n f o
Article history: Received 8 January 2017 Received in revised form 1 May 2017 Accepted 1 May 2017 Available online xxxx Editor: D. Barcelo Keywords: Agrochemicals Soil enzyme 16S rRNA gene Bacterial community diversity and structure
a b s t r a c t Agrochemical applications may have unintended detrimental effects on soil microorganisms 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 microorganisms. In this study, an incubation experiment was established to evaluate the potential influences of the fungicide iprodione and the nitrification inhibitor 3, 4-dimethylpyrazole phosphate (DMPP) on soil enzyme activities and bacterial properties. Weekly iprodione applications decreased the activities of all enzymes tested, and DMPP application inhibited soil urease activity. Compared with the blank control, bacterial 16S rRNA gene abundance decreased following repeated iprodione applications, but increased after DMPP application. After 28 days of incubation, the treatment receiving both iprodione and DMPP application had higher bacterial 16S rRNA gene abundance and Shannon diversity index than the treatment with iprodione applications alone. Repeated iprodione applications significantly increased the relative abundance of Proteobacteria, but decreased the relative abundances of Chloroflexi and Acidobacteria. Simultaneously, bacterial community structure was changed by repeated iprodione applications, alone or together with DMPP. These results showed that repeated iprodione applications exerted negative effects on soil enzyme activities, bacterial biomass and community diversity. Moreover, relative to iprodione
⁎ Correpondence to: M Zhang Environmental Futures Research Institute, School of Natural Sciences, Griffith University, Brisbane, Queensland 4111, Australia. ⁎⁎ Corresponding authors. E-mail addresses: [email protected] (M. Zhang), [email protected] (Y. Teng), zhihong.xu@griffith.edu.au (Z. Xu).
http://dx.doi.org/10.1016/j.scitotenv.2017.05.011 0048-9697/© 2017 Elsevier B.V. All rights reserved.
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applications alone, additional DMPP application could alleviate the toxic effects of iprodione applications on bacterial biomass and community diversity. © 2017 Elsevier B.V. All rights reserved.
1. Introduction Fungicides play important roles in protecting 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 intensified fungicide applications in recent decades (O'Maille, 2015). Previous research has shown that in some developing countries, fungicide application rate was as high as 8 kg ha− 1 y−1 (Liu et al., 2015). Iprodione, as a broad-spectrum fungicide, has been widely used in intensive agriculture to control the phytopathies of crops, and iprodione residues have already been detected in water (Goewie and Hogendoorn, 1985; Sauret et al., 2006), soil (Leistra and Matser, 2004) and farm products (Picó et al., 2004; Juan-García et al., 2005; Angioni et al., 2012). According to a report by U.S. Department of Agriculture (2014), the iprodione was the most frequently detected agrochemical in the imported fruit, and it was even detected in baby food. Besides the crop phytopathies, low utilization efficiency of nitrogen (N) fertilizer and nitrous oxide (N2O) emission are also worldwide problems in agricultural production (Clough et al., 2007; Menéndez et al., 2012). As a result, nitrification inhibitors are increasingly applied to reduce fertilizer N loss, and one the most widely used nitrification inhibitors in recent years is 3, 4-dimethylpyrazole phosphate (DMPP) (Menéndez et al., 2012; Florio et al., 2014). Fungicides are designed to control fungal pathogens, but their lethal effects are not constrained to the fungi only (Muñoz-Leoz et al., 2013; Schnug et al., 2015; Fang et al., 2016). Once entering into agricultural soils, 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, because of its wide and repeated applications in agricultures (Leistra and Matser, 2004; Verdenelli et al., 2012; Morales et al., 2013). 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 occur in intensively managed cropping systems. Furthermore, the iprodione and other agrochemicals (such as DMPP) may be applied into agriculture soils simultaneously. To the best of our knowledge, few studies have been conducted to evaluate the interactive effects of these different agrochemicals. Researches are, therefore, required to better understand the effects of combined iprodione and DMPP applications on soil enzyme and bacterial properties. In this study, the iprodione and DMPP were applied into an agricultural soil. Soil enzyme activity, bacterial 16S rRNA gene abundance and community structure were determined. The objectives of this study were to (1) assess the effects of iprodione and DMPP applications on soil enzyme activities; (2) evaluate the impacts of these two agrochemicals on soil bacterial biomass (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 would improve our current understandings of the ecological risks of iprodione and DMPP applications, alone or together, to soil nutrient cycling and bacterial population. 2. Materials and methods 2.1. The agrochemicals and test soil A commercial wettable powder formulation of iprodione (Bayer Crop Science, Hangzhou, China) and a chemical reagent DMPP (purity
N97.0%; CIVI-CHEM, Shanghai, China) were used for soil treatments. Soil samples were taken from a vegetable farmland (36.78′ N, 118.67′ E) located in Shandong Province, China. The surface soils (0–20 cm) were collected, air-dried, mixed thoroughly and ground to pass through a 2 mm sieve. Selected physical and chemical properties of the soil were as follows: sand (50–2000 μm), 31.4 ± 1.4%; silt (2–50 μm), 36.9 ± 0.8%; clay (b 2 μm), 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; and 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 (NH+ 4 -N) was available for soil nitrification. 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 and each application at 1.5 mg kg− 1 dry soil (the frequency followed the instruction); 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 the Treatments 2 and 3. Each treatment was prepared in triplicates. The iprodione and DMPP were dissolved in double distilled H2O (ddH2O) and then applied into the test soils. Sixty glass jars (4 treatments × 5 sampling time × 3 replications) were filled with the treated soils at 150 g dry weight equivalent per bottle. Soil water content was adjusted to 60% waterholding capacity and was maintained with ddH2O addition. The treated soils were then incubated at 28 °C in darkness. After 0, 7, 14, 21 and 28 days of incubation, three jars per treatment were sampled for the analyses of soil enzyme and bacterial properties. 2.3. Determinations of soil enzyme activities Soil β-glucosidase activity was determined using a soil enzyme assay kit (Catalogue No. HK000218, Toyongbio Company, Shanghai, China), and the procedure followed manufacturer's protocol. The soil samples were treated with toluene and then incubated with the p-nitrophenylβ-d-glucoside and citrate-phosphate buffer (pH = 6.0) for 1 h at 37 °C. Concentrations of the reaction product (p-nitrophenol) were determined with a spectrophotometer at 410 nm, and the β-glucosidase activity was expressed as μg p-nitrophenol g− 1 dry soil d− 1. Potential urease, acid phosphatase and alkaline phosphatase activities were determined with the commercially available quantitative analytical kits supplied by the Jiancheng Bioengineering Institute (Nanjing, China). Soil samples were previously treated with the toluene to avoid microbial proliferation during enzyme assays. Urease activity assay (Catalogue No. T017) consisted of a 24 h incubation of test soil at 37 °C in the presence of urea (100 g L− 1) and citrate buffer (pH = 6.7). The formed NH+ 4 -N was quantified by the indophenol blue method, and the urease −1 dry soil d−1. The determinaactivity was expressed as μg NH + 4 -N g tions of soil acid and alkaline phosphatases followed the analytical kits (Catalogue No. T008 and T009). Hydrolyses of disodium phenyl phosphate were performed at pH = 5.0 (acetate buffer) and pH = 9.4 (borate buffer) for 24 h at 37 °C to determine the activities of acid and alkaline phosphatases, respectively. The formed phenol was determined at 660 nm, and the phosphate activity was expressed as μg phenol g−1 dry soil d−1.
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Soil arylsulphatase activity was determined according to the method of Floch et al. (2009) with minor modifications. Soil samples were incubated with p-nitrophenyl sulfate (reaction substrate) and 0.5 M acetate buffer (pH = 5.8). The reaction was halted by the additions of 0.5 M CaCl2 and 1 M NaOH after 1 h of incubation. The p-nitrophenol concentrations were measured with a spectrophotometer at 410 nm, and soil arylsulphatase activity was expressed as μg p-nitrophenol g−1 dry soil d−1.
The geometric means of enzyme activities (GMEA) were calculated to integrate data from variables that have different units and variation ranges. The calculation was made according to the method of Hinojosa et al. (2004).
1=5
GMEA ¼ ðGlu Ure Acp Alp AryÞ
ð1Þ
Fig. 1. Effects of iprodione and DMPP applications on soil enzyme activities: (A) β-glucosidase, (B) urease, (C) acid phosphatase, (D) alkaline phosphatase and (E) arylsulphatase. CK, without iprodione or DMPP applications; IPR, weekly iprodione applications; DAA, nitrification inhibitor DMPP application at commencement; and I + D, weekly iprodione applications and DMPP application at commencement. Different lower case letters indicate significant differences (P b 0.05) among treatments for a particular incubation time, and different capital letters indicate significant differences (P b 0.05) among different incubation times for a particular treatment.
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where Glu, Ure, AcP, AlP and Ary were soil β-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 sample was extracted from approximately 0.5 g of soil with a Fast DNA SPIN Kit for Soil (MP Biomedicals). Soil bacterial biomass was estimated by bacterial 16S rRNA gene abundance, which was quantified using the qPCR with the universal primers 515F (5′-GTGCCAGCMGCCGCGG-3′) and 907R (5′-CCGTCAATT CMTTTRAGTTT-3′). The standard curve of qPCR was obtained by performing serial dilutions of the plasmid with bacterial 16S rRNA gene. Each qPCR reaction was prepared in a 20.0 μL of solution consisting of 10.0 μL of SYBR® Premix Ex Taq™ (TaKaRa, Dalian, China), 7.6 μL of sterile ddH2O, 2.0 μL of soil template DNA and 0.4 μL of universal primers (Zhang et al., 2016). 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. A melting curve step was added to check the specificity of amplification product. Negative control was run with sterile ddH2O as the template. Testing of the diluted DNA suspension indicated that there were no detectable inhibitions for the qPCR, and the amplification efficiencies in this study were 110.0%–114.5%, with R2 N 0.995. 2.5. The Illumina MiSeq and sequenced data analysis At the end of incubation, soil bacterial community was also analyzed. 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) approximately 300 bp reads were truncated at the end side, receiving an average quality score of b20 over a 10 bp sliding window, and shorter reads (truncated length b 50 bp) were discarded; (2) raw reads with vague bases were discarded; and (3) only sequences with N 10 bp overlap were assembled with reference to the overlapped sequences, and the unassembled reads were discarded (Wang et al., 2016). Operational taxonomic units (OTUs) were clustered at 97% identity via the UPARSE (version 7.1) for assessing community richness (Ace and Chao1 richness estimators) and community diversity (Shannon and Simpson diversity indices). The Ace and Chao1 richness estimators were nonparametric and abundance-based estimators, which could predict the true value of taxa based on the proportion of rare taxa in a sample (Sogin et al., 2006; Gihring et al., 2012). The Shannon and Simpson diversity indices were used for heterogeneity assessments, and the main difference between them was in the calculation method of taxa abundance. The phylogenetic affiliations of bacterial 16S rRNA gene sequences were analyzed with the SILVA database. 2.6. Statistical analysis Two-way analysis of variance was employed to assess the effects of agrochemical applications, incubation times and their interactions on
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enzyme activities and bacterial 16S rRNA gene abundances. Duncan's multiple range test was further employed to compare statistically significant differences (P b 0.05) of the means among different treatments for each sampling time and among different incubation times for a specific treatment. Linear discriminant analysis effect size (LEfSe) method (http://huttenhower.sph.harvard.edu/galaxy/root) was used to identify the 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) clustering analysis. 3. Results 3.1. Soil enzyme activities and GMEA The soil enzyme activities were significantly affected by the treatments, but the interactions between treatments and sampling times were not significant for the β-glucosidase and alkaline phosphatase activities (Table S1). The activities of soil β-glucosidase, urease and arylsulfatase in the CK treatment significantly (P b 0.05) increased during the first 7 days of incubation (Fig. 1). By the end of the incubation, soil enzyme activities in the CK treatment changed from 1004 ± 51 to 1278 ± 133 μg p-nitrophenol g−1 dry soil d−1 for the β-glucosidase, −1 dry soil d−1 for the urefrom 60.9 ± 4.9 to 323.0 ± 19.6 μg NH+ 4 -N g −1 ase, from 698 ± 129 to 802 ± 76 μg phenol g dry soil d−1 for the acid phosphatase, from 208.4 ± 11.8 to 210.5 ± 12.0 μg phenol g−1 dry soil d−1 for the alkaline phosphatase, and from 502.1 ± 64.8 to 690.5 ± 55.2 μg p-nitrophenol g−1 dry soil d−1 for the sulphatase. After 7 days of incubation, there were no significant differences in soil enzyme activities between the 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 did not exert significantly negative effects on soil phosphatase or arylsulphatase activities during the whole incubation period, but soil urease activity was consistently inhibited by the DMPP application (76.5% of the CK treatment after 28 days of incubation). 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 (P b 0.05) during the first 7 days and remained relatively stable during the following 21 days of incubation. 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 CK counterparts from 7 days onwards. Consistent with the trend presented in Fig. 1, the GMEA in the I + D treatment was significantly (P b 0.05) higher than its IPR counterpart after 28 days of incubation. 3.2. Soil bacterial 16S rRNA gene abundances Both the treatments and sampling times 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 dry soil during the 28 days of incubation (Fig. 2). A single
Table 1 The geometric means of enzyme activities of the four treatments. Treatments
0 day
CK IPR DAA I+ D
337.45 ± 349.61 ± 342.58 ± 346.81 ±
7 day 4.54 aB 27.2 aD 7.51 aB 6.81 aD
547.01 ± 489.02 ± 498.44 ± 519.77 ±
14 day 36.34 aA 13.26 bA 21.68 bA 13.73 abA
509.86 ± 413.68 ± 481.28 ± 463.85 ±
21 day 27.15 aA 16.04 cB 14.44 abA 6.94 bC
506.94 ± 403.18 ± 481.59 ± 466.85 ±
28 day 25.32 aA 31.82 bBC 12.32 aA 16.6 aC
544.35 ± 364.46 ± 484.35 ± 488.14 ±
25.24 aA 12.23 cCD 28.34 b A 7.16 bB
Values represent mean ± standard deviation of triplicate measurements. Different lower case letters in the same column indicate significant differences (P b 0.05) among treatments at a particular incubation time, and different capital letters in the same row indicate significant differences (P b 0.05) among different incubation times in a particular treatment. Treatment abbreviations and explanations are the same as those in Fig. 1.
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Fig. 2. Effects of iprodione and DMPP applications on soil bacterial 16S rRNA gene abundances. Treatment abbreviations and explanations are the same as those in Fig. 1. Different lower case letters indicate significant differences (P b 0.05) among treatments at a particular incubation time, and different capital letters indicate significant differences (P b 0.05) among different incubation times for a particular treatment.
iprodione application generated a negligible effect on soil bacterial 16S rRNA gene abundance after 7 days of incubation, but repeated iprodione applications significantly (P b 0.05) decreased soil bacterial 16S rRNA gene abundances, 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. At the end of incubation, bacterial 16S rRNA gene abundance in the I + D treatment was significantly (P b 0.05) higher than that in the IPR treatment.
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 richness estimators, and Shannon diversity index for the CK treatment were 1863 ± 37, 1853 ± 24 and 5.55 ± 0.15, respectively (Table 2). The IPR treatment had the lowest richness estimators and Shannon diversity index among the four treatments, while the I + D treatment had the highest richness estimators and Shannon diversity index. The Simpson index showed no significant differences among the four treatments. Relative to the CK treatment, DMPP application did not exert significantly adverse effects on the richness estimators and diversity indices.
3.3. Soil bacterial community diversity 3.4. Soil bacterial community structure A total of 624,067 raw sequences (N 200 bp) were obtained from the four treatments, and the average length of valid sequences was 396.7. The similarities and differences among OTUs of the four treatments were demonstrated in a four-set Venn diagram (Fig. 3). The unique
The OTUs could be assigned into 11 predominant phyla in the following orders: Proteobacteria, Actinobacteria, Gemmatimonadetes, Chloroflexi, Firmicutes, Acidobacteria, Bacteroidetes, Planctomycetes, Nitrospirae, Saccharibacteria and Verrucomicrobia (Fig. 4A). The relative abundances of these phyla varied among the different treatments. The phylum Proteobacteria was the most abundant, and the relative abundances were 37.2%, 45.9%, 36.4% and 39.8% for the CK, IPR, DAA and I + D treatments, respectively. There were no significant differences in relative abundances of the predominant phyla between the CK and DAA treatments. However, compared with the CK treatment, repeated iprodione applications significantly (P b 0.05) increased the relative abundance of phylum Proteobacteria, but decreased the relative Table 2 The richness estimators and diversity indices of the four treatments at the end of incubation. Treatments
CK IPR DAA I+ D Fig. 3. A Venn diagram demonstrating the unique and common bacterial OTUs among the different treatments. Treatment abbreviations and explanations are the same as those in Fig. 1.
Richness estimators
Diversity indices
Ace
Shannon
Simpson
5.55 ± 0.15 ab 5.40 ± 0.05 b 5.56 ± 0.12 ab 5.64 ± 0.10 a
0.018 ± 0.008 a 0.017 ± 0.001 a 0.015 ± 0.003 a 0.013 ± 0.001 a
1863 ± 1804 ± 1831 ± 1878 ±
Chao 1 37 a 14 b 20 ab 34 a
1853 ± 1772 ± 1811 ± 1888 ±
24 ab 17 c 46 bc 54 a
Values represent mean ± standard deviation of triplicate measurements. Different lower case letters in the same column indicate significant differences (P b 0.05) among treatments. Treatment abbreviations and explanations are the same as those in Fig. 1.
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Fig. 4. Soil bacterial taxonomic distribution at the phylum level: (A) the predominant phyla and (B) the phyla with significantly different abundances among the four treatments. Treatment abbreviations and explanations are the same as those in Fig. 1.
abundances of phyla Chloroflexi and Acidobacteria (Fig. 4B). At the genus level, the genera Micromonospora, Gemmatimonas, Haliangium and Bacillus accounted for large proportions in the twelve soil samples (Fig. S1). 3.5. Comparison of bacterial community structure LEfSe analysis demonstrated that there were significant associations among predominant bacterial taxa in the four treatments (Fig. 5). The predominant bacterial taxa were the families Opitutaceae and Xanthomonadales in the CK treatment, the families Xanthomonadaceae, Erythrobacteraceae, Sphingomonadaceae, Sphingomonadales and Rhodocyclaceae in the IPR treatment, the families Gemmatimonaceae and Cytophagaceae in the DAA treatment, and the families Gaiellaceae, Microbacteriaceae, Nocardioidaceae, and Methylobacteriaceae in the I + D treatment. The result of LEfSe analysis further revealed that, consistent with the results shown in Fig. 4, the relative abundance of Proteobacteria increased following repeated 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%). There was no significant difference in the PCoA values (both PCoA1 and PCoA2) between the
CK and DAA treatments (Fig. 6A). This suggested that soil bacterial community structure was not significantly altered by the DMPP application. However, relative to the CK treatment, 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 trend presented in the two-dimensional PCoA plot, four clusters could be grouped for these twelve soil samples (Fig. 6B): Cluster 1 contained samples of the DAA treatment, CK_1 and CK_2; the CK_3 sample alone was classified into Cluster 2; Cluster 3 consisted of three samples of the 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 toxicities to soil bacteria on various aspects including the biomass and community diversity (Duah-Yentumi and Johnson, 1986; Verdenelli et al., 2012). Previous study revealed that the principal degradation metabolite of iprodione (3,5-dichloroanniline) was more biologically toxic and stable
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Fig. 5. The taxa of bacteria with significantly different abundance in the treatments identified with the linear discriminant analysis effect size method. Treatment abbreviations and explanations are the same as those in Fig. 1.
than its parent compound (Athiel et al., 1995). Consequently, both the iprodione and its degradation metabolites have the potential to inhibit the non-target bacteria. On the other hand, the broad-spectrum fungicides could inhibit fungal proliferation, which could further exhibit the indirect impacts on soil bacterial community (Muñoz-Leoz et al., 2011; Verdenelli et al., 2012). The β-glucosidase, urease, phosphatase and arylsulfatase are essential in the cycling of C, N, phosphorus (P) and sulfur (S) in soils, respectively (Muñoz-Leoz et al., 2011). The activities of these enzymes tended to decline after repeated iprodione applications (Fig. 1), 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-availabilities 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 decline of soil bacterial biomass caused by iprodione applications might be a reason of the decreases of soil enzyme activities in the IPR treatment. Soil bacterial 16S rRNA gene (both the abundance and community diversity) has been used as an important eco-physiological index for assessing soil contamination (Sipilä 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 an earlier finding of Duah-Yentumi and Johnson (1986) that the impacts of iprodione applications 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
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Fig. 6. The (A) principal coordinate analysis and (B) unweighted pair group method with arithmetic mean clustering analysis of soil bacterial community. Treatment abbreviations and explanations are the same as those in Fig. 1.
degradation products following repeated fungicide applications increased the eco-toxicities (Trabue et al., 2001; Zhang et al., 2016). Direct measurement of soil bacterial community could reveal some shifts in the community 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 reductions in the values of richness estimators and Shannon diversity index (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 a key role in soil N cycling (Sorokin et al., 2012). As decomposers in soil environment, the Acidobacteria could degrade organic matters derived from plants and soil animals, maintaining soil nutrient cycling and energy flow (Ward et 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 soil bacterial community structure (Fig. 6). In contrast, Wang et al. (2004) showed that a single iprodione application was not detrimental to the soil bacterial community. Given that the iprodione was often repeatedly applied at high dosages in intensive agriculture, shifts in the bacterial community as observed in this study could lead to a series of alternations in soil microbial community and nutrient cycling. Therefore, more attention should be paid to the long-term eco-toxic effects caused by repeated iprodione applications. 4.2. Effects of DMPP application on soil enzyme and bacteria Compared with the CK treatment, DMPP application resulted in significantly lower soil urease activity (Fig. 1), which was largely responsible for declines in the GMEA of the DAA treatment (Table 1). It is interesting to note that soil β-glucosidase, as a proxy for soil organic matter mineralization capacity, tended to be negatively affected by DMPP application. Maienza et al. (2014) revealed that DMPP application had adverse impacts on the growths of soil heterotrophic bacteria and fungi. These results suggested that DMPP might have the potential to slow down soil organic matter decomposition. This was in agreement with the previous research results that DMPP application could reduce soil carbon dioxide (CO2) and methane (CH4) emissions (Weiske et al., 2001; Maris et al., 2015). The LEfSe analysis further revealed that in
the DAA treatment, the families Gemmatimonadetes and Cytophagia played key functional roles in soil bacterial community (Fig. 5). The Gemmatimonadetes containing photosynthesis gene can assimilate CO2 into organic material via a phototrophic pathway and transform solar radiation into metabolic energy, which contributes to the increase of soil organic matter content (Zeng et al., 2014). Some strains of the family Cytophagaceae have the nifH gene and can 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 abundance. 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 and N2O emissions; (2) slowing down soil organic matter decompositions; (3) promoting the proliferations of some functional microorganisms; and (4) promoting the activities of N-fixing bacteria (Weiske et al., 2001; Dong et al., 2013b; Maris et al., 2015). Consequently, although soil urease and β-glucosidase were inhibited, the whole soil bacterial biomass increased following DMPP application (Fig. 2), which is also one of the positive effects generated by DMPP application. Based on the data presented in Table 2, we found that DMPP application did not adversely affect soil bacterial community diversity. The result was in agreement with the finding 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 CK treatment, which indicated that DMPP application generated negligible negative effect on soil bacterial community. The result might be regarded as a biosafety evidence of DMPP. Taken together the results of bacterial biomass and community structure, it can be concluded that DMPP application at the recommended dosage is not detrimental to soil bacterial community. This conclusion is also supported by a previous study that DMPP application promoted a relatively active soil bacterial community (Dong et al., 2013a). 4.3. Interactive effects of iprodione and DMPP applications on soil enzyme and bacteria Soil microorganisms were usually considered to be N-limited, and extra N addition could result in shifts in the predominant microbial strategies, favoring a more active microbial community (Fierer et al., 2012). As mentioned above, DMPP application had the potential to improve soil C and N contents, which might have a bio-stimulation effect similar to that of organic N fertilizer application (Muñoz-Leoz et al., 2012). Consequently, extra DMPP application had the potential to reduce the negative effects of repeated iprodione applications on soil
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bacterial biomass (Fig. 2). Moreover, relative to the IPR treatment, extra DMPP application increased bacterial community diversity and positively stimulated the families Gaiellaceae, Microbacteriaceae, Nocardioidaceae and Methylobacteriaceae (Fig. 5). These microorganisms tended to be increased by organic matter additions and were capable of degrading a series of organic pollutants (Stevens et al., 2007; Tsiamis et al., 2012; Albuquerque and Costa, 2014). These results further indicated that DMPP application could stimulate the activities and relative abundances of biodegrading bacteria in soils contaminated with organic pollutants, alleviating the toxicities of iprodione applications. We here, based on soil enzyme activities, bacterial 16S rRNA abundance and community diversity, showed that the detrimental effects of repeated iprodione applications on bacterial population could be largely offset by the extra DMPP application. Despite the wellacknowledged functions of bacteria in soil nutrient cycling and pollutant decomposition, the assessments on combined effects of fungicides and other agrochemicals on soil bacteria are still in their nascent stages. Moreover, the impacts of applied agrochemicals on soil microorganisms also depend on soil properties and environmental conditions. Further studies are, therefore, required to evaluate how the soil types and environmental factors influence the effects of different agrochemicals on soil bacteria. 5. Conclusion Repeated iprodione applications exerted negative effects on the activities of soil enzymes associated with the cycling of C, N, P and S, bacterial biomass, and relative abundances of functional bacteria Chloroflexi and Acidobacteria. DMPP application inhibited soil urease activity, but increased soil bacterial biomass. Moreover, DMPP application at the recommended dosage was not detrimental to soil bacterial community, and relative to iprodione applications alone, extra DMPP application had the potential to alleviate the toxic effects of iprodione applications on soil bacterial population. Given that the iprodione is widely and repeatedly applied in intensive agriculture, more attentions should be paid to iprodione residues and their negative effects on soil environmental quality. Further field studies are also needed to evaluate how environmental factors influence the effects of these agrochemicals on soil microorganisms. Acknowledgements This work was financially supported by the Griffith University Ph.D. scholarships and operating fund and the Outstanding Youth Fund of Jiangsu Province (No. BK20150049). Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2017.05.011. References Albuquerque, L., Costa, M.S., 2014. The family gaiellaceae. In: Rosenberg, E., DeLong, E.F., Lory, S., Stackebrandt, E., Thompson, F. (Eds.), The prokaryotes: Actinobacteria. Springer, Heidelberg, pp. 357–360. Angioni, A., Porcu, L., Dedola, F., 2012. Determination of famoxadone, fenamidone, fenhexamid and iprodione residues in greenhouse tomatoes. Pest Manag. Sci. 68, 543–547. Athiel, P., Mercadier, C., Vega, D., Bastide, J., Davet, P., Brunel, B., Cleyet-Marel, J., 1995. Degradation of iprodione by a soil Arthrobacter-like strain. Appl. Environ. Microbiol. 61, 3216–3220. Bell, T.H., Hassan, S.E.D., Lauron-Moreau, A., Al-Otaibi, F., Hijri, M., Yergeau, E., St-Arnaud, M., 2014. Linkage between bacterial and fungal rhizosphere communities in hydrocarbon-contaminated soils is related to plant phylogeny. ISME J. 8, 331–343. Clough, T.J., Buckthought, L.E., Kelliher, F.M., Sherlock, R.R., 2007. Diurnal fluctuations of dissolved nitrous oxide (N2O) concentrations and estimates of N2O emissions from a spring-fed river: implications for IPCC methodology. Glob. Chang. Biol. 13, 1016–1027.
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