Effect of biochar additions to soil on nitrogen leaching, microbial biomass and bacterial community structure

European Journal of Soil Biology 74 (2016) 1e8

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

Original article

Effect of biochar additions to soil on nitrogen leaching, microbial biomass and bacterial community structure Nan Xu a, Guangcai Tan a, Hongyuan Wang b, *, Xiapu Gai b a

Key Laboratory for Heavy Metal Pollution Control and Reutilization, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China b Key Laboratory of Nonpoint Source Pollution Control, Ministry of Agriculture, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 July 2015 Received in revised form 16 February 2016 Accepted 17 February 2016 Available online xxx

Previous studies already demonstrated that biochar addition reduces nitrogen (N) leaching in soil, but little information is available about its effects on N leaching and bacterial community structure under the application of organic N. This study investigated the effects of corn-straw biochar under the application of urea (250 kg N ha
1) in layered soil columns. The PCR-amplified partial 16S rRNA genes in soil were sequenced before and after biochar treatment in order to assess the change of bacterial diversity and community structure utilizing the Illumina technology. With the application of 2% (B2), 4% (B4) and 8% (B8) biochar (mass ratio), the cumulative amount of total leached nitrogen was reduced by 18.8%, 19.5% and 20.2%, respectively (P < 0.05). More than 90% of the total nitrogen leaching was in the form of nitrate, and increasing amount of biochar resulted in reduced amount of N leaching. The water holding capacity, microbial biomass, pH, electrical conductivity, net N mineralization and respiration rate of the soil were all increased under biochar treatments, except that the B8 treatment decreased soil respiration rate and net N mineralization in comparison with B4. Bacterial diversity increased in biochar-amended soil and was positively correlated with the addition ratio of biochar. Dominant phyla across all samples were Proteobacteria, Acidobacteria, Chloroflexi, Bacteroidetes, Actinobacteria, Nitrospirae and Gemmatimonadetes. The relative abundance of Acidobacteria, Chloroflexi and Gemmatimonadetes decreased under biochar treatments, while that of Proteobacteria, Bacteroidetes and Actinobacteria increased. Overall, biochar increased water holding capacity, enhanced microbial biomass and changed bacterial community structure of the soil which may all have contributed to the reduction of nitrogen leaching. © 2016 Elsevier Masson SAS. All rights reserved.

Handling Editor: C.C. Tebbe Keywords: Biochar Nitrogen leaching Microbial biomass Bacterial community structure High-throughput sequencing

1. Introduction Excessive and/or unbalanced application of nitrogen fertilizers has caused the translocation of nitrogen (N) from farmlands into aquatic systems. Nitrogen, especially in the form of nitrate, is easily soluble in soil pore water, and readily infiltrates beneath the active soil layer with crop root. The N leaching may deplete soil fertility, accelerate soil acidification and reduce crop yields [1]. Moreover, N leaching is regarded as a major contributor to the eutrophication of surface and ground water [2]. Recently, the interest in applying biochar in soil has grown, which is due to the dual benefits of biochar on both climate change

* Corresponding author. E-mail address: [email protected] (H. Wang). http://dx.doi.org/10.1016/j.ejsobi.2016.02.004 1164-5563/© 2016 Elsevier Masson SAS. All rights reserved.

mitigation and positive soil amendment [3,4]. Biochar is a solid carbon-rich organic material generated by heating biomass under condition of limited or no oxygen [5]. Previous studies already demonstrated that biochar addition reduces N leaching. This could be attributed to the increase of cation and anion exchange capacities (CEC, AEC) of soil by the biochar material [6,7]. Another reason could be the physical retention of available N dissolved in the soil solution, as the water holding capacity also increased in biocharamended soil [6]. Although organic N, like urea, is widely used in agriculture, little information is available about the effect of biochar on N leaching and biological interactions under the application of organic N. Soil amendment with biochar could modify physical and chemical properties of the habitat for microbial colonization, and therefore affect soil microbial activity and community structure [8,9]. Transformation of microbial communities can be associated

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N. Xu et al. / European Journal of Soil Biology 74 (2016) 1e8

with the change of nutrient turnover and utilization after the addition of biochar [10]. The carbon-rich “Amazonian dark soils” (Arthrosols) are evidence, which host distinct microbial communities in comparison with adjacent carbon-poor soil, and have higher microbial biomass and diversity as well [11]. Various methods have been used to investigate the microbial communities in biochar-amended soils. The bacterial community composition in Brazilian anthrosols and adjacent soils was investigated by using traditional culturing [11]. Some studies adopted phospholipid fatty acids analysis to describe soil microbial communities responding to biochar [12,13]. PCR-denaturing gradient gel electrophoresis method was also widely deployed to analyze the changes of microbial structure under the addition of biochar [14,15]. However, most of these studies were conducted under a constant incubation condition, instead of the simulated N leaching condition which would be better. Also, the previous studies have only considered the dominant microbial taxa, while next-generation DNAsequencing technologies of PCR products now offer the potential to also detect less abundant taxa and thus giving a more complete picture of the microbial communities [16]. The main objectives of the present work were thus to (i) study the effect of biochar on N leaching through different soil layers during the application of organic N fertilizer to agricultural soil in layered columns; and (ii) to investigate the effect of biochar on soil bacterial community structure under simulated leaching condition via high-throughput sequencing method.

2. Materials and methods 2.1. Soil and biochar materials Plow layer soil was collected from a farmland at the fluvo-aquic soil test base of Chinese Academy of Agricultural Sciences, Changping County, Beijing, China. The soil was air-dried and passed through a 2 mm nylon sieve and mixed to get a homogeneous soil sample before use. Corn straw (Zea mays L.) was oven dried (80  C) and converted into biochar through slow pyrolysis using a furnace (Olympic 1823HE) in a N2 environment at 500  C for 1.5 h. Biochar samples were ground and sieved to get <1 mm sized particles. Basic properties of the tested soil and corn straw biochar are presented in Table 1. The soil had a high pH value due to the presence of many coral limestone fragments that released calcium ions. Compared to soil, biochar had a higher pH (10.0) and electrical conductivity (EC, 1319 mS cm
1). The pH and EC of soil and biochar (1:5 and 1:10 w/v, respectively) were measured in deionized water using a pH meter (Mettler Toledo Delta 320) and an electrical conductivity meter (DDS-307A), respectively. The concentrations of soil ammonium and nitrate were determined using a flow injector auto analyzer (Auto Analyzer 3, High Resolution Digital Colorimeter, Germany) in 1 M KCl extract (1:10 w/v) [17]. The CEC of soil and biochar was measured with the ammonium-acetate

compulsory displacement method [18]. Ash content was determined by combusting the biochar at 750  C for 6 h in open crucibles on a dry weight basis. The carbon (C), hydrogen (H), nitrogen (N) and oxygen (O) contents of biochar were measured using an elemental analyzer (vario PYRO cube, Germany). BrunauereEmmetteTeller specific surface area of the biochar was determined using nitrogen gas on a Micrometrics ASAP 2010 system (Micrometrics, Norcross, GA, USA).

2.2. Leaching experiment Layered soil column was constructed according to previous methods [19,20] as depicted in Fig. S1. This device consisted of three separated sections which were well joined and sealed throughout the experiment. Soil column with dimension of 10 cm inner diameter and 42 cm length were constructed with polymethyl methacrylate pipes and fitted with polyvinyl chloride endcap. There were three sampling openings on the column, i.e. a small hole drilled on the sidewall at three different heights, representing soil depths of 10, 20, and 30 cm along the soil profile. The sampling opening was for extraction of soil leachate from different layers in the profile. A 5-cm thick layer of coarse sand was placed at the bottom of each column to further prevent soil loss. A simple water container was used for supplying deionized water to the column to simulate leaching conditions. About three kilograms of prepared soil were packed into the columns to achieve an initial bulk density of about 1.3 g cm
3. The top 10 cm soil in the column was subjected to thorough mixing with 0.325 g urea (equal to 250 kg N ha
1) and biochar with four different application rates of 0, 2, 4 and 8% (mass ratio of biochar/soil, equivalent to 0, 40, 80 and 160 t ha
1), which were designated as CK, B2, B4 and B8, respectively. Three replicates were conducted for each treatment. The columns were kept in an artificial greenhouse at 25 ± 2  C and a relative humidity of 65%. Before starting the leaching experiment, about 1200 mL deionized water was added from the top of each column over a period of 7 days for the initiation of ammonification and nitrification in soil. During the leaching period, deionized water was added slowly into each column. Around 10 mL leachate was sampled from the openings at 10, 20 and 30 cm depth along the soil column respectively. Once the leachate volume approached 10 mL, the addition of deionized water was suspended, and the total volume of leachate was measured. All the sampling openings were sealed when not sampling. Leachate was sampled at an interval of half a month during the first three months and of one month during the last two months for a total period of five months. The leachate samples were filtered through disposable 0.45 mm pore-size filters (Whatman, Clifton NJ, USA) and analyzed for pH, EC, nitrate, ammonium and total N according to the methods mentioned above.

Table 1 Basic physiochemical properties of the tested soil and corn straw biochar. Soil pH Organic matter (g kg
1) Ammonium N (mg kg
1) Nitrate N (mg kg
1) Soil bulk density (g cm
3) Cation exchange capacity (cmol kg
1) Electrical conductivity (mS cm
1) Field moisture capacity (%)

Corn straw biochar 8.1 16.4 0.8 5.7 1.58 17.4 141.4 24.8

pH C (%) H (%) O (%) N (%) Ash content (%) Cation exchange capacity (cmol kg
1) Electrical conductivity (mS cm
1) Specific surface area (m2 g
1)

10.0 58.0 2.7 21.5 2.3 16.7 23.8 1319 14.7

N. Xu et al. / European Journal of Soil Biology 74 (2016) 1e8

2.3. Soil microbial biomass, respiration rate and net N mineralization The soil in the first layer was sampled at the end of the experiment. Soil microbial biomass, respiration rate and net N mineralization were measured. Soil microbial biomass carbon (MBC) and nitrogen (MBN) were measured using a chloroform fumigationdirect extraction procedure [21,22]. The value to calculate biomass from the C and N determinations (KEC and KEN) was 0.45 and 0.68 [21,23]. For each column, duplicate soil samples (20 g dry weight equivalent) were weighed out. One was directly extracted with 0.5 mol L
1 K2SO4 at a soil to solution ratio of 1:4. Another was fumigated with chloroform for 24 h, followed by extraction with the same K2SO4 solution. The concentrations of C and N in the extracts were determined by an automated total organic carbon/ total nitrogen analyzer (Multi N/C, 3100/HT1300, Analytik Jena, Germany). Soil basal respiration (SBR) was measured at the end of the experiment through incubation at the condition of 25  C and 60% water holding capacity. The soil samples (20 g) were sealed in 1 L jars, and CO2 was collected with 10 mL of 0.01 M NaOH solution during a 4 h period. The resulted solution was then titrated with HCl solution to determine the amount of absorbed CO2 [24]. Active microbial biomass was measured using the substrate-induced respiration (SIR) method [25]. Briefly, 1:4 glucose/talcum mixture was added to the samples, then incubated under the same conditions as for the basal respiration study, at a concentration of 12.0 g glucose kg
1 soil. Respiration rates were reported as milligram CO2 per kilogram soil per day. As a method of assessing the efficiency of microbial biomass, the metabolic quotient (qCO2) was calculated by dividing SBR by MBC [25]. Net N mineralization was determined with a reported method [26]. For this purpose, duplicate soil samples of 10 g dry weight were taken from the top 10 cm layer of the column at the end of the experiment. One was directly extracted with 1 mol L
1 KCl at a 1:10 of soil to solution ratio. Another was incubated in the dark at constant humidity (45% of soil water holding capacity) and temperature (25  C) for 15 days. At the end of the incubation, the samples were subjected to extraction with the same extractant. N concentrations in the extracts were determined, and net mineralized N in soil was the difference in extracted N before and after incubation. 2.4. DNA extraction, PCR-amplification of 16S rRNA gene fragments and DNA sequencing At the end of the experiment, soil samples were taken from the top 10 cm layer of triplicate columns and mixed for bacterial community analysis for each treatment. Total microbial DNA was extracted from approximately 5 g soil with the MoBio PowerMax Soil DNA isolation kit (MoBio Laboratories, Carlsbad, CA, USA). DNA concentrations were quantified using a NanoDrop ND-1000 UVeVis spectrophotometer (NanoDrop Technologies, USA). The V3eV4 region of 16S rRNA gene was used as the bacterialspecific fragment with the primers 338F (5 0 -ACTCCTACGGGAGGCAGCAG-3 0 ) and 806R (5 0 -GGACTACHVGGGTWTCTAAT-3 0 ) [27]. Error-correcting barcodes were added to both forward and reverse primers [28]. PCR was conducted using a PTC 100 thermal cycler (MJ Research, Waltham, MA, USA). All amplifications were performed in 25 mL reactions with four replicates. Each reaction volume contained 1 mL of DNA template (about 20 ng), 0.5 mL of each appropriate primer (at a final concentration of 0.2 mM), 0.25 mL of bovine serum albumin (at a final concentration of 6 mM) (Takara, Japan), 12.5 mL of 2  DreamTaq Green PCR Master Mix (Thermo Scientific, USA). The following cycle parameters were used: initial

3

denaturation for 3 min at 95  C; 27 cycles of 30 s at 95  C, 30 s at 55  C, and 45 s at 72  C; and final extension for 10 min at 72  C. PCR products were separated by gel electrophoresis, and fragments with size in the range of 500e600 bp were excised from the gel and extracted by using the Qiagen gel extraction kit (Qiagen, Valencia, CA). Further purification was performed with Qiagen PCR purification kit (Qiagen). Samples were pooled at equal concentrations. Sequencing of the amplicons was performed by using the Illumina HiSeq platform (Illumina, San Diego, CA, USA). Raw sequences were classified with the Ribosomal Database Project (RDP) training set using a confidence cut-off of 60% and clustered into operational taxonomic units (OTUs) at 97% identity with consensus taxonomy by single sequence analysis software the Quantitative Insights into Microbial Ecology (QIIME 1.6.0) toolkit. This generated a quality filtered dataset. The dataset was then abundance filtered by removing OTUs with <20 counts across all samples. Rarefaction curves were generated for quality-filtered and quality plus abundance-filtered data sets to observe the sampling efficiency. The internal complexity of individual sample was calculated by a-diversity indices including Shannon-Weaver (H) and Simpson index, Chao1, Ace and observed species. The multiple samples similarity tree was constructed using an approximate maximum likelihood method designed for large alignments as implemented by the software FastTree. 2.5. Statistical analysis The soil physicochemical and N leaching results were expressed as means and standard deviations. Statistical analysis was performed by using Statistical Product and Service Solutions 22.0 (SPSS Inc., Chicago, IL, USA). Significant differences were obtained by the one-way analysis of variance (ANOVA) with means compared using the Duncan's multiple range test. The correlation was analyzed with the Pearson test (two-tailed) at p ¼ 0.05. Any differences between the mean values at p < 0.05 were considered statistically significant. 3. Results 3.1. Nitrogen leaching The mass cumulative nitrate, ammonium and total N in the leachates from all three layers under different treatments are shown in Fig. 1. The nitrate, ammonium and total N leaching all decreased under biochar treatments. The temporal changes of the nitrate, ammonium and total N in leachates from different layers of the soil columns under different treatments are shown in Fig. S2, S3 and S4, respectively. In particular, the difference in cumulative mass of total N leaching between the control and biochar treatments was more significant in the second layer as depicted in Fig. S4. The change pattern of total N in leachates from different layers under different treatments was similar to that of nitrate, as more than ninety percent of total leached N was in the form of nitrate. In detail, biochar significantly reduced the cumulative amount of leached nitrate from all three layers by 16.0%, 16.7% and 19.3% in the 2%, 4% and 8% biochar treatment, respectively (p < 0.05), as compared to CK (33.6 mg, Fig. 1a). Similarly, the cumulative amount of leached ammonium was decreased by 19.1%, 26.9% and 28.1% with 2%, 4% and 8% biochar treatment, respectively (p < 0.05), as compared to CK (0.9 mg, Fig. 1b). In all, biochar significantly reduced the cumulative amount of total N leached by 18.8%, 19.5% and 20.2% in the 2%, 4% and 8% treatment, respectively (p < 0.05), as compared to the control (37.3 mg, Fig. 1c). This meant that increasing amount of biochar resulted in reduced amount of N leaching.

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þ Fig. 1. Cumulative mass of (a) NO
3 , (b) NH4 and (c) total N in the leachates from all three layers of the soil columns under different treatments (CK: no biochar; B2, B4 and B8 with 2%, 4% and 8% biochar/soil, respectively). Significant differences are indicated by different letters (p < 0.05).

As revealed in Fig. S5, in order to obtain the same amount of leachate (around 10 mL) from each layer, the cumulative volume of added water was 1276, 1380, 1421 and 1489 mL for CK, B2, B4 and B8, increased by 8.1%, 11.4% and 16.7% as compared to the control (p < 0.05), respectively. In addition, significant difference was also observed under B8 as compared to B2 and B4 (p < 0.05). 3.2. Leachate pH and EC, soil microbial biomass, respiration rate and net N mineralization Figs. 2 and 3 depict the temporal change of pH and EC in the leachates from different layers of soil columns under different treatments, respectively. Leachate pH was higher under biochar treatments, and increased with elevated amount of added biochar in the first layer. At the end of the experiment, leachate pH in the first layer increased by 0.21 unit on average under the biochar treatments, compared to CK. Although leachate pH was still higher in the second and third layers under biochar treatments, it was no longer correlated with the biochar addition ratio. Unlike leachate pH, leachate EC gradually increased with the elevated adding ratio of biochar in all three layers, and increased along the soil profile (p < 0.05) as depicted in Fig. 3. Compared to CK, leachate EC increased by 46.7%, 48.8% and 79.5%, respectively, in the third layer under 2%, 4% and 8% biochar treatments at the end of the experiment. Table 2 lists soil biochemical parameters and soil respiration rate in the top 10 cm soil layer. Similarly, soil pH was increased in the first layer under biochar treatments and had a positive correlation with the addition ratio of biochar (p < 0.05). In terms of MBC and MBN, significant difference was only observed between B8 treatment and the control (p < 0.05). With 8% biochar treatment, MBC increased by 10.8% in comparison to the control (75.1 mg kg
1), and MBN increased by 7.5% as compared to CK (8.2 mg kg
1). SBR

pH of leachate

8.4

8.0

a

10 cm

CK B2 B4 B8

8.0

a a a b 7.6

b

increased by 32.3% on average as compared to the control (70.7 mg CO2 kg
1 d
1) (p < 0.05), and significant difference between all the biochar treatments and CK was observed. SIR increased by 28.7% on average in comparison with the control (152.9 mg CO2 kg
1 d
1) (p < 0.05). In addition, compared to B4 (214.6 mg CO2 kg
1 d
1), SIR significantly decreased under B8 treatment (p < 0.05). Similar to SBR, soil metabolic quotient also significantly increased under biochar treatments (p < 0.05). Net N mineralization was also significantly enhanced by 40.3%, 34.4% and 18.0% in the 2%, 4% and 8% treatment, respectively (p < 0.05), in comparison to the control (1.3 mg kg
1 d
1). However, the net N mineralization decreased as the addition ratio of biochar increased, especially for B8. 3.3. Soil bacterial community structure After sequence filtering there were 108,900 high-quality sequences in total from all 4 samples. The average read length was 440 bp. The number of sequences per sample ranged from 25,624 to 28,395 with an average of 27,225. RDP Classifier was used to assign these sequences to different OTUs with a 3% nucleotide cutoff. A total of 5427 OTUs were recovered from the 4 samples. Table 3 lists a-diversity indices, read numbers and coverages under different treatments. The sampling coverage was more than 99% suggesting almost complete sampling coverage of diversity within samples. Bacterial diversity increased under biochar treatments in comparison with the control, and had a positive correlation with the addition ratio of biochar. Fig. 4 showed the multiple samples similarity tree and relative abundances of dominant bacterial phylum taxa in four different treatments. Relative abundances of dominant bacterial genera in four different treatments were depicted in Fig. S6. Relative abundances of taxa at genera level in four dominant phyla detected in different treatments were showed in Fig. S7. These results revealed

20 cm

a a 7.6 ab b 7.2

7.6

c

30 cm a b b b

7.2

7.2

6.8 0 15 30 45 60 75 90 105 120 135 150

0 15 30 45 60 75 90 105 120 135 150

0 15 30 45 60 75 90 105 120 135 150

Incubation time (d) Fig. 2. Temporal change of pH in the leachates from different layers of the soil columns under different treatments (CK: no biochar; B2, B4 and B8 with 2%, 4% and 8% biochar/soil, respectively). Significant differences are indicated by different letters (p < 0.05).

N. Xu et al. / European Journal of Soil Biology 74 (2016) 1e8

a

Electrical conductivity -1 of leachate (μs cm )

1200

2400

10 cm

CK B2 B4 B8

1000 800 600

5000

a 1600

4000

b 1200 c

200

d 800

0

6000

20 cm

2000

400

0

b

15 30 45 60 75 90 105 120 135 150

400

5

c

30 cm

3000

a 2000 ab b c 1000 0

15 30 45 60 75 90 105 120 135 150

a b b c 0

15 30 45 60 75 90 105 120 135 150

Incubation time (d) Fig. 3. Temporal change of electrical conductivity in the leachates from different layers of the soil columns under different treatments (CK: no biochar; B2, B4 and B8 with 2%, 4% and 8% biochar/soil, respectively). Significant differences are indicated by different letters (p < 0.05).

Table 2 Soil physicochemical parameters, soil respiration, and net N mineralization under different treatments (CK: no biochar; B2, B4 and B8 with 2%, 4% and 8% biochar/soil, respectively). MBC ¼ microbial biomass carbon; MBN ¼ microbial biomass nitrogen; SBR ¼ soil base respiration; SIR ¼ substrate-induced respiration; qCO2 ¼ soil metabolic quotient. Different letters in a single row indicate significant difference between the treatments at p < 0.05 (Duncan's multiple range test). Values are presented as means ± standard deviation with n ¼ 3. CK pH MBC (mg kg
1) MBN (mg kg
1) SBR (mg CO2 kg
1 d
1) SIR (mg CO2 kg
1 d
1) qCO2 (d
1) Net N mineralization (mg kg
1 d
1)

B2

7.84 75.12 8.24 70.68 152.95 0.94 1.28

± ± ± ± ± ± ±

0.18c 4.63b 0.31b 5.23b 12.81c 0.04b 0.19c

8.17 79.45 8.56 89.19 186.41 1.12 1.80

B4 ± ± ± ± ± ± ±

0.20b 4.27ab 0.50ab 5.76a 10.35b 0.11a 0.19a

8.21 75.31 8.59 96.86 214.58 1.29 1.72

B8 ± ± ± ± ± ± ±

0.14a 4.21b 0.42ab 6.31a 10.41a 0.12a 0.15a

8.25 83.27 8.86 94.53 189.51 1.14 1.51

± ± ± ± ± ± ±

0.12a 5.01a 0.30a 5.89a 9.58b 0.03a 0.12b

Table 3 Comparison of a-diversity indices, read numbers and coverages under different treatments at a genetic distance of 3% (CK: no biochar; B2, B4 and B8 with 2%, 4% and 8% biochar/soil, respectively). Treatment

Read numbers

Coverages

OTU

Chao1

Ace

ShannoneWeaver

CK B2 B4 B8

19,693 19,557 20,989 21,097

0.992028 0.992126 0.992186 0.992795

1279 1327 1401 1420

1361 1402 1493 1498

1357 1401 1477 1487

6.27 6.29 6.36 6.44

Fig. 4. Multiple samples similarity tree (left) and relative abundances of dominant bacterial phyla in four different treatments (right) (CK: no biochar; B2, B4 and B8 with 2%, 4% and 8% biochar/soil, respectively).

that bacterial community structure was different between biochar treatments and the control. Biochar treatments with high addition ratios (B4 and B8) have higher similarity as depicted in Fig. 4. The dominant phyla observed across all treatments included Proteobacteria, Acidobacteria, Chloroflexi, Bacteroidetes, Actinobacteria, Nitrospirae and Gemmatimonadetes. These taxa accounted for more than 85% of the bacterial sequences in all the four treatments (Fig. 4). Acidobacteria was the most sensitive phylum under

different treatments, with relative abundances ranging from 22.9% to 8.6% and decreased gradually under biochar treatments. Relative abundances of Gemmatimonadetes and Chloroflexi were also decreased with biochar addition. On the contrary, Proteobacteria, Bacteroidetes and Actinobacteria were increased after biochar application. Number of sequences classified to be within six ammonium oxidizing bacteria (AOB) genera under four treatments is shown in Table 4. Although there was no obvious difference

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N. Xu et al. / European Journal of Soil Biology 74 (2016) 1e8

Table 4 Number of sequences classified to be within the six ammonia oxidizing bacterial genera under four treatments (CK: no biochar; B2, B4 and B8 with 2%, 4% and 8% biochar/soil, respectively). Gene

CK

B2

B4

B8

Nitrolancea Nitrosomonas Nitrosospira Nitrospira Nitrosomonadaceae_uncultured Nitrospinaceae_uncultured

4 7 30 1121 976 11

4 9 161 893 507 17

0 23 201 1090 1010 23

3 5 120 1220 1074 9

between biochar treatments and CK in the total number of AOB sequences, biochar addition changed the relative abundance of these AOB genera. In particular, the relative abundance of Nitrosospira obviously increased under biochar treatments. 4. Discussion 4.1. Effect of biochar on N leaching It has been reported that enhanced nitrogen retention in the biochar-treated soil was related to increased soil aggregation resulting in higher water holding capacity [6]. Soil aggregation was dependent on the number of pores and pore size distribution as well as the specific surface area of soil [6]. As revealed in Fig. S5, in order to obtain the same amount of leachate (around 10 mL) from each layer, more water addition was needed for the columns with biochar treatments. This could be due to the high porosity of biochar. As more water was added under biochar treatments, nitrogen concentration in the leachate declined as depicted in Fig S2, S3 and S4. Urea is transformed to ammonium bicarbonate when applied in soil which is a natural process resulting from the activity of urease enzyme. Then the ammonium is generally converted to nitrate through nitrification [29]. With the addition of biochar in soil, the nitrate, ammonium and total N leaching all decreased. Nitrate leaching was about one order magnitude greater than ammonium, while the cumulative mass of leached ammonium from all three soil layers was less than 1 mg in all treatments. The result was consistent with the findings of previous work [30] in which ammonium sulfate was applied in a short-term lysimeter study. The results suggested that ammonium leaching from agricultural soil was not a major problem because it was readily adsorbed onto negatively charged clay minerals in soil. Compared to nitrate leaching, there had a significant difference between the lowest addition ratio of biochar (B2) and higher addition of biochar treatments (B4 and B8) in terms of the cumulative mass of leached ammonium (p < 0.05). The results indicated the stronger adsorption of free NHþ 4 on biochar particles due to the relatively higher CEC of biochar (23.8 cmol kg
1) in comparison with soil (17.4 cmol kg
1) [31]. 4.2. Effect of biochar on leachate pH and EC, soil microbial biomass, respiration rate and net N mineralization The potential liming effect of biochar has been reported [32]. Decarboxylation of organic anions (i.e. ash alkalinity) of added biochar consumes protons thus the soil pH and leachate pH both increased. The increment in leachate EC could be attributed to the ash content in biochar (16.7% by mass) which contained an amount of mineral ions, such as calcium, magnesium, potassium and sodium. As the mineral ions dissolved and leached in water, leachate EC was increased under biochar treatments.

Microbial biomass carbon and nitrogen had no significant increase under B2 and B4 treatments. No significant change of microbial biomass was also observed under low biochar addition ratio (<8%) in temperate soil [33]. However, some other studies showed significant increase of soil microbial biomass under low biochar application rate (<2%) [8,34]. These discrepant results may be explained in part by the variation of biochar (i.e. biochar feedstock, pyrolysis temperature, etc.) and soil types. Both soil and biochar were alkaline in the present study, and pH has been reported as one of the driving parameters for any effect on soil microbial biomass, community, and activity [5]. Higher respiration rates for biochar amended soil could have been mediated by an improved soil structure, leading to enhanced aeration and microbial activity [35]. The significant increment of soil metabolic quotient under biochar treatments (p < 0.05) was consistent with a previous study [24] in which the value of qCO2 was also suggested as an indicator of bioenergetic status of microbial biomass. The increment in net N mineralization under biochar treatments could be due to the labile C in biochar which enhanced soil microbial activity thereby influenced N transformation [36]. Similarly, enhanced net N mineralization was observed in the soil amended with N fertilizer and manure biochar [37]. These results showed that biochar addition could improve soil microbial activity which could be due to the labile C in biochar and more available nitrogen in soil under biochar treatments. In turn, higher microbial activity indicated possibly higher turnover ratio of nutrient such as nitrogen thereby N leaching may be reduced under biochar treatments. However, it should be noted that SIR of B8 (189.5 CO2 kg
1 d
1) significantly decreased (p < 0.05) as compared to B4 (214.9 CO2 kg
1 d
1), and net N mineralization of B8 (1.7 mg kg
1 d
1) also significantly decreased (p < 0.05) as compared to B4 (1.51 mg kg
1 d
1), suggesting that there are other factors which could slow down microbial activity in soil at the higher biochar application rate, such as heavy metals in biochar [38]. 4.3. Effect of biochar on soil bacterial community structure It has been suggested that biochar may affect soil bacterial community via improving soil physicochemical properties [9]. Combining the results of Figs. 1e4 and Table 2, biochar addition increased soil pH and EC, decreased N leaching, increased microbial biomass and shifted the bacterial community composition. These results were consistent with the previous report in which the biochar impacts on soil microbial community composition was investigated in an acidic soil [9]. In addition, because of the high porosity and various functional groups, biochar may build up biogeochemical interfaces (BGIs). The compositional heterogeneity of BGIs could diversify the niche microhabitats thus support growth of highly diverse bacterial communities [39]. Thereby the bacterial diversity would be higher with more added biochar. This could be one reason why B4 and B8 treatments have higher similarity while the control was different from all the biochar treatments in terms of bacterial diversity as depicted in Fig. 4. As to the bacterial community composition, the relative abundance of Acidobacteria, Chloroflexi and Gemmatimonadetes decreased under biochar treatments, while Proteobacteria, Bacteroidetes and Actinobacteria increased. This could be due to synergistic effects, such as co-metabolism or syntrophy, and/or similar response patterns to biological, chemical or physical variables, i.e. occupation of similar niche space [10]. The phylum Proteobacteria was the most predominant taxa in all soil samples, which was known to colonize nutrient-rich environments [40]. It has been reported that Actinobacteria are often associated

N. Xu et al. / European Journal of Soil Biology 74 (2016) 1e8

with the degradation of recalcitrant polymers and thus considered to be ecologically important in the turnover of organic matter in soil [41]. The higher presence level of Actinobacteria in biocharamended soil in comparison with CK may be a consequence of their ability to degrade recalcitrant carbon compounds [42]. Generally, biochar amendment was characterized by an increase in the relative abundance of Actinobacteria [11,14], as confirmed in the present study. Previous studies suggested that Acidobacteria played an important role in biogeochemical cycling of carbon and consequently might be adaptable to the environment of large variety of carbon sources present in biochar [42]. However, the soil showed a more alkaline environment after biochar amendment, which is not favorable for Acidobacteria, a phylum of bacteria usually being acidophilic [43]. As a result, the abundance of Acidobacteria decreased with biochar addition. The relative abundance of Gemmatimonadetes declined possibly because they prefer drier soils [44]. The phylum Nitrospirae was responsible for biogeochemical cycling of nitrogen and was accessible to the large amount of nitrogen resources added in the form of urea. Unlike the previous study [45] in which very few sequences (<100 reads) were shown to belong to AOB in forest soils using pyrosequencing method, a considerable number of sequences from the AOB genera were observed in the present study. This could be due to the fertilized agricultural soil (and applied with 250 kg N ha
1) used which has higher nitrogen content in comparison with forest soil. As the genera Nitrosospira was also reported to play an important role in the emission of nitrous oxide [46], the increment of its sequence under biochar treatments suggested that biochar may increase greenhouse gas emission [47]. These results indicated that the composition of N cycling-related bacterial community was changed under biochar treatments, thus the microbial transformation of N could have been influenced by biochar which may be another mechanism for reduced N leaching [6]. 5. Conclusions Simulated nitrogen leaching experiments were conducted with the application of organic N fertilizer (urea) in layered soil columns. Due to the biological transformation of urea into ammonium and then nitrate, and the strong sorption of ammonium in soil, more than ninety percent of total N leaching was in the form of nitrate. Total N leaching was reduced by 18.8%, 19.5% and 20.2% under the application of 2%, 4% and 8% biochar treatment in comparison with the control, respectively (P < 0.05). The relative abundance of Acidobacteria, Chloroflexi and Gemmatimonadetes decreased under biochar treatments, while Proteobacteria, Bacteroidetes and Actinobacteria increased. Soil microbial biomass slightly increased, while soil bacterial diversity was significantly higher, which may have contributed to the transformation of organic N fertilizer and reduction of N leaching. Acknowledgments This study was financially supported by the Special Fund for Agro-scientific Research in the Public Interest (201303095-10), the National Natural Science Foundation of China (41301311), and the Open Fund of Key Laboratory of Nonpoint Source Pollution Control, Ministry of Agriculture, China (2014-37). Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.ejsobi.2016.02.004.

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