Soil microbial community structure and function are significantly ...

Applied Soil Ecology 96 (2015) 75–87

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Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil

Soil microbial community structure and function are significantly affected by long-term organic and mineral fertilization regimes in the North China Plain Juan Lia , Julia Mary Cooperb , Zhi'an Lina , Yanting Lia , Xiangdong Yanga , Bingqiang Zhaoa,* a Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture / Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, PR China b Nafferton Ecological Farming Group, Newcastle University, Nafferton Farm, Stocksfield, Northumberland NE43 7XD, UK

A R T I C L E I N F O

A B S T R A C T

Article history: Received 21 February 2015 Received in revised form 2 June 2015 Accepted 1 July 2015 Available online xxx

An improved understanding of the complex interactions and relationships in the soil ecosystem is essential to predict the impact of farming practices on soil quality and its capacity for agricultural production. This study aims to improve our understanding of the impacts of fertilization strategy on key indicators of soil biological and chemical quality. We studied soils from a winter wheat-summer maize rotational experiment in the North China Plain with six different fertility treatments: no amendments (CK); standard mineral fertilizer treatment (SMF) or standard organic manure treatment (SMA) reflecting local farmer practice; mixed treatment with fertilizer and manure at half the rates for the SMF and SMA treatments (1/2 SMF + 1/2 SMA); double mineral fertilizer treatment (DMF); and double organic manure treatment (DMA). Soil organic C (SOC), total N (TN), total P (TP), pH, and dissolved organic C (DOC) and N (DON) and microbial biomass C (Cmic) and N (Nmic) were determined using standard methods. Soil bacterial community structure was assessed by denaturing gradient gel electrophoresis (DGGE), and activities for 10 extracellular enzymes (EEAs) were measured as indicators of soil function. Repeated application of either organic manure or mineral fertilizer increased SOC, TN, TP, DOC, DON, Cmic and Nmic, and decreased soil pH. Higher rates of organic manure fertilization significantly affected soil chemical properties compared to the lower rate. Soil bacterial community structure was significantly altered by the long-term fertilization regimes and diversity was significantly higher in the double manure rate treatment relative to mineral fertilizer. The higher urease, a-glycosidase, N-acetyl-b-glucosaminidase, L-leucine aminopeptidase (involved in N cycling), b-glucosidase, b-xylosidase and b-cellobiosidase (involved in C cycling), and alkaline phosphatase (involved in P cycling) activities for organic manure fertilized soils reflected a higher nutrient cycling capacity compared to mineral fertilized and control plots. Soil bacterial community diversities increased with Cmic and variations in EEAs were strongly correlated with soil DOC availability. Our study has demonstrated that a long-term fertilization strategy can be used to improve soil quality. Clearly, the use of organic fertilizers where available, is a win–win strategy for maintaining soil quality and crop productivity, while ensuring the delivery of soil ecosystem services into the future. ã 2015 Elsevier B.V. All rights reserved.

Keywords: Long term fertilization Organic manure Soil extracellular enzyme activity Soil bacterial community Soil quality indicators

1. Introduction

* Corresponding author at: Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture / Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China. Fax: +86 10 82108664. E-mail address: [email protected] (B. Zhao). http://dx.doi.org/10.1016/j.apsoil.2015.07.001 0929-1393/ ã 2015 Elsevier B.V. All rights reserved.

Chinese agriculture has intensified greatly since the early 1980s on a limited land area with large inputs of mineral fertilizers and other resources to meet the food demand of its increasing population (Guo et al., 2010). Cereal grain yields have increased by 65% between 1980 and 2010 (Zhang et al., 2012), but this success has come at a cost: overuse of mineral fertilizer not only induces low fertilizer use efficiency and the rapid depletion of known

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J. Li et al. / Applied Soil Ecology 96 (2015) 75–87

P-deposits, but also has led to the degradation of the environment, through increased greenhouse gas emissions, nutrient run-off and biodiversity loss (Zhu and Chen, 2002; Kahrl et al., 2010; Miao et al., 2011; Zhang et al., 2013). All these phenomena have led Chinese people to become increasingly concerned about the sustainability of current intensive agricultural management practices. In order to ensure the future sustainability of agricultural production, maintenance of soil quality is essential. Soil quality is “the capacity of a specific kind of soil to function, within natural or managed ecosystem boundaries, to sustain plant and animal productivity, maintain or enhance water and air quality, and support human health and habitation” (Doran and Parkin, 1994). Soil quality can be assessed by measuring a range of biological, physical and chemical indicators which are sensitive to changes in management (Fließbach et al., 2007), and linked to key soil functions. Measurement of soil quality indicators is therefore a useful approach for assessing and comparing the sustainability of different crop production strategies. The replacement of mineral fertilizer with organic manure could be one way to solve the problems of excessive mineral fertilizer use while at the same time improving soil quality such as physical and chemical properties, carbon stocks, and biological properties including soil biodiversity (Mäeder et al., 2002; Edmeades, 2003; Hole et al., 2005; Fließbach et al., 2007; Gattinger et al., 2012; Sradnick et al., 2013). Use of organic manures as fertilizers can also reduce nutrient losses (Zhao et al., 2011) and climate change impacts (Kustermann et al., 2008), and support similar or higher crop yields than mineral fertilization in certain contexts (Melero et al., 2006; Lin et al., 2009; Seufert et al., 2012). Mäeder et al. (2002) reported that while yields were 20% lower in organic systems relying on manure fertilization, they have higher nutrient use efficiencies than conventional systems. Lin et al. (2009) in our research group reported similar yields in manure fertilized treatments compared to mineral fertilized treatments after fifteen years in the same experiment. Soil microbiota regulate biogeochemical nutrient processes and their activities play a critical role in terrestrial ecosystems. Meanwhile, microbial properties such as microbial biomass C, N and P, respiration, and metabolic quotient are often used as indicators of soil quality because of their sensitivity to environmental changes, land use (Ndiaye et al., 2000; Acosta-Martinez et al., 2008; Xu et al., 2009) and agricultural management (Li et al., 2008). Numerous reports indicated that fertilization management significantly affected soil microbial properties and community composition (Mäder et al., 2002; Enwall et al., 2005; Gu et al., 2009; Feng et al., 2015). The addition of different amounts of nitrogen fertilizer induced a shift in microbial community structure resulting in an increase in fungal biomarkers but a significant decrease in the soil microbial community’s growthresponse in treatments with higher rates of N addition (e.g. 2,000 mg N g1 soil (Yevdokimov et al., 2008)). Following addition of organic manure, soil microbial communities usually experience increases in biomass and activity that release nutrients in plantavailable forms promoting plant vegetative growth and contributing to crop productivity (Kallenbach and Grandy, 2011; Jackson et al., 2012). Feng et al. (2015) revealed that the size of soil bacterial community increased in a long-term organic manure fertilized alkaline soil in the North China Plain (NCP). Soil microorganisms depolymerize and mineralize organic matter by producing extracellular enzymes (Allison et al., 2007). These enzymes have been recognized by soil scientists as one of the more sensitive components of the soil ecosystem and their activities (EEA) provide an early indication of the soil's functional status and microbial nutrient demand (Allison et al., 2007; Giacometti et al., 2014). Previous research has shown that soil enzyme activities were influenced by tillage, land use and farming

practices (Li et al., 2008; Fan et al., 2012). For example, soil hydrolytic enzyme activities became higher after regular organic manure application (García-Ruiz et al., 2008; Li et al., 2008). Fan et al. (2012) demonstrated that long-term mineral fertilizer input decreased cellobiohydrolases (CBH) activity, while long-term manure input increased CBH activity. This evidence demonstrates that different fertilization strategies can alter soil physical, chemical and biological quality, and have an impact on crop yields. It is also clear that there is a link between soil chemical/biological properties and soil biodiversity and function. Assessing the impact that organic manure and mineral fertilizers and their combined application could have on soil quality within a Chinese production system will therefore help to contribute to the development of more sustainable food production systems that meet the demands of a growing population while preventing soil degradation. The objective of this study is to determine how long-term contrasting organic and mineral fertilization regimes have impacted on indicators of soil quality including: soil chemical/ biological properties, bacterial community structure and extracellular enzyme activities (EEAs). We hypothesize that long-term organic manure fertilization will enhance soil chemical and biological quality indicators, and alter soil microbial community structure by increasing diversity. We also hypothesize that the changes in soil chemical and biological properties will drive changes in the soil microbial community function (EEAs). This research should result in an improved understanding of the relationship between soil fertilization strategy and soil quality which will contribute to the development of guidelines for more effective use of organic and mineral fertilizers in Chinese agricultural production systems. 2. Material and methods 2.1. Site descriptions and experimental design This experiment was started in 1986 at Dezhou Experimental Station (116 340 E, 36 500 N, altitude: 20 m), Chinese Academy of Agricultural Sciences (CAAS), which is located in Yucheng City, Shandong Province, in North China Plain (NCP), China. The site’s mean annual precipitation and temperature are 569 mm and 13.4 C, respectively. The experimental soil is a Fluvo-aquic type formed from the sediments of the Yellow River with light loam texture (clay 21.4%; silt 65.6%; sand 13.0%). Baseline soil chemical properties at the start of the experiment in 1985 were 3.93 g total organic carbon kg1, 0.51 g total nitrogen kg1,7.50 mg Olsen P kg1, 1,73.00 mg ammonium acetate-extractable K kg1, 0.96 g soluble salt kg1. The experiment mimicked the standard winter wheat-summer maize double cropping system which is widely used in the NCP and produces on average a total grain yield (wheat yield plus maize yield) of 15 t ha1 annum1 (Lin et al., 2009). Standard commercial tillage and irrigation regimes are used. 2.1. Fertilization treatments The experiment consists of 24 plots of six fertilization treatments with four replicates arranged in a randomized complete block design. Each plot is 28 m2 (4 m 7 m), and is separated by a 0.8 m concrete slab to prevent the flow of water and fertilizer between the plots. The fertilization treatments include a control (CK) with no amendments added, a standard mineral fertilizer (SMF) treatment and a standard organic manure treatment (SMA) that both reflect local farmer practice, a mixed treatment (1/2SMF + 1/2SMA) with fertilizer and manure both applied at half the rates for the SMF and SMA treatments, a double mineral fertilizer treatment (DMF) and a double organic manure treatment


(DMA). The organic manure was cattle manure from the dairy industry nearby and was composted by regular turning (3–4 times) over a 4 month period before application. All manure applications in the experiment are made based on manure total N content. Mineral fertilizers and organic manures were uniformly broadcast onto the soil surface by hand and immediately incorporated into the plowed soil (0–20 cm depth) by tillage before sowing. Details of the rates and timings of manure and fertilizer treatments are included in Table 1. 2.2. Soil sample collection and analysis of chemical properties and microbial biomass Soils were sampled on October 7, 2011, prior to the annual application of organic manure to minimize effects of recent fertilizer additions on the soil chemical and biological properties measured. At least five cores (3 cm diameter, 0–20 cm depth) were taken per plot and mixed to create one combined soil sample and then separated into 3 parts. The first part was air-dried and sieved (0.25 mm); the second part was sieved (2 mm) and stored at 4 C, while the third part was sieved (2 mm) and stored at 80 C. The air-dried portion was analyzed for organic C by vitriol acid– potassium dichromate oxidation method (SOC), total N by the Kjeldahl method (TN) and total P by the HClO4-H2SO4 method (TP), and soil pH was measured in a 1:2.5 (soil:water) mixture using the potentiometric method (Lu, 2000). The second part (fresh soil stored at 4 C) was used for measuring soil dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) by shaking with 0.5 mol/L K2SO4 (1:4 soil:K2SO4 solution) for 30 min and

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filtering. DOC and DON were measured in the filtrates by dichromate oxidation and Kjeldahl methods respectively. Microbial biomass C (Cmic) and biomass N (Nmic) contents were assessed on the 4 C component using the chloroform-fumigation– extraction method (Vance et al., 1987) as we described previously (Li et al., 2008). 2.3. Soil bacterial community structure and diversity analysis The structure and diversity of bacterial groups of different longterm fertilized soil samples were investigated by a PCR-DGGE (polymerase chain reaction denaturing gradient gel electrophoresis) approach. The soil samples maintained at 80 C were used for the extraction of soil microbial DNA. Soil DNA was extracted using the Ultraclean Soil DNA Isolation Kit (Mo Bio Laboratories, Solana Beach, USA) according to the manufacturer’s instructions. The PCR amplification of the 16S rRNA gene was performed with the universal bacterial primers (V3 region of 16SrRNA gene) GC-clamp338F and 518R (Muyzer et al., 1993) and the extracted DNA as template. The reaction mixture (50 ml) containing 25 ml EasyTaq Mix (TransGen Biotech, Beijing), 0.2 mM of each primer, 2 ml bovine serum albumin (100 mg/ml), and 10 ng/ml DNA template was run on a Thermo Scientific Arktik Thermal Cycler. The cycling program consisted of a 95 C initial denaturating step for 5 min, followed by 20 cycles of 94 C denaturation for 1 min, 65 C annealing for 30 s (reduced by 0.5 C each cycle), and 72 C extension for 3 min, followed by 10 cycles of 94 C for 1 min, 55 C annealing for 1 min, 72 C for 3 min; and a final 72 C extension for 10 min. DGGE was performed using about 200 ng PCR product on a 6% (w/v)

Table 1 Summary of composition, rates and timing of applications for treatments that received organic manure or mineral fertilizer (control treatment received no amendments and are not shown in this table). Rates represent the total amount applied for the wheat and maize crops in a year. All N application rates based on total N contents; fertilizer N is urea (47% N); fertilizer P is mono-calcium phosphate (17% P2O5); fertilizer K is potassium sulphate (50% K2O). Organic manure is composted with typical nutrient concentrations 1.00–1.84% N; 0.58–1.67% P2O5; 0.98–1.34% K2O. Treatment

Standard mineral fertilizer (SMF)

Standard organic manure (SMA)

Mixed mineral fertilizer Double standard Double standard organic and organic manure (1/ mineral fertilizer (DMF) manure (DMA) 2SMF + 1/2SMA)

Organic manure

–

375 kg N ha1 (1986– 1993); 450 kg N ha1 (1994–present)

187.5 kg N ha1 (1986– 1993); 225 kg N ha1 (1994–present)

–

750 kg N ha1 (1986– 1993); 900 kg N ha1 (1994–present)

Timing of manure application

–

50% of total before wheat sowing and 50% before maize sowing (1986–1996); 100% before wheat sowing (1997–present)

50% of total before wheat sowing and 50% before maize sowing (1986–1996); 100% before wheat sowing (1997–present)

–

50% of total before wheat sowing and 50% before maize sowing (1986–1996); 100% before wheat sowing, (1997–present)

Mineral fertilizer

– 375 kg N ha1, 225 kg P2O5 ha1(1986–1993); 450 kg N ha1, (1994– present); 300 kg P2O5 ha1 (1994–1999); 150 kg K2O ha1 (1993– present); 240 kg P2O5 ha1 (2000– present)

187.5 kg N ha1, 112.5 kg P2O5 ha1 (1986–1993); 225 kg N ha1 (1994– present); 150 kg P2O5 ha1 (1994–1999); 75 kg K2O ha1 (1993– present); 120 kg P2O5 ha1 (2000–present)

– 750 kg N ha1, 450 kg P2O5 ha1 (1986–1993); 900 kg N ha1, (1994– present); 600 kg P2O5 ha1 (1994–1999); 300 kg K2O ha1 (1993– present); 480 kg P2O5 ha1 (2000– present)

– Timing of mineral fertilizer application Total amount of fertilizer N was applied twice annually. 50% of total N was applied before winter wheat sowing and 50% before maize sowing. Winter wheat—40% N, 100% P2O5 and K2O before sowing ; 60% N GS31; Maize—40% N before sowing; 60% GS31

Total amount of fertilizer N was applied twice annually. 50% of total N was applied before winter wheat sowing and 50% before maize sowing. Winter wheat—40% N, 100% P2O5 and K2O before sowing; 60% N GS31; Maize—40% N before sowing; 60% GS31

Total amount of – fertilizer N was applied twice annually. 50% of total N was applied before winter wheat sowing and 50% before maize sowing. Winter wheat—40% N, 100% P2O5 and K2O before sowing; 60% N GS31; Maize—40% N before sowing; 60% GS31

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acrylamide:bisacrylamide (37.5:1, m:m) gel with 35–60% denaturing gradient at 120 V and 60 C for 8 h using a DCode universal mutation detection system (Bio-Rad Laboratories, Hercules, USA). The gels were stained with 1:10,000 SYBR Green I DNA stain solution (Sigma, USA) for 30 min and photographed using the Gel Documentation System and analyzed using the software Quantity One (Bio-Rad Laboratories, Hercules, USA). The gel included 12 lanes which allowed 2 replicates of each of the six treatments to be run (a total of two gels were used, see the other one in Fig. S1). 2.4. Soil extracellular enzyme activities (EEAs) analysis Fluorometric substrates linked to 4-methylumbelliferone (MUB) and 7-amino-4-methylcoumarin (AMC) from Sigma (St Louis, MO, USA) were used for assays of seven hydrolytic enzymes (Table 2). Enzyme assays were performed as described by DeForest (2009) with slight modifications of the buffer concentrations due to the alkalinity of the soil in this experiment. Briefly, assays were conducted by homogenizing each fresh soil sample (equivalent weight to 1.0 g dry mass soil) in 125 ml of 50 mM Tris buffer (pH 8.2) in a 200 ml screw-cap Nalgene bottle, and then stirring the mixture vigorously to maintain a uniform suspension. For the hydrolytic enzymes, the soil sample, Tris buffer, 10 mM references and 200 mM fluorometric substrates were distributed into a black 96-well plate in the order as described by DeForest (2009). Plates were incubated in the dark at 25 C for 4 h until 10 ml 0.5 M NaOH was added to stop the reaction by bringing the pH in the well to 10. Fluorescence (excitation 360 nm; emission 450 nm) was read using a Thermo fluorometer. The non-fluorometric enzymes (phenol oxidase and peroxidase) were measured spectrophotometrically using 3, 4-dihydroxyphenylalanine (L-DOPA) from Sigma (St Louis, MO, USA) as a substrate (Table 2). For phenol oxidase and peroxidase, the soil sample, Tris buffer and 25 mM L-DOPA were pipetted into a clear 96-well microplate as described by DeForest (2009). Peroxidase activity required the addition of 10 ml 0.3% H2O2 solution into every well. Plates were incubated in the dark at 25 C for 20 h, and the absorbance at 450 nm was measured using a Thermo fluorometer. Urease activity was assayed using urea as the substrate as described by Lu (2000). Briefly, fresh soil equivalent to 5 g oven-dry soil was incubated with 10 ml buffered urea solution (pH 9.0) and 0.2 ml toluene in a 50-ml volumetric flask at 37 C for 2 h, and diluted with 38 C water to 50 ml then filtered. The released ammonium in the soil suspension was determined by the indophenol blue reaction and measured spectrophotometrically at 578 nm (Crowther and Large, 1956).

2.5. Calculation and Statistical analyses The degree of similarity in soil bacterial community structure (DGGE profiles) among the fertilizer treatments was determined by cluster analysis using the Diversity Database Fingerprinting software (Bio-Rad Laboratories) to generate similarity dendrograms among banding patterns. The Dice similarity index based on UPGAMA (Unweighted Pair Group Method using Arithmetic Averages) clustering method was used. The microbial community richness (S, number of bands in each lane of DGGE gels) and microbial diversity index (Shannon–Wiener’s diversity index, H’) were calculated as Zak et al. (1994) described. The hydrolytic enzymes activities and non-fluorometric enzymes activities were calculated as described by DeForest (2009) and urease activity was calculated as described by Lu (2000). All enzyme activities were expressed as nmol h1 g1 dry soil. SPSS 11.5 software and MS Excel 2007 were used to carry out data processing and statistical analysis (ANOVA). The full set of treatments was used to determine the effect of fertility treatment on response variables using one-way analysis of variance (ANOVA) with means compared using the least-significant differences (LSD) test. A subset of four treatments (SMF, SMA, DMF, DMA) was used to test the effects of the interaction between fertilizer input type and fertilizer input level using two-way ANOVA (p < 0.05). A constrained ordination technique (CANOCO for Windows 4.5 and CANODRAW for Windows) was used to evaluate the relationships between soil enzyme data (the absolute activities of soil extracellular enzymes), soil bacterial diversity indices and soil chemical/biological properties using redundancy discriminant analysis (RDA). Forward selection of soil biological and chemical properties (9 variables: SOC, TN, TP, C/N ratio, pH, DOC, DON, Cmic, Nmic) was performed independently for each set of response variables (either enzyme activities or diversity indices) to generate a minimum set of significant explanatory variables. 3. Results 3.1. Soil chemical characteristics Soil organic C and N were affected by fertilization treatments (Table 3). SOC and TN content increased in all treatments in comparison with the original soil after 25 years, and the CK treatment had 87.3% more C and 149.0% more N than the original soil. On average, soils receiving manure had greater amounts of SOC and TN than mineral fertilized soils, and the SOC content increased markedly with increasing rates of manure addition. Soil C/N ratio ranged from 5.82 to 8.84 with significantly higher values

Table 2 Extracellular enzymes assayed in soils under long-term fertilization regimes, their enzyme commission number (ECa ) and corresponding substrate (L-DOPA = L-3,4dihydroxyphenylalanine, 4-MUB = 4-methylumbelliferyl). Nutrient Cycle

Enzyme

Abbrev.

Substrate

ECa

N cycle

Urease a-glucosidase L-leucine aminopeptidase N-acetyl-b-glucosaminidase

Urease AG LAP NAG

Urea 4-MUB-a-D-glucoside L-Leucine-7-amino-4-methylcoumarin hydrochloride 4-MUB-N-acetyl-b-D-glucosaminide

3.5.1.5 3.2.1.20 3.4.11.1 3.2.1.30

C cycle

b-1,4-glucosidase b-D-cellobiosidase b-xylosidase

BG CBH BXYL

4-MUB-b-D-glucoside 4-MUB-b-D-cellobioside 4-MUB-b-D-xyloside

3.2.1.21 3.2.1.91 3.2.1.37

P cycle

Alkaline Phosphatase

AP

4-MUB-phosphate

3.1.3.1

phenolic compounds oxidase

Phenol oxidase Peroxidase

POX PER

L-DOPA

1.10.3.2 1.11.1.7

L-DOPA

a EC, Enzyme Commission number describing enzymatic function at increasing level of detail (the first number distinguishes 1-oxidoreductases, 2-transferases, 3hydrolases, 4-lyases, 5-isomerases, and 6-ligases)


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Table 3 Effect of fertilizer treatments (full set of treatments) and the interaction between fertilizer input type and level (subset of four treatments) on soil chemical characteristics in a long-term fertilizer input trial. Long-term means (SE) followed by the same letter in the same column are not significantly different (LSD p < 0.05), “–” indicates that the effect of fertilizer treatment, fertilizer input type or level or the interaction was not significant at the p < 0.05 level. Treatments

SOC (g kg1)

TN (g kg1)

TP (g kg1)

C/N

DOC (mg kg1)

DON (mg kg1)

pH

CK SMF SMA 1/2SMF+1/2SMA DMF DMA

7.4 ( 0.28) f 9.4 ( 1.33) e 16.1 ( 0.87) b 13.5 ( 0.56) c 10.7 ( 0.52) d 25.7 ( 0.67) a

1.3 ( 0.05) e 1.5 ( 0.17) d 2.1 ( 0.05) b 1.7 ( 0.21) c 1.6 ( 0.08) cd 2.9 ( 0.17) a

0.8 ( 0.04) c 1.2 ( 0.07) b 1.2 ( 0.09) b 1.2 ( 0.09) b 1.8 ( 0.11) a 2.0 ( 0.15) a

5.8 ( 0.12) d 6.4 ( 0.36) cd 7.7 ( 0.23) b 7.9 ( 0.74) b 6.6 ( 0.19) c 8.8 ( 0.32) a

9.6 ( 3.17) e 30.0 ( 6.99) d 83.4 ( 8.50) b 50.4 ( 4.82) c 42.9 ( 7.51) c 132.4 ( 6.99) a

13.0 ( 3.90) c 15.1 ( 1.39) c 24.4 ( 1.48) a 21.7 ( 1.52) a 9.7 ( 2.90) d 17.0 ( 2.07) bc

8.7 ( 0.07) a 8.5 ( 0.03) bc 8.5 ( 0.10) b 8.4 ( 0.03) c 8.1 ( 0.06) d 8.1 ( 0.08) d

One-way ANOVA Treatments

p < 0.0001

p < 0.0001

p < 0.0001

p < 0.0001

p < 0.0001

p < 0.0001

p < 0.0001

Fertilizer input Type (T) Mineral Fertilizer(MF) Manure(MA)

10.1 ( 1.19) 20.9 ( 5.14)

1.6 ( 0.15) 2.5 ( 0.45)

1.5 ( 0.35) 1.6 ( 0.40)

6.5 ( 0.29) 8.3 ( 0.65)

36.5 ( 9.63) 107.9 ( 26.86)

12.4 ( 3.55) 20.7 ( 4.22)

8.3 ( 0.21) 8.3 ( 0.22)

Fertilizer input Level (L) Standard Double

12.7 ( 3.75) 18.2 ( 7.99)

1.8 ( 0.35) 2.3 ( 0.69)

1.2 ( 0.08) 1.9 ( 0.14)

7.0 ( 0.78) 7.7 ( 1.23)

56.7 ( 29.04) 87.6 ( 47.65)

19.7 ( 5.08) 13.4 ( 4.53)

8.5 ( 0.07) 8.1 ( 0.07)

Two-way ANOVA T L TL

p < 0.0001 p < 0.0001 p < 0.0001

p < 0.0001 p < 0.0001 p < 0.0001

– p < 0.0001 –

p < 0.0001 p < 0.0001 p < 0.01

p < 0.0001 p < 0.0001 p < 0.0001

p < 0.0001 p < 0.0001 –

– p < 0.0001 –

where manure was used as a fertilizer (Table 3). Long-term fertilization regimes also significantly affected soil total phosphorous (TP), which indicated that similar rates of mineral or manure fertilization increased TP. SOC, TN, DOC, C/N ratio and TP were lowest in CK and the highest in the DMA treatment while pH showed the opposite trend, with declining values with increasing rates of manure or mineral fertilizer application. DON was highest in the treatments with standard or half the organic manure input level compared to treatments with double rates of either fertilizer input type. Doubling fertilizer input level increased SOC, TN, C/N ratio, DOC and DON. Use of manure also increased all soil chemical properties except for pH, which was decreased. Fertilizer input type (organic versus mineral) significantly affected SOC, TN, C/N ratio, DOC and DON, but had no significant effect on soil TP (p = 0.159) and pH (p = 0.839). Futhermore, the higher fertilizer input level (double rate versus single rate) significantly increased SOC, TN, TP, C/N ratio and DOC and decreased DON and pH. The interaction of fertilizer input ype and fertilizer input level also had a significant effect on SOC, TN, DOC and C/N ratio, but had no significant effect on TP, DON and pH.

Table 4 Effect of fertilizer treatments (full set of treatments) and the interaction between fertilizer input type and level (subset of four treatments) on soil microbial biomass (Cmic and Nmic) in a long-term fertilizer input trial. Long-term means (SE) followed by the same letter in the same column are not significantly different (LSD p < 0.05), “–” indicates that the effect of fertilizer treatment, fertilizer input type or level or the interaction was not significant at the p < 0.05 level. Treatments

Cmic (mg kg1)

Nmic (mg kg1)

Cmic/Nmic

CK SMF SMA 1/2SMF + 1/2SMA DMF DMA

249.4 (39.78)d 285.9 (34.77)cd 457.0 (24.28)b 344.5 (46.05)c 263.8 (16.60)d 593.7 (87.17)a

33.4 (9.02)d 30.0 (3.76)d 83.4 (5.80)b 62.1 (7.43)c 50.1 (6.55)c 109.9 (14.21)a

6.9 (0.61)b 9.1 (0.47)a 5.5 (0.08)c 5.5 (0.20)c 5.0 (0.30)c 5.2 (0.43)c

p < 0.0001

p < 0.0001

p < 0.0001

275.6 (129.20) 535.1 (96.18)

44.9 (18.32) 99.6 (18.03)

7.0 (2.24) 5.3 (0.35)


359.2 (92.73) 439.8 (181.50)

56.7 (28.08) 85.0 (32.57)

7.3 (1.93) 5.1 (0.36)

Two way ANOVA T L TL

p < 0.0001 p < 0.01 p < 0.0001

p < 0.0001 p < 0.0001 –

p < 0.0001 p < 0.0001 p < 0.0001

One way ANOVA Treatments Fertilizer input Type (T) Mineral Fertilizer (MF) Manure(MA)

3.2. Soil microbial biomass carbon and nitrogen (Cmic, Nmic) Cmic and Nmic were significantly influenced by the long-term fertilizer treatments. Both of them were the lowest in CK and were significantly favored by the addition of manure. Manure addition increased Cmic and Nmic contents relative to the control, and double rate of manure addition resulted in the highest soil Cmic and Nmic contents. The addition of the standard or double rate of mineral fertilizer did not increase Cmic relative to the control, but Nmic in the double rate mineral fertilizer (DMF) treatment was higher than in the standard rate mineral fertilizer input (SMF) treatment. In this study, the Cmic/Nmic ratio was highest in the SMF treatment followed by the CK treatment; the other four treatments were significantly lower (Table 4). Fertilizer input type showed significant impacts on Cmic, Nmic and Cmic/Nmic ratio and the higher rate of input significantly increased both Cmic and Nmic and decreased the Cmic/Nmic ratio.

There was a significant interaction between input type and level for Cmic and Cmic/Nmic. 3.3. Soil bacterial community structure and diversity Comparison of bacterial communities between soils managed with long-term fertilization treatments showed quite markedly different profiles across the 16S rDNA-DGGE gels. The analysis of replicates 1 and 2 showed similar banding patterns to replicates 3 and 4; therefore the results for replicates 1 and 2 only are shown here (Fig. 1). The banding pattern in the DMA treatment (lanes 9 and 10) was very different from the other treatments as

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illustrated by the band labeled A on the figure. This band was present in all treatments except for DMA, indicating a clear difference in community structure for this treatment. This was reflected in the results of the cluster analysis. This analysis showed each pair of replicates grouped together for each fertilizer treatment and CK (Fig. 2), indicating a good replication of bacterial community structure within the same treatment. Patterns of the treatments receiving the same type of fertilizers (only manure or only mineral fertilizer) clustered together. Treatments which had received a mixture of manure and mineral fertilizer (1/2SMF + 1/2SMA) were separated from the treatments receiving only manure (SMA and DMA). Control treatments were an even more separated from the 1/2SMF + 1/2SMA treatments and the treatments receiving only manure (SMA and DMA) (Fig. 2). Finally, patterns of the treatments receiving only mineral fertilizers (SMF and DMF) were separated from the other treatments. For soil bacteria community richness (S) and diversity (H’) the DMA treatment had the highest levels with lowest values for the control (Table 5). Fertilizer input type significantly affected S and H’ but fertilizer input level had no impact on them, although there was a significant interaction between type and level.

3.4. Patterns of soil microbial community structure RDA was carried out using soil chemical and biological properties (TN, SOC, TP, C/N ratio, pH, DOC, DON, Cmic and Nmic) as explanatory variables and the relative abundance of 2 indicators (S and H’) of soil bacterial community structure as response variables (Fig. 3a). The explanatory variables accounted for 67.1% of the total variation (adjusted explained variation is 46.0%). Axis 1 and axis 2 accounted for 66.6% and 0.6% of the variation respectively. The most significant factor selected by forward selection was Cmic (p < 0.01) and the variance of soil bacterial community structure data explained by Cmic was 52.8%. Increases in S and H’ along axis 1 strongly correlated with Cmic (Fig. 3a). Variations along axis 1 were also driven by DOC, TN, SOC, Nmic, and C/N ratio, while TP was positively associated with both axis 1 and axis 2. Soil pH had a negative effect on axis 1 and axis 2 and DON was positively associated with axis 1 while negatively affecting axis 2. The circles on Fig. 3b indicate the separation between treatments which applied with manure (DMA treatment and SMA treatment) and the other treatments along axis 1 indicating different soil bacterial community structures when organic manure was applied for a prolonged period. CK treatment with no fertilizers input showed the lowest values along axis 1 and had the highest correlation with pH. Within the same standard fertilizer input level, the SMA treatment had the highest values along axis 1 and did not overlap with 1/2SMF + 1/2SMA and SMF. 3.5. Soil extracellular enzyme activities (EEAs) To clarify the patterns of extracellular enzyme activities under the different treatments we expressed each enzyme as a percentage of the control (Ai et al., 2012). Extracellular enzyme activities (EEAs) were significantly affected by long-term fertilizer treatments (p < 0.05). Fertilizer input type significantly affected eight EEAs with the exception of POX and PER. All ten EEAs were significantly affected by fertilizer input level. Urease activity, which is involved in N acquisition, was highest in the treatments which received only manure (Fig. 4a). At the same standard N input level, the greatest urease activity was found in the SMA treatment followed by the 1/2SMF + 1/2SMA treatment, and the lowest urease activity was measured in the SMF treatment. Compared to CK, long-term fertilized treatments had higher AG activity except for DMF treatment in which AG activity was lower than the control. AG activity was significantly higher in treatments which received manure compared to the other treatments. Similarly, treatments with manure addition had a positive effect on activities for the carbohydrate-degrading enzymes BG, BXYL and CBH. Compared to the control, the chitin degradation enzyme (NAG) activity declined and the polypeptide degradation enzyme LAP increased in the SMF treatment. In both cases application of double the manure rate resulted in the highest increase in EEAs relative to the control. Alkaline phosphatase (AP) activity showed a similar pattern of responses to the urease activity. POX and PER decreased with increasing N input level, showing an opposite trend compared with the other enzymes. 3.6. Patterns of soil enzyme activities

Fig. 1. DGGE profile of amplified 16S rRNA genes V3 fragments from soils under different long term fertilizer treatments. (block 1 and 2). CK: control with no amendments added; SMF: standard mineral fertilizer treatment reflect local farmer practice; SMA: standard organic manure treatment reflect local farmer practice; 1/ 2 SMF + 1/2 SMA: mixed treatment with fertilizer and manure both applied at half the rates for the SMF and SMA treatments; DMF: double mineral fertilizer treatment; DMA: double organic manure treatment. Subscripts refer to block number.

RDA was performed using soil chemical and biological properties (TN, SOC, TP, C/N ratio, pH, DOC, DON, Cmic and Nmic) as factors and all ten enzyme activities as response variables (Fig. 5a). Results showed that the explanatory variables accounted for 75% of the total variation (adjusted explained variation is 58.9%). Based on permutation tests, DOC was the most significant variable selected by forward selection explaining 53.4% of the variance of enzyme data (p < 0.01, padj < 0.05). The first two RDA


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Fig. 2. DGGE Cluster analysis (UPGMA) of 16SrDNA profiles of bacterial communities in soils under different long-term fertilizer treatments. (Block 1 and 2). CK: control with no amendments added; SMF: standard mineral fertilizer treatment reflect local farmer practice; SMA: standard organic manure treatment reflect local farmer practice; 1/ 2 SMF + 1/2 SMA: mixed treatment with fertilizer and manure both applied at half the rates for the SMF and SMA treatments; DMF: double mineral fertilizer treatment; DMA: double organic manure treatment. Subscripts refer to block number.

Table 5 Effect of fertilizer treatments (full set of treatments) and the interaction between fertilizer input type and level (subset of four treatments) on diversity properties of soil bacteria using DGGE bands pattern data associated with different long-term fertilizer treatments. Long-term means (SE) followed by the same letter in the same column are not significantly different (LSD p < 0.05), “–” indicates that the effect of fertilizer treatment, fertilizer input type or level or the interaction was not significant at the p < 0.05 level. Fertilizer Treatments

Richness (S detected band)

Shannon Weiner index (H’)

CK SMF SMA 1/2SMF + 1/2SMA DMF DMA

38 (3)c 42 (1)b 43 (2)ab 41 (2)b 41 (1)b 45 (1)a

3.60 (0.09)c 3.70 (0.03)ab 3.73 (0.03)ab 3.68 (0.03)b 3.66 (0.00)b 3.76 (0.03)a

One-way ANOVA Treatments

p < 0.001

p < 0.01

Fertilizer input Type (T) Mineral Fertilizer (MF) Manure(MA)

41 (1) 44 (2)

3.68 (0.03) 3.74 (0.03)


42 (1) 43 (2)

3.71 (0.03) 3.71 (0.06)

Two way ANOVA T L TL

p < 0.0001 – p < 0.05

p 0.001 – p < 0.05

axes accounted for 55.34% and 8.08% of the total variation. The soil properties TP, TN, SOC, DOC, C/N ratio, Cmic and Nmic were positively correlated with the first axis (1), while pH loaded negatively along axis 1 and axis 2. Axis 1 largely differentiated activities of C-cycling enzymes CBH, BG and BXYL, N-cycling enzymes AG, Urease, NAG and LAP, and the P-cycling enzyme AP. Axis 2 primarily explained variability in POX and PER which oxidize phenolic compounds, and were largely driven by pH. The clear separation of fertility treatments based on their extracellular enzyme activities is shown in Fig. 5b with the CK, SMA, and DMA treatments differentiated from the other treatments. Soil properties driving these differences in enzyme activity were primarily soil organic carbon and nitrogen which positively

affected axis 1, and pH which negatively affected axis 1. Within the same standard fertilizer input level, the SMA treatment showed higher values along axis 1 compared to 1/2SMF + 1/2SMA and SMF. The SMF treatment had slightly lower values than the 1/2SMF + 1/ 2SMA treatment along axis 1 due to its lower soil C and N contents and higher pH. 4. Discussion This research approach provides insight into how soil chemical and biological properties, total bacterial community structure and soil extracellular enzyme activities respond to the contrasting 25year organic and mineral fertilization regimes. Long-term fertilization significantly impacted soil nutrient availability, and in turn

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Fig. 3. Redundancy analysis (RDA) of soil microbial community structure constrained by soil chemical and biological properties under long-term fertilization regimes. (a) Vectors represent selected soil chemical and biological properties from (b) six different fertilizer treatments (~s (RDA) = CK, control with no amendments added; = SMF, standard mineral fertilizer treatment reflect local farmer practice; = 1/2SMF+1/2SMA, mixed treatment with fertilizer and manure both applied at half the rates for the SMF and SMA treatments;^ = SMA, mixed treatment with fertilizer and manure both applied at half the rates for the SMF and SMA treatments; = DMF, double mineral fertilizer treatment; * = DMA, double organic manure treatment). Subscripts refer to block number.

affected soil microbial community structure and function (EEAs). Bacterial community diversity, biomass and extracellular enzyme activities involved in nutrient transformations were enhanced in treatments receiving annual applications of manure. This was linked to increased levels of soil chemical and biological properties especially soil carbon availability in these treatments. 4.1. Effect of long-term fertilization on soil chemical indicators The increase in SOC in control plots during the 25-year experiment is consistent with previous experimental results at the same site (Lin et al., 2009), and is also in line with Meng et al. (2005) and Yan et al. (2007) who reported that SOC content in the control soil increased by 18.6% in a 13-year experiment and by

27.4% in a 25-year trial on different soil types. This effect may be due to the changes in crop varieties and the consistent accumulation of root residues and root exudates. Long-term fertilization with either manure or mineral fertilizer increased many indicators of soil quality. The 25-year repeated manure applications led to considerably higher SOC and TN contents, which can be attributed to annual additions of manure and crop residues (Xie et al., 2014). Enhanced SOC and TN under long term mineral fertilizer application may be an indirect effect of higher plant biomass production and C return to soils (Giacometti et al., 2013), although this is not always the case. Xie et al. (2014) found no increase in soil organic matter relative to the control in a 25-year long continuous mineral fertilization experiment. Geisseler and Scow (2014) summarized 107 datasets of 64 long-term


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Urease

Alkaline Phosphatase (AP)

350

250

a ab

a

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Percent difference (%) from CK


300 b

200

c

150 100 50

50

bc c

c

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60 40 20

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DMF

1/2SMF+1/2SMA

SMA

SMF

DMA

DMF

1/2SMF+1/2SMA

SMA

c.

b

100

0 SMF

-60

a

a

80

d. β-Glucosidase (BG)

β-Cellobiosidase (CBH)

250

350 a

250 200

b

150 c 100

c

a Percent difference (%) from CK

300 Percent difference (%) from CK

DMA

DMF

1/2SMF+1/2SMA

SMA

b. α-Glucosidase(AG)

100


b

100

SMF

a.

150

0

DMA

DMF

1/2SMF+1/2SMA

SMA

SMF

0

d

200

c

50

200

150

100

b bc

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bc

c

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DMF

SMA

SMF

DMA

DMF

1/2SMF+1/2SMA

SMA

SMF

e.

1/2SMF+1/2SMA

0

0

f.

Fig. 4. Percent difference of soil Extracellular Enzyme Activities (EEAs) in the fertilizer treatments compared to the corresponding control treatments (CK) calculated as [(fertilizer treatmentCK)/CK 100]. CK: control with no amendments added; SMF: standard mineral fertilizer treatment reflect local farmer practice; SMA: standard organic manure treatment reflect local farmer practice; 1/2 SMF + 1/2 SMA: mixed treatment with fertilizer and manure both applied at half the rates for the SMF and SMA treatments; DMF: double mineral fertilizer treatment; DMA: double organic manure treatment. Means labeled with the same letter are not significantly different at p < 0.05 (LSD test on actual values of the EEAs).

experiments and found that the mineral fertilization increased SOC content relative to the control by a mean of 12.8%, which agrees well with our results.

The long-term application of fertilizers can decrease pH in alkaline soils, as found in another 15-year trial in the NCP where pH declined after repeated fertilizer application, especially when

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N-acetyl-β-Glucosaminidase (NAG) 180



a

25

160 140 120 100 80

b

60

c c

40 20 0 d

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10 5 0 -5 -10 -15

d DMA

DMF

1/2SMF+1/2SMA

SMA

SMF

g.

b

-20

DMA

DMF

SMA

SMF

1/2SMF+1/2SMA

-20

L-leucine aminopeptidase (LAP)

30

a

h. Peroxidase (PER) 20

Phenol oxidase (POX)

a

5

10



15 b

5 0 -5

c

-10 -15

b

-5

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-10

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-15 -20 -25 -30

d

d

d DMA

DMF

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i.

1/2SMF+1/2SMA

-35 DMA

DMF

1/2SMF+1/2SMA

SMF

SMA

-20

a

0

j.

Fertilizer Treatments Fig. 4. (Continued)

manure was used (Liang et al., 2012). This was also observed in our trial where pH declined with increasing application rate, regardless of the input type. The mechanism for this pH decline may not be the same for each input type. Although hydrolysis of urea results in a slight increase in pH, this is followed by a decrease as ammonium is converted to nitrate through nitrification processes, which could result in a pH decline in our experiment. Manure applications can increase soil pH due to the liming effect of added carbonates and organic matter (Cooper and Warman, 1997); however, in this trial the long-term additions of manure may have resulted in an accumulation of organic acids resulting in a decline in pH (Liang et al., 2012). In this study, standard rate fertilizer input treatments had similar effects on TP, which is consistent with the previous report (Lin et al., 2009). Fertilizer input level was the predominant factor influencing TP (Table 2). Fertilizer input type and level also had an impact on soil DOC and DON contents, which are key indicators of agricultural soil quality (Haynes, 2000). At very high rates of organic manure (DMA) DOC was highest, but DON was reduced relative to the SMA treatment. This suggests that the high levels of DOC were stimulating microbial activity leading to immobilization of N from the DON pool. This is supported by the evidence from the

EEAs which were significantly higher for enzymes involved in C cycling (e.g. BG, CBH and BXYL). 4.2. Effect of long-term fertilization on soil microbial biomass The higher soil microbial biomass in the manure treatments may have been due to the addition of microbial populations in the manure and the additional C, which activates the soil indigenous microbiota. Enhancement of soil microbial biomass after organic manure addition has been reported during long-term experiments with the additional carbon sources which are benefit for the growth of soil microorganisms and the increases of soil nutrients contents (Li et al., 2008). Several studies have shown that mineral fertilizer application can increase the crop residues returned back to the soil and stimulate soil microbial growth and activity (Giacometti et al., 2013). This has been demonstrated even when the aboveground crop was removed at harvest, possibly because of not only increased root biomass but also the stimulation of bulk or rhizospheric microbial activity (Gu et al., 2009). In our experiment, this effect was not observed, and even the double mineral fertilizer rate input treatment had a Cmic similar with that of the control. This is in line with previous studies which found lower Cmic at


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Fig. 5. Redundancy analysis (RDA) of soil extracellular enzyme activities constrained by soil chemical and biological properties under long-term fertilization regimes. (a) Vectors represent selected soil chemical and biological properties from (b) six different fertilizer treatments (~(RDA) = CK, control with no amendments added; = SMF, standard mineral fertilizer treatment reflect local farmer practice; = 1/2SMF + 1/2SMA, mixed treatment with fertilizer and manure both applied at half the rates for the SMF and SMA treatments; ^ = SMA, mixed treatment with fertilizer and manure both applied at half the rates for the SMF and SMA treatments; = DMF, double mineral fertilizer treatment; * = DMA, double organic manure treatment). Subscripts refer to block number.

high nitrogen fertilizer rates (Li et al., 2013). In contrast, Nmic increased with the addition of increasing mineral fertilizer input levels, which could be explained by the report of Li et al. (2013). This report demonstrated that soil microorganisms could act as a sink for mineral N and immobilized nitrogen in the short-term in high fertilizer N treatments. Cmic and Nmic significantly correlated with SOC, TN and C/N ratio (data not shown), which showed that soil microbial growth was affected by substrate availability. Gunapala and Scow (1998) reported a higher Cmic/Nmic ratio in conventionally fertilized soils compared to organic fertilization, indicating that fungi are more dominant in conventional soils. We also found a higher Cmic/Nmic ratio in the SMF treatment compared to the organically fertilized treatments, although the DMF treatment did not show a similar effect. 4.3. Effect of long-term fertilization on soil bacterial community structure and diversity

the development of a soil bacterial community with higher biodiversity that was distinct from the community developed under mineral fertilization (Table 5), which was in agreement with the previous reports from other long-term fertilizer trials (Hallin et al., 2009; Wessén et al., 2010; Giacometti et al., 2013). This was attributed to the increased soil nutrient availability in the manure treatments, particularly the increase of soil Cmic content which is the most important fraction of soil labile carbon (Haynes, 2000) (Fig 3a). Bacterial communities may also have been affected by pH with higher diversities at lower pH values. This is consistent with other long-term studies which have found that soil microbial communities were strongly affected by pH (Geisseler et al., 2014; Jiang et al., 2014). These results further indicated that the longterm application of manure supported the development of higher biodiversity of the soil bacterial community, largely due to effects on soil chemical and biological properties, especially soil microbial biomass carbon (Cmic). 4.4. Effect of long-term fertilization on soil functions (EEAs)

All environmental changes could alter soil microbial community structure and diversity to some extent (Burns et al., 2013), and even small changes are hypothesized to impact on the soil microbial community and then lead to a “butterfly effect” in the dynamics of soil ecosystems and crop production systems. Repeated application of farmyard manure for 25 years facilitated

Soil enzyme activities are often assessed to test the impact of soil management practices on soil functions in agricultural systems (Frossard et al., 2012). In our study we found there was some consistency in the patterns observed for the activities of the hydrolytic enzymes such as urease, AG, LAP, NAG, BG, BXYL, CBH

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and AP in the organically fertilized and the combined organic and mineral fertilized soils. Soil enzyme activities could be explained by soil chemical and biological properties such as nutrient availability and microbial activity, which were strongly influenced by long-term fertilization regime. Hojjati and Nourbakhsh (2007) reported a positive correlation between the activity of hydrolytic enzymes and total organic carbon content, DOC and TN which increased significantly under organic fertilization. The addition of organic fertilizers activates microorganisms to produce hydrolases involved in the nutrient cycles, which respond to the increased supply of easily degradable organic matter (Hojjati and Nourbakhsh, 2007). In addition, long-term mineral fertilizer application promoted the production of hydrolytic enzyme activities related to C, N and P cycles, which is consistent with several previous studies (Melero et al., 2006; Li et al., 2008). The potential activity of the P-cycling enzyme AP (alkaline phosphatase) was previously demonstrated to have a strong positive relationship with soil microbial biomass carbon (Bowles et al., 2014) and an inverse relationship with high P availability (Olander and Vitousek, 2000; Allison et al., 2007). Our analysis indicated that 8 soil chemical and biological quality indicators (TN, SOC, TP, C/N ratio, pH, DOC, Cmic and Nmic) (data not shown) and soil bacterial community diversity indicators S (p < 0.01) and H’ (p < 0.01) had strongly positive relationships with AP activity. Oxidases such as phenol oxidase (POX) and peroxidase (PER) which mainly catalyze the process of lignin degradation are generally produced by fungi (Burns et al., 2013), and their activities were significantly different from those of all other enzymes in this experiment. Sinsabaugh (2010) reported that POX and PER activities increased with soil pH, and can decrease with N amendment. We also found significant reductions in POX activity with increasing rates of either organic or mineral fertilizers, as well as increasing PER and POX activities with increasing pH (Fig. 4, Fig. 5). Our results have demonstrated that key soil functions relating to nutrient cycling are enhanced by long-term manure addition. These changes in soil function may indicate the evolution of a soil microbial community after long-term manure application that is better adapted to the metabolism of organic fertilizers. This adapted community could contribute to more efficient cycling of nutrients from organic sources in the long-term. 5. Conclusions In a Fluvo-aquic soil of the North China Plain, long-term organic manure application enhanced various chemical indicators of soil quality (SOC, TN, TP, DOC, DON content) as well as microbiological indicators (Cmic and Nmic content). The bacterial structures and diversities were significantly affected by long-term fertilization strategy, and were constrained by alterations of soil resource availability (SOC). Soil function related to nutrient cycling was also enhanced in the soil with a history of manure amendment. These results indicate that use of organic fertilizers can result in the development of a soil adapted to metabolism of a variety of organic substrates. This has relevance for future crop production where it is expected that more organic waste materials will be recycled to the land. An additional benefit of cropping systems that rely on organic fertilizers for nutrients is the enhancement of soil ecosystem service provision. Soil organic C is expected to increase under systems reliant on organic fertilizers, with the concomitant ecosystem services of greenhouse gas (GHG) mitigation (due to C sequestration) and water regulation (drought and flood mitigation). Enhanced SOC will also lead to improvements in soil structure with reduced risk of off-site damage due to soil erosion and sedimentation. In addition, soils with high SOC levels and microbial activities have been shown to have a higher degree of resilience to both

environmental (floods, drought) and manmade (intensification of agricultural production) stresses (Kumar et al., 2014). Our study has demonstrated that a long-term fertilization strategy can be used to improve soil quality in a variety of ways. Clearly, the use of organic fertilizers where available, is a win–win strategy for maintaining soil quality and crop productivity, while ensuring the delivery of soil ecosystem services into the future. Acknowledgements The authors gratefully acknowledge funding from National Natural Science Foundation of China (NSFC, Grant No. 31301843), National Nonprofit Institute Research Grant of CAAS (Grant No. IARRP-202-5) and the European Community financial participation under the Seventh Framework Programme for Research, Technological Development and Demonstration Activities, for the Integrated Project NUE-CROPS FP7-CP-IP 222645. The views expressed in this publication are the sole responsibility of the author(s) and do not necessarily reflect the views of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use which might be made of the information contained herein. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j. apsoil.2015.07.001. References Acosta-Martinez, V., Acosta-Mercado, D., Sotomayor-Ramırez, D., Cruz-Rodrıguez, L., 2008. Microbial communities and enzymatic activities under different management in semiarid soils. Appl. Soil Ecol. 38 (3), 249–260. Ai, C., Liang, G., Sun, J., Wang, X., Zhou, W., 2012. Responses of extracellular enzyme activities and microbial community in both the rhizosphere and bulk soil to long-term fertilization practices in a fluvo-aquic soil. Geoderma 173, 330–338. Allison, S.D., Gartner, T., Holland, K., Weintraub, M., Sinsabaugh, R.L., 2007. Soil enzymes: linking proteomics and ecological process. Man. Environ. Microbiol. 704–711. Bowles, T.M., Acosta-Martínez, V., Calderón, F., Jackson, L.E., 2014. Soil enzyme activities, microbial communities, and carbon and nitrogen availability in organic agroecosystems across an intensively-managed agricultural landscape. Soil Biol. Biochem. 68, 252–262. Burns, R.G., DeForest, J.L., Marxsen, J., Sinsabaugh, R.L., Stromberger, M.E., Wallenstein, M.D., Weintraub, M.N., Zoppini, A., 2013. Soil enzymes in a changing environment: Current knowledge and future directions. Soil Biol. Biochem. 58, 216–234. Cooper, J.M., Warman, P.R., 1997. Effects of three fertility amendments on soil dehydrogenase activity, organic C and pH. Can. J. Soil Sci. 77 (2), 281–283. Crowther, A.B., Large, R.S., 1956. Improved conditions for the sodium phenoxidesodium hypochlorite method for the determination of ammonia. Analyst 81, 64–65. DeForest, J., 2009. The influence of time, storage temperature, and substrate age on potential soil enzyme activity in acidic forest soils using MUB-linked substrates and L-DOPA. Soil Biol. Biochem. 41, 1180–1186. Doran, J.W., Parkin, T.B., 1994. Defining and assessing soil quality. In: Doran, J.W., Coleman, D.C., Bezdicek, D.F., Stewart, B.A. (Eds.), Defining Soil Quality for a Sustainable Environment. Soil Science Society Americca Journal, Madison, pp. 3–21. Edmeades, D.C., 2003. The long-term effects of manures and fertilizers on soil productivity and quality: a review. Nutr. Cycling Agroecosyst. 66 (2), 165–180. Enwall, K., Philippot, L., Hallin, S., 2005. Activity and composition of the denitrifying bacterial community respond differently to long-term fertilization. Appl. Environ. Microbiol. 71, 8335–8343. Fan, F., Li, Z., Wakelin, S.A., Yu, W., Liang, Y., 2012. Mineral fertilizer alters cellulolytic community structure and suppresses soil cellobiohydrolase activity in a longterm fertilization experiment. Soil Biol. Biochem. 55, 70–77. Feng, Y., Chen, R., Hu, J., Zhao, F., Wang, J., Chu, H., Zhang, J., Dolfing, J., Lin, X., 2015. Bacillus asahii comes to the fore in organic manure fertilized alkaline soils. Soil Biol. Biochem. 81, 186–194. Fließbach, A., Oberholzer, H.R., Gunst, L., Mäder, P., 2007. Soil organic matter and biological soil quality indicators after 21 years of organic and conventional farming. Agric. Ecosyst. Environ. 118, 273–284.

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