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Hydrolase activities, microbial biomass and bacterial community in a soil after long-term amendment with different composts
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Soil Biology & Biochemistry 38 (2006) 3443–3452 www.elsevier.com/locate/soilbio
Hydrolase activities, microbial biomass and bacterial community in a soil after long-term amendment with different composts M. Rosa,, J.A. Pascuala, C. Garciaa, M.T. Hernandeza, H. Insamb a
Centro de Edafologia y Biologia Aplicada del Segura (CEBAS-CSIC), Department of Soil and Water Conservation and Organic Waste Management, P O. Box 164, 30100 Espinardo-Murcia, Spain b Leopold-Franzens-Universita¨t, Institut fu¨r Mikrobiologie, TechnikerstraX e 25, 6020 Innsbruck, Austria Received 26 January 2006; received in revised form 26 May 2006; accepted 31 May 2006 Available online 10 July 2006
Abstract The use of composts in agricultural soils is a widespread practice and the positive effects on soil and plants are known from numerous studies. However, there have been few attempts to compare the effects of different kinds of composts in one single study. The aim of this paper is to investigate to what extent and to which soil depth four major types of composts would affect the soil and its microbiota. In a crop-rotation field experiment, composts produced from (i) urban organic wastes, (ii) green wastes, (iii) manure and (iv) sewage sludge were applied at a rate equivalent to 175 kg N ha1 yr1 for 12 years. General (total organic C (Corg), total N (Nt), microbial biomass C (Cmic), and basal respiration), specific (enzyme activities related to C, N and P cycles), biochemical properties and bacterial genetic diversity (based on DGGE analysis of 16S rDNA) were analyzed at different depths (0–10, 10–20 and 20–30 cm). Compost treatment increased Corg at all depths from 11 g kg1 for control soil to 16.7 g kg1 for the case of sewage sludge compost. Total N increased with compost treatment at 0–10 cm and 10–20 cm depths, but not at 20–30 cm. Basal respiration and Cmic declined with depth, and the composts resulted in an increase of Cmic and basal respiration. Enzyme activities were different depend on the enzyme and among compost treatments, but in general, the enzyme activities were higher in the upper layers (0–10 and 10–20 cm) than in the 20–30 cm layer. Diversity of ammonia oxidizers and bacteria was lower in the control than in the compost soils. The type of compost had less influence on the composition of the microbial communities than did soil depth. Some of the properties were sensitive enough to distinguish between different compost, while others were not. This stresses the need of multi-parameter approaches when investigating treatment effects on the soil microbial community. In general, with respect to measures of activity, biomass and community diversity, differences down the soil profile were more pronounced than those due to the compost treatments. r 2006 Elsevier Ltd. All rights reserved. Keywords: Compost; Hydrolase activities; Microbial activity; PCR-DGGE; Bacterial community; Ammonia oxidizers
1. Introduction Land application of products from organic wastes, such as composts and bio-fertilizers, is gaining importance all over Europe, as integrated and biological agriculture are becoming increasingly popular. This is because such products are often considered beneficial for the soil and at the same time the problem of organic waste streams is alleviated, resulting in an environmentally acceptable way Corresponding author. Tel.: +34 968396200; fax: +34 968396213.
E-mail address: [email protected] (M. Ros). 0038-0717/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.soilbio.2006.05.017
of recycling waste materials (Lalande et al., 2000; Masciandaro et al., 2000). Organic amendments activate the autochthonous microorganisms of the soil, and indirectly stimulate the biogeochemical cycles therein (Pascual et al., 1997), and they provide various minerals (e.g. N, P, and S) essential for plant nutrition. They also increase the soil organic matter content, and influence soil structure and many other related physical, chemical and biological properties. In addition, the microbial biodiversity may be increased (Peacock et al., 2001) and soil-borne pathogens may be reduced by stimulation of antagonistic organisms
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(Tilston et al., 2002) allowing less use of potentially harmful fumigants or pesticides (Pascual et al., 2000; Ros et al., 2005). Soil microorganisms, mainly bacteria and fungi, and their extracellular enzymes, mostly of microbial origin (Tabatabai, 1994) are responsible for the biological transformations that make nutrients available to plants and for sustaining soil functions. Since soil microbial communities play a critical role in the recovery of a soil from a disturbance (Bending et al., 2000; Breure, 2005), measurements of the characteristics of the microbial community provide invaluable information for soil quality and for a sustainable management of agricultural soils. The use of biological indicators has the problem of knowing which indicator responds to a specific soil treatment or contaminant. Therefore, the use of multiple biological and biochemical properties is often suggested. General biochemical properties such as microbial biomass carbon (Brookes, 1995), or ecophysiological quotients (Anderson and Domsch, 1993), as well as specific biochemical properties such as hydrolytic soil enzymes related to C, N and P cycles (Nannipieri et al., 1990) are suggested. Molecular techniques, such as denaturing or temperature gradient gel electrophoresis (DGGE or TGGE); (Muyzer et al., 1993), or terminal restriction fragment length polymorphism (TRFLP) (Clement et al., 1998), amplified ribosomal DNA restriction analysis (ARDRA) (Tiquia et al., 2002), and 16S rDNA sequence analysis (Borneman and Triplett, 1997) have successfully been used to explore microbial diversity and to identify microorganisms (Muyzer and Ramsing, 1995). The diversity, abundance and activity of soil microorganisms are known to decrease with depth, since a major source of nutrient input is above-ground plant litter. Several authors have studied the vertical distribution of bacteria in soil (Fritze et al., 2000; Ekelund et al., 2001). However, little information is available on the vertical distribution of bacterial microbial activity and structure of the soil microbiota amended with different composts for long periods of time. The aim of this paper was to study the effect on soil microbial properties the addition of different composts (from urban organic waste, green waste, manure and sewage sludge) to a soil subjected to 12 yr crop rotation at different depths (0–10; 10–20 and 20–30 cm).
2. Materials and methods 2.1. Experimental design In 1991, a long-term crop rotation (maize, summerwheat and winter barley) experiment was performed near Linz (Austria). At the beginning of the experiment, the soil had a pH (H2O) of 6.8, 1.9% organic matter and 260 and 300 mg kg1available P and K, respectively (Aichberger et al., 2000).
The experiment was performed using a randomized design of five treatments with four replicates. Each plot had an area of (10 m 3 m) and was bordered by metal sheets. The treatments were added annually in spring time as follows: (1) Soil without fertilization (control). (2) Urban organic waste compost from domestic organic (kitchen) waste (OWC). (3) Green waste compost (GC) from leaf fall, tree pruning, garden clippings, and other bulky cellulose and ligninrich materials. (4) Cattle manure compost (MC) containing straw bedding impregnated with liquid and solid manure. (5) Sewage sludge compost, (SSC) from anaerobically stabilised sewage sludge produced by a municipal wastewater treatment plant combined with wood chips and bark as bulking agents. The main characteristics of the composts averaged over 12 yr are given in Table 1. Composting was carried out in heaps with periodical turning. Composts were incorporated into the plots by ploughing (0–25 cm depth) at an N rate equivalent of 175 kg N ha1. The composts were supplemented with a mineral fertilization of 80 kg N (NH4NO3) per hectare. Since the composts were all mature, only limited immediate availability of nutrients was anticipated (it is estimated that about 15% of the compost N is available during the first year after application (Amlinger et al., 2003). Total heavy metal contents meet Austrian legislation for Class A+ composts (best category, Kompostverordnung, 2002), except for the sewage sludge compost. Soils were sampled on 15 October 2003 after maize harvest. Ten random soil cores from each treated plot at different depths (0–10, 10–20 and 20–30 cm, 6 cm diameter) were collected and bulked. The samples were immediately transported to the laboratory, sieved (o2 mm) and stored at 4 1C for biochemical analysis, at 4 1C for microbial community analysis and at room temperature for chemical analysis. 2.2. Chemical analysis The pH was measured in an aqueous extract (1/5 w/v). Total organic C (Corg) was measured by dry combustion (Insam, 1996). Total N (Nt) was measured by the Kjeldahl method. Total P, total K and heavy metals were determined with Atomic Absorption Spectroscopy after wet acid digestion of the samples (O¨NORM L 1085, 1999). 2.3. Microbial biomass and respiration Basal respiration was measured as CO2 evolution from moist (60% WHC) soil samples at 22 1C, using a continuous flow infrared gas analysis system (IRGA) (Heinemeyer et al., 1989). Microbial biomass carbon (Cmic)
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Table 1 Chemical properties of different composts Compostsa
Urban organic wastes compost
Total organic C (g kg1) Total N (g kg1) C/N P2O5 (g kg1) K2 O (g kg1) Cu (mg kg1) Zn (mg kg1) Ni (mg kg1) Cr (mg kg1) Pb (mg kg1) Cd (mg kg1) Hg (mg kg1)
258 12 16 27 6 70 277 21 32 75 0.56 0.24
a
(42)b (1.8) (0.1) (1.3) (0.5) (1.5) (4.5) (1.3) (1.2) (2.8) (0.02) (0.01)
Green compost
Manure compost
Sewage sludge compost
274 16 13 14 13 38 163 22 28 28 0.34 0.15
211 13 10 12 13 41 213 19 15 13 0.20 0.07
368(38) 22 (2.0) 12 (0.1) 19 (1.6) 32 (0.9) 168 (1.0) 630 (4.3) 36 (0.8) 40 (1.3) 70 (2.4) 0.89 (0.01) 0.85 (0.1)
(29) (0.6) (0.1) (1.0) (0.5) (1.3) (3.8) (1.0) (0.6) (2.2) (0.01) (0.009)
(35) (0.7) (0.1) (0.8) (0.2) (1.4) (2.8) (0.5) (0.5) (1.8) (0.01) (0.009)
Data is on a dry mass basis and an average of chemical properties obtained during 12 years for each compost. Numbers in parenthesis indicate standard deviation.
b
was determined by substrate-induced respiration (SIR) after the addition of 1% glucose (Anderson and Domsch, 1978), using the IRGA as above. 2.4. Soil hydrolase activity Urease was determined by incubation of 0.48% urea with borate buffer at pH 10 (2 h at 37 1C). Activity was determined by measuring the released NH+ with a 4 spectrophotometer (Helios a, Thermo) at 690 nm (Kandeler and Gerber, 1988). Protease activities were determined by incubation of 0.03 M N-a-benzoyl-L-argininamide (BAA) with 0.1 M phosphate buffer at pH 7 (1 h at 40 1C) (Bonmatı´ et al., 1998). Activity was determined by quantification of the released NH+ 4 with a spectrophotometer (Helios a, Thermo) at 690 nm (Kandeler and Gerber, 1988). Phosphatase and b-glucosidase activity were determined using 0.115 M p-nitrophenyl phosphate (PNPP) dissolved in MUB (pH 11) (1 h at 37 1C) (Tabatabai and Bremmer, 1969) and 0.05 M p-nitrophenyl-b-D-glucopyranoside (PNG) dissolved in modified universal buffer (MUB-HCl buffer pH 6) (Eivazi and Tabatabai, 1988) respectively as substrates. These assays are based on the release of p-nitrophenol (PNP), which was measured with a spectrophotometer (Helios a, Thermo) at 400 nm.
(DGGE). Each polymerase chain reaction (PCR) mixture contained 2 ml of extracted DNA diluted 1:250 as a template, 0.2 mM of each primer, 0.04 U ml1 Bio ThermTM DNA Polymerase (Gene Craft), 1 DNA polymerase buffer, Bovine serum albumin (BSA) 10 mg ml1, 20 mM tetramethylammonium chloride (TMA), 0.2 mmol of each of the dNTPs and 3 mM MgCl2 in a final volume of 50 ml. The PCR included an initial 5 min denaturation at 94 1C and was followed by 30 thermal cycles of 1 min at 95 1C, 1 min at 56 1C, and 1 min at 72 1C. Thermal cycling was completed with an extension step at 72 1C for 5 min. Products were checked by electrophoresis in 1.5% (w/v) agarose gels and ethidium bromide staining (10 mg ml1). DGGE was performed with the Bio-Rad DCode System. Two microliter of PCR product was loaded on polyacrylamide gels with a denaturing gradient of 40% (7%(w/v) acrylamide–bisacrylamide (37.5:1), 2.55 M urea, 14.68% formamide) to 70% (7%(w/v) acrylamide– bisacrylamide (37.5:1), 3.57 M urea, 20.56% formamide) with 1 Tris–acetate EDTA (EDTA) buffer at 60 1C and 60 V for 16 h. After silver staining of the gels (Sanguinetti et al., 1994) in an automated gel stainer (Hoefer, Amersham Pharmacia, Germany), gels were air dried and scanned. 2.6. Community structure of ammonia oxidizers
2.5. Bacterial community structure Total DNA was extracted from the bulk soil using the Fast DNA Spin Kit for soil (BIO 101, USA). The amount of DNA was estimated visually after electrophoresis in 1.5% agarose gels by ethidium bromide (10 mg ml1) staining. Soil DNA was amplified in a PCR thermocycler (PCR Express, ThermoHybaid) with the universal bacterial primer set for 16S rDNA: 338f-GC (Muyzer et al., 1993) and 907r (Schwieger and Tebbe, 1998), to obtain products of about 570 bp for denaturing gradient gel electrophoresis
DNA was extracted directly from soil as described above. Two sets of PCR primers were used to recover NH3oxidizing bacterial communities. Primers 63f and 1378r were used to amplify the entire 16S rDNA sequence (1.3 Kb) (Boon et al., 2002). One microliter of the first PCR product was used as template DNA in a second PCR amplification with the primers CTOf189-GC and CTO654r, for DGGE analysis. These primers specifically amplify a 465-bp fragment of the 16S rDNA gene from b-proteobacterial NH3-oxidizing bacteria (Kowalchuk
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et al., 1997). The PCR conditions were as described above, with 1 ml of template in a final volume of 25 ml. The first PCR amplification was performed at 94 1C for 1 min, followed by 30 thermal cycles at 95 1C for 1 min, 54 1C for 1 min, and 72 1C for 2 min, and a final extension at 72 1C for 10 min. The second PCR was performed at 95 1C for 3 min, followed by 30 thermal cycles at 95 1C for 1 min, 57 1C for 1 min, and 72 1C for 1 min, and a final extension at 72 1C for 10 min. An aliquot (1.5 ml) of the PCR products (465 bp) recovered with the CTO primers was subjected to DGGE under the conditions as described above. 2.7. Analysis of DGGE patterns Scanned gels were analyzed after normalization with the GelCompar software (version 3.50; Applied Maths, Ghent, Belgium). The similarity matrices for the DGGE profiles were based on the Jaccard coefficient (Jaccard, 1908), using optimized search criteria determined in GelCompar (for bacteria: 0% optimization, 0.72% position tolerance, 0.50% minimum height; for ammonia oxidizer: 0% optimization, 0.48% position tolerance 4% minimum height). The dendrograms were created using a clustering method based on the Ward method (Ward, 1963). The Shannon–Weiner diversity index (H) (Hill et al., 2003), was calculated for bacteria and ammonia-oxidizers P by using the following function: H 0 ¼ pi ðln pi Þ, where pi is the importance of the bands in a lane. The index (H0 ) was calculated on the basis of peak heights of the bands. The importance probability pi was calculated as pi ¼ ni/N; where ni is the height of peak and N is the sum of all peak heights in the lanes.
3. Results 3.1. Chemical properties Total organic C and Nt generally declined with depth (Table 2). The only exception was Nt for the control soils. In general, compost-treated soils resulted in significantly (Pp0:05) higher Corg contents compared to control soil at 0–10 cm and 10–20 cm, and SSC-treated soil showed the highest Corg content (Table 2). For total N there was a significant (Pp0:05) interaction between treatments and depth. Total N across the 0–20 cm depth was significantly (Pp0:05) higher in the compost-treated soils than in the control plots. No significant differences (Pp0:05) between compost-treated soils were found, and no difference between control and compost-treated soils was found at 20–30 cm depth. 3.2. Bulk biological properties Microbial biomass carbon and basal respiration showed a significant (Pp0:05) interaction between treatments and depths, and in general, they declined significantly (Pp0:05) with depth (Table 3). At 0–10 cm depth, no difference among treatments was found for Cmic, while at 10–20 cm and 20–30 cm depth Cmic values for compost-treated soils were higher than those for the control. In most cases, basal respiration in compost-treated soils was enhanced compared to the control. The effect was not consistent throughout the depths. Basal respiration was significantly correlated with Cmic, and Corg (Spearman correlation 0.65 and 0.62 (Pp0:01), respectively), and also Cmic and Corg were closely correlated (Spearman correlation 0.51 (Pp0:01)).
2.8. Statistical analysis 3.3. Soil hydrolase activities Data were analyzed by SPSS 13.0 software. Two-way univariate ANOVA was used for the statistical analysis of the effects of treatments and depths. In cases of significant F-statistics Tukey’s posthoc test (Pp0:05) was selected to separate the means. Spearman correlation coefficients were calculated between chemical, biochemical and diversity properties.
Significant differences (Pp0:05) among treatments and depths were found for protease, phosphatase and b-glucosidase (Fig. 1). At each depth no significant differences (Pp0:05) were found for urease activity between compost-treated soils and control soil. The lowest values of urease activity were found at 20–30 cm depth
Table 2 Chemical properties of soil samples collected at different depths from the field experiment
Treatments Control OWC GC MC SSC
Corg (g C kg1 soil)
Nt (g N kg1 soil)
Depth (cm)
Depth (cm)
0–10 11.86a 15.18b 13.88ab 14.15ab 16.70c
(0.73) (0.05) (0.22) (0.17) (0.14)
10–20 10.96a 15.10bc 14.50bc 13.08ab 15.80c
(0.90) (0.29) (0.12) (0.12) (0.04)
20–30 10.9a 12.13a 12.95a 12.85a 15.45b
(0.22) (0.06) (0.19) (0.09) (0.11)
0–10 1.5a 1.80c 1.80c 1.70b 1.77b
(0.04) (0.08) (0.01) (0.01) (0.05)
10–20 1.5a (0.03) 1.73b (0.05) 1.73b (0.05) 1.70b (0.01) 1.73b (0.01)
20–30 1.5a (0.04) 1.50a (0.01) 1.50a (0.01) 1.53a (0.05) 1.43a (0.05)
Numbers in parenthesis indicate standard deviation, n ¼ 4. For each depth, values with the same letters are not significantly different (Pp0:05). OWC: Urban organic waste compost; GC: green waste compost; MC: manure compost; SSC: Sewage sludge compost.
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Table 3 Biochemical properties of soil samples collected at different depths from the field experiment
Treatments Control OWC GC MC SSC
Cmic (mgC g1 soil)
Basal respiration (mg CO2 g1 soil h1)
Depth (cm)
Depth (cm)
0–10 170.2a 170.3a 168.5a 173.5a 168.3a
(14.9) (7.34) (12.4) (6.59) (10.9)
10–20 135.9a 189.4c 146.8b 146.2b 171.7c
(9.0) (6.78) (9.9) (10.0) (8.12)
20–30 103.6a 119.3b 119.9b 122.6b 116.8b
(9.7) (7.0) (5.7) (12.3) (14.1)
0–10 0.69ab 0.76ab 0.60a 1.02ab 1.09a
(0.03) (0.05) (0.22) (0.17) (0.14)
10–20 0.52a (0.04) 0.99b (0.09) 0.52a (0.12) 0.50a (0.12) 1.07b (0.04)
20–30 0.28a 0.55bc 0.69c 0.43ab 0.71c
(0.06) (0.06) (0.19) (0.09) (0.11)
Numbers in parenthesis indicate standard deviation, n ¼ 4. For each depth, values with the same letters are not significantly different (Pp0:05). OWC: Urban organic waste compost; GC: green waste compost; MC: manure compost; SSC: Sewage sludge compost.
(Fig. 1a). The highest protease activity in all treatments was showed at 10–20 cm and 20–30 cm depths. At 0–10 cm and 20–30 cm compost-treated soils showed, in general, significant (Pp0:05) higher activity than control, although differences were not always significant (Fig. 1b). Urease activity was not significantly correlated with Corg, Cmic, and basal respiration, whereas protease activity was significantly negatively correlated with Corg (Spearman correlation 0.32, Pp0:05), Cmic and basal respiration (0.44 and 0.53 (Pp0:01), respectively). Phosphatase activity was, in general, significant (Pp0:05) higher in compost-treated soils than in control soil for all depths although differences were not always significant. The highest activity was found at 10–20 cm (Fig. 1c). Sewage sludge and manure compost addition yielded the highest values of phosphatase activity. The activity of b-glucosidase was significantly (Pp0:05) higher in compost-treated soils than in the control soil, although differences were not always significant. The highest activity was found at 0–10 cm and 10–20 cm in all treatments (Fig. 1d). Manure compost addition showed the highest values of b-glucosidase activity.
treated soils, in general, showed less than 20% similarity compared with control soil. Using a more specific bacterial primer targeted at the ammonia oxidizers we found a similar pattern (Fig. 2b). Samples were again grouped in two major clusters, mainly separating among different depths. One cluster contained only the 20–30 cm layer samples (except GC 10–20 cm), while the other cluster was comprised of samples from 0 to 10 cm and 10 to 20 cm. The Shannon–Weiner diversity index was calculated for the bacteria and ammonia oxidizers from their DGGE patterns (Table 4). The range was from 1.29 to 1.41 and 0.74 to 1.09, respectively. Bacterial diversity, in general was significantly (Pp0:05) higher in compost-treated soil compared to control soil at 0–20 cm. Diversity of ammonia oxidizers for compost-treated soils tended to decrease with depth. No such decrease was found for the control soil (Table 4). Most compost-treated soils showed a significantly (Pp0:05) higher ammonia oxidizer diversity than the control soil at 0–10 cm and 10–20 cm. A positive and significant correlation (Spearman correlation 0.47, Pp0:01) between bacterial diversity and Cmic was found, and also between ammonia-oxidizer diversity and Cmic (Spearman correlation 0.68, Pp0:01).
3.4. Community analysis with PCR-DGGE Genetic fingerprinting by PCR-DGGE of bacterial 16S rDNA amplified fragments of soil DNA showed a complex DNA banding pattern, with some strong bands, some of lower intensity and a number of faint bands. Profiles of replicates from the same treatments were generally very similar. Cluster analysis was performed to infer similarities among the different banding patterns and the resulting dendrogram is presented (Fig. 2). The treatments were compared using the Jaccard similarity coefficient and Ward clustering. This procedure showed, for the general bacterial primer, two major clusters, one clustered together the deepest layer (20–30 cm) (30) of compost-treated soils and two samples of 10–20 cm depth (20). The second major cluster was comprised of samples from the upper layers (0–10 cm) (10) of compost-treated soils, a few of the 10–20 cm depth (20) and all control soils. Compost-
4. Discussion Generally, our results from this 12 yr long-term crop rotation experiment show significant differences of various chemical, biochemical and molecular properties between different depths and different treatments. 4.1. Chemical properties The decrease of organic C and N down the profile is in accordance with our knowledge of agricultural soils. Similar results have previously been found in agricultural long-term field experiments using sewage sludge compost (Zaman et al., 2004), municipal solid waste (Crecchio et al., 2004), and also in forest soil profiles (Agnelli et al., 2004). The application of different compost to the soil increased
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2.5
10-20 cm a b a
2.0 a
a
a a
a
1.5
a
a a a
a
aa
+
mol NH4g-1 h-1
probably due to the lignocellulosic material used as a bulking agent (tree bark) for composting the sewage sludge, which is not easily biodegradable. Total N decreased in compost-treated soils from the top to the lower layers, which is usually attributed to gaseous N losses, N-uptake by crops and NO 3 leaching (Zaman et al., 2004). From an environmental viewpoint it is interesting to note that Nt significantly increased on the compost-treated soils within the 0–20 cm layer, but not at all in the 20–30 cm layer. No differences were found for Nt between compost treatments probably due to the fact that the different composts were applied at equivalent N rates.
20-30 cm
1.0 0.5 0.0
(a)
Control 0-10 cm
7
+
mol NH4g-1 h-1
OWC
GC 10-20 cm a
6 5
a
4
SSC 20-30 cm c
ab
a b
a
MC
a a ab c
c
bc
3 2 1 0
(b)
Control
mol PNP g-1 h-1
60
OWC
0-10 cm
GC
MC
10-20 cm
SSC
20-30 cm c
50 b
40 a
30 20
a
a
ab
b
b
ab ab
ab
b
b
b b
10 0 Control
(c)
mol PNP g-1 h-1
20
OWC
0-10 cm a a
GC
MC
10-20 cm ab b
ab ab
15
b
SSC
20-30 cm b
b
c
b ab b
b
10 a
5 0
(d)
4.2. Bulk biological properties
a
a
Control
OWC
GC
MC
SSC
Fig. 1. Soil enzyme activities from samples collected at different depths in the field experiment: (a) urease; (b) protease (c) phosphatase (d) bglucosidase. (Bars represent standard deviation, n ¼ 4. For each depth, values with the same letters are not significantly different (Pp0:05)). OWC: Urban organic waste compost; GC: green waste compost; MC: manure compost; SSC: Sewage sludge compost.
Corg, compared to the control soil due to the organic matter incorporated with the compost, which also is in accordance with previous findings e.g. (Ros et al., 2003). The application of sewage sludge compost significantly increased Corg with respect to the other treatments; this is
Microbial biomass C is more sensitive than total organic C to indicate soil changes because it is related to soil microorganisms that are sensitive to soil variations (Powlson et al., 1987). According to earlier findings (Ekelund et al., 2001 and Fierer et al., 2003) values of Cmic and Corg decrease with soil depth. Microbial biomass C of the compost-treated soils was higher than that of the control soils, but only at 10–20 cm and 20–30 cm. Similar results were found by Garcia-Gil et al. (2000) and Ros et al. (2003) in soils amended with urban organic wastes compost at 0–25 cm. The increase of microbial biomass is mainly due to the microbial biomass contained in the organic residues and the addition of substrate C, which stimulates the indigenous soil microbiota. Similar dual effects have been reported (Garcia et al., 1998; Ros et al., 2003). The lack of a difference in the 0–10 cm layer may be attributed to an enhanced decomposition of the labile C fraction of the added organic matter in this layer (exhaustion of the easily available substrates in the time elapsed from the compost application to sampling). This is in agreement with data found by others, e.g. Powlson et al. (1987). The correlations between basal respiration, Corg and Cmic are in agreement with other research (e.g. Garcia et al., 2002). In general, Cmic was low compared to literature data. Borken et al. (2002) found a Cmic from 190 to 490 mg Cmic g1 for soil amended with organic waste compost after only one application; Garcia Gil et al. (2000) reported a range of 226–301 mg Cmic g1 in soils amended with compost and manure compost for five consecutive years. The relatively low microbial biomass in the present study may be attributed to the climatic conditions: the present data fit perfectly in the C equilibrium model of Insam et al. (1989) stating that when precipitation (P) equals potential evaporation (E) (P/E ¼ 1) at a certain site, the Cmic/Corg ratio is lower than found under other climatic conditions. At the site studied here, P/E is close to 1. Equilibrium has probably been reached and microorganisms maintain a low but constant activity due to adequate conditions for decomposition.
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20
40
60
80
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100
MC (-30) OWC (-30) SSC (-30) GC (-30) SSC (-20) MC (-20) GC (-10) OWC (-10) SSC (-10) MC (-10) GC (-20) OWC (-20) Control (-30) Control (-10) Control (-20)
(a) 0
20
40
60
80
100
Control (-30) OWC (-30) GC (-20) MC (-30) GC (-30) SSC (-30) GC (-10) OWC (-10) MC (-10) OWC (-20) Control (-20) SSC (-10) Control (-10) MC (-20) SSC (-20)
(b)
Fig. 2. Cluster analysis of the denaturing gradient gel electrophoresis patterns from soil samples collected at different depths in the field experiment (a) bacteria; (b) ammonia oxidizers. (The X-axis represents the percentage of similarity, based on the Jaccard coefficient). OWC: Urban organic waste compost; GC: green waste compost; MC: manure compost; SSC: Sewage sludge compost. (10) 0–10 cm layer; (20) 10–20 cm layer; (30) 20–30 cm layer.
Table 4 Shannon–Wiener diversity index of microbial diversity of soil samples collected at different depth increments in the field experiment Shannon–Wiener diversity index
Treatments Control OWC GC MC SSC
Bacteria, general (Hb)
Ammonia-oxidizers (Ha)
Depth (cm)
Depth (cm)
0–10 1.34a 1.31a 1.39b 1.37b 1.37b
(0.02) (0.03) (0.03) (0.03) (0.03)
10–20 1.27a (0.02) 1.31b (0.03) 1.31b (0.04) 1.33b (0.04) 1.41c (0.04)
20–30 1.31a 1.27a 1.37b 1.26a 1.33ab
(0.04) (0.05) (0.05) (0.04) (0.04)
0–10 0.87a 1.09d 1.0d 0.91b 0.96c
(0.03) (0.04) (0.04) (0.04) (0.04)
10–20 0.87a (0.03) 0.98b (0.03) 0.89a (0.05) 1.03c (0.05) 0.98b (0.03)
20–30 0.86b (0.04) 0.89c (0.03) 0.74a (0.05) 0.86c (0.05) 0.81b (0.03)
Numbers in brackets indicate standard deviation, n ¼ 4. For each depth, values with the same letters are not significantly different (Pp0:05). OWC: Urban organic waste compost; GC: green waste compost; MC: manure compost; SSC: Sewage sludge compost.
4.3. Soil hydrolase activities Urease and protease hydrolyze N compounds to ammonium, using urea and low molecular weight protein
substrates, respectively. No significant enhancement was found for urease in compost-treated soils compared to control soil, possibly due to a high amount of ammonium in compost-treated soils from the NH4NO3 incorporated
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with compost, which makes unnecessary the synthesis of urease activity. The lowest urease activity was found between 20 and 30 cm, which can be attributed to the lack of specific substrates in this layer and the lower content of microbial biomass carbon. Protease activity showed the highest activity from 10 to 30 cm depth in all treatments. It could be due to lixiviation of protease substrates to the deeper layer during raining periods and/ or protease enzyme released after cell lysis of micro organisms at the end of their life cycle (Perucci, 1990).The latest was based on the negative correlation of protease activity with biomass carbon. This is in contrast to the results of Zaman et al. (2002), who found the highest protease activities in soils amended with dung to be in the top 5 cm. Phosphatase activity plays an essential role in the mineralization of organic P and generally, this enzyme is activated when P availability is low, (Nannipieri et al., 1979). In general, compost-treated soils showed significantly higher phosphatase activity than control soil suggesting a higher amount of available substrates in compost-treated soils. This is in agreement with many reports on enhancement of phosphatase activities by organic matter addition (Jordan et al., 1995; Kremer and Li, 2003). The highest activity for all treatments was at 10–20 cm, which could be due to synthesis of the enzyme by root excretions and, also inorganic P demand by plants which would lead to protease synthesis (Nannipieri et al., 1990) could not be discarded. The hydrolysis of b-glucosides in soil or in decomposing plant residues (Hayano and Tubaki, 1985) is an important reaction making degradable substrates available to soil microorganisms (Eivazi and Tabatabai, 1990). Activation of b-glucosidase by compost indicates enhanced hydrolysis of the C derived from the incorporated organic matter, and remaining root and plant residues after harvest. The high b-glucosidase activity in MC-treated soil indicates an effect of substrate composition. This manure compost derives mainly from cereal straw (used as bedding for livestock), which is potentially more easily degradable than the main bulking agents of the other composts. Similar results have been found by other researchers (Dick et al., 1988; Marcote et al., 2001). After 12 yr of organic matter application, enzymes could be highly immobilized in soil, principally in the deeper layer. Enzymes are generally likely to adsorb to humic colloids and/or clay minerals (Burns, 1986), which provide them with a great resistance against thermal denaturation, dehydration and proteolysis (Perez-Mateos and Rad, 1989). Immobilised enzymes not only represent a biological capacity of the soil for substrate hydrolysis that is not dependent on the microbial community, but may also contribute to the permanence of the soil ecosystem and to important cycles such as those of C, N and P. immobilization of enzymes in compost has been observed, e.g., Garcia et al., 1993 found urease and phosphatase enzymes in the
compost organic matrix. Benitez et al. (2005) found b-glucosidase, urease and phosphatase in vermicomposting of a lignocellulosic olive. In soil, e.g., Pascual et al. (2002) demonstrated the persistence of total and immobilized urease and phosphatase in soils amended with compost. Wittman et al. (2004) found high activity of b-glucosidase in the humus layer of a forest soil. 4.4. Community analysis with PCR-DGGE Cluster analysis of 16S rDNA community profiles based on a general bacterial primer pair revealed complex profiles reflecting the high diversity of the microbial community. The bands in the DGGE profiles represent the dominant microbial populations (Muyzer et al., 1993). The DGGE banding patterns suggest that there are several dominant groups, which are relatively stable, independent of treatments and depths. The observed differences of patterns are likely due to differences in fainter bands. The control soil showed a similarity of o20% to compost-treated soils and the effect of different compost were less marked than depth. These data support the findings of Fierer et al. (2003) as well as Bundt et al. (2001) for Swiss forest soils using PCR-RFLP. Similar results were found by Boehm et al. (1993) who reported that differences in organic matter levels among different potting mixes compost amended dark peat mix, slightly decomposed light peat mix and decomposed peat mix had little impact on the diversity of rhizosphere communities. Ammonia oxidizing bacteria (AOB) play a key role in soil N cycling and are responsible for converting ammonia/ ammonium to nitrate via nitrite. Urease catalyzes hydrolysis of urea to produce ammonia that can be used by AOB. The results of cluster analysis and diversity index suggest that the ammonia-oxidizer community at (0–10 cm and 10–20 cm) depths was different to that from the deeper layer (20–30 cm) for all treatments including the control soil. These results are in agreement with the urease data. Urease activity was lower at 20–30 cm depth compared with the others depths, producing less ammonium, the substrate for ammonia-oxidizers. The ammonia-oxidizers showed higher diversity for compost-treated soils compared to control soil and the type of compost did not seem to influence the composition of the ammonia oxidizer community, despite considerable differences in the number of AOBs that have been found in differently treated soils (Innerebner et al., 2006). The correlation of bacterial and ammonia diversity and Cmic confirms earlier findings that microbial diversity and biomass are likely to be related to each other (Lynch et al., 2004). This paper shows that the continued addition of composts to soils enhanced Corg, Cmic, basal respiration and enzyme activities compared to control soil and that these effects declined with depth. A higher diversity of bacteria and ammonia oxidizers in compost-treated soils compared to control soil was evident, but the type of compost did not seem to influence the composition of microbial community
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as depth. The data support the commonly held view that the use of composts supports agricultural soil biodiversity and enhances soil C sequestration. Acknowledgments This study was supported by the Austrian Research Fund (FWF). M. Ros acknowledges a postdoc grant from Ministerio de Educacio´n, Cultura y Deporte. We also wish to express our gratitude to Austrian Agency for Health and Food Safety in particular J. So¨llinger and K. Aichberger for support with chemical soil analyses and for setting up and maintaining the plots. References Agnelli, A., Ascher, J., Corti, G., Ceccherini, M.T., Nannipieri, P., Pietramellara, G., 2004. Distribution of microbial communities in a forest soil profile investigated by microbial biomass, soil respiration and DGGE of total extracellular DNA. Soil Biology & Biochemistry 36, 859–868. Aichberger, K., Wimmer, J., Mayr, R., 2000. Auswirkung der Kompostanwendung auf Ertrag und Bodeneigenschaften. Alpenla¨ndisches Expertenforum, pp. 81–83. Amlinger, F., Go¨tz, B., Dreher, P., Geszti, J., Weissteiner, C., 2003. Nitrogen in biowaste and yard waste compost: dynamics of mobilisation and availability—a review. European Journal of Soil Biology 39, 107–116. Anderson, J.P.E., Domsch, K.H., 1978. Mineralization of bacteria and fungi in chloroform fumigated soils. Soil Biology & Biochemistry 10, 207–213. Anderson, T.H., Domsch, K.H., 1993. The metabolic quotient CO2 (QCO2) as a specific activity parameter to assess the effects of environmental conditions, such as pH, on the microbial biomass of forest soils. Soil Biology & Biochemistry 25, 393–395. Bending, G.D., Putland, C., Rayns, F., 2000. Changes in microbial community metabolism and labile organic matter fractions as early indicators of the impact of management on soil biological quality. Biology and Fertility of Soils 31, 78–84. Benitez, E., Sainz, H., Nogales, R., 2005. Hydrolytic enzyme activities of extracted humic substances during the vermicomposting of a lignocellolosic olive waste. Bioresource Technology 96, 785–790. Boehm, M., Madden, L.V., Hoitink, H.A.J., 1993. Effect of organic matter decomposition level on bacterial species diversity and composition in relationship to Pythium damping-off severity. Applied and Environmental Microbiology 59, 4171–4179. Bonmatı´ , M., Ceccanti, B., Nannipieri, P., 1998. Protease extraction from soil by sodium pyrophosphate and chemical characterization of the extracts. Soil Biology & Biochemistry 30, 2113–2125. Boon, N., De Windt, W., Verstraete, W., Top, E.M., 2002. Evaluation of nested PCR-DGGE (denaturing gradient gel electrophoresis) with group specific 16S rRNA primers for the analysis of bacterial communities from different wastewater treatment plants. FEMS Microbiology Ecology 39, 101–112. Borken, W., Muhs, A., Beese, F., 2002. Changes in microbial and soil properties following compost treatment of degraded temperate forest soils. Soil Biology & Biochemistry 34, 403–412. Borneman, J., Triplett, E.W., 1997. Molecular microbial diversity in soils from eastern Amazonia: evidence for unusual microorganisms and microbial population shifts associated with deforestation. Applied and Environmental Microbiology 63, 2647–2653. Breure, A.M., 2005. Ecological soil monitoring and quality assessment. In: Doelman, P., Eijsackers, H.J.P. (Eds.), Vital Soil: Function, Value and Properties. Elsevier, Amsterdam, pp. 281–305.
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Soil Biology & Biochemistry 38 (2006) 3443–3452 www.elsevier.com/locate/soilbio
Hydrolase activities, microbial biomass and bacterial community in a soil after long-term amendment with different composts M. Rosa,, J.A. Pascuala, C. Garciaa, M.T. Hernandeza, H. Insamb a
Centro de Edafologia y Biologia Aplicada del Segura (CEBAS-CSIC), Department of Soil and Water Conservation and Organic Waste Management, P O. Box 164, 30100 Espinardo-Murcia, Spain b Leopold-Franzens-Universita¨t, Institut fu¨r Mikrobiologie, TechnikerstraX e 25, 6020 Innsbruck, Austria Received 26 January 2006; received in revised form 26 May 2006; accepted 31 May 2006 Available online 10 July 2006
Abstract The use of composts in agricultural soils is a widespread practice and the positive effects on soil and plants are known from numerous studies. However, there have been few attempts to compare the effects of different kinds of composts in one single study. The aim of this paper is to investigate to what extent and to which soil depth four major types of composts would affect the soil and its microbiota. In a crop-rotation field experiment, composts produced from (i) urban organic wastes, (ii) green wastes, (iii) manure and (iv) sewage sludge were applied at a rate equivalent to 175 kg N ha1 yr1 for 12 years. General (total organic C (Corg), total N (Nt), microbial biomass C (Cmic), and basal respiration), specific (enzyme activities related to C, N and P cycles), biochemical properties and bacterial genetic diversity (based on DGGE analysis of 16S rDNA) were analyzed at different depths (0–10, 10–20 and 20–30 cm). Compost treatment increased Corg at all depths from 11 g kg1 for control soil to 16.7 g kg1 for the case of sewage sludge compost. Total N increased with compost treatment at 0–10 cm and 10–20 cm depths, but not at 20–30 cm. Basal respiration and Cmic declined with depth, and the composts resulted in an increase of Cmic and basal respiration. Enzyme activities were different depend on the enzyme and among compost treatments, but in general, the enzyme activities were higher in the upper layers (0–10 and 10–20 cm) than in the 20–30 cm layer. Diversity of ammonia oxidizers and bacteria was lower in the control than in the compost soils. The type of compost had less influence on the composition of the microbial communities than did soil depth. Some of the properties were sensitive enough to distinguish between different compost, while others were not. This stresses the need of multi-parameter approaches when investigating treatment effects on the soil microbial community. In general, with respect to measures of activity, biomass and community diversity, differences down the soil profile were more pronounced than those due to the compost treatments. r 2006 Elsevier Ltd. All rights reserved. Keywords: Compost; Hydrolase activities; Microbial activity; PCR-DGGE; Bacterial community; Ammonia oxidizers
1. Introduction Land application of products from organic wastes, such as composts and bio-fertilizers, is gaining importance all over Europe, as integrated and biological agriculture are becoming increasingly popular. This is because such products are often considered beneficial for the soil and at the same time the problem of organic waste streams is alleviated, resulting in an environmentally acceptable way Corresponding author. Tel.: +34 968396200; fax: +34 968396213.
E-mail address: [email protected] (M. Ros). 0038-0717/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.soilbio.2006.05.017
of recycling waste materials (Lalande et al., 2000; Masciandaro et al., 2000). Organic amendments activate the autochthonous microorganisms of the soil, and indirectly stimulate the biogeochemical cycles therein (Pascual et al., 1997), and they provide various minerals (e.g. N, P, and S) essential for plant nutrition. They also increase the soil organic matter content, and influence soil structure and many other related physical, chemical and biological properties. In addition, the microbial biodiversity may be increased (Peacock et al., 2001) and soil-borne pathogens may be reduced by stimulation of antagonistic organisms
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(Tilston et al., 2002) allowing less use of potentially harmful fumigants or pesticides (Pascual et al., 2000; Ros et al., 2005). Soil microorganisms, mainly bacteria and fungi, and their extracellular enzymes, mostly of microbial origin (Tabatabai, 1994) are responsible for the biological transformations that make nutrients available to plants and for sustaining soil functions. Since soil microbial communities play a critical role in the recovery of a soil from a disturbance (Bending et al., 2000; Breure, 2005), measurements of the characteristics of the microbial community provide invaluable information for soil quality and for a sustainable management of agricultural soils. The use of biological indicators has the problem of knowing which indicator responds to a specific soil treatment or contaminant. Therefore, the use of multiple biological and biochemical properties is often suggested. General biochemical properties such as microbial biomass carbon (Brookes, 1995), or ecophysiological quotients (Anderson and Domsch, 1993), as well as specific biochemical properties such as hydrolytic soil enzymes related to C, N and P cycles (Nannipieri et al., 1990) are suggested. Molecular techniques, such as denaturing or temperature gradient gel electrophoresis (DGGE or TGGE); (Muyzer et al., 1993), or terminal restriction fragment length polymorphism (TRFLP) (Clement et al., 1998), amplified ribosomal DNA restriction analysis (ARDRA) (Tiquia et al., 2002), and 16S rDNA sequence analysis (Borneman and Triplett, 1997) have successfully been used to explore microbial diversity and to identify microorganisms (Muyzer and Ramsing, 1995). The diversity, abundance and activity of soil microorganisms are known to decrease with depth, since a major source of nutrient input is above-ground plant litter. Several authors have studied the vertical distribution of bacteria in soil (Fritze et al., 2000; Ekelund et al., 2001). However, little information is available on the vertical distribution of bacterial microbial activity and structure of the soil microbiota amended with different composts for long periods of time. The aim of this paper was to study the effect on soil microbial properties the addition of different composts (from urban organic waste, green waste, manure and sewage sludge) to a soil subjected to 12 yr crop rotation at different depths (0–10; 10–20 and 20–30 cm).
2. Materials and methods 2.1. Experimental design In 1991, a long-term crop rotation (maize, summerwheat and winter barley) experiment was performed near Linz (Austria). At the beginning of the experiment, the soil had a pH (H2O) of 6.8, 1.9% organic matter and 260 and 300 mg kg1available P and K, respectively (Aichberger et al., 2000).
The experiment was performed using a randomized design of five treatments with four replicates. Each plot had an area of (10 m 3 m) and was bordered by metal sheets. The treatments were added annually in spring time as follows: (1) Soil without fertilization (control). (2) Urban organic waste compost from domestic organic (kitchen) waste (OWC). (3) Green waste compost (GC) from leaf fall, tree pruning, garden clippings, and other bulky cellulose and ligninrich materials. (4) Cattle manure compost (MC) containing straw bedding impregnated with liquid and solid manure. (5) Sewage sludge compost, (SSC) from anaerobically stabilised sewage sludge produced by a municipal wastewater treatment plant combined with wood chips and bark as bulking agents. The main characteristics of the composts averaged over 12 yr are given in Table 1. Composting was carried out in heaps with periodical turning. Composts were incorporated into the plots by ploughing (0–25 cm depth) at an N rate equivalent of 175 kg N ha1. The composts were supplemented with a mineral fertilization of 80 kg N (NH4NO3) per hectare. Since the composts were all mature, only limited immediate availability of nutrients was anticipated (it is estimated that about 15% of the compost N is available during the first year after application (Amlinger et al., 2003). Total heavy metal contents meet Austrian legislation for Class A+ composts (best category, Kompostverordnung, 2002), except for the sewage sludge compost. Soils were sampled on 15 October 2003 after maize harvest. Ten random soil cores from each treated plot at different depths (0–10, 10–20 and 20–30 cm, 6 cm diameter) were collected and bulked. The samples were immediately transported to the laboratory, sieved (o2 mm) and stored at 4 1C for biochemical analysis, at 4 1C for microbial community analysis and at room temperature for chemical analysis. 2.2. Chemical analysis The pH was measured in an aqueous extract (1/5 w/v). Total organic C (Corg) was measured by dry combustion (Insam, 1996). Total N (Nt) was measured by the Kjeldahl method. Total P, total K and heavy metals were determined with Atomic Absorption Spectroscopy after wet acid digestion of the samples (O¨NORM L 1085, 1999). 2.3. Microbial biomass and respiration Basal respiration was measured as CO2 evolution from moist (60% WHC) soil samples at 22 1C, using a continuous flow infrared gas analysis system (IRGA) (Heinemeyer et al., 1989). Microbial biomass carbon (Cmic)
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Table 1 Chemical properties of different composts Compostsa
Urban organic wastes compost
Total organic C (g kg1) Total N (g kg1) C/N P2O5 (g kg1) K2 O (g kg1) Cu (mg kg1) Zn (mg kg1) Ni (mg kg1) Cr (mg kg1) Pb (mg kg1) Cd (mg kg1) Hg (mg kg1)
258 12 16 27 6 70 277 21 32 75 0.56 0.24
a
(42)b (1.8) (0.1) (1.3) (0.5) (1.5) (4.5) (1.3) (1.2) (2.8) (0.02) (0.01)
Green compost
Manure compost
Sewage sludge compost
274 16 13 14 13 38 163 22 28 28 0.34 0.15
211 13 10 12 13 41 213 19 15 13 0.20 0.07
368(38) 22 (2.0) 12 (0.1) 19 (1.6) 32 (0.9) 168 (1.0) 630 (4.3) 36 (0.8) 40 (1.3) 70 (2.4) 0.89 (0.01) 0.85 (0.1)
(29) (0.6) (0.1) (1.0) (0.5) (1.3) (3.8) (1.0) (0.6) (2.2) (0.01) (0.009)
(35) (0.7) (0.1) (0.8) (0.2) (1.4) (2.8) (0.5) (0.5) (1.8) (0.01) (0.009)
Data is on a dry mass basis and an average of chemical properties obtained during 12 years for each compost. Numbers in parenthesis indicate standard deviation.
b
was determined by substrate-induced respiration (SIR) after the addition of 1% glucose (Anderson and Domsch, 1978), using the IRGA as above. 2.4. Soil hydrolase activity Urease was determined by incubation of 0.48% urea with borate buffer at pH 10 (2 h at 37 1C). Activity was determined by measuring the released NH+ with a 4 spectrophotometer (Helios a, Thermo) at 690 nm (Kandeler and Gerber, 1988). Protease activities were determined by incubation of 0.03 M N-a-benzoyl-L-argininamide (BAA) with 0.1 M phosphate buffer at pH 7 (1 h at 40 1C) (Bonmatı´ et al., 1998). Activity was determined by quantification of the released NH+ 4 with a spectrophotometer (Helios a, Thermo) at 690 nm (Kandeler and Gerber, 1988). Phosphatase and b-glucosidase activity were determined using 0.115 M p-nitrophenyl phosphate (PNPP) dissolved in MUB (pH 11) (1 h at 37 1C) (Tabatabai and Bremmer, 1969) and 0.05 M p-nitrophenyl-b-D-glucopyranoside (PNG) dissolved in modified universal buffer (MUB-HCl buffer pH 6) (Eivazi and Tabatabai, 1988) respectively as substrates. These assays are based on the release of p-nitrophenol (PNP), which was measured with a spectrophotometer (Helios a, Thermo) at 400 nm.
(DGGE). Each polymerase chain reaction (PCR) mixture contained 2 ml of extracted DNA diluted 1:250 as a template, 0.2 mM of each primer, 0.04 U ml1 Bio ThermTM DNA Polymerase (Gene Craft), 1 DNA polymerase buffer, Bovine serum albumin (BSA) 10 mg ml1, 20 mM tetramethylammonium chloride (TMA), 0.2 mmol of each of the dNTPs and 3 mM MgCl2 in a final volume of 50 ml. The PCR included an initial 5 min denaturation at 94 1C and was followed by 30 thermal cycles of 1 min at 95 1C, 1 min at 56 1C, and 1 min at 72 1C. Thermal cycling was completed with an extension step at 72 1C for 5 min. Products were checked by electrophoresis in 1.5% (w/v) agarose gels and ethidium bromide staining (10 mg ml1). DGGE was performed with the Bio-Rad DCode System. Two microliter of PCR product was loaded on polyacrylamide gels with a denaturing gradient of 40% (7%(w/v) acrylamide–bisacrylamide (37.5:1), 2.55 M urea, 14.68% formamide) to 70% (7%(w/v) acrylamide– bisacrylamide (37.5:1), 3.57 M urea, 20.56% formamide) with 1 Tris–acetate EDTA (EDTA) buffer at 60 1C and 60 V for 16 h. After silver staining of the gels (Sanguinetti et al., 1994) in an automated gel stainer (Hoefer, Amersham Pharmacia, Germany), gels were air dried and scanned. 2.6. Community structure of ammonia oxidizers
2.5. Bacterial community structure Total DNA was extracted from the bulk soil using the Fast DNA Spin Kit for soil (BIO 101, USA). The amount of DNA was estimated visually after electrophoresis in 1.5% agarose gels by ethidium bromide (10 mg ml1) staining. Soil DNA was amplified in a PCR thermocycler (PCR Express, ThermoHybaid) with the universal bacterial primer set for 16S rDNA: 338f-GC (Muyzer et al., 1993) and 907r (Schwieger and Tebbe, 1998), to obtain products of about 570 bp for denaturing gradient gel electrophoresis
DNA was extracted directly from soil as described above. Two sets of PCR primers were used to recover NH3oxidizing bacterial communities. Primers 63f and 1378r were used to amplify the entire 16S rDNA sequence (1.3 Kb) (Boon et al., 2002). One microliter of the first PCR product was used as template DNA in a second PCR amplification with the primers CTOf189-GC and CTO654r, for DGGE analysis. These primers specifically amplify a 465-bp fragment of the 16S rDNA gene from b-proteobacterial NH3-oxidizing bacteria (Kowalchuk
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et al., 1997). The PCR conditions were as described above, with 1 ml of template in a final volume of 25 ml. The first PCR amplification was performed at 94 1C for 1 min, followed by 30 thermal cycles at 95 1C for 1 min, 54 1C for 1 min, and 72 1C for 2 min, and a final extension at 72 1C for 10 min. The second PCR was performed at 95 1C for 3 min, followed by 30 thermal cycles at 95 1C for 1 min, 57 1C for 1 min, and 72 1C for 1 min, and a final extension at 72 1C for 10 min. An aliquot (1.5 ml) of the PCR products (465 bp) recovered with the CTO primers was subjected to DGGE under the conditions as described above. 2.7. Analysis of DGGE patterns Scanned gels were analyzed after normalization with the GelCompar software (version 3.50; Applied Maths, Ghent, Belgium). The similarity matrices for the DGGE profiles were based on the Jaccard coefficient (Jaccard, 1908), using optimized search criteria determined in GelCompar (for bacteria: 0% optimization, 0.72% position tolerance, 0.50% minimum height; for ammonia oxidizer: 0% optimization, 0.48% position tolerance 4% minimum height). The dendrograms were created using a clustering method based on the Ward method (Ward, 1963). The Shannon–Weiner diversity index (H) (Hill et al., 2003), was calculated for bacteria and ammonia-oxidizers P by using the following function: H 0 ¼ pi ðln pi Þ, where pi is the importance of the bands in a lane. The index (H0 ) was calculated on the basis of peak heights of the bands. The importance probability pi was calculated as pi ¼ ni/N; where ni is the height of peak and N is the sum of all peak heights in the lanes.
3. Results 3.1. Chemical properties Total organic C and Nt generally declined with depth (Table 2). The only exception was Nt for the control soils. In general, compost-treated soils resulted in significantly (Pp0:05) higher Corg contents compared to control soil at 0–10 cm and 10–20 cm, and SSC-treated soil showed the highest Corg content (Table 2). For total N there was a significant (Pp0:05) interaction between treatments and depth. Total N across the 0–20 cm depth was significantly (Pp0:05) higher in the compost-treated soils than in the control plots. No significant differences (Pp0:05) between compost-treated soils were found, and no difference between control and compost-treated soils was found at 20–30 cm depth. 3.2. Bulk biological properties Microbial biomass carbon and basal respiration showed a significant (Pp0:05) interaction between treatments and depths, and in general, they declined significantly (Pp0:05) with depth (Table 3). At 0–10 cm depth, no difference among treatments was found for Cmic, while at 10–20 cm and 20–30 cm depth Cmic values for compost-treated soils were higher than those for the control. In most cases, basal respiration in compost-treated soils was enhanced compared to the control. The effect was not consistent throughout the depths. Basal respiration was significantly correlated with Cmic, and Corg (Spearman correlation 0.65 and 0.62 (Pp0:01), respectively), and also Cmic and Corg were closely correlated (Spearman correlation 0.51 (Pp0:01)).
2.8. Statistical analysis 3.3. Soil hydrolase activities Data were analyzed by SPSS 13.0 software. Two-way univariate ANOVA was used for the statistical analysis of the effects of treatments and depths. In cases of significant F-statistics Tukey’s posthoc test (Pp0:05) was selected to separate the means. Spearman correlation coefficients were calculated between chemical, biochemical and diversity properties.
Significant differences (Pp0:05) among treatments and depths were found for protease, phosphatase and b-glucosidase (Fig. 1). At each depth no significant differences (Pp0:05) were found for urease activity between compost-treated soils and control soil. The lowest values of urease activity were found at 20–30 cm depth
Table 2 Chemical properties of soil samples collected at different depths from the field experiment
Treatments Control OWC GC MC SSC
Corg (g C kg1 soil)
Nt (g N kg1 soil)
Depth (cm)
Depth (cm)
0–10 11.86a 15.18b 13.88ab 14.15ab 16.70c
(0.73) (0.05) (0.22) (0.17) (0.14)
10–20 10.96a 15.10bc 14.50bc 13.08ab 15.80c
(0.90) (0.29) (0.12) (0.12) (0.04)
20–30 10.9a 12.13a 12.95a 12.85a 15.45b
(0.22) (0.06) (0.19) (0.09) (0.11)
0–10 1.5a 1.80c 1.80c 1.70b 1.77b
(0.04) (0.08) (0.01) (0.01) (0.05)
10–20 1.5a (0.03) 1.73b (0.05) 1.73b (0.05) 1.70b (0.01) 1.73b (0.01)
20–30 1.5a (0.04) 1.50a (0.01) 1.50a (0.01) 1.53a (0.05) 1.43a (0.05)
Numbers in parenthesis indicate standard deviation, n ¼ 4. For each depth, values with the same letters are not significantly different (Pp0:05). OWC: Urban organic waste compost; GC: green waste compost; MC: manure compost; SSC: Sewage sludge compost.
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Table 3 Biochemical properties of soil samples collected at different depths from the field experiment
Treatments Control OWC GC MC SSC
Cmic (mgC g1 soil)
Basal respiration (mg CO2 g1 soil h1)
Depth (cm)
Depth (cm)
0–10 170.2a 170.3a 168.5a 173.5a 168.3a
(14.9) (7.34) (12.4) (6.59) (10.9)
10–20 135.9a 189.4c 146.8b 146.2b 171.7c
(9.0) (6.78) (9.9) (10.0) (8.12)
20–30 103.6a 119.3b 119.9b 122.6b 116.8b
(9.7) (7.0) (5.7) (12.3) (14.1)
0–10 0.69ab 0.76ab 0.60a 1.02ab 1.09a
(0.03) (0.05) (0.22) (0.17) (0.14)
10–20 0.52a (0.04) 0.99b (0.09) 0.52a (0.12) 0.50a (0.12) 1.07b (0.04)
20–30 0.28a 0.55bc 0.69c 0.43ab 0.71c
(0.06) (0.06) (0.19) (0.09) (0.11)
Numbers in parenthesis indicate standard deviation, n ¼ 4. For each depth, values with the same letters are not significantly different (Pp0:05). OWC: Urban organic waste compost; GC: green waste compost; MC: manure compost; SSC: Sewage sludge compost.
(Fig. 1a). The highest protease activity in all treatments was showed at 10–20 cm and 20–30 cm depths. At 0–10 cm and 20–30 cm compost-treated soils showed, in general, significant (Pp0:05) higher activity than control, although differences were not always significant (Fig. 1b). Urease activity was not significantly correlated with Corg, Cmic, and basal respiration, whereas protease activity was significantly negatively correlated with Corg (Spearman correlation 0.32, Pp0:05), Cmic and basal respiration (0.44 and 0.53 (Pp0:01), respectively). Phosphatase activity was, in general, significant (Pp0:05) higher in compost-treated soils than in control soil for all depths although differences were not always significant. The highest activity was found at 10–20 cm (Fig. 1c). Sewage sludge and manure compost addition yielded the highest values of phosphatase activity. The activity of b-glucosidase was significantly (Pp0:05) higher in compost-treated soils than in the control soil, although differences were not always significant. The highest activity was found at 0–10 cm and 10–20 cm in all treatments (Fig. 1d). Manure compost addition showed the highest values of b-glucosidase activity.
treated soils, in general, showed less than 20% similarity compared with control soil. Using a more specific bacterial primer targeted at the ammonia oxidizers we found a similar pattern (Fig. 2b). Samples were again grouped in two major clusters, mainly separating among different depths. One cluster contained only the 20–30 cm layer samples (except GC 10–20 cm), while the other cluster was comprised of samples from 0 to 10 cm and 10 to 20 cm. The Shannon–Weiner diversity index was calculated for the bacteria and ammonia oxidizers from their DGGE patterns (Table 4). The range was from 1.29 to 1.41 and 0.74 to 1.09, respectively. Bacterial diversity, in general was significantly (Pp0:05) higher in compost-treated soil compared to control soil at 0–20 cm. Diversity of ammonia oxidizers for compost-treated soils tended to decrease with depth. No such decrease was found for the control soil (Table 4). Most compost-treated soils showed a significantly (Pp0:05) higher ammonia oxidizer diversity than the control soil at 0–10 cm and 10–20 cm. A positive and significant correlation (Spearman correlation 0.47, Pp0:01) between bacterial diversity and Cmic was found, and also between ammonia-oxidizer diversity and Cmic (Spearman correlation 0.68, Pp0:01).
3.4. Community analysis with PCR-DGGE Genetic fingerprinting by PCR-DGGE of bacterial 16S rDNA amplified fragments of soil DNA showed a complex DNA banding pattern, with some strong bands, some of lower intensity and a number of faint bands. Profiles of replicates from the same treatments were generally very similar. Cluster analysis was performed to infer similarities among the different banding patterns and the resulting dendrogram is presented (Fig. 2). The treatments were compared using the Jaccard similarity coefficient and Ward clustering. This procedure showed, for the general bacterial primer, two major clusters, one clustered together the deepest layer (20–30 cm) (30) of compost-treated soils and two samples of 10–20 cm depth (20). The second major cluster was comprised of samples from the upper layers (0–10 cm) (10) of compost-treated soils, a few of the 10–20 cm depth (20) and all control soils. Compost-
4. Discussion Generally, our results from this 12 yr long-term crop rotation experiment show significant differences of various chemical, biochemical and molecular properties between different depths and different treatments. 4.1. Chemical properties The decrease of organic C and N down the profile is in accordance with our knowledge of agricultural soils. Similar results have previously been found in agricultural long-term field experiments using sewage sludge compost (Zaman et al., 2004), municipal solid waste (Crecchio et al., 2004), and also in forest soil profiles (Agnelli et al., 2004). The application of different compost to the soil increased
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2.5
10-20 cm a b a
2.0 a
a
a a
a
1.5
a
a a a
a
aa
+
mol NH4g-1 h-1
probably due to the lignocellulosic material used as a bulking agent (tree bark) for composting the sewage sludge, which is not easily biodegradable. Total N decreased in compost-treated soils from the top to the lower layers, which is usually attributed to gaseous N losses, N-uptake by crops and NO 3 leaching (Zaman et al., 2004). From an environmental viewpoint it is interesting to note that Nt significantly increased on the compost-treated soils within the 0–20 cm layer, but not at all in the 20–30 cm layer. No differences were found for Nt between compost treatments probably due to the fact that the different composts were applied at equivalent N rates.
20-30 cm
1.0 0.5 0.0
(a)
Control 0-10 cm
7
+
mol NH4g-1 h-1
OWC
GC 10-20 cm a
6 5
a
4
SSC 20-30 cm c
ab
a b
a
MC
a a ab c
c
bc
3 2 1 0
(b)
Control
mol PNP g-1 h-1
60
OWC
0-10 cm
GC
MC
10-20 cm
SSC
20-30 cm c
50 b
40 a
30 20
a
a
ab
b
b
ab ab
ab
b
b
b b
10 0 Control
(c)
mol PNP g-1 h-1
20
OWC
0-10 cm a a
GC
MC
10-20 cm ab b
ab ab
15
b
SSC
20-30 cm b
b
c
b ab b
b
10 a
5 0
(d)
4.2. Bulk biological properties
a
a
Control
OWC
GC
MC
SSC
Fig. 1. Soil enzyme activities from samples collected at different depths in the field experiment: (a) urease; (b) protease (c) phosphatase (d) bglucosidase. (Bars represent standard deviation, n ¼ 4. For each depth, values with the same letters are not significantly different (Pp0:05)). OWC: Urban organic waste compost; GC: green waste compost; MC: manure compost; SSC: Sewage sludge compost.
Corg, compared to the control soil due to the organic matter incorporated with the compost, which also is in accordance with previous findings e.g. (Ros et al., 2003). The application of sewage sludge compost significantly increased Corg with respect to the other treatments; this is
Microbial biomass C is more sensitive than total organic C to indicate soil changes because it is related to soil microorganisms that are sensitive to soil variations (Powlson et al., 1987). According to earlier findings (Ekelund et al., 2001 and Fierer et al., 2003) values of Cmic and Corg decrease with soil depth. Microbial biomass C of the compost-treated soils was higher than that of the control soils, but only at 10–20 cm and 20–30 cm. Similar results were found by Garcia-Gil et al. (2000) and Ros et al. (2003) in soils amended with urban organic wastes compost at 0–25 cm. The increase of microbial biomass is mainly due to the microbial biomass contained in the organic residues and the addition of substrate C, which stimulates the indigenous soil microbiota. Similar dual effects have been reported (Garcia et al., 1998; Ros et al., 2003). The lack of a difference in the 0–10 cm layer may be attributed to an enhanced decomposition of the labile C fraction of the added organic matter in this layer (exhaustion of the easily available substrates in the time elapsed from the compost application to sampling). This is in agreement with data found by others, e.g. Powlson et al. (1987). The correlations between basal respiration, Corg and Cmic are in agreement with other research (e.g. Garcia et al., 2002). In general, Cmic was low compared to literature data. Borken et al. (2002) found a Cmic from 190 to 490 mg Cmic g1 for soil amended with organic waste compost after only one application; Garcia Gil et al. (2000) reported a range of 226–301 mg Cmic g1 in soils amended with compost and manure compost for five consecutive years. The relatively low microbial biomass in the present study may be attributed to the climatic conditions: the present data fit perfectly in the C equilibrium model of Insam et al. (1989) stating that when precipitation (P) equals potential evaporation (E) (P/E ¼ 1) at a certain site, the Cmic/Corg ratio is lower than found under other climatic conditions. At the site studied here, P/E is close to 1. Equilibrium has probably been reached and microorganisms maintain a low but constant activity due to adequate conditions for decomposition.
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20
40
60
80
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100
MC (-30) OWC (-30) SSC (-30) GC (-30) SSC (-20) MC (-20) GC (-10) OWC (-10) SSC (-10) MC (-10) GC (-20) OWC (-20) Control (-30) Control (-10) Control (-20)
(a) 0
20
40
60
80
100
Control (-30) OWC (-30) GC (-20) MC (-30) GC (-30) SSC (-30) GC (-10) OWC (-10) MC (-10) OWC (-20) Control (-20) SSC (-10) Control (-10) MC (-20) SSC (-20)
(b)
Fig. 2. Cluster analysis of the denaturing gradient gel electrophoresis patterns from soil samples collected at different depths in the field experiment (a) bacteria; (b) ammonia oxidizers. (The X-axis represents the percentage of similarity, based on the Jaccard coefficient). OWC: Urban organic waste compost; GC: green waste compost; MC: manure compost; SSC: Sewage sludge compost. (10) 0–10 cm layer; (20) 10–20 cm layer; (30) 20–30 cm layer.
Table 4 Shannon–Wiener diversity index of microbial diversity of soil samples collected at different depth increments in the field experiment Shannon–Wiener diversity index
Treatments Control OWC GC MC SSC
Bacteria, general (Hb)
Ammonia-oxidizers (Ha)
Depth (cm)
Depth (cm)
0–10 1.34a 1.31a 1.39b 1.37b 1.37b
(0.02) (0.03) (0.03) (0.03) (0.03)
10–20 1.27a (0.02) 1.31b (0.03) 1.31b (0.04) 1.33b (0.04) 1.41c (0.04)
20–30 1.31a 1.27a 1.37b 1.26a 1.33ab
(0.04) (0.05) (0.05) (0.04) (0.04)
0–10 0.87a 1.09d 1.0d 0.91b 0.96c
(0.03) (0.04) (0.04) (0.04) (0.04)
10–20 0.87a (0.03) 0.98b (0.03) 0.89a (0.05) 1.03c (0.05) 0.98b (0.03)
20–30 0.86b (0.04) 0.89c (0.03) 0.74a (0.05) 0.86c (0.05) 0.81b (0.03)
Numbers in brackets indicate standard deviation, n ¼ 4. For each depth, values with the same letters are not significantly different (Pp0:05). OWC: Urban organic waste compost; GC: green waste compost; MC: manure compost; SSC: Sewage sludge compost.
4.3. Soil hydrolase activities Urease and protease hydrolyze N compounds to ammonium, using urea and low molecular weight protein
substrates, respectively. No significant enhancement was found for urease in compost-treated soils compared to control soil, possibly due to a high amount of ammonium in compost-treated soils from the NH4NO3 incorporated
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with compost, which makes unnecessary the synthesis of urease activity. The lowest urease activity was found between 20 and 30 cm, which can be attributed to the lack of specific substrates in this layer and the lower content of microbial biomass carbon. Protease activity showed the highest activity from 10 to 30 cm depth in all treatments. It could be due to lixiviation of protease substrates to the deeper layer during raining periods and/ or protease enzyme released after cell lysis of micro organisms at the end of their life cycle (Perucci, 1990).The latest was based on the negative correlation of protease activity with biomass carbon. This is in contrast to the results of Zaman et al. (2002), who found the highest protease activities in soils amended with dung to be in the top 5 cm. Phosphatase activity plays an essential role in the mineralization of organic P and generally, this enzyme is activated when P availability is low, (Nannipieri et al., 1979). In general, compost-treated soils showed significantly higher phosphatase activity than control soil suggesting a higher amount of available substrates in compost-treated soils. This is in agreement with many reports on enhancement of phosphatase activities by organic matter addition (Jordan et al., 1995; Kremer and Li, 2003). The highest activity for all treatments was at 10–20 cm, which could be due to synthesis of the enzyme by root excretions and, also inorganic P demand by plants which would lead to protease synthesis (Nannipieri et al., 1990) could not be discarded. The hydrolysis of b-glucosides in soil or in decomposing plant residues (Hayano and Tubaki, 1985) is an important reaction making degradable substrates available to soil microorganisms (Eivazi and Tabatabai, 1990). Activation of b-glucosidase by compost indicates enhanced hydrolysis of the C derived from the incorporated organic matter, and remaining root and plant residues after harvest. The high b-glucosidase activity in MC-treated soil indicates an effect of substrate composition. This manure compost derives mainly from cereal straw (used as bedding for livestock), which is potentially more easily degradable than the main bulking agents of the other composts. Similar results have been found by other researchers (Dick et al., 1988; Marcote et al., 2001). After 12 yr of organic matter application, enzymes could be highly immobilized in soil, principally in the deeper layer. Enzymes are generally likely to adsorb to humic colloids and/or clay minerals (Burns, 1986), which provide them with a great resistance against thermal denaturation, dehydration and proteolysis (Perez-Mateos and Rad, 1989). Immobilised enzymes not only represent a biological capacity of the soil for substrate hydrolysis that is not dependent on the microbial community, but may also contribute to the permanence of the soil ecosystem and to important cycles such as those of C, N and P. immobilization of enzymes in compost has been observed, e.g., Garcia et al., 1993 found urease and phosphatase enzymes in the
compost organic matrix. Benitez et al. (2005) found b-glucosidase, urease and phosphatase in vermicomposting of a lignocellulosic olive. In soil, e.g., Pascual et al. (2002) demonstrated the persistence of total and immobilized urease and phosphatase in soils amended with compost. Wittman et al. (2004) found high activity of b-glucosidase in the humus layer of a forest soil. 4.4. Community analysis with PCR-DGGE Cluster analysis of 16S rDNA community profiles based on a general bacterial primer pair revealed complex profiles reflecting the high diversity of the microbial community. The bands in the DGGE profiles represent the dominant microbial populations (Muyzer et al., 1993). The DGGE banding patterns suggest that there are several dominant groups, which are relatively stable, independent of treatments and depths. The observed differences of patterns are likely due to differences in fainter bands. The control soil showed a similarity of o20% to compost-treated soils and the effect of different compost were less marked than depth. These data support the findings of Fierer et al. (2003) as well as Bundt et al. (2001) for Swiss forest soils using PCR-RFLP. Similar results were found by Boehm et al. (1993) who reported that differences in organic matter levels among different potting mixes compost amended dark peat mix, slightly decomposed light peat mix and decomposed peat mix had little impact on the diversity of rhizosphere communities. Ammonia oxidizing bacteria (AOB) play a key role in soil N cycling and are responsible for converting ammonia/ ammonium to nitrate via nitrite. Urease catalyzes hydrolysis of urea to produce ammonia that can be used by AOB. The results of cluster analysis and diversity index suggest that the ammonia-oxidizer community at (0–10 cm and 10–20 cm) depths was different to that from the deeper layer (20–30 cm) for all treatments including the control soil. These results are in agreement with the urease data. Urease activity was lower at 20–30 cm depth compared with the others depths, producing less ammonium, the substrate for ammonia-oxidizers. The ammonia-oxidizers showed higher diversity for compost-treated soils compared to control soil and the type of compost did not seem to influence the composition of the ammonia oxidizer community, despite considerable differences in the number of AOBs that have been found in differently treated soils (Innerebner et al., 2006). The correlation of bacterial and ammonia diversity and Cmic confirms earlier findings that microbial diversity and biomass are likely to be related to each other (Lynch et al., 2004). This paper shows that the continued addition of composts to soils enhanced Corg, Cmic, basal respiration and enzyme activities compared to control soil and that these effects declined with depth. A higher diversity of bacteria and ammonia oxidizers in compost-treated soils compared to control soil was evident, but the type of compost did not seem to influence the composition of microbial community
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