Microbial community structure and function in a soil ...

Soil Biology & Biochemistry 38 (2006) 327–341 www.elsevier.com/locate/soilbio

Microbial community structure and function in a soil contaminated by heavy metals: effects of plant growth and different amendments Alfredo Pe´rez-de-Moraa,*, Pilar Burgosa, Engracia Madejońa, Francisco Cabreraa, Petra Jaeckelb, Michael Schloterb a

Sostenibility Soil–Plant–Atmosphere System, Instituto de Recursos Naturales y Agrobiologıá, Av. Reina Mercedes 10, P.O. Box 1052, 41080 Sevilla, Spain b Institute of Soil Ecology, GSF—National Research Center for Environment and Health, Ingolsta¨dter Landstr. 1, 85764 Neuherberg, Germany Received 6 August 2004; received in revised form 29 April 2005; accepted 13 May 2005

Abstract We studied the effects of in situ remediation of a heavy metal (HM) contaminated soil on some soil chemical properties, microbial function and microbial structural diversity after 18 months. The experiment was carried out at semifield scale in containers filled with HM contaminated soil from the Aznalco´llar mine accident (Southern Spain, 1998). The remediation measures consisted of the application of different amendments and/or establishment of a plant cover (Agrostis stolonifera L.). Seven treatments were established: four organic treatments (municipal waste compost (MWC), biosolid compost (BC), leonardite (LEO) and litter (LIT)), one inorganic treatment (sugar beet lime (SL)) and two controls (control with plant cover (CTRP) and control without plant cover (CTR)). Several soil chemical (pH, soluble HM, total organic C (TOC), water-soluble C (WSC) and available-P) and biochemical properties (microbial biomass C (MBC), MBC/TOC ratio and enzyme activities) were determined. Microbial community structure was studied by means of ARDRA (amplified ribosomal DNA restriction analysis). The SL, MWC and BC treatments were the most efficient to raise soil pH and decrease soluble HM concentrations. Total organic C was increased in the organic treatments by 2 to 4-fold, whereas water-soluble C was statistically similar in the CTRP, SL and the organic treatments, probably due to the presence of a root system in all these treatments. Available-P was also increased in the BC, SL and MWC treatments due to the higher P content of the amendments applied in these treatments. Soil microbial function was generally enhanced in the amended and CTRP treatments. The MWC, BC and SL treatments were particularly efficient to increase microbial biomass C, the MBC/TOC ratio and the dehydrogenase and aryl-sulphatase enzyme activities. These results could be attributed to the amelioration of some of the soil chemical properties: increase in soil pH and water-soluble C and decrease of HM soluble concentrations. ARDRA analyses showed changes in structural diversity in both the bacterial and fungal community under the different treatments. Fingerprinting patterns of the 16S rDNA obtained with Hinf-I and of the 18S rDNA with Hpa-II revealed higher similarity percentages among samples from the same treatment compared with samples from the other treatments. In addition, a higher similarity was found between samples from all treatments under the Agrostis influence. The use of certain amendments and/or a plant cover is important for in situ remediation of HM contaminated soils, since these practices can affect soil chemical properties, as well as the microbial community function and structure. q 2005 Elsevier Ltd. All rights reserved. Keywords: Amendments; Agrostis; ARDRA fingerprints; Enzyme activities; Heavy metal contamination; In situ remediation; Microbial community structure

1. Introduction Heavy metals (HM) constitute a potential hazard for waters, soils and sediments. It has been shown that HM at certain concentrations can have long-term toxic effects

* Corresponding author. Tel.: C34 954 624 711; fax: C34 954 624 002. E-mail address: [email protected] (A. Pe´rez-de-Mora).

0038-0717/$ - see front matter q 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.soilbio.2005.05.010

within ecosystems (Majer et al., 2002) and have a clear negative influence on biologically mediated soil processes (Lee et al., 2002). It is generally accepted that accumulated HM reduce the amount of soil microbial biomass (SMB) (Brookes and McGrath, 1984; Chander et al., 1995) and various enzyme activities, leading to a decrease in the functional diversity in the soil ecosystem (Kandeler et al., 1996) and changes in the microbial community structure (Frostega˚rd et al., 1993; Pennanen et al., 1998). However, metal exposure may also lead to the development of metal tolerant microbial populations (Ellis et al., 2003). Due to

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A. Pe´rez-de-Mora et al. / Soil Biology & Biochemistry 38 (2006) 327–341

their relation to soil functionality, the soil microbial population and activity have been proposed as useful indicators of soil improvement and soil degradation (Pankhurst et al., 1995; Dick et al., 1996). In addition, soil enzyme activities are considered as sensitive and early indicators of both natural and anthropogenic disturbances (Giller et al., 1998). Besides the soil microbial function, molecular fingerprinting methods may provide a qualitative and quantitative measure of microbial diversity and community composition in undisturbed and contaminated soils (White et al., 1998) as they reflect the status of the microbial gene pool in the investigated systems (Head et al., 1998; van Elsas et al., 1998). Therefore, the combination of more traditional soil biochemical methods with more recent molecular techniques can provide valuable information about the microbiological status of the soil. The main problem associated with HM contamination is that, in contrast to organic contaminants, they cannot be degraded. This fact increases their relevance as one of the most serious groups of environmental contaminants (Kabata-Pendias, 2001). Therefore, reclamation of soils contaminated with HM is only possible by using techniques that extract or stabilise the contaminants. Extraction techniques are generally carried out ex situ, and imply soil structure deterioration and high costs, which limit their use on vast contaminated areas. Stabilization techniques are carried out in situ and are less expensive. These techniques are based on the use of amendments and/or plants and their associated microorganisms to alter the physical form of HM, reducing their mobility and bioavailability (Vangronsveld and Cunnigham, 1998; Wenzel et al., 1999; USEPA, 2000). Moreover, vegetation cover can also prevent wind-blow of contaminated particles and reduce water pollution by interception of a substantial proportion of the incident precipitation (Tordoff et al., 2000). The most widely used amendments can be either inorganic (lime, phosphate minerals, Al and Fe oxides) or organic (sewage sludge or biosolids) (Knox et al., 2000; Basta et al., 2001). In general, periodic applications are recommended, since the effects of these amendments may be only effective in the short- or mid-term (Brown, 1997). In the case of organic amendments, some authors have suggested that organic matter decomposition may counteract the immobilising potential of organic amendments (Brown, 1997; Madrid, 1999), while other studies have shown a stabilization of HM availability with time after the addition of organic amendments (Chang et al., 1997; Canet et al., 1998). Therefore, further studies are needed to determine the potential of the application of these techniques in the restoration of the chemical and biological properties of HM contaminated soils. The aims of this study were to determine the effects of the application of different amendments and/or a plant cover on (i) some chemical properties, (ii) microbial function and (iii) microbial community structure of a soil contaminated by HM. We hypothesized that the remediation measures

(amendment application and plant cover development) would reduce HM solubility, increase soil fertility and enhance soil microbial functionality. We also hypothesized that the addition of different amendments and the development of a root system might induce shifts in the microbial community structure among the different treatments. To prove these hypotheses we (i) determined and compared the effects of the different treatments on several chemical variables (pH, total organic C (TOC), watersoluble C (WSC), available-P and soluble Cd, Cu and Zn concentrations); (ii) several biochemical properties (microbial biomass C (MBC), MBC/TOC ratio, arylsulphatase, dehydrogenase, b-glucosidase and acid-phosphatase enzyme activities); (iii) we also studied the soil bacterial and fungal community structure assessed by the ARDRA fingerprinting technique.

2. Materials and methods 2.1. Soil characteristics Soil was collected in an area affected by the Aznalco´llar mine accident named ‘El Vicario’ (N 37826 0 21 00 ; W 6812 0 59 00 ), where the only remediation activity carried out by the authorities was the removal of the sludge layer together with the first 15 cm of the top soil. The soil is a clay loam soil classified as Typic Xerofluvent (Soil Survey Staff, 1996). Its most relevant characteristics are presented in Table 1. 2.2. Experimental design The experiment was carried out in containers (70 cm long!60 cm wide!40 cm deep) that were placed outdoors and filled with the first 20 cm of the contaminated soil (1.32 g cmK3 bulk density). Containers were arranged according to a complete randomised block design with seven treatments (four organic treatments, one inorganic treatment and two control treatments) and four replicates Table 1 Characterization of the soil

pH TOC (g kgK1) N (g kgK1) P (g kgK1) K (g kgK1) Ca (g kgK1) As (mg kgK1) Cd (mg kgK1) Cu (mg kgK1) Mn (mg kgK1) Pb (mg kgK1) Zn (mg kgK1)

Average

SD

3.32 5.40 0.74 0.42 2.30 4.70 120 2.43 78.3 645 201 226

0.76 0.07 0.01 0.01 0.40 0.40 2.65 0.04 1.41 24.6 5.51 1.53

nZ3 (number of samples analysed); SDZstandard deviation; TOCZtotal organic C; total concentrations of HM and As are shown.

nZ3 (number of samples analysed for each amendment); standard deviations in parenthesis; ECZelectrical conductivity; TOCZtotal organic C; MWCZmunicipal waste compost; BCZbiosolid compost; LEOZleonardite; LITZlitter; SLZsugar beet lime; Total concentrations of HM and As are shown.

396(40.3) 138(31.0) 385(77.3) 39.2(6.67) 252(10.5) 297(10.3) 362(32.0) 51.0(8.20) 1.49(0.71) 0.43(0.14) 0.43(0.08) 0.53(0.05) 0.44(0.06) 0.51(0.06) 185(22.9) 67.0(15.4) 7.36(0.30) 9.04(0.08) MWC SL

6.16(1.01) ND

1.04(0.02) 0.98(0.04)

8.37(1.12) 1.63(0.34)

27.0(5.16) 64.5(1.06) 258(18.4) 9.36(0.31) 22.0(2.33) 137(26.2) 676(12.7) 66.2(1.41) 257(24.7) 6.45(0.33) 28.2(2.40) 121(5.60) nd(–) 0.83(0.11) 0.73(0.40) 1.90(0.38) 34.9(3.46) 5.63(1.47) 0.19(0.06) 3.97(0.08) 0.93(0.23) 0.04(0.001) 0.04(0.003) 1.24(0.18) 0.90(0.03) 1.17(0.02) 1.31(0.06) 544(6.84) 289(3.86) 195(12.2) 4.49(0.02) 6.08(0) 6.93(0.03) LIT LEO BC

0.92(0.03) 17.4(0.73) 2.91(0.18)

K (%) P (%) N (%) TOC (g kgK1) EC (dS mK1) pH

Table 2 Mean values of some characteristics of the amendments

As (mg kgK1)

Cd (mg kgK1)

Cu (mg kgK1)

Mn (mg kgK1)

Pb (mg kgK1)

Zn (mg kgK1)


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per treatment. The organic amendments were: a municipal waste compost (MWC) from a city refuse treatment plant; a biosolid compost (BC) made of wastewater sludge from a water treatment plant mixed with vegetative waste from parks and gardens; a litter (LIT) collected from a deciduous forest; and a leonardite (LEO), a low rank coal between peat and sub-bituminous rich in humic acids. Furthermore, an inorganic amendment, sugar beet lime (SL), a residual material from the sugar manufacturing process with 70– 80% of CaCO3 (dry basis) was also tested, because of its common use in regulating the pH in acid and contaminated soils (Chlopecka and Adriano, 1996). These amendments were chosen because they constitute low-cost, representative amendment materials for land treating extensive areas. The characteristics of the amendments are shown in Table 2. Trace element content of all amendments was below the limits established by the European Union (CEC, 1986) for sewage sludge application on agricultural soils. The amendments were applied on a fresh basis (20–25% moisture content) and mixed with the topsoil (10 cm) in the containers. Within the 18 months of the study two doses of each amendment were applied: the first one at the beginning of the experiment (100 Mg haK1) and the second one (50 Mg haK1) 12 months later. The containers were sown with Agrostis stolonifera L. (167 kg haK1) twice: the first 1 month after the initial amendment addition and the second 2 weeks after the second amendment application. Agrostis stolonifera L. was selected because of its tolerance to HM (Siedlecka et al., 2001). Two control treatments without amendments were also established: control with plant (CTRP) and control without plant (CTR). Containers were also watered regularly to ensure water supply to the plant. 2.3. Soil sampling Ten soil cores (2 cm diameter, 10 cm depth) regularly distributed along the surface were taken from each container to make a composite sample 18 months after the beginning of the experiment. Each composite sample was divided into three subsamples (for soil chemical, biological and molecular analysis). For chemical analysis soil samples were air-dried crushed, sieved (2 mm) and ground (! 60 mm). Soil samples for microbial biomass and enzyme activities were sieved (2 mm) and stored at 4 8C prior to analysis (within 2 weeks after the sampling); soil samples for microbial diversity analysis were directly frozen and stored at K20 8C until analysis. 2.4. Chemical analysis The pH of the soil and the amendments was measured in a 1/2.5 sample/1 M KCl extract after shaking for 1 h. Total HM and As concentrations in the soil (!60 mm) and in the amendments were determined by ICP-OES (IRIS ADVANTAGE, Thermo Jarrel Ash Corporation, MA, US) after aqua

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regia digestion in a microwave oven (Microwave Laboratory Station Milestone ETHOS 900, Milestone s.r.l., Sorisole, Italy) . Soil CaCl2 soluble trace elements concentrations were determined in 1/10 soil sample (!2 mm)/0.01 M CaCl2 extracts (Ure et al., 1993) using ICP-OES. Total organic C (TOC) was analysed by dichromate oxidation and titration with ferrous ammonium sulphate (Walkley and Black, 1934). Water-soluble carbon (WSC) was determined in an (1/10) aqueous extract by oxidation with dichromate and measurement of absorbance at 590 nm (Lambda EZ210 UV/ vis Spectrophotometer, Perkin–Elmer, CT, US) (Sims and Haby, 1971). Available-P was measured as described by Olsen et al. (1954). 2.5. Microbiological analysis Microbial biomass C (MBC) content was determined by the chloroform fumigation–extraction method modified by Gregorich et al. (1990). The concentration of C in the extract was measured as described by Jenkinson and Powlson (1976) using dichromate digestion. An extraction efficiency coefficient of 0.38 was used to convert the difference in soluble C between the fumigated and the unfumigated soil to MBC (Vance et al., 1987). Microbial biomass C was expressed in mg C kg dry soilK1. 2.6. Enzyme activities Dehydrogenase activity was determined in a 1 M TRIS– HCl buffer (pH 7.5) by the method of Trevors (1984), using INT (2(p-iodophenyl)-3-(p-nytrophenyl) 5-phenyl tetrazolium chloride) as the electron acceptor. The iodonitrotetrazolium formazan (INTF) produced was measured spectrophotometrically at 490 nm. Aryl-sulphatase activity was determined as proposed by Tabatabai and Bremmer (1970) after soil incubation with pnitrophenyl sulphate and measurement of p-nitrophenol (PNP) absorbance at 400 nm. b-glucosidase activity was measured as indicated by Tabatabai (1982) after soil incubation with p-nitrophenyl-bD-glucopyranoside and measurement of PNP absorbance at 400 nm. Acid phosphatase activity was measured after soil incubation with p-nitrophenyl phosphate disodium in a 0.5 M maleate buffer (pH 6.5) and measurement of PNP absorbance at 398 nm (Nannipieri et al., 1980). All enzyme activities are expressed in mg PNP kg dry soilK1 hK1, except dehydrogenase activity, which is expressed in mg INTF kg dry soilK1 hK1.

DNA extraction was done using the FastDNAwSPIN Kit for soil (QBIOgene) following the manufacturer’s instructions. The kit is designed to extract PCR-ready Genomic DNA from soil samples in less than 30 min and it consists of three general components: (i) a lysing matrix designed to lyse all microorganisms (ii) homogenization reagents which enable complete sample homogenization and protein solubilization and (iii) DNA purification and elution reagents which facilitate DNA purification with a proprietary silica matrix and eliminate contaminants that inhibit subsequent reactions. PCR amplification of the 16S rDNA was carried out with the universal bacterial primer system B27/L1401 (Nu¨bel et al., 1996; Orphan et al., 2001). The 16S rDNA PCR mixture consisted of 5 ml of 10! Buffer, 5 ml of 50 mM MgCl2, 5 ml of 3% bovine serum albumin (BSA), 5 ml of 2 mM nucleotide mix, 1 ml of 10 mM of each primer, 5 U Taq polymerase and 1 ml of template in a final volume of 50 ml. The following PCR program was used: initial denaturation for 10 min at 95 8C (hotstart), the addition of Taq polymerase at 80 8C, 27 cycles consisting of denaturation at 94 8C for 1 min, an annealing step at 54 8C for 1 min and an elongation step at 72 8C for 1 min. Cycling was followed by a final elongation step at 72 8C for 10 min. The universal fungal primer pair EF4/EF3 was used for PCR amplification of 18S rDNA (Smit et al., 1999; van Elsas et al., 2000). The 18S rDNA PCR mixture consisted of 5 ml 10! Buffer, 3.75 ml of MgCl2 50 mM, 5 ml of 3% BSA, 5 ml of 2 mM nucleotide mix, 1 ml of each primer, 5 U of Taq polymerase and 1 ml of template in a final volume of 50 ml. The cycling program included an initial denaturation for 10 min at 95 8C (hotstart), the addition of Taq polymerase at 80 8C, 30 cycles consisting of denaturation at 94 8C for 1 min, annealing at 48 8C for 1 min and elongation at 72 8C for 1 min. Cycling was followed by a final elongation step at 72 8C for 10 min. After PCR amplification, PCR products were purified using the QIAquick PCR Purification Kit (Qiagen) according to the instructions of the manufacturer. Restriction digestion was carried out on a total volume of 20 ml including 10 U of either Hpa-II or Hinf-I restriction enzymes and 9–10 ml of purified PCR product. Restriction digestion consisted of 3 h at 37 8C and 20 min at 65 8C. Digestion products were then purified with MinElute Reaction Cleanup Kit (Qiagen) before electrophoresis on a 10% polyacrylamide gel (CleanGel, Amersham Biosciences). Band patterns were visualized by silver staining (Heukeshoven and Dernick, 1988). 2.8. Statistical analysis

2.7. Microbial diversity analysis Soil microbial diversity was analyzed by amplified ribosomal DNA restriction analysis (ARDRA) fingerprinting of 16S and 18S rDNA fragments.

All statistical analyses were carried out with the program SPPS 11.0 for Windows. A normality test was carried out for all variables prior to analysis of the variance. The chemical and microbiological data was analysed by


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Table 3 Mean values of soil pH, soil soluble (0.01 M CaCl2) heavy metals, soil total organic C (TOC), soil water-soluble C (WSC) and soil available-P (Avail-P) in the different treatments (see Table 2 for treatment description) Treatment

pH

CaCl2–Cda (mg kgK1)

CaCl2–Cu (mg kgK1)

CaCl2–Zna (mg kgK1)

TOC (g kgK1)

WSC (mg kgK1)

Avail-Pa (mg kgK1)

CTR CTRP LEO LIT MWC BC SL

4.40a 4.63a 4.73a 5.58b 6.69c 6.73c 7.49d

0.22c 0.12c 0.08b 0.08b 0a 0a 0a

3.38c 2.56b 0.30a 0.56a 0.83a 0.75a 0.71a

94.9e 30.6d 25.1d 9.10c 2.10b 1.50ab 0.82a

5.00a 7.70a 30.9c 21.7b 16.8b 17.4b 9.70a

225a 356bc 315ab 507d 582d 462cd 455d

18.6a 18.6a 16.7a 18.7ab 30.8b 104c 58.1c

a

No homogeneity of the variance. Values followed by the same letter in the same column do not differ significantly (P!0.05).

ANOVA, considering the treatment as the independent variable. Significant statistical differences of all variables between the different treatments were established by Tukey’s test when there was homogeneity of the variance and by Games–Howell’s test in the opposite case. A correlation matrix between all chemical and biochemical parameters was calculated. The significance level reported (P!0.01 and P!0.05) is based on Pearson’s coefficients. ARDRA patterns were analysed with the Gel Compare II V.3.00 (Applied Math) software program. All gels were normalised prior to analysis. Genetic similarity between populations in each sample was determined by comparison of the presence and absence of bands. Dice’s coefficient was selected to calculate the resemblance matrix while the unweighted pair-group method using arithmetic means (UPGMA) was chosen as the fusion strategy for elaborating the dendrograms.

Water-soluble C mean concentrations varied between 225 and 582 mg kgK1 and were generally higher in the amended treatments compared with the two control treatments, although statistical differences were not always observed (Table 3). Available-P was highest in the BC treatment (104 mg kg K1) followed by the SL and the MWC treatments (Table 3). On the contrary, the LEO and the

3. Results 3.1. Chemical analyses Soil pH was significantly higher in the SL, BC, MWC and LIT treatments compared with the control treatments (Table 3). The highest pH value was observed in the SL treatment (7.70), whereas pH was lowest in the CTR treatment (4.40). In general, soluble HM concentrations were significantly lower in all the amended treatments (Table 3). The SL, BC and MWC treatments were the most effective to reduce HM soluble concentrations. Although As and Pb total concentrations of the soil were very high (Table 1), soluble As and Pb concentrations were below the detection limit of the method used (0.01 mg kgK1 for both elements). This can be related to the very low mobility of both elements even when present at high concentrations in the soil (Evans et al., 1995; Kabata Pendias and Pendias, 2001). The TOC content of the soil was significantly higher in all the organic treatments (Table 3). Mean values ranged between 5.00 and 30.9 g kgK1 and were highest in the LEO treatment.

Fig. 1. Mean values of (a) microbial biomass C (MBC) and (b) MBC/TOC ratio in the soil. Bars with the same letter do not differ significantly (P! 0.05).

332


LIT treatments showed similar values to those of the control treatments (18.6 mg kgK1). 3.2. Microbial and biochemical analyses As a rule, MBC mean values were significantly higher in the amended treatments (Fig. 1(a)). The lowest value was observed in the CTR treatment (19.2 mg kgK1), while MBC was highest in the MWC treatment (443.9 mg kgK1). The MBC/TOC ratio was also generally higher in the amended treatments, although statistical differences with the control treatments were only found for the SL treatment (Fig. 1(b)). Differences in enzyme activities among treatments varied depending on the activity studied. In the case of dehydrogenase and aryl-sulphatase activities, the amended treatments showed in most cases higher activity than the control treatments (Fig. 2(a) and (b)). Dehydrogenase activity mean values were particularly low in the CTR treatment (0.08 mg INTF kgK1 hK1) and were highest in the MWC treatment (10.9 mg INTF kgK 1 K1 h ). A similar trend was observed in aryl-sulphatase mean values, which were lowest in the CTR treatment

(117 mg PNP kgK1 hK1) and highest in the MWC treatment (1360 mg PNP kgK1 hK1). b-glucosidase activity mean values ranged between 85.4 and 1586 mg PNP kgK1 hK1. All treatments showed significantly higher activity mean values than the CTR treatment. Nevertheless, statistical differences between the amended treatments and the other control treatment (CTRP) were only found for the LIT treatment (Fig. 2(c)). Mean values of acid-phosphatase varied between 1610 and 7398 mg PNP kgK1 hK1 and were highest in the LIT treatment (Fig. 2(d)). In general, there were no significant differences between mean values of the amended and control treatments, except for the LIT treatment. 3.3. Pearson’s correlations Correlation coefficients between the different chemical and microbiological variables were calculated (Table 4). A negative correlation was observed between pH and Cd, Cu and Zn soluble concentrations, whereas positive correlations were found between pH and WSC, available-P, MBC, MBC/TOC and aryl-sulfatase and dehydrogenase activities. In general, biochemical properties were

Fig. 2. Mean values of enzyme activities: (a) dehydrogenase, (b) aryl-sulphatase, (c) b-glucosidase and (d) acid-phosphatase. Bars with the same letter do not differ significantly (P!0.05).

TOCZtotal organic C; WSCZwater-soluble C; Avail-PZavailable-P; MBCZmicrobial biomass C; ArylZarylsulphatase activity; b-gluZb-glucosidase activity; DHAZdehydrogenase activity; PhosphZ phosphatase activity; nZ28 (number of samples used to calculate correlation coefficients).

K0.292 0.434* 0.388* K0.400* 0.026 K0.215 K0.229 K0.139 K0.400* K0.191 0.864** K0.284 1 0.925** 0.008 0.663** 0.525** K0.821** K0.520** K0.684** 0.695** 0.835** 0.860** 0.049 1 K0.162 0.382* 0.624** K0.183 K0.177 K0.379* K0.390* 0.019 K0.180 0.091 1 0.722** 0.087 0.606** 0.397* K0.717** K0.416* K0.584** 0.680** 0.637** 1 0.813** K0.057 0.429* 0.593** K0.737** K0.474* K0.592** 0.781** 1 0.643** 0.485** 0.466* 0.494** K0.768** K0.718** K0.648** 1 K0.554** K0.740** K0.586** K0.313 0.792** 1 pH TOC WSC Avail-P Cd Cu Zn MBC MBC/TOC Aryl b-gluc DHA Phosph

1

0.003 1

0.621** 0.258 1

0.659** K0.610 0.218 1

K0.835** K0.353 K0.674** K0.581** 1

K0.709** K0.413* K0.735** K0.442* 0.941** 0.809** 1

MBC/TOC Cu Cd Avail-P WSC TOC pH

Table 4 Correlation coefficients between soil chemical and biochemical properties

Zn

MBC

Aryl

b-gluc

DHA

Phosph


333

negatively correlated with soluble HM and positively correlated with WSC. Acid-phosphatase was also negatively correlated with available-P. 3.4. Microbial community analysis 3.4.1. Bacterial community analysis ARDRA analyses of the 16S rDNA revealed shifts in the bacterial community structure between the different treatments for both the Hinf-I (Fig. 3) and Hpa-II (data not shown) fingerprints. The total length of the restriction bands obtained with Hinf-I ranged between 2000 and 100 bp, whereas it varied between 700 and 80 bp for Hpa-II. The CTR treatment showed the highest number of bands per sample (23–25) in the Hinf-I fingerprint, while the MWC, BC and SL treatments showed the highest number of bands per sample (22–25) in the Hpa-II fingerprint. In general, a high percentage of similarity (90–95%) was observed between banding profiles of replicates from the same container, as well as between banding patterns of samples from different containers but within the same treatment (80– 95%). The cluster analysis ordination of the 16S rDNA banding profiles generated by Hinf-I restriction showed a first division between samples from the CTR treatment and samples from the other treatments at 65% similarity level. A second division at 68% similarity level separated the BC and LIT treatments from the other treatments. Further divisions allowed the discrimination between samples from different treatments and the generation of individual clusters representative of each treatment. The cluster ordination of the 16S rDNA obtained by Hpa-II restriction also generated individual clusters of each particular treatment, although no initial discrimination between the CTR treatment and the other treatments was observed. 3.4.2. Fungal community analysis ARDRA analyses of the 18S rDNA also revealed shifts in the fungal community structure between the different treatments for both the Hpa-II (Fig. 4) and Hinf-I (data not shown) fingerprints. The number of bands per sample in the Hpa-II patterns was around 15, while it varied between 15 and 20 bands in Hinf-I. Most bands showed a total length between 2000 and 100 bp. The reproducibility of the fungal fingerprints was lower compared to the bacterial fingerprints between replicates from the same container (80–90%), as well as between samples from different containers but within the same treatment (75–80%). The cluster ordination of the Hpa-II patterns differed from that of Hinf-I. In the Hpa-II fingerprint, there was a first division at 50% similarity level, which isolated samples from the CTR treatment from samples of the other treatments. A second division at 54% similarity level separated samples from the LEO, BC and LIT treatments from samples from the CTRP, SL and MWC treatments.

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Fig. 3. Cluster analysis of 16S rDNA-ARDRA profiles of the Hinf-I fingerprint. Nomenclature used for the samples: first the treatment (MWC, BC, etc.), second the number of container, and third the replicate (a, b or c). Missing samples could not be properly amplified for restriction digestion, and therefore, do not appear on the dendrogram.

Further divisions revealed individual clusters characteristic of each particular treatment (Fig. 4). In contrast, in the HinfI fingerprint there was no initial separation between the CTR treatment and the other treatments, as well as no discrimination between samples from the CTRP and LIT treatments (data not shown).

4. Discussion 4.1. Soil chemical properties One of the main reasons for the application of the amendments was to increase soil pH and reduce HM


335

Fig. 4. Cluster analysis of 18S rDNA-ARDRA profiles of the Hpa-II fingerprint. Nomenclature used for the samples: first the treatment (MWC, BC, etc.), second the number of container, and third the replicate (a, b or c). Missing samples could not be properly amplified for restriction digestion, and therefore, do not appear on the dendrogram.

solubility. Increasing soil pH is a common practice in acid soils affected by trace element pollution (Adriano, 2001), since most of these elements are less soluble at high pH. In fact, one of the first remediation measures taken after the removal of the sludge cover in the

Guadiamar valley was the liming of the affected area (Aguilar et al., 2004). Reducing HM solubility may improve soil functional quality in contaminated soils, since soil quality related parameters such as enzyme activities or related processes

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are more dependant on bio-available HM concentrations rather than total concentrations (Speir et al., 1995). The determination of soluble HM concentrations has been used for ecological risk assessment in recent studies in the Guadiamar area (Clemente et al., 2003; Nagel et al., 2003). The utilisation of 0.01 M CaCl2 has been proposed as a suitable technique for the determination of the bio-available pool of HM (Houba et al., 1999). As a rule, higher pH and lower HM soluble concentrations were found in the amended treatments, especially in the SL, MWC and BC treatments (Table 3). This could be attributed to the high CaCO3 content of sugar beet lime and the base cations (Ca2C, Mg2C, NaC, KC) present in the organic amendments (Cavallaro et al., 1993). It has been proved that each unit of increase in pH results in approximately a 2-fold decrease in HM concentrations such as Zn, Ni and Cd in the soil solution (Christensen, 1984; Sanders et al., 1986). Therefore, the increase in soil pH seems to be the most important amendment effect in reducing HM solubility in our soil. The addition of organic amendments should also increase the organic matter content of this highly degraded soil. Soil organic matter has been recognised as being crucial to soil quality and to the regulation of many soil functions (Piccolo, 1996). Organic amendments have been used, for instance, in the restoration of a Zn mine site (Bergholm and Steen, 1989) and degraded soils in semiarid Mediterranean areas (Dıáz et al., 1994; Roldań et al., 1996). Organic treatments increased TOC mean values by 2 to 4-fold compared with the SL and the control treatments (Table 3). This was particularly important in this soil which was deprived of a superficial layer of approximately 15 cm during the cleanup operations. Conversely, the WSC content in the organic treatments did not always differ statistically from mean values in the inorganic (SL) and CTRP treatments (Table 3). The WSC has been used as an estimator of early changes in soil organic matter (Bolinder et al., 1999) and is considered as an indicator of soil potential microbial activity (Ceccanti and Garcıá, 1994). Our results suggest that the WSC input from the crop could be as much as that of the organic amendments and even more in some cases. Since root exudates contain between 10 and 40% of the total net C assimilated in the rhizosphere (Martin and Merckx, 1992), the presence of root system may contribute to increase WSC levels in the soil (Garcıá et al., 1997). Available-P was significantly increased in the BC, SL and MWC treatments (Table 3). This can be attributed to the P content of the amendments applied in these treatments (Table 2). The interest of determining available-P in this study was also related to its effect on acid-phosphatase activity, which is discussed in the following section. 4.2. Shifts in microbial biomass and enzyme activities Traditionally, remediation studies on HM contaminated soils have focused on the determination of changes in the

bio-available or total HM pool. However, the information about the effects of such remediation practices on the soil microbial community is very scarce. Due to the crucial role of soil microorganisms in nutrient cycling (Nannipieri et al., 2002), the study of soil microbial function can provide important information when evaluating soil remediation. Our results showed that the amelioration of some of the chemical properties analysed enhanced most of the biochemical parameters studied. This can be contrasted by looking at the lower values obtained for most biochemical parameters in the CTR treatment, where no remediation measures were carried out. However, different responses were also observed depending on the biochemical parameter and treatment considered. The MBC has been widely used as an approach to evaluate soil quality (Gil-Sotres et al., 2005). After 18 months there were clear differences in MBC content among the different treatments. The low values observed in the CTR and CTRP treatments display the poor microbiological status of the original soil. The growth of a plant cover helped to promote microbial growth, but this effect did not seem to be as influential as that of the amendments. Amendments increased generally TOC and WSC mean values and these two parameters were positively correlated with the MBC content (Table 4). The microbial biomass contained in the organic amendments and the addition of substrate-C could also account for these results (Garcıá-Gil et al., 2000). This dual effect of organic amendments has been also reported by other authors (Perucci, 1993; Garcıá et al., 1998). At the same time, higher soluble HM concentrations could have hindered microbial growth. MBC was negatively correlated with Cd, Cu and Zn soluble concentrations, which were in turn higher in the CTR and CTRP treatments. HM are known to be toxic to microorganisms (Kandeler et al., 1996) and can reduce SMB (Chander et al., 1995). In the case of the SL treatment, the low soluble HM concentrations and the relatively high WSC content could account for the high MBC values found in this treatment. The ratio of microbial biomass carbon/total organic carbon (MBC/TOC) showed a very similar pattern as the MBC. This ratio has been proposed as a useful index of soil pollution by HM (Brookes, 1995) and can be an indicative measure of the changes undergone by the organic matter of the soil (Insam and Merschack, 1997). A higher ratio indicates that more active organic matter is present and that soil organic matter is more susceptible to change (Spargling, 1992). The MBC/TOC ratio was higher in the SL, BC and MWC treatments, which had in turn lower soluble HM concentrations (Fig. 1(b)). Besides, negative correlations were found between this ratio and soluble HM concentrations (Table 4). Under normal conditions, the MBC/TOC ratio lies between 10 and 40 mg gK1 (Gigliotti and Farini, 2002). This was the case of the SL, MWC and BC treatments, while this ratio was less than 10 mg gK1 in the


other treatments. A similar effect was observed by Kunito et al. (2001) in a long-term sludge amended soil. Dehydrogenase and aryl-sulphatase activities have been proposed as sensitive indicators of HM toxicity (Dick et al., 1996; Rossel et al., 1997). Nevertheless, formazan colour development inhibition by Cu may bias the results for dehydrogenase activity measurements (Chander and Brookes, 1991; Brookes, 1995). However, soluble Cu concentrations in our experiment were as much as 0.34 mg Cu lK1. This value is below 1 mg Cu mlK1 which produces a 5% inhibition in the colour development of the formazan product (Obbard, 2001). Therefore, colour inhibition due to Cu did not appear to be the case in this study. Dehydrogenase and aryl-sulphatase enzyme activities showed a similar trend: they were generally higher in the amended treatments and significant differences were found between the MWC, BC and SL treatments and the control treatments (Fig. 2(a) and (b)). Both enzymes were positively correlated with each other and with soil pH and MBC, and negatively correlated with soluble HM concentrations (Table 4). Jiang et al. (2003) also found high correlations between these two enzyme activities and the MBC and the soil pH in a Zn contaminated soil. Whereas Kunito et al. (2001) attributed this positive correlation between enzyme activities and MBC to an indirect positive correlation between MBC and soil pH, Ellis et al. (2001) suggested a direct effect of the soil pH on dehydrogenase activity. The low dehydrogenase activity values measured in the LEO treatment (Fig. 2(a)), where MBC was not so low (Fig. 1(a)) could be attributed to the high content of humified organic matter, which is more resistant to microbial mineralization (Tate, 1987) as well as to the acid nature of the leonardite amendment. b-glucosidase activity showed a different response to the remediation practices compared with the other biochemical properties previously commented. This extracellular enzyme is involved in the hydrolysis of cellulose (Alef and Nannipieri, 1995). b-glucosidase mean values were significantly higher in all treatments compared to the CTR treatment (Fig. 2(c)), proving that the remediation measures improved this activity. However, significant differences with the other control treatment (CTRP) were only found in the case of the LIT treatment (Fig. 2(c)). Due to the composition of plant litter, it is comprehensible that b-glucosidase activity was highest in the LIT treatment. However, variations in mean values of b-glucosidase activity in the CTRP and the other amended treatments cannot only rely on differences on the TOC or WSC contents, even though these two parameters were positively correlated with this activity (Table 4). Contradictory reports have been given on the relation between b-glucosidase activity and organic C. While Eivazi and Tabatabai (1990) reported b-glucosidase activity to be positively correlated with TOC, Kunito et al. (2001) did not find such a correlation after sewage sludge addition. Garcıá-Gil et al. (2000) showed an increase in b-glucosidase activity in

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organically amended soils and higher in those treatments with more labile C in the organic matter. Since the LEO treatment, which had the highest TOC content, showed lower activity than most of the other treatments and since the CTRP treatment, which had a lower WSC content than the BC or SL treatments, showed similar activity values compared with these treatments it can be suggested that (i) the labile C was more important for b-glucosidase activity enhancement than the TOC content of the soil, and (ii) that the nature of this C input could induce differences in b-glucosidase activity. Apparently, b-glucosidase activity was not so affected by soluble HM concentrations as dehydrogenase or aryl-sulphatase activities, even though negative correlations (P!0.05) between this activity and soluble Cu and Zn concentrations were observed (Table 4). Although negative correlations between b-glucosidase and HM have been found by other authors (Lee et al., 2002), Tyler (1974) and Aoyama et al. (1993) reported that b-glucosidase activity was less sensitive to Cu and Zn concentrations than other enzymatic activities. This endurance to heavy metal toxicity could also account for the b-glucosidase activity values found in the CTRP treatment, which were similar to those found in the MWC and BC and higher than those in the SL and LEO treatments. Acid-phosphatase is one of the enzymes involved in the mineralization of organic phosphate esters in acid soils (Dick et al., 1983; Pant and Warman, 2000). This activity has been frequently used for estimating changes in soil quality due to either management or the presence of contaminants (Gil-Sotres et al., 2005). The utility of this enzyme as an indicator of remediation was somewhat masked in our study, since the BC, MWC and SL treatments showed mean values of acid-phosphatase activity similar to the CTR treatment (Fig. 2(d)). This can be attributed to feedback inhibition of the enzyme by available-P (Madejoń et al., 2003). In fact, a negative correlation between acidphosphatase and available-P was found (Table 4). On the contrary, in the CTRP, LEO and LIT treatments this activity was increased compared with the CTR treatment (Fig. 2(d)), proving that the remediation measures in these treatments enhanced this parameter. Thus the utilisation of acidphosphatase might not be worthy when monitoring remediation effects after application of amendments with a high P content. Although the remediation measures improved soil functionality in most cases, it is extremely hard to discern to what degree the amelioration of soil pH, the reduction of soluble HM or the increase in C availability influenced microbial function enhancement. It is likely that a combination of the changes induced in these chemical parameters accounted for the differences observed in the various treatments. Moreover, changes in the microbial community structure composition due to the remediation can also affect soil functionality and thus it should not be discarded.

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4.3. Microbial community analysis The SMB cannot differentiate the heterogeneity of the microbial community. The application of molecular genetic tools in microbial ecology can widen our comprehension about the changes undergone by microbial populations under different conditions. Molecular fingerprinting techniques such as ARDRA have been effectively used for instance in assessing the effects of HM and organic contaminants on the microbial community (Smit et al., 1997; Brim et al., 1999; Tiedje et al., 1999). In order to have a deeper look at the effects of the remediation practices on the soil microbial population, we used the ARDRA fingerprinting technique to assess possible shifts in the microbial community structure. Several samples both from the 16S rDNA and 18S rDNA could not be amplified properly and showed a very poor definition on the polyacrylamide gel. They were, therefore, not considered for the cluster analysis. This could be due to biases and limitations at different stages such as soil heterogeneity, with its temporal and spatial changing microhabitats (van Elsas and Smalla, 1997), differences in DNA extraction efficiency (Suzuki and Giovani, 1996) or differences in the PCR itself (Kozdro´j and van Elsas, 2001). ARDRA analysis of the 16S rDNA and the 18S rDNA revealed differences in both the bacterial and fungal community structures of the various treatments. However, different results were obtained with the two restriction enzymes employed (Hinf-I and Hpa-II) in the bacterial and fungal fingerprinting patterns. Wenderoth and Reber (1999) found different sample ordination after ARDRA analyses using Alu-I and Hae-III separately. Smit et al. (1997) suggested that a number of different enzymes should be tried to generate the best profiles. In this sense, the Hinf-I fingerprint of the bacterial community (Fig. 3) and the Hpa-II fingerprint of the fungal community (Fig. 4) showed a first separation between samples from the CTR treatment and samples from the other treatments. Moreover, these fingerprints allowed complete discrimination between samples from the different treatments generating the individual clusters characteristics of each treatment. The presence of plants could account for the first cluster division both in the bacterial and the fungal community. The rhizosphere is known to change physico-chemical conditions in the surrounding soil, dissolve nutrients and release significant quantities of organic compounds, which can be used by microorganisms as an energy source. Thus microbial biomass activity and community structure are highly influenced by specific physico-chemical and biological characteristics prevailing in this habitat (Pearce et al., 1995; So¨rensen, 1997). Griffiths et al. (1999), using community hybridisation, % GCC profiling and phospholipid fatty acid analysis (PLFA), showed significant changes in microbial community structure in response to synthetic

root exudates, which were applied continuously to a soil held at a constant water potential. Kozdro´j and van Elsas (2000) reported generations of different community patterns by denaturing gradient gel electrophoresis (DGGE) depending on the availability of root exudates and prevailing conditions in the habitat of soils contaminated with heavy metals. The generation of individual clusters representative of each treatment supports the theory of substrate input or the particular soil conditions induced by the remediation measures. This is in accordance with Tiedje et al. (1999), who suggested that the major factors that control community composition are the different types of carbon from litter, the rhizosphere and the different chemical reactions of the soil environment, especially soil pH and key nutrients. Therefore, the diversity and different complexity of the organic amendments could enhance specific groups of bacteria and fungi, which could best utilise the substrates added: for instance, litter is rich in lignin and cellulose, whereas leonardite is rich in humic acids. Different soil chemical conditions such as the pH in the case of the SL treatment could be also responsible for the establishment of different microorganisms. Meanwhile, higher HM soluble concentrations could favour more tolerant organisms in treatments such as CTR and CTRP, where soluble HM concentrations were higher. The presence of elevated metal concentrations can exert a selective pressure on the microbial community such that levels of metal-tolerant or resistant species are increased (Ba˚a˚th et al., 1998). In fact, a similar and even higher number of bands was found in the CTR and CTRP treatments (Figs. 3 and 4), which indicates no decrease in microbial diversity structure in contrast to the lower MBC concentrations measured in these treatments. Our results show that the distinct nature of the amendments employed and the development of a root system induced shifts in the microbial community structure. This is particularly interesting in soil remediation of contaminated soils, since changes in soil microbial populations can also affect soil functionality, thereby influencing nutrient turnover and the restoration process of the affected soil. However, an analysis of the original amendment material would be necessary to see how much influence was imparted by other variables such as the soil pH and HM soluble concentrations of the soil. Likewise, there was still a reasonable percentage of similarity between the CTR treatment individual cluster and the cluster comprising the rest of treatments (65% similarity for bacteria and 50% for fungi) (Figs. 3 and 4). This supports in part, that there is still a great number of microorganisms from the original soil present in the microbial community, even though the soil’s chemical and biological properties changed greatly due to the remediation measures.


5. Conclusions The use of amendments and/or a plant cover was a suitable technique to increase soil pH, decrease heavy metal solubility and improve the water-soluble C content of the soil at the end of the experimental period. The amelioration of these soil chemical properties generally enhanced soil microbial function. In fact, the CTR treatment, in which no remediation measures were carried out, showed the lowest values of all biochemical properties studied. The MWC, BC and SL treatments were the most efficient treatments to increase microbial biomass C, the MBC/TOC ratio and the enzyme activities dehydrogenase and aryl-sulphatase. Conversely, the b-glucosidase and acid-phosphatase activities were not so affected by changes in soil pH and soluble heavy metal concentrations. The two tested composts proved to be generally as good and even more efficient organic matter sources than the two natural amendments (litter and leonardite) in raising soil pH, diminishing soluble heavy metal concentrations and promoting microbial activity. Hence their application is in accordance with sustainable management, when applied at the right doses and monitored regularly. The combination of a fingerprinting technique with the other biochemical variables measured proved to be useful in determining differences in the soil microbiological status of the various treatments. The use of particular amendments and the presence of a root system may influence the structure of the microbial community present in the soil. This fact might be of great significance in soil remediation because of the role of microorganisms in nutrient turnover and plant development. As HM mobility may be reversed in soils where organic matter is applied, and re-acidification may also occurred if amendment applications are not repeated periodically, further monitoring at the molecular and biochemical level might be necessary to evaluate changes in the soil microbiological status with time. Acknowledgements This study was supported by the Spanish Ministry of Science and Technology. Mr Pe´rez-de-Mora thanks the Spanish MCDE the financial support by the fellowship. Dr Burgos thanks the European Social Fund. We also thank Benjamin James Wright for revising the language of the manuscript. References Adriano, D.C., 2001. Trace Elements in Terrestrial Environments: Biogeochemistry, Bioavailability and Risks of Metals, second ed. Springer, New York. 867pp.. Aguilar, J., Dorronsoro, C., Fernańdez, E., Fernańdez, J., Garcıá, I., Martıń, F., Simoń, M., 2004. Soil pollution by a pyrite mine spill in Spain: evolution in time. Environmental Pollution 132, 395–401.

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