Microbial performance in soils along a salinity gradient under acidic conditions

Microbial performance in soils along a salinity gradient under acidic conditions

Applied Soil Ecology 23 (2003) 237–244 Microbial performance in soils along a salinity gradient under acidic conditions Mafalda Sardinha a,1 , Torste...

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Applied Soil Ecology 23 (2003) 237–244

Microbial performance in soils along a salinity gradient under acidic conditions Mafalda Sardinha a,1 , Torsten Müller a , Helge Schmeisky b , Rainer Georg Joergensen a,∗ b

a Department of Soil Biology and Plant Nutrition, University of Kassel, Nordbahnhofstr. 1a, 37213 Witzenhausen, Germany Department of Landscape Ecology and Nature Conservation, University of Kassel, Nordbahnhofstr. 1a, 37213 Witzenhausen, Germany

Received 13 December 2002; received in revised form 24 February 2003; accepted 26 February 2003

Abstract The aim of our research was to study how a gradient in salinity under low pH conditions affected activity, community structure, and biomass of soil microorganisms. The study was conducted near Heringen, Germany, at five sites in the floodplain of the river Werra, which were affected by saline liquid residues from potassium mining injected into the underground geological formations. The content of soluble salts ranged from 2.1 at site 1 to 9.7 mg g−1 soil at site 5. Soil pH ranged from 3.85 to 4.55. Microbial biomass C, biomass N, fungal ergosterol and adenosine triphosphate (ATP) were highly significantly interrelated with correlation coefficients between r = 0.89 and 0.96 (P < 0.0001, n = 25). All soil biological properties except adenosine monophosphate had highest values at the low saline site 1 and lowest at the most acidic and most saline site 5. The strongest decrease with salinity was shown by ATP and ergosterol, achieving only 12 and 4% of the site 1 values, respectively. The ATP-to-microbial biomass C ratio declined to 46% of the maximum level at site 1, the microbial biomass C-to-soil organic C ratio to 38%, and the ergosterol-to-microbial biomass C ratio to 19%. All microbial indices, except basal respiration, exhibited strong salinity effects due to shifts in the microbial community structure towards prokaryotic microorganisms. Consequently, salinity is one of the most stressing environmental conditions for soil microorganisms. © 2003 Elsevier Science B.V. All rights reserved. Keywords: Microbial biomass C; Biomass N; Ergosterol; ATP; Adenylates; Acidification

1. Introduction Salinisation is a process of soil degradation with increasing importance throughout the world (Keren, 2000). Salinity is a severe problem in many soils es∗ Corresponding author. Tel.: +49-5542-98-1591; fax: +49-5542-98-1596. E-mail address: [email protected] (R.G. Joergensen). 1 Present address: Escola Superior Agraria de Coimbra Rua Ant´onio Lima Fragoso, Quinta do Cahlet—Pocarica, 3060 Cantahede, Portugal.

pecially of arid and semiarid regions under irrigated agriculture where salts accumulate at the soil surface (Keren, 2000; Rietz and Haynes, 2003). In arid or semiarid climates, salinity is usually combined with high soil pH, because of calcium carbonate enrichment in the uppermost soil layers (saline soils) or hydrolysis of sodium carbonate (sodic soils). To a lesser extent, saline soils exist also under humid and temperate climatic conditions, for example in the salt-marsh areas along the North Sea coast, along motorways to which salts are applied during the winter months (Blomqvist and Johansson, 1999; Bryson and

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Barker, 2002), and saline waste dumps and salt influenced locations caused by industrial potassium mining (Westhus et al., 1997; Schmeisky and Podlacha, 2000). Most studies of saline soils have been carried out on high pH soils from arid or semiarid areas. While the effects of salinity on soil chemical and physical properties and on plant growth are well documented (Keren, 2000), soil microbiological aspects of saline environments have been studied less intensively (Zahran, 1997; Rietz and Haynes, 2003). In grassland soils, organic matter input and consequently microbial biomass and activity are typically concentrated in the top few centimetres (Lavahun et al., 1996). Here, salinisation may greatly disturb a large variety of microbially mediated processes in soil. Contradictory results, i.e. both increases and decreases in C or N mineralisation have been reported with increasing salinity (Singh et al., 1969; Laura, 1974; McClung and Frankenberger, 1987; Nelson et al., 1996; Pathak and Rao, 1998). Depressive effects of salinity on microbial biomass C have been reported in most studies published to date (Sarig and Steinberger, 1994; Sarig et al., 1996; Batra and Manna, 1997; Rietz and Haynes, 2003). Among the soil microbial community, bacteria have received much attention while research concerning fungi in saline soils has been extremely rare (Zahran, 1997). Currently, bacteria are considered to play the dominant role in saline environments (Zahran, 1997), although fungi have been found to be the principal microbial decomposers in standing decaying salt-marsh grasses (Newell and Porter, 2000). Our central aim was to study how a gradient in salinity under low pH conditions affects activity, community structure, and biomass of soil microorganisms in floodplain soils of the river Werra, in the centre of humid temperate Germany. Here, saline liquid residues from potassium mining were injected into the underground geological formations. As a result, salt reached the surface of soils characterised by low pH values (Schmeisky and Podlacha, 2000). Basal respiration, ergosterol, microbial biomass C and biomass N, as well as the adenine nucleotides adenosine triphosphate (ATP), ADP and AMP are useful indicators of microbial performance in soil. Adenylates, especially ATP are not only indices for microbial biomass (Contin et al., 2001; Dyckmans et al., 2003), but also for the physiological status of the soil microbial

community. There are several indications that both the ATP-to-microbial biomass ratio and the adenylate energy charge (AEC) decline under extreme soil conditions (Chander et al., 2001; Salamanca et al., 2002). The fungi-specific membrane component ergosterol has been successfully used as a biomarker solely for fungal biomass in a large variety of soils (West et al., 1987; Eash et al., 1994; Zeller et al., 2000), but not in saline environments such as our floodplain soils.

2. Materials and methods 2.1. Soil sampling and analysis Five core samples (250 cm−3 ) were taken at 0–5 cm depth on 24 May 2002 from five sites used as meadow in the floodplain of the river Werra close to Heringen in North Hessia, Germany (Schmeisky and Podlacha, 2000). At these sites, saline liquid residues originally injected into the geological underground from a potassium plant nearby have been coming to the surface for over 50 years. The fives sites were classified according to their vegetation: (1) Alopecurus pratensis, Poa pratensis, Arrhenatherum elatius, and Festuca rubra (45 m distance to site 2), (2) Agropyron repens (7.5 m distance to site 3), (3) Puccinellia distans (5.5 m distance to site 4), (4) Spegularia salina (2.5 m distance to site 5), and (5) no vegetation. The soil at site 1 can be classified as a Dystric Fluvisol and the soils at the other four sites as Salic Fluvisols according to the WRB classification system (Bailly et al., 1998). All field-moist soil samples were sieved (<2 mm), adjusted to 50% of their water holding capacity, homogenised, pre-incubated at room temperature for 2 weeks, and stored in polyethylene bags at 4 ◦ C prior to carrying out the biological analyses. Soil pH was measured in 0.01 M CaCl2 using a soil-to-solution ratio of 1:2.5. Cation exchange capacity was measured according to Mehlich after elution with an unbuffered 0.1 M BaCl2 solution (Schlichting et al., 1995). Subsamples of dried soil were finely ground in a ball mill. Total C and total N were determined using gas chromatography after combustion at 1200 ◦ C to CO2 and N2 using a Carlo Erba ANA 1400 Analyser.

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2.2. Soil microbial properties For the measurement of basal respiration, 100 g (oven-dry basis) of a moist soil sample was weighed into a 1 l stoppered Pyrex jar, adjusted to 50% of its maximum water-holding capacity and pre-incubated for 1 day at 20 ◦ C in the dark. Then, CO2 production was measured for another 4 days. The CO2 evolved was absorbed in 20 ml 0.5 M NaOH solution and determined by titration of the excess NaOH with 0.1 M HCl. The metabolic quotient qCO2 was calculated as follows: (␮g CO2 –C evolved in 4 days g−1 soil)/(␮g biomass C g−1 soil at the end of the 4-day incubation period)/4 days × 1000 = mg CO2 -C per day g−1 biomass C. Microbial biomass C and biomass N were estimated by fumigation-extraction (Brookes et al., 1985; Vance et al., 1987). Two portions equivalent to 25 g oven-dry soil were taken from the 100 g soil sample used for measuring basal respiration. One portion was fumigated for 24 h at 25 ◦ C with ethanol-free CHCl3 . Following fumigant removal, the soil was extracted with 100 ml 0.5 M K2 SO4 by 30 min horizontal shaking at 200 rev min−1 and filtered (Schleicher and Schuell 595 1/2). The non-fumigated portion was extracted similarly at the time fumigation commenced. Organic C in the extracts was measured as CO2 by infrared absorption after combustion at 850 ◦ C using a Dimatoc 100 automatic analyser (Dimatec, Essen). Microbial biomass C was calculated as follows: Microbial biomass C = EC /kEC , where EC = (organic C extracted from fumigated soils) − (organic C extracted from non-fumigated soils) and kEC = 0.45 (Wu et al., 1990; Joergensen, 1996). Total N bound in the extracts was measured as NO• 2 by chemoluminescence detection after combustion at 850 ◦ C using a Dimatoc 100/Dima-N automatic analyser. Microbial biomass N was calculated as follows: Microbial biomass N = EN /kEC , where EN = (total N extracted from fumigated soils) − (total N extracted from non-fumigated soils) and kEN = 0.54 (Brookes et al., 1985; Joergensen and Mueller, 1996). Ergosterol was measured in 5 g moist soil taken from the 100 g soil sample used for measuring basal respiration. Ergosterol was extracted with 100 ml ethanol for 30 min by oscillating shaking at 250 rev min−1 and filtered (Whatman GF/A) (Djajakirana et al., 1996). Quantitative determination

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was performed by reversed-phase HPLC analysis at 26 ◦ C using a column of 125 mm × 4 mm Sphereclone 5 ␮m ODS II with a Phenomenex guard column (4 mm × 3 mm). The chromatography was performed isocratically with methanol (100%) and a resolution of detection of 282 nm (Dionex UVD 170 S). Measurements of adenine nucleotides and calculations of the adenylate energy charge (AEC = (ATP+0.5×ADP)/(AMP+ADP+ATP)) were made according to the procedure of Bai et al. (1988) as described by Dyckmans and Raubuch (1997) on a molar basis. A moist sample of 4 g was extracted with a mixture of 4 ml dimethylsulphoxide (DMSO), 16 ml buffer (10 mM Na3 PO4 -buffer + 20 mM EDTA adjusted to pH 12 with KOH). Then, 500 ␮l of this suspension was mixed with 500 ␮l benzalkonium chloride solution in a centrifuge tube and mixed for 5 s in an ultrasonic bath. The benzalkonium chloride solution contained 2 mM Mg–EDTA, 10 mM ammonium acetate and 20 mM Tris(hydroxymethyl)-aminomethane, pH 7.75 with acetate (Martens, 2001). After derivatisation with chloracetaldehyde, the adenine nucleotides were determined by HPLC, consisting of a Dionex P 580 pump, a Dionex ASI 100 automatic sample injector, and a Dionex RF 2000 fluorescence detector. The chromatography was performed isocratically with 50 mm ammonium acetate buffer containing 1 mM EDTA and 0.4 mM TBAHS mixed with methanol (89.5/10.5 (v/v)) as a mobile phase. Column temperature was set to 26 ◦ C using a Dionex STH 585 column oven. Fluorometric emission was measured at a wavelength of 410 nm with 280 nm as the excitation wavelength. 2.3. Statistical analysis The results presented in Tables 1, 2 and 4 are arithmetic means of five core samples and are expressed on an oven-dry basis (about 24 h at 105 ◦ C). The significance of treatment effects was tested by one-way analysis of variance using the Tukey/Kramer HSD-test (honestly significant difference). The combined effects of soil pH and soil organic C content on cation exchange capacity were compared by multiple linear regression analysis. The relationships between the different soil properties were analysed by principal component analysis (PCA) using the orthotran/varimax rotation to achieve either small or large component loading and an Eigenvalue of 0.1 as the

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Table 1 Chemical and physical properties of soil samples Site (cm)

pH (CaCl2 )

Sand

Silt (%)

Clay

CEC (␮molC g−1 )

Salt (mg g−1 soil)

Electrical conductivity (␮S cm−1 )

Soil organic C (%)

Soil C/N

1 2 3 4 5 HSD

4.32 4.55 4.54 4.55 3.85 0.54

74 50 52 51 51 11

16 26 23 28 25 8

10 24 25 21 24 7

103 146 134 129 102 26

2.2 3.0 4.6 5.5 13.2 2.9

0.06 0.46 0.75 0.96 2.66 0.49

4.6 5.6 4.6 4.9 3.6 2.1

13.1 12.7 11.9 12.3 11.5 0.8

HSD: honestly significant difference (P < 0.05, n = 5). Table 2 Microbial properties of the soil samples Site (cm)

Microbial biomass C (␮g g−1 soil)

Microbial biomass N (␮g g−1 soil)

Ergosterol (␮g g−1 soil)

ATP ADP AMP Basal respiration (nmol g−1 soil) (nmol g−1 soil) (nmol g−1 soil) (␮g CO2 -C per day g−1 soil)

1 2 3 4 5 HSD

572 411 219 251 158 257

96 51 35 34 20 46

5.87 2.23 1.37 1.09 0.26 2.55

5.32 2.33 1.72 1.50 0.65 1.89

1.19 0.99 0.83 0.81 0.40 0.56

0.69 0.73 0.69 0.74 0.23 0.43

41.7 36.2 30.4 26.1 16.3 32.3

HSD: honestly significant difference (P < 0.05, n = 5).

lower limit. For the calculation of Pearson correlation coefficients, data of electric conductivity (EC) and microbial ratios were log-transformed to improve the significance. All statistical analyses were performed using StatView 5.0 (SAS Inst. Inc.). 3. Results Sites 2–5 did not differ in their particle size distribution, the average contents of sand, silt and clay at these four sites being 51, 26 and 23%, respectively. The sand content of site 1 was significantly higher, while the silt and clay contents were significantly lower (Table 1). The soils at all five sites contained soluble salts, but the species composition of the vegetation at site 1 did not exhibit any influence of salinity. The content of soluble salts increased from 2.1 at site 1 to 9.7 mg g−1 soil at site 5. The salt consisted on average of 63% NaCl, 11% MgCl2 , and 26% CaCl2 at sites 2–5. The electric conductivity paralleled this increase in salt content linearly according to the following relationship: EC = −0.28 + 0.22 salt, r = 0.99 (P < 0.0001, n = 25).

Soil pH varied between 3.85 and 4.55 and was lowest at site 5 in combination with highest electric conductivity (Table 1). The cation exchange capacity averaged about 120 and was significantly affected by soil pH (77%) and soil organic C (23%) content according to multiple linear regression analysis. The soil organic C content averaged about 4.9% at sites 1–4 and was Table 3 Correlation coefficients between different microbial indices and soil pH or electrical conductivity (n = 25) Variable

Electrical conductivitya

pH-CaCl2

Microbial biomass C Microbial biomass N Ergosterol ATP Basal respiration Ergosterol/microbial biomass Ca ATP/microbial biomass Ca Microbial biomass C/soil organic Ca

−0.70∗∗∗ −0.72∗∗∗∗ −0.81∗∗∗∗ −0.84∗∗∗∗ −0.48∗ −0.72∗∗∗∗ −0.73∗∗∗∗ −0.71∗∗∗∗

0.42∗ 0.37 0.27 0.27 0.58∗∗ 0.32 0.15 0.30

a

Log-transformed data. P < 0.05. ∗∗ P < 0.01. ∗∗∗ P < 0.001. ∗∗∗∗ P < 0.0001. ∗

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Table 4 Ratios of soil microbial properties Site (cm)

Microbial biomass C/N

Microbial biomass C/soil organic C (%)

Ergosterol/microbial biomass C (%)

ATP/microbial biomass C (␮mol g−1 )

Adenylate energy charge (AEC)

qCO2 (mg CO2 -C per day g−1 microbial biomass C)

1 2 3 4 5 HSD

6.0 9.4 7.1 7.9 8.5 4.3

1.24 0.71 0.46 0.51 0.47 0.42

1.01 0.58 0.47 0.42 0.19 0.46

9.3 6.2 7.7 5.8 4.3 2.6

0.82 0.69 0.64 0.62 0.66 0.11

74 90 103 105 118 88

HSD: honestly significant difference (P < 0.05, n = 5).

significantly lower at the vegetation-free site 5. The soil C-to-N ratio ranged from 11.5 at site 5 to 13.5 at site 1. Microbial biomass C, biomass N, ergosterol and ATP were significantly interrelated, with correlation coefficients between r = 0.89 and 0.96 (P < 0.0001, n = 25). The relationships of these biomass indices to basal respiration were not as close, with correlation coefficients between r = 0.60 and 0.74 (P < 0.0001, n = 25). All soil biological properties except AMP were highest at site 1 and lowest at site 5 (Table 2). At this most acidic and most saline site, the basal respiration rate declined to 39% of the site 1 value, ADP and AMP to roughly 33%, microbial biomass C to 28% and biomass N to 21%. The strongest decrease was shown by ATP and ergosterol, achieving only 12 and 4% of the values at site 1, respectively. Correlation analysis revealed strong significant depressive (non-linear) effects of increasing electric conductivity on all microbial indices analysed, especially on ATP and ergosterol (Table 3). Soil pH was positively correlated with microbial biomass C and basal respiration. However, only the pH effects on basal respiration exceeded those of electric conductivity. Most of soil biological ratios were also highest at site 1 and lowest at site 5 (Table 4). The ATP-tomicrobial biomass C ratio declined to 46% of the site 1 level, the microbial biomass C-to-soil organic C ratio to 38%, and the ergosterol-to-microbial biomass C ratio to 19%. The metabolic quotient was the only ratio that tended to increase from sites 1 to 5. The AEC was 0.82 at the sandier site 1, and averaged about 0.65 at the saline but also more clayey sites. The biomass C-to-N ratio averaged about 7.8 with relatively wide range, but without obvious relation to any of the other

Table 5 Oblique solution primary pattern matrix of the principal component analysis for the ratios of the different microbial properties (orthotran/varimax transformation; n = 25); AEC = adenylate energy charge; bold: definite assignation to a certain factor Factors

Ergosterol/microbial biomass C ATP/microbial biomass C qCO2 AEC Microbial biomass C/soil organic C Microbial biomass C/N Eigenvalue

I

II

III

0.95 0.84 0.12 0.38 0.11 0.00 3.04

−0.09 0.18 −0.90 0.73 0.72 0.00 1.24

0.01 −0.02 −0.19 −0.09 −0.36 0.97 0.77

soil properties. This view was supported by the principal component analysis separating the microbial biomass C-to-N ratio from the other ratios as factor III (Table 5). The metabolic quotient qCO2 , AEC, and the microbial biomass C-to-soil organic C ratio were combined as factor II, indicating substrate availability to soil microorganisms integrating the effects of clay content, soil pH and soil organic matter quality. Factor I was formed by the ergosterol-to-microbial biomass C ratio and the ATP-to-microbial biomass C ratio, indicating salinity-induced shifts in the microbial community structure.

4. Discussion Salinisation under low pH conditions has not been described in the literature and is probably a rare and interesting situation. The floodplain soils of the river Werra at Heringen are dominated by carbonate-free sediments mainly derived from New Red Sandstone

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so that acidification probably occurred during the early stages of soil development. Lime was never applied to the present floodplain soils mainly used as meadow. Salinisation of the soils started much later as a result of potassium mining at the end of the 19th century (Bönsel, 1989). The salinity of the soils is characterized by distinct small scale variability and strong fluctuations throughout the year caused by differences in transpiration, but especially in evaporation caused by rainfall events, wind and solar radiation (Westhus et al., 1997). Our samples were taken during a relatively wet period in spring so that the electrical conductivities presented here do not reflect the site-specific maximum salt concentrations. However, the site-specific environmental conditions over a longer period are integrated by the formation of vegetation (Westhus et al., 1997) and the soil microbial community (Smith and Paul, 1990; Höper and Kleefisch, 2001). The significantly lower soil pH at the most saline site 5 indicates that a markedly lower portion of protons was buffered by the cation exchange capacity of the soil. The salt solution at this site probably has a much stronger effect on the proton exchange than the 0.01 m CaCl2 solution. Although salinity obstructed plant growth, the most saline and acidic site 5 contained a significant microbial community with considerable activity. However, the microbial biomass content at site 1 with lowest salt concentration was markedly below other grassland soils (Höper and Kleefisch, 2001), leading to a maximum microbial biomass C-to-soil organic C ratio of 1.2%, only. In grassland soils, microbial biomass C-to-soil organic C ratios above 2% are common and even 3% and more have been regularly observed (Höper and Kleefisch, 2001). The generally low level of the microbial biomass C-to-soil organic C ratio in the present soils is probably due to the acidic pH of the present sites causing both (1) a reduced substrate-utilisation efficiency and (2) an increased recalcitrance of the C input by the acid-tolerant plants (Anderson and Domsch, 1993; Anderson and Joergensen, 1997). Ratios around 0.5% as observed at our strongly saline sites 1–3 have been described until now solely in the subsoil under temperate humid climate (Kaiser and Heinemeyer, 1993; Lavahun et al., 1996; Joergensen et al., 2002). The combined effects of salinity and acidity in our set of soils were stronger than those of a strong heavy-metal pollution

under acidic conditions (Chander et al., 2001), probably due to an even more drastic shift in the microbial community structure. A shift in the microbial community structure towards prokaryotic microorganisms, i.e. mainly bacteria, is indicated by the strong decrease in the ergosterol-to-microbial biomass C ratio with increasing salinity. The apparent sensitivity of fungi to salinisation is in accordance with the results of Badran (1994) and Pankhurst et al. (2001), both obtained by PLFA analysis. At site 1 with lowest salt content, fungi represent 90% of the microbial biomass if ergosterol is recalculated into fungal biomass C by multiplication by 90 (Djajakirana et al., 1996). At site 5 with lowest pH and highest salt content, fungi represent only 17% of the microbial biomass. A prokaryotic biomass of 10% at site 1 and 83% at site 5 means that the content of this microbial fraction would increase from 60 to 130 ␮g g−1 soil. However, we do not have any direct evidence of this increase. A salinisation-induced net increase in bacterial ester-linked fatty acids of 30% was observed by Pankhurst et al. (2001). Salinisation might affect not only the composition of the bacterial (Thieman and Imhoff, 1991), but also that of the fungal cell membranes (Newell et al., 1987). Therefore, our data need to be interpreted with some care because the possibility cannot be completely excluded that the fungi of our soils generally have low ergosterol contents. Another possibility is that salinisation might lower fungal biomass indirectly by reducing vegetation and thus the input of root and litter debris as the most important energy source for saprotrophic microfungi. Low percentages of fungi may lead to underestimation of biomass C and biomass N by using constant kEC and kEN values, mainly calibrated in European silt loams dominated by fungal biomass (Anderson and Domsch, 1973). In comparison to fungi, a smaller part of the bacterial biomass is rendered extractable by fumigation (Greenfield, 1995; Eberhardt et al., 1996). However, increasing salinity may lead to changes in the morphology of bacterial cells, probably affecting the extractability to an unknown extent (Zahran, 1997). The cells are often elongated and larger (Zahran et al., 1992; Zahran, 1997), the ratio of cell wall C-to-cytoplasmic C decreases (Schimel et al., 1989) and the chemical structure of membranes changes (Thieman and Imhoff, 1991). The complex

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interaction between changes in microbial community structure and changes in cell morphology may be an important reason for the large variability of the microbial biomass C-to-N ratio. A salinity-induced decrease in this ratio has not been observed along the present salinity gradient, although this could be expected from studies with laboratory cultures observing the storage of glycine betaine or amino acids in the cytoplasm as an osmoregulant (Schimel et al., 1989; Csonka and Hanson, 1991; Zahran, 1997). An ATP-to-microbial biomass C ratio of 9.3 at site 1 with lowest salt content is in the upper part of the range given by Dyckmans et al., 2003, which varied around 7.3 in a range of soils differing widely in amount and quality of the C input by the vegetation. An ATP-to-microbial biomass C ratio of 4.3 at the most saline and acidic site 5 is in the lower range. One explanation may be that the microbial community is less competitive in saline soils, because only specialised and adapted species survive. They do not have to maintain a high ATP-to-microbial biomass C ratio as a survival strategy, in contrast to the microbial community in normal non-saline and non-acidic agricultural soils (De Nobili et al., 2001). This hypothesis would be in line with the relatively low AEC values at the more saline sites, which are at the lower end of the range given by Dyckmans et al., 2003.

5. Conclusion Salinisation has a strong depressive effect on the microbial biomass and caused a pronounced shift of the microbial community structure towards prokaryotic microorganisms even at low pH, where the microbial biomass is usually dominated by fungi. Salinisation apparently has stronger effects than heavy-metal pollution observed at other sites and is probably one of the most stressing environmental conditions for soil microorganisms.

Acknowledgements We thank Gabriele Dorman, Anett Grosskurth, Ingrid Ostermeyer, Christian Ropte and Karin Schmidt for their skilled technical assistance and Professor Bernard Ludwig for useful discussion.

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