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Salinity-induced differences in soil microbial communities around the hypersaline Lake Urmia.

Introduction

Soil salinisation is a serious and increasing problem in many parts of the world, particularly in arid and semi-arid areas (Giri et al. 2003; Al-Karaki 2006), where evaporation leads to the accumulation of salt in the topsoil. More than 20% of the world's irrigated land is affected by an excess of salt (FAO 2005). The negative effects of soil salinity on agricultural production are huge (Tester and Davenport 2003) because they reduce the growth and productivity of land vegetation (Giri et al. 2007; Mathur et al. 2007).

The soil microbial community plays a key role in biogeochemical cycles (Wall and Virginia 1999) and soil organic matter turnover (Srivastava et al. 1996; Batra and Manna 1997), as well as in the formation of soil structure (Dodd et al. 2000). Hence, it is important to understand microbial reactions to environmental stressors such as high salt concentration. The morphology of microorganisms that usually grow in non-saline environments may change under salt stress because of swelling, elongation or shrinkage (Zahran 1997), whereas salt-tolerant microorganisms may exhibit structural modifications. A change in the composition of the cell envelope and membranes is perhaps the most important structural adaptation to salt stress (Russell 1989). The structural adaptation of membranes primarily involves changes in the composition and synthesis of lipids (including fatty acids) and proteins (Kates 1986; Russell 1989; Thiemann and Irnhoff 1991). Some microorganisms may show limited cell modifications; however, more profound changes in the cellular properties of microorganisms in response to salt stress occur at concentrations of NaCl >2m (Kogut 1991). Salinity leads to a reduction in the osmotic potential of the soil water and may cause ion imbalance in cells and thus direct cell toxicity (Evelin et al. 2009; Hammer et al. 2011a). Soil microorganisms have two strategies for coping with high salinity (Galinski and Triiper 1994; Zahran 1997): one is to maintain a cytoplasmic KCl concentration similar to the surrounding environment, and the other is to accumulate organic osmolytes in the cell cytoplasm (Galinski and Truper 1994).

Analysis of phospholipid fatty acid (PLFA) patterns is a method that can be used for the assessment of microbial community structure that does not rely on the culturing of microorganisms (Frostegard et al. 1991). This technique allows the estimation of microbial biomass and community structure and its physiological adaptations, and thus has the potential to illustrate the effects of different environmental stressors in soil (Kaur et al. 2005). PLFAs can be divided into general bioindicators, which provide a measure of the total soil microbial biomass, and specific bioindicators, which can be used to estimate the biomass of certain groups of microorganisms. A change in the PLFA pattern thus reflects changes in the microbial community and microbial groups (Tunlid and White 1992).

In Iran, slightly and moderately salt-affected soils cover ~25.5 Mha, and severe salinity affects another 8.5 Mha (FAO 2000). Lake Urmia, in north-western Iran, is one of the largest hypersaline lakes in the world (Zarghami 2011). The surrounding area is important for agriculture as well as for biodiversity. The lake has been designated by UNESCO as a Biosphere Reserve. The surface area of the lake has declined dramatically in recent decades because of drought and irrigation (UNEP/GEAS 2012). Several studies have been carried out on the effects of increased salinity in the aboveground ecosystem around Lake Urmia (Karbassi et al. 2010; Flassanzadeh et al. 2012; UNEP/GEAS 2012). However, the effect of salinity on the belowground ecosystem has rarely been investigated (Barin et al. 2013). Studies on the effects on the microbial community are necessary to understand the long-term effects of salinity on ecosystem processes.

The main objective of this study was to assess soil microbial biomass and the structure of the microbial community in the soil around the roots of two glycophytes, Medicago sativa L. (lucerne or alfalfa) and Allium cepa L. (onions), and the native halophyte Salicornia europaea L. (Chcnopodiaceae) (samphire) in areas with varying salinity around Lake Urmia. We previously studied the effects of salinity on arbuscular mycorrhizal fungi (Barin et al. 2013) in the same soil samples (and the corresponding root samples) used in this study. Here, we use signature PLFAs to investigate the overall saprotrophic microbial community in the soils and its relationships to salinity as well as other physical and chemical soil properties. We tested three hypotheses: (i) increasing salinity decreases soil microbial biomass; (ii) microbial community structure is changed by increased salinity; and (iii) any changes in the community that are brought about by increasing salinity will reflect adaptations in the PLFA composition resulting from microbial cell stress.

Materials and methods

Site description and sampling

The study was carried out on the eastern coastal plain of Lake Urmia, between the city of Azarshahr and Lake Urmia, in the northernmost part of Iran (Fig. 1). The area is almost 444 [km.sup.2], situated between 37[degrees]49' and 37[degrees]59'N, and 45[degrees]30' and 46[degrees]0'E. The altitude is 1350 m above sea level, mean annual precipitation is 328 mm, and the annual mean air temperature is 12.4[degrees]C. The soil has low salinity near Azarshahr and salinity increases towards Lake Urmia. Cultivated crops in the area include onions, lucerne and barley (Hordeum vulgare L.). The natural vegetation along the shore of Lake Urmia is dominated by halophytes such as Salsola spp., Salicornia spp. and Atriplex spp. (Aliasgharzadeh et al. 2001).

During the last week of August 2011, soil samples were collected from sites where onions (cv. Azarshahr; n = 39) and lucerne (cv. Hamedani; n = 29) were cultivated, and where the native herb samphire (n = 27) was growing (see Barin et al. 2013). Electrical conductivity (EC) had been determined previously with a portable EC meter (measurements in 1 :5 soil: water mixture) at a large number of locations, determined using GPS (Barin et al. 2013). The locations were chosen to cover the largest possible range in EC for soil sampling. Five samples from the upper 30 cm at each location were pooled to provide one composite sample. In the laboratory, all visible roots were removed and the soil samples were divided into two. One half was frozen (-20[degrees]C) for PLFA analysis, and the other was air-dried in the shade at ambient laboratory temperature and then sieved (2-mm mesh size) before chemical and physical analysis.

Laboratory analyses

The soil pH and EC of the soil saturated extract (ECc) were determined. Concentrations of potassium (K), sodium (Na), calcium (Ca) and magnesium (Mg) were determined by atomic absorption spectrometry, chloride (Cl) by Mohr's titration method (Tandon 1993), and sulfate (S[O.sub.4]) content as the turbidity created by precipitated colloidal barium sulfate suspension, using a spectrophotometer at 490 nm (Tandon 1993). The sodium absorption ratio (SAR) was measured in saturated soil extract, and the calcium carbonate equivalent (% CCE) using titration. Total OC (%) was determined using the Walkley-Black method (Nelson and Sommers 1986), and available phosphorus (P) according to the method described by Olsen and Sommers (1986). Soil texture was classified according to Gee and Bauder (1986). The results of these analyses are given in Table 1.

Extraction of PLFAs

Lipid extraction was performed using the method described by van Aarle and Olsson (2003). Briefly, 3 g of freeze-dried soil was extracted in a one-phase mixture of citrate buffer:methanol:chloroform (0.8:2:1, v/v/v, pH 4.0). After the extract had been separated into two phases by adding 4 mL chloroform and 4mL citrate buffer, the extracted lipids were fractionated into neutral lipids, glycolipids and polar lipids on silicic acid columns (Bond Elut; Varian Inc., Palo Alto, CA, USA) by eluting with 1.5 mL chloroform, 6mL acetone and 1.5 mL methanol, respectively. Methanolysis of the polar lipids (phospholipids) was conducted in 0.2 m methanol ic K.OH, and methyl nonadecanoate (fatty acid methyl ester 19:0) was added as an internal standard. Fatty acid methyl esters (FAMEs) were analysed on a Hewlett-Packard 5890 gas chromatograph with a flame ionisation detector and a 50-m HP5 capillary column (Hewlett-Packard, Palo Alto, CA, USA), according to details given by Frostegard et al. (1993). The PLFAs were identified by using the relative retention times in comparison to the internal standard, and were compared with those identified previously by gas chromatography-mass spectrometry (for further details see Frostegard et al. 1993).

Data analyses

PLFA concentrations were calculated using the FAME 19 : 0 as an internal standard. An indication of the total microbial biomass in each sample (expressed as nmol [g.sup.-1] dry soil) was obtained based on the contents of individual PLFAs. In total, 24 different PLFAs were identified and quantified. Twelve bacteria-specific PLFAs were chosen to represent bacterial biomass: i15:0, a15:0, 15:0, i16:0, 16:1[omega]9, 16:1[omega]7, i17:0, a17:0, cy17:0, 17:0, 18:1[omega]7, and cy19:0 (Frostegard and Baath 1996; Aliasgharzad et al. 2010). The PLFA 18:2[omega]6,9 was used as an indicator of the biomass of saprotrophic fungi (Olsson et al. 1995; Frostegard and Baath 1996; Olsson 1999). PLFAs 10Me16:0, 10Me17:0, and 10Me18:0 were used as biomarkers for actinomycetes. PLFAs a15:0, i15:0, i16:0 and a 17:0 were generally used as signature fatty acids biomarkers for Gram-positive bacteria (G+), whereas the three most abundant PLFA signatures of Gram-negative bacteria (G-) were 16:1[omega]7, 18:1[omega]7 and cy19:0 (Frostegard and Baath 1996). The ratio of the amount of 16:1[omega]c to 16:1[omega]t (i.e. the cis/trans ratio), the ratio of PLFAs indicating G- to those indicating G+, the ratio of saturated (S) to monounsaturated (M) PLFAs (S/M), and the ratio of the sum of cyclopropyl PLFAs to the sum of their monoenoic precursors ((cy17:0 + cy19:0)/(16:1[omega]+18:1[omega]7); called cy/pre) were analysed because they are considered indicators of physiological or nutritional stress in bacterial communities (Guckert et al. 1986; Kaur et al. 2005). The ratio of fungal to bacterial PLFAs (F/B) was used as a biomass index to detect changes in the ratio of fungal to bacterial biomass (Baath and Anderson 2003).

Statistical analyses

Principal component analysis (PCA), Pearson correlations and analysis of variance were performed using SPSS 16.0 (SPSS Inc., Chicago, 1L, USA). Significant differences in biochemical parameters and physico-chemical properties in the soil around the roots of the three different plants were determined by using Tukey's post-hoc test. The results are given as the mean and standard error of the mean (s.e.). PCA was used to compare fatty acid profiles in all of the soil samples, and to present scores for all soil samples from areas with the different plants. Regression analysis was used to test for relations between microbial biomass and microbial stress indicators.

Results

Physico-chemical data for the soils from sites used to cultivate onions and lucerne and sites where native samphire was growing are presented in Table 1. Fields in which onions were cultivated were the most sandy, whereas samphire was found mostly in clay-textured soil, and lucerne was grown on soils with intermediate contents of clay and sand. Measurements of EC and SAR showed that the soil in areas where samphire grew was much more saline than at other locations where the two crops were grown. The lowest soil salinity (EC 0.9 dS [m.sup.-1]) was found where onions were grown, and the highest (EC 74.2dS [m.sup.-1]) in areas inhabited by samphire. Because pH was about neutral and SAR was >13, the soil in areas of samphire can be considered saline-sodic. High soil concentrations of [Na.sup.+], [K.sup.+], [Ca.sup.2+], [Mg.sup.2+], CE, and S[O.sub.4.sup.2-] and low P availability were associated with high salinity (Tabic 1).

The PCA of all identified soil PLFAs revealed that the areas in which samphire was growing were mainly separated from soils on which onions and lucerne were cultivated along PCA axis 1 (Fig. 2). The PCA also indicated that the variation in PLFA composition within soil samples from areas of samphire was greater than the variation in soil samples from other locations.

Total PLFAs and PLFAs indicating bacteria, actinomycetes, saprotrophic fungi, and G- and G+ bacteria were positively related to soil OC (Fig. 3). No significant relationships were found between EC and the microbial groups. This was also the case when the EC was calculated per g OC (Fig. 4a, b).

Twenty-three PLFAs were identified (Fig. 5). For most of these, the amount in the soil around the lucerne roots was higher than in the soil around the roots of samphire and onions, except for 16:1[omega]t, for which the greatest amount was found in the soil around samphire roots. The total PLFA content was significantly higher in soil from lucerne roots than from onion roots. No difference in total PLFAs was found between soil samples collected from lucerne roots and samphire roots (Fig. 6b). The trends were similar for G- PLFA content (Fig. 6a). The G+ PLFA and actinomycete PLFA contents were significantly lower in soil samples from onion and samphire roots than in soil samples from lucerne roots (Fig. 6a). Saprotrophic fungal PLFA content was significantly lower in soil from areas where onions were cultivated than in soil from lucerne and samphire roots; no significant difference was found between soil from lucerne and samphire roots (Fig. 6a).

The F/B ratio was significantly higher in soil from samphire roots than in soil from onion roots. We also found that the ratios of fungal PLFA to G+ and G- PLFAs (F/G-) were higher in soil from samphire roots than both onion and lucerne roots (Fig. 6c).

The PCA loading plot showed that the physical and chemical properties, microbial groups of PLFAs and stress indicators were separated into three groups (Fig. 7). PCA 1 explained 47.2% and PCA 2 explained 30.7% of the total variation. One group consisted of the salinity variables (EC; [Na.sup.+], [Ca.sup.2+], [Mg.sup.2+], [Cl.sup.-], S[O.sub.4.sup.2] concentrations; SAR) and stress-related indicators such as G-/G+, S/M and cy/pre ratios (Table 2). The second group included OC and microbial biomass indicators (total, fungal, bacterial, actinomycete, G+ and G- PLFAs).

All of the stress indicators calculated from the PLFA data were significantly higher in soil from samphire roots than in soil from lucerne and onion roots (Fig. 8). The cy/pre and S/M ratios increased with increasing EC (Fig. 9a-h). However, the relationship was not significant for the S/M ratio. When analysing the relationships between EC and microbial stress indicators, significant second-order polynomial functions were found in most cases. For soil from lucerne and onion roots, stress seemed to increase with increasing salinity, whereas in soil from samphire, the stress seemed to be highest at intermediate salinity levels (Fig. 9). The lowest proportion of saturated branched fatty acids was found in the soil around the roots of samphire (Fig. 10).

Discussion

Microbial biomass as indicated by total PLFAs did not decrease with increasing salinity, which contradicts our first hypothesis. Other studies have shown that the ratio of microbial biomass to soil organic C may decrease across salinity gradients (Sardinha et al. 2003). Our results show that the microbial communities at the study site are well adapted to salinity, and the long period of salinity in the study area may have contributed to adaptation in the microbial communities. Instead, soil OC was overall the most important driver of microbial biomass over a wide salinity gradient. This suggests that OC can mitigate salinity stress in microorganisms. In order to cope with salt stress, microorganisms produce compounds that act as osmotic pressure regulators, in particular organic compounds such as glutamine, proline, glycine and betaine (Oren 1999; Kogej et al. 2007). The synthesis of such compounds requires a great deal of energy, which is obtained from the decomposition of organic matter (Oren 1999).

We found not only that organic matter content increased microbial biomass, but also that organic matter influenced the structure of the microbial community. According to Kang (2005), OC not only acts as an energy source for microbial growth, but also moderates soil environmental conditions in the soil. We found the lowest microbial biomass in onion fields. The soil in these fields was particularly sandy and had a lower organic content than the other soil (Table 1). The low surface area of soil particles and pore space in sandy soils with low organic content, in particular in combination with drought stress, usually results in low microbial biomass (Kang 2005). Agricultural practices and allelopathic effects of the root of this plant (secretion of the antimicrobial substance allicin) may also decrease microbial abundance in the soil around its roots (Ankri and Mirelman 1999).

We found that microbial stress indices increased with salinity, in accordance with our second hypothesis. The highest values of the stress indices were found in the soils around samphire roots, which were also those with the highest salinity. PCA confirmed a high correlation between salinity and stress indices (Fig. 7). In response to stresses, such as high salinity, cis unsaturated fatty acids in the microbial cell membrane may be converted into trans and cyclopropane fatty acids, and saturated fatty acids into unsaturated fatty acids. Such physiological adaptations enhance the resistance to environmental stress (Kaur et al. 2005; Moore-Kucera and Dick 2008). We cannot say from the results of this study whether this shift is due to a direct change in membrane structure in the same microorganism, or whether the salinity-stressed habitats harboured microbial genotypes that have more stress-adapted membranes (Denich et al. 2003). Since the salinity in the area has been high for very long time, it is likely that genotypes adapted to the saline environment have evolved.

High salinity caused overall changes in major microbial groups, which is in accordance with our third hypothesis. We found more G- bacteria than G+ bacteria (Fig. 6a) and more fungal biomass than bacterial biomass (Fig. 6c) at high salinity. According to the amount of their typical PLFAs, the G- bacteria were common in the soil around the roots of the three plants studied (Fig. 6a). The stress tolerance of G bacteria may be related to the existence of cyclopropane fatty acid in the membrane, as well as the external lipopolysaccharide layer, which has greater tolerance to conditions of stress (Kaur et al. 2005). Osmotic stress can lead to a more than 10-fold increase in the synthesis of glutamate in G- bacteria compared with G+ bacteria (Killham and Firestone 1984). Our findings are in contrast to those of Baumann and Marschner (2013), who reported a higher abundance of G+ bacteria in the high salinity treatment in experimental manipulations.

Previous studies have shown that the actinomycetes comprise a small proportion of the microbial community in saline soils, possibly due to a lower tolerance to salinity than other bacteria (Quesada et al. 1982; Zahran et al. 1992; Yokoyama et al. 1992). We found no major decrease in actinomycete indicators in saline soils, but both G+ bacteria and actinomycetes seemed relatively less abundant in the saline soils. This is agreement with the findings of Wiehern et al. (2006), who reported an increase in the ratio of fungi to bacteria with increasing salinity. The high F/B ratio (Fig. 6c) suggests that the tolerance of fungi to salinity is higher than that of the bacterial community. Fungi can accumulate polyols, such as glycerol, as osmotic regulators in response to salt stress (Killham and Firestone 1984).

Soil salinity is one of the most important factors in determining the microbial community structure in soils. However, salinity has multiple effects on soil microorganisms, such as increased osmotic pressure and toxicity and, through its influence on nutrient and water availability, C mineralisation and plant growth (Wichem et al. 2006; Evelin et al. 2009; Baumann and Marschner 2013). We conclude that OC content was the dominant determinant of microbial biomass, while salinity influenced the structure of the microbial community and caused adaptations to stress in the microbial fatty acid composition. The importance of organic matter for high microbial biomass in severely stressed soils indicates that organic matter amendment may be used to mitigate salt stress and as a method of managing saline soils (Hammer et al. 2011a). Furthermore, the relatively large amounts of G- bacteria and saprotrophic fungi indicate that these could be used in future biotechnological cultivation techniques. Helper bacteria are usually G- bacteria and may function in saline soils (Zahran 1997). In an earlier study, we found a low abundance of arbuscular mycorrhizal fungi in saline soils (Barin et al. 2013). These could also be favoured by amendment with organic matter, although they are not decomposers (Hammer et al. 20116). Further investigations are needed to elucidate the potential use of saprotrophic microorganisms in biotechnological applications in saline soils, in particular, how organic matter can be used to stimulate microorganisms with important functions for plant growth in areas where agricultural practices are hampered by drought and salinity stress.

Acknowledgements

The authors are grateful to the Department of Biology at Lund University, Sweden, where the PLFA analysis was performed. This study was supported by the Department of Soil Science, at the Universities of Tabriz and Urmia, Iran. We thank Dr Johannes Rousk for valuable comments on the manuscript.

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http://dx.doi.org/10.1071/SR14090

Mohsen Barin (A,D), Nasser Aliasgharzad (A), Pal Axel Olsson (B), and MirHassan Rasouli-Sadaghianic

(A) Department of Soil Science, Faculty of Agriculture, University of Tabriz, Tabriz 5166616471, Islamic Republic of Iran.

(B) Biodiversity, Department of Biology, Ecology Building, Lund University, SE-223 62 Lund, Sweden,

(C) Department of Soil Science, Faculty of Agriculture, University of Urmia, PO Box 165, Urmia 57134, Islamic Republic of Iran.

(D) Corresponding author. Email: barin.mohsen@yahoo.com; m.barin@tabrizu.ac.ir

Received 12 April 2014, accepted 15 August 2014, published online 12 March 2015

Table 1. General physico-chemical characteristics (mean [+
or -] s.e.) of the soil samples taken from the roots of two
crops and a native herb in a region on the Tabriz Plain on
the east shore of Lake Urmia, northwestern Iran

EC, Electrical conductivity in saturated soil extract (dS
[m.sup.-1]); pH in saturated soil extract; %CCE, percentage
calcium carbonate equivalents in soil; [Na.sup.+],
[Ca.sup.2+], [Mg.sup.2+], [Cl.sup.-], S[O.sub.4.sup.2]
concentrations of sodium, calcium, magnesium, chloride and
sulfate ions in saturated soil extract ([mmol.sub.c]
[L.sup.-1]); SAR, sodium absorption ratio ([mmol.sub.c]
[L.sup.-1]); Olsen P, Olsen soil available phosphorus (mg
[kg.sup.-1]); OC, organic carbon and percentage clay and
sand were published in Barin et at. 2013). Results were
analysed with 1-way ANOVA. Within rows, means followed by
the same letter are not significantly different at P=0.05
according to Tukey's post-hoc test

Property                        Lucerne                 Onion
                                (n = 28)               (n = 39)

EC                         6.80 [+ or -] 0.55b     5.1 [+ or -] 0.4b
PH                         7.69 [+ or -] 0.03a    7.72 [+ or -] 0.03a
CCE                        12.8 [+ or -] 0.7b     10.8 [+ or -] 0.5b
[K.sup.+]                  3.30 [+ or -] 0.24b    3.40 [+ or -] 0.38b
[Na.sup.+]                 39.3 [+ or -] 4.2b     38.5 [+ or -] 3.5b
[K.sup.+]/[Na.sup.+]       0.11 [+ or -] 0.01a    0.10 [+ or -] 0.01a
[Ca.sup.2+]/[Na.sup.+]     0.58 [+ or -] 0.05a    0.44 [+ or -] 0.05a
[Ca.sup.2+]                19.1 [+ or -] 1.4b     14.6 [+ or -] 1.4b
[Mg.sup.2+]                12.4 [+ or -] 0.9b        8 [+ or -] 0.7b
[Cl.sup.-]                 59.2 [+ or -] 4.2b     38.4 [+ or -] 1.7b
S[O.sub.4.sup.2+]          14.8 [+ or -] 1.8b     29.9 [+ or -] 4.7b
SAR                        10.2 [+ or -] 1.1b     11.6 [+ or -] 0.8b
Olsen P                    30.1 [+ or -] 3.7b     55.1 [+ or -] 5.7a
Clay                       21.8 [+ or -] 1.9b     12.4 [+ or -] 1.2c
Silt                         37 [+ or -] 1.7a     17.4 [+ or -] 1.4b
Sand                       41.1 [+ or -] 2.5b     70.2 [+ or -] 2.5a
OC                          1.9 [+ or -] 0.2a      1.1 [+ or -] 0.1b

Property                        Samphire          P-value
                                (n = 27)

EC                         46.4 [+ or -] 2.8a     <0.001
PH                         7.15 [+ or -] 0.03b    <0.001
CCE                        21.2 [+ or -] 0.5a     <0.001
[K.sup.+]                  11.7 [+ or -] 2.5a     <0.001
[Na.sup.+]                716.5 [+ or -] 47.2a    <0.001
[K.sup.+]/[Na.sup.+]      0.010 [+ or -] 0.002b   <0.001
[Ca.sup.2+]/[Na.sup.+]     0.10 [+ or -] 0.01b    <0.001
[Ca.sup.2+]                  73 [+ or -] 5.1a     <0.001
[Mg.sup.2+]                54.8 [+ or -] 4.3a     <0.001
[Cl.sup.-]                578.6 [+ or -] 42.4a    <0.001
S[O.sub.4.sup.2+]         274.5 [+ or -] 21.5a    <0.001
SAR                        90.2 [+ or -] 4.3a     <0.001
Olsen P                    14.3 [+ or -] 1.7c     <0.001
Clay                       44.7 [+ or -] 2.3a     <0.001
Silt                       37.3 [+ or -] 1.5a     <0.001
Sand                         18 [+ or -] 1.7c     <0.001
OC                          1.3 [+ or -] 0.3b     <0.001

Table 2. Correlation coefficients (r-values) for soil
chemistry and biological data and the loading scores from
the PCA shown in Fig. 7

EC, Electrical conductivity; OC, organic carbon; CCE,
calcium carbonate equivalents; SAR, sodium absorption ratio;
G , G+, Gram-negative and -positive bacteria; PLFAs,
phospholipid fatty acids; cy/pre, ratio of the sum of
cyclopropyl PLFAs to the sum of their monoenoic precursors;
S/M, ratio of the sum of saturated to the sum of
monounsaturated PLFAs

Property                   Component

                       PC 1      PC 2

EC                     0.960     0.106
pH                    -0.856    -0.095
OC                    -0.192     0.838
CCE                    0.807     0.162
[Na.sup.+]             0.950     0.175
[Ca.sup.2+]            0.895     0.187
[Mg.sup.2+]            0.888     0.303
[Cl.sup.-]             0.938     0.164
S[O.sub.4.sup.2-]      0.893     0.241
SAR                    0.949     0.114
Olsen P               -0.499     0.119
Clay                   0.799     0.261
Sand                  -0.757    -0.316
G-/G+ ratio            0.669     0.186
Cy/pre ratio           0.494    -0.180
S/M ratio              0.666    -0.449
Total PLFAs           -0.190     0.969
Fungal PLFA           -0.149     0.937
Bacterial PLFAs       -0.270     0.954
Actinomycete PLFAs    -0.277     0.901
G+ PLFAs              -0.363     0.914
G- PLFAs              -0.201     0.964
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Author:Barin, Mohsen; Aliasgharzad, Nasser; Olsson, Pal Axel; Rasouli-Sadaghianic, MirHassan
Publication:Soil Research
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Date:Aug 1, 2015
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