Diversity of anthropogenically influenced or disturbed soil microbial communities

E. Laczko¹, A. Rudaz² and M. Aragno³

1 Solvit, Langsägestrasse 15, CH-6010 Kriens

2 IUL, Schwarzenburgstrasse 155, CH-3097 Bern

3 Université Neuchâtel, Institut de Botanique, rue Emile Argand 11, CH-2007 Neuchâtel

Published in: Insam, H., Rangger, A. (eds.). 1997. Microbial communities. Functional versus structural approaches. Springer Verlag, Heidelberg, pp 57-67.

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Abstract. The objectives of this study are to assess the influences of land use and of heavy metal loads on the soil microbial community. For this purpose we collected soils from 27 sites throughout Switzerland and analyzed saturated, mono- and polyunsaturated PLFAs (phospho lipid fatty acid), ATP (total adenylates) and the total content of the heavy metal cadmium. We found a positive correlation between the sum of PLFA and ATP. Further, we found that land use and cadmium load are reflected by PLFA contents. Based on the organismic origin we formed guilds of individual PLFA. These guilds relate to taxonomic units and trophic function at the same time. Therefore, it is possible to infer the structure (structural diversity) and trophic diversity (functional diversity) of the soil microbial communities. We found a negative correlation between functional diversity and cadmium load. Functional diversity differentiated also land use types. PLFA analysis may reveal structural and functional in situ properties of whole soil microbial communities. Substrate utilization tests, which are restricted to cultivable organisms, predominantly Bacteria and Fungi, may supplement PLFA analysis with data about specific activities. Finally, our results indicate, that PLFA can be used to estimate critical pollutant loads.

Key words. Microbial community, structural diversity, functional diversity, soil, land use, heavy metals, cadmium, PLFA analysis, substrate utilisation

1. Introduction

The main goal of this study is to assess the influence of soil cadmium loads on the soil microbial community in a range of soils, which are representative for the intensively used Swiss midlands and for the extensively used remote areas.

A recent Swiss survey study revealed that topsoils mostly show cadmium, copper, lead and zinc loads, which are above geogenic background contents (Vogel et al. 1989). These sites may be considered as polluted. The authors of the survey claim, that this pollution has anthropogenic sources, affects the whole surface of Swiss soils and is still increasing. The results further indicate that Cadmium may serve as an indicator of direct and indirect anthropogenic impact. The survey showed that the general heavy metal pollution has not yet reached levels, which were reported to reduce biomass or global activity of the soil microbial community (e.g. Domsch 1985). The question may be raised, whether heavy metal loads above the geogenic background contents, but below the apparently toxic levels, already affect soil microbial communities. If heavy metal resistence is not the same among the species of a given community, then increasing heavy metal loads will exert a selective pressure and will alter initial community composition. If heavy metal sensitive microorganisms become eventually extinct, then this alteration may be accompanied by loss of metabolic capabilities. This loss must not immediately affect global activity or biomass of the community, because the loss might be counteracted by unaffected species. A recent laboratory study of Burkhardt et al. (1993) on soil bacteria seems to support this view. The authors found, that in bacterial communities affected by copper, nickel, lead or zinc, uncommon degradative capabilities are rarer than in unaffected ones. In a recent field study (Pennanen et al. 1996) the authors found changes in soil microbial community composition at lower soil copper contents than changes in bacterial biomass and global activity (measured as respiration and thymidine incorporation). Both studies deal with very polluted soils from the surroundings of metal mines or metal smelters. Similar investigations, which adress the functional or structural diversity of soil bacteria or microorganisms in soils, with moderate heavy metal load, do not exist, but would be highly desirable in establishing a sustainable soil conservation practice (Rudaz and Brüning 1990; Albers et al. 1994).

In our study the microbial communities are characterized in terms of biomass, diversity and trophic function. We infer all these parameters from the analysis of phospholipid fatty acids (PLFA), which are taxonomically relevant constituents of the cell membranes of all organisms. This method offers a quantitative approach of the microbial community structure and minimizes methodological bias and artifacts (White 1995). PLFA analysis was already succesfully used by us to study the relation between soil microbial diversity and vitamin deficiency (Korner and Laczko 1992). Others used PLFA analysis for demonstrating the influence of land use practice (e.g. Zelles et al. 1995) or the effects of pollution (e.g. Baath 1992 et al.; Pennanen et al. 1996) on the soil microbial community.

With the present study we wanted to show how community structure and functional diversity may be inferred from the PLFA analysis and how functional diversity is related to structural diversity. Furthermore, we want to show the influence of land use and cadmium loads, below global toxicity levels, on the soil microbial community structure as well as on the trophic functions within these communities. The second objective has general environmental relevance, because the adressed trophic functions are tightly connected with the cycling and mineralization of organic matter in soils (e.g. Hunt et al. 1987; Hassink et al. 1994).

2. Methods

For the purpose of the study we collected 27 soil samples in Switzerland. Four sampling sites are cultivated lands in a rural area of the Swiss midlands (area 1A). Three sites are cultivated lands in the vicinity of a steel factory and an urban area of the Swiss midlands (area 2A). Five sampling sites are cultivated lands in a rural area of the Swiss midlands, which were fertilized during several years with an industrial waste water sludge (area 3A). Seven sites are extensively used meadows in remote rural areas of the Swiss midlands, Jura mountains and prealpes (Areas 1M). Six sites are meadows in the viccinity of a steel factory and an urban area of the Swiss midlands (area 2M). Two sites are meadows in a rural area of the Swiss Jura mountains (area 3M). These last two sites are exclusively used for multidisciplinary research, conducted in the framework of the Priority Programme Environment, and are described in detail by Baur et al. (1996). According to Baur et al. these sites were intensively grazed by cows until 1993.

At each sampling site, 25 soil cylinders of not more than 20cm length were taken from the A horizon with a 30mm gauge auger and mixed to form one sample. The mixed sample was immediately sieved through a 6-mm mesh steel sieve. Visible plant roots were removed carefully. A homogeneous soil portion of about 12 to 15 g was immediately filled in a preweighted screw bottle containing the extraction solvents for PLFAs (see below). An equal portion for the determination of the moisture content of the freshly collected samples was filled in a preweighted gastight jar. The rest of the soil sample was stored at 4°C.

pH in water, the content of calcium carbonate, organic carbon and cadmium were analyzed according to the standard procedures of the Swiss Institute of Environmental Protection and Agriculture (FAC, 1989). Total adenylates were measured using the method of Maire (1982, 1984).

An extensive description of the PLFA analysis is given in the publications of Zelles et al. (1993). In short, we extracted the lipids from approximately 12 to 15 grams of fresh soil (directly on the sampling site, see above) according to the procedure of Bligh and Dyer (1959). The phospholipids were isolated by silica gel chromatography and transesterified by a mild alkaline methanolysis. The methyl esters of the PLFA were then extracted and seperated by two consecutive solid phase extractions into three fractions: saturated PLFA (SATFA), monounsaturated PLFA (MUFAS) and polyunsaturated PLFA (PUFAS). Each fraction was analyzed seperately by GC-MS. The resulting chromatogramms were evaluated by a software (Solvit E. Laczko, unpublished), which identifies and quantifies two hundred and sixty-four PLFAs on the basis of mass spectras, retention times and an internal standard.

We used the information about the organismic origin of the PLFA to form biological guilds of PLFA (in contrast to the chemical guilds like SATFA, MUFAS or PUFAS, or guilds defined by statistics like "PLFA showing covariation with heavy metal load"). The guilds we formed comprise PLFA from roots of higher plants, algae, protozoa, fungi, vesicular-arbuscular-mycorhiza, cyanobacteria and bacteria (Appendix PLFA guilds). Each of these guilds represents not only a taxonomic unit but also a distinct trophic function of the soil microbial community. Therefore, it is possible to infer the relative biomass of distinct taxonomic and functional units, and to characterize the microbial community structure, or to identify sensitive parts or functions within the community. Further, we applied an approach of Huston (1994). Huston suggests the use of a biologically meaningful diversity index and named it functional diversity. He defined functional diversity as the number of functional guilds multiplied by the mean number of units in those functional guilds. According to Huston a function may be a metabolic, an ecological or any other function, which is related to a biotic structure. The units may be molecules, species or any other biotic structure. For our case we defined functional PLFA diversity as the number of PLFA guilds multiplied by the mean number of individual PLFAs in those guilds. To calculate functional diversity, the identified PLFAs of a sample were first classified into the mentioned guilds, then the number of PLFAs in each guild was determined (PLFA count). The relative biomass of a guild was estimated as the sum of the mass of the related PLFAs. PLFA diversity was calculated according to the proposition by Hill (1973). The diversity measure of Hill is used as a measure of the structural diversity of the soil microbial communities.

3. Results and discussion

The sampling sites are briefly characterized in Table 1. All soil samples had a sandy loam texture (qualitative observation). The pH ranges from slightly acidic to neutral values. The organic carbon content is somewhat lower in cultivated lands and lies (with one exception) between 1.5% and 7% of the soil dry weight. All in all the analyzed soils may be considered similar in respect of texture, pH and organic carbon content.

Values are means; values in brackets indicate the corresponding data range
DW = dry weight; tot = extracted with 1M nitric acid; sol = extracted with 0.1M aquous sodium nitrate solution

The selected sites are in a different way influenced by human activities. This is reflected by the soluble and total cadmium content shown in Table 1. In the rural and remote areas 1A and 1M a low anthropogenic impact may be suspected. The sole impacts are due to (similar) atmospheric depositions and land use practice. The pollution level may be considered low. In the areas 2A and 2M, in the vicinity of a steel factory, a point source of various pollutants, a gradient of low to high industrial impact may be suspected. The pollution level may be considered ranging from low to elevated. Although the total cadmium content is low in cultivated lands, the soluble cadmium content tends to elevated values. In the rural and remote areas 3A and 3M a very local and uniform agricultural impact may be suspected. The pollution level may be considered elevated or high. The somehow surprising cadmium pollution in the remote Jura mountains (area 3M) is not an isolated observation. Atteia et al. (1995) and the Office for environmental protection of the Canton Basel-Landschaft (Bono, 1993) found soil cadmium contents up to 1500 ng/gDW in the Jura mountains. The high soil cadmium contents were related to yet unknown pollution sources (Atteia et al. 1995).

The microbial characteristics of the analyzed soils are summarized in Table 2. The contents of all individual PLFAs were summed to obtain a measure of total PLFA. The obtained values for total PLFA correlate positively with the content of total adenylates (r = 0.812, n = 27), indicating that we are analyzing PLFA from living biomass (Figure 1). Further, we observed a tendency towards low total PLFA contents (and low ATP contents) in cultivated soils and in soils with elevated cadmium loads (Figure 2). No relationship between ATP (biomass) and PLFA diversity or functional diversity was found (Figure 3). On the other hand we found negative correlations between the functional diversity and the total soil cadmium content of cultivated lands with cadmium loads above 200 ng/gDW (r = -0.748, n = 12) and of meadows with cadmium loads above 290 ng/gDW (r = -0.904, n = 15) (Figure 4). The mean PLFA mass of all PLFA guilds is lower in cultivated lands (areas 1A, 2A, 3A) and in soils with elevated cadmium loads (Table 2). The soil microbial communities of meadows seem to be more affected by the soil cadmium loads, than the communities under cultivated lands. Different PLFA guilds are affected in different ways, indicating changes in the community structure (Table 2).

FD = functional diversity; R = plant roots; A = algea; P = protozoa; F = fungi; VAM = vesicular arbuscular mykorrhiza; CB = cyanobacteria; B = bacteria

Figure 1. The relationship between total PLFA and ATP

(not displayed)

Figure 2. The relationship between PLFA, ATP and total soil cadmium content

(not displayed)

Figure 3. The relationship between PLFA diversity, functional diversity and ATP

(not displayed)

Figure 4. The relationship between PLFA (structural), or functional diversity and soil cadmium content

(not displayed)

The presented results show that soil cadmium contents between

200 ng/gDW and 1000 ng/gDW have an influence on the soil microbial community. We found a weak negative correlation between soil cadmium load and microbial biomass. On the other hand we found no relationship between biomass and PLFA diversity or functional diversity. Thus the decrease of functional diversity at elevated soil cadmium contents reflects the impact of both land use and cadmium loads and is not an analytical artifact. We conclude, that the microbial community is affected in meadows at cadmium contents above 300 ng/gDW and in cultivated lands above 200 ng/gDW. These values are 3 to 4 times beyond the pollution limits of the swiss legislation and 10 times beyond the levels which are reported to inhibit total soil respiration (e.g. Domsch 1985). Further, cultivated soils seem to have a lower critical load value of cadmium pollution than meadows. This means, that any disturbance that reduces functional diversity permanently, as ploughing does, results eventually in an enhanced susceptibility of the microbial community towards further disturbances. This is contrasted by the observation, that the magnitude of biomass changes is bigger in meadows.

The impact of cadmium on the guilds is not significantly different. Nevertheless some tendencies may be observed. Regardless of the differences between cultivated lands and meadows, the biomass of bacteria and cyanobacteria covaries. The biomass of fungi and especially of protozoa seems to be more affected by cadmium loads than the biomass of bacteria or cyanobacteria. The opposite is true for the covarying biomass of plant roots and the associated VAM. Heavy metal sensitivity of fungi and heavy metal tolerance of VAM were also observed by Pennanen et al. (1996). Burkhardt et al. (1993) tested degradative capabilities of bacterial communities in the rhizosphere and found that heavy metal contamination reduced the ability of bacteria to degrade aromatic compounds. However, the reported differences between polluted and unpolluted soils were statistically insignificant.

The chemical analysis of structural cell components like PLFA delivers primarily structural information about the living biomass. Because we know the organismic origin of many PLFA, we may relate structural information to taxonomic knowledge (e.g. Suzuki et al. 1993). The taxonomic relation finally alows to infer functional properties of the identified taxonomic units. In addition, the PLFA analysis provides structural information, which is nearly unbiased by methodological artifacts (White 1995). Thus PLFA analysis may reveal in situ structural and functional properties of the analysed biomass at the same time. However, most relationships between PLFA and taxonomic units, or functional properties, are not straight. Normally several interpretations of the PLFA data must be considered. This uncertainty was respected by the formation of the biological PLFA guilds. PLFAs with potentially multiple origin were related to all possible guilds.

Substrate use analysis delivers primarily functional information about the living biomass, but structural information may be inferred, too (e.g. Dean-Ross 1989). In contrast to the the PLFA analysis, substrate use must be tested always in an experimental approach, ex situ. The bias by methodological artifacts is strong and often not under control. Haack et al. (1995) demonstrated for example the pitfalls and problems of the BIOLOG" test. Moreover, substrate tests mostly (probably always) are, unlike PLFA analysis, restricted to a group of organisms, predominantly Bacteria and Fungi. Nevertheless, substrate tests are the only way to confirm the presence of specific activities in microbial communities. In this way, substrate tests may supplement structural analyses like the PLFA analysis and may reduce the uncertainty in the interpretation of structural data.

4. Conclusions

Biomass, community structure and functional diversity of soil microbial communities, as inferred from PLFA analysis, are interpretable parameters in low impact studies. Our study showed that moderate cadmium pollution reduces functional diversity of soil microbial communities. The relationship between functional diversity and pollutant load can be used to estimate critical pollutant loads. In the case of cadmium the critical loads, which affect the soil microbial community, are 290 ng/gDW in meadows and 200 ng/gDW in cultivated lands. This values are ten times lower than the values estimated on the basis of soil respiration tests. To clarify the impact of cadmium (or other pollutants) on specific guilds, or functions, of the soil microbial community, specific substrate use tests should be performed.

Acknowledgments

We thank Gertrud Fischer for measuring soil PLFAs, Astrid Schwarz for revising the presentation of the results and Karin Klapproth for revising the English.

This study was supported by the Swiss National Science Foundation (grant 5001-34859) and Solvit.

References

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Appendix. PLFAs, which form the biological guilds plant roots (R), algea (A), protozoa (P), fungi (F), vesicular arbuscular mykorrhiza (VAM), cyanobacteria (CB), and bacteria (B) (Suzuki et al.1993, Ratledge and Wilkinson 1988, Vestal and White 1989, Zelles et al. 1992, Olsson et al. 1995, Pennanen et al. 1996)

Numbers in brackets are relativ retention times in relation to n19:0

R: 18:3(0,949), 18:3(0,956), 18:3_6,9,12, 18:3_10,12,16, n24:0, n26:0, n26:0(1,534)

A: 18:2(0,882), 18:2(0,898), 18:2(0,901), 18:2(0,903), 18:2(0,932), 18:2_5,10, 18:2_6,10, 18:2_9,12, d6:0, d8:0, d9:0, d10:0, d11:0, d12:0, d13:0, d14:0, d15:0, d16:0, d17:0, d18:0, d20:0, d21:0, d22:0

P: 20:4_4,8,11,14, 20:3(1,053), 20:3(1,065), 20:3(1,066), 20:2(1,042), 20:2_5,10, 20:2_10,14, 22:2(1,186), 22:2(1,192), 22:2(1,202), n14:0

F: n23:0, 20:4_4,8,11,14, 18:2(0,882), 18:2(0,898), 18:2(0,901), 18:2(0,903), 18:2(0,932), 18:2_5,10, 18:2_6,10, 18:2_9,12, 16:1,11(1,271), n14:0, n16:0, n18:0, n10:0, n11:0, n12:0, n13:0, n15:0, n17:0, n19:0, n20:0, n21:0, n22:0, 18:1,9_(1,370), 18:1,9_(1,401), 18:1,9_(1,406), 18:1,9_(1,418), 18:1,11(1,401)cis, 18:1,11(1,406)cis, 18:1,11(1,418)cis

VAM: 20:4_4,8,11,14, 16:1,11(1,271), 18:1,11(1,401)cis, 18:1,11(1,418)cis

CB: 20:3(1,053), 20:3(1,065), 20:3(1,066), 16:3(0,725), 16:3_5,7,10, 20:3_5,8,11, 20:3_5,11,15, 22:3(1,111), 18:3(0,949), 18:3(0,956), 18:3_6,9,12, 18:3_10,12,16, 14:1,4_(1,098), 15:1,4_(1,147), 15:1,7_(1,147), 15:1,4_(1,154), 15:1,7_(1,154), 15:1,4_(1,176), 15:1,7_(1,176), 16:1,4_(1,225), 16:1,7_(1,225), 16:1,4_(1,253), 16:1,7_(1,253), 16:1,11(1,277), 17:1,4_(1,299), 17:1,9_(1,299), 17:1,11(1,299), 17:1,4_(1,307), 17:1,9_(1,307), 17:1,11(1,307), 17:1,4_(1,327), 17:1,9_(1,327), 17:1,11(1,327), 17:1,4_(1,334), 17:1,9_(1,334), 17:1,11(1,334), 18:1,4_(1,370), 18:1,4_(1,401), 18:1,4_(1,418), 18:1,13(1,418), 19:1,13(1,423), 19:1,7_(1,446), 19:1,4_(1,449), 19:1,7_(1,449), 19:1,4_(1,471), 19:1,11(1,477), 20:1,8_(1,570), 20:1,11(1,570), n14:0, n16:0, n18:0, n10:0, n11:0, n12:0, n13:0, n15:0, n17:0, n19:0, n20:0, n21:0, n22:0, i15:0, a15:0, i17:0, a17:0, i13:0, a13:0, i14:0, i16:0, i18:0

B: 16:1,11(1,271), 14:1,4_(1,098), 15:1,4_(1,147), 15:1,7_(1,147), 15:1,4_(1,154), 15:1,7_(1,154), 15:1,4_(1,176), 15:1,7_(1,176), 16:1,4_(1,225), 16:1,7_(1,225), 16:1,4_(1,253), 16:1,7_(1,253), 16:1,11(1,277), 17:1,4_(1,299), 17:1,9_(1,299), 17:1,11(1,299), 17:1,4_(1,307), 17:1,9_(1,307), 17:1,11(1,307), 17:1,4_(1,327), 17:1,9_(1,327), 17:1,11(1,327), 17:1,4_(1,334), 17:1,9_(1,334), 17:1,11(1,334), 18:1,4_(1,370), 18:1,4_(1,401), 18:1,4_(1,418), 18:1,13(1,418), 19:1,13(1,423), 19:1,7_(1,446), 19:1,4_(1,449), 19:1,7_(1,449), 19:1,4_(1,471), 19:1,11(1,477), 20:1,8_(1,570), 20:1,11(1,570), n14:0, n16:0, n18:0, n10:0, n11:0, n12:0, n13:0, n15:0, n17:0, n19:0, n20:0, n21:0, n22:0, i15:0, a15:0, i17:0, a17:0, i13:0, a13:0, i14:0, i16:0, i18:0, br9:0, p2-15:0, p6-13:0, br13:0(0,483), p3-15:0(0,599), p2-18:0, p8-15:0(0,608), br15:0(0,610), br15:0(0,613), p2-16:0(0,642), br16:0(0,646), p8-16:0(0,661), br16:0(0,663), br16:0(0,692), br16:0(0,707), p2-17:0(0,725), br17:0(0,731), br17:0(0,748), br17:0(0,750), br17:0(0,753), p2-17:0(0,773), p2-18:0(0,776), br17:0(0,782), br17:0(0,785), br17:0(0,787), br17:0(0,789), br17:0(0,791), br17:0(0,795), br17:0(0,815), p2-18:0(0,818), br18:0(0,834), br18:0(0,835), br18:0(0,836), met16:0, p2-18:0(0,859), p2-19:0(0,861), br18:0(0,871), p3-20:0, br18:0(0,893), br19:0(0,910), p2-20:0(0,943), br19:0(0,949), br19:0(0,953), br19:0(0,969), p2-20:0(0,973), br19:0(0,976), p6-20:0, br20:0(1,029), br20:0(1,031), br20:0(1,049), p4-21:0(1,063), p2-21:0(1,103), br21:0(1,107), p4-21:0(1,116), p2-21:0(1,122), p2-22:0(1,129), p2-22:0(1,130), br21:0(1,135), p4-22:0(1,140), p4-22:0(1,141), p4-22:0(1,165), p4-22:0(1,237), 16:1,9_(1,259)cis, 16:1,9_(1,261)cis, 16:1,9_(1,263)cis, 18:1,9_(1,370), 18:1,9_(1,401), 18:1,9_(1,406), 18:1,9_(1,418), 18:1,10(1,404), 14:1,5_(1,098), 14:1,9_(1,114), 15:1,5_(1,147), 15:1,9_(1,147), 15:1,5_(1,154), 15:1,9_(1,154), 15:1,5_(1,176), 15:1,9_(1,176), 15:1,9_(1,185), 16:1,5_(1,225), 16:1,9_(1,225)trans, 16:1,5_(1,253), 16:1,10(1,261), 17:1,5_(1,286), 17:1,5_(1,299), 17:1,5_(1,307), 17:1,5_(1,327), 17:1,5_(1,334), 18:1,5_(1,370), 18:1,5_(1,401), 18:1,5_(1,406), 18:1,5_(1,418), 19:1,5_(1,449), 19:1,9_(1,449), 20:1,9_(1,570), p10-17:0, p10-18:0, p10-19:0, cy19:0(0,906), cy19:0(0,923), cy19:0(0,925), cy19:0(0,963), cy19:0(0,989), cy19:0, cy19:0(0,994), cy17:0(0,824), cy17:0(0,825), cy17:0(0,829), cy16:0(0,736), cy18:0(0,874), cy18:0(0,898), cy18:0(0,907), 18:1,11(1,401)cis, 18:1,11(1,406)cis, 18:1,11(1,418)cis, p10-16:0, 18:1,12(1,418)cis, 18:1,11(1,370)trans

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