Aquatic hyphomycete communities as potential bioindicators for assessing anthropogenic stress

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a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m

w w w. e l s e v i e r. c o m / l o c a t e / s c i t o t e n v

Aquatic hyphomycete communities as potential bioindicators for assessing anthropogenic stress M. Soléa,⁎, I. Fetzera , R. Wennrichb , K.R. Sridharc , H. Harmsa , G. Kraussd a

Helmholtz Centre for Environmental Research — UFZ, Department of Environmental Microbiology, Permoserstrasse 15, D-04318 Leipzig, Germany b Helmholtz Centre for Environmental Research — UFZ, Department of Analytical Chemistry, Permoserstrasse 15, 04318 Leipzig, Germany c Microbiology and Biotechnology, Department of Biosciences, Mangalore University, Mangalagangotri, Mangalore 574 199, Karnataka, India d Helmholtz Centre for Environmental Research — UFZ, Department of Environmental Microbiology, Theodor-Lieser-Strasse. 4, 06120 Halle/Saale, Germany

AR TIC LE I N FO

ABS TR ACT

Article history:

With a profound knowledge of how physico-chemical parameters affect these communities,

Received 5 June 2007

microbial communities could be used as indicators for environmental changes and for

Received in revised form

risk assessment studies. We studied aquatic hyphomycete communities in rivers and

8 September 2007

aquifers from sites shaped by intense mining activities (namely the “Mansfeld region”) and

Accepted 12 September 2007

chemical industry (cities of Halle and Bitterfeld) in Central Germany. Environmental stress

Available online 1 November 2007

factors such as high concentrations of heavy metals, sulphate, and nitrate as well as low concentrations of oxygen significantly reduced the diversity and biomass of hyphomycetes

Keywords:

in the investigated samples. Redundancy analysis (RDA) indicates that variations in water

Aquatic hyphomycetes

chemistry cause a significant proportion of the change in fungal community structure

Freshwater geochemistry

(86.2%). Fungi were negatively correlated with high metal and nutrient concentrations. RDA

Anthropogenic stressors

also showed a strong influence of organic matter on individual species, with Anguillospora

Community structure

longissima (Sacc. et Syd.), Clavatospora longibrachiata (Ingold), Clavariopsis aquatica (De Wild),

Multivariable statistics

Flagellospora curvula (Ingold), Heliscus lugdunensis (Sacc. et Thérry), Tumularia aquatica

Redundancy analysis (RDA)

(Ingold) and Lemonniera aquatica (De Wild) being most sensitive. We propose that aquatic

Bioindicator

hyphomycete communities can be used as sensitive and integrative indicators for freshwater quality. © 2007 Elsevier B.V. All rights reserved.

1.

Introduction

Anthropogenic influences on natural ecosystems are often multifaceted, and their consequences are difficult to interpret (e.g. impact on biodiversity, ecosystem stability and function), since the impact of individual factors within an array of environmental stressors may be impossible to isolate (Hilborn and Stearns, 1982; Underwood, 1997). Multivariate analyses of the environmental factors are therefore impor-

tant in order to gain insights into the complex impacts on natural systems. Microbial communities are suitable for detection of stresses in natural systems because of their ubiquity and rapid response to environmental changes. Moreover, they thrive even in the harshest habitats, such as extremely dry and cold places, or at heavily polluted sites (Brock, 1978; Anton et al. 2000; Price, 2000; Krauss et al. 2005a). However, due to the high complexity of natural microbial communities, it is exceedingly

* Corresponding author. Tel.: +49 341 235 3255; fax: +49 341 235 2247. E-mail address: [email protected] (M. Solé). 0048-9697/$ – see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.scitotenv.2007.09.010

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difficult if not impossible to identify every member of such communities and they are therefore often considered as a ‘black box’ (Tiedje et al., 1999). However, monitoring the relative abundance of individual microbial species within their polluted habitats is of prime importance to (1) identify key players for future attempts at bioremediation; and (2) detect relevant species that can act as bioindicators in risk assessment monitoring programs. Aquatic hyphomycetes, an important part of the freshwater microbial communities, are excellent candidates for bioindicators. In contrast to bacteria aquatic fungal communities are composed of a manageable number of species. Together with bacteria they play a vital role in the functioning of aquatic ecosystems and fulfill crucial activities as part of food webs and in nutrient cycling (Buesing and Gessner, 2006). They initiate the degradation of organic material by e.g. increasing the palatability of litter and wood (Arsuffi and Suberkropp, 1984; Sridhar et al., 2001). In addition, aquatic hyphomycetes can degrade organic compounds in harsh habitats such as rivers highly enriched in nutrients (Pascoal and Cássio, 2004; Pascoal et al., 2003), contaminated by heavy metals (Krauss et al., 2001; Sridhar et al., 2000, 2001) or organic xenobiotic compounds (Au et al., 1992; Raviraja et al., 1998; Junghanns et al. 2005, in press; Krauss et al. 2005a). Surprisingly, in situ experiments performed in groundwater wells showed that leaf litter is also colonised and degraded in this habitat where oxygen is generally limited (Krauss et al., 2003b, 2005b). Fungal communities survive even in coarse particulate organic matter (CPOM) and fine particulate organic matter (FPOM) of sediments polluted with heavy metals or organics (Bärlocher and Murdoch, 1989). There is a general trend that, independent of its type, pollution usually leads to a decline in the diversity of aquatic hyphomycetes (for a review see Krauss et al. 2003a). A drastic decline in diversity and sporulation of aquatic hyphomycetes, accompanied by changes in species dominance (e.g. top conidia producers) has been reported in habitats highly polluted by heavy metals (Krauss et al., 2001). In moderately polluted habitats, changes in fungal diversity and abundance are less pronounced, and therefore the relationship between water geochemistry and the composition of fungal communities is more difficult to assess. In order to reduce complexity, different statistical approaches have been applied to such environmental and biotic datasets. In a river system, Pascoal and Cássio (2004) using a correspondence analysis (CA) showed that shifts in the structure of aquatic hyphomycete communities are associated with changes in water chemistry. However, it was not possible to extract the main environmental factors shaping the fungal community in that system. In this study, we used a multivariate technique, namely a redundancy analysis (RDA; ter Braak, 1994; van Wijngaarden et al., 1995), to relate water geochemistry and aquatic hyphomycete communities. The objectives of this study were to (1) extract the main environmental factors responsible for constraining the community structure of aquatic hyphomycetes; and (2) investigate whether species assemblages of aquatic hyphomycetes might be used as potential indicators for the detection of minute environmental

changes. We focused on surface and groundwaters in Central Germany, in a region highly impacted by anthropogenic activities during the last century.

2.

Material and methods

2.1.

Site locations

Samples were taken at 11 sites in Central Germany (SaxonyAnhalt) (Fig. 1). Sites cover a broad range of environmental and anthropogenic stresses. Samples originated from the Mansfeld Region, the Saale River and the Spittelwasser stream. Samples were collected between the 24th and 30th of April 2003. Samples from the Mansfeld region (H4, H8, H9) were surface waters taken from a former industrial area around an abandoned copper shale smelter (Helbra). The UHH samples were collected along the Saale River. The sites UHH9, UHH8 were located upstream, UHH5 downtown, and UHH2 downstream of the city of Halle. The sites UHH5 and UHH8 were situated on a side arm of and directly on the Saale River. The site UHH9 was located at the confluence of the Weiβe Elster stream and the Saale River. Sample UHH2 was taken in a drainage channel flowing into the Saale River. Finally, sample SpWFL was taken from the Spittelwasser stream, which was formerly used as wastewater drainage. Samples P1 (7.5 m below surface), P10A (9.6 m) and GWM/2893 (8.9 m) were samples taken from groundwater wells. While P1 and P10A were located in the Mansfeld region, GWM/2893 came from a groundwater well near the Spittelwasser stream.

2.2.

Water chemistry

Water temperature, pH, conductivity, redox (Eh) potential and dissolved oxygen were measured in the morning in the field with a MultiLine P4-WTW, Germany (Table 1). For chemical analyses, water was collected in sterilized dark-brown Schott– Duran glass flasks at 10–20 cm depth (surface water) and 1.5– 2.5 m depth (groundwater) and transferred to the lab in a cold box at 4 °C. Groundwater samples were taken at much greater depths to ensure the original anaerobic conditions usually present within groundwater were maintained. Dissolved (DOC) and total organic carbon TOC (TOC-5050 Shimadzu) were determined according to the German standard procedure for the examination of water, wastewater, and sludge (heated to 680 °C, measured in non-dispersive IR) referred to DIN 38409 H3-1 (Deutsches Institut für Normung e.V.). All measurements were done in triplicate for each sample.

2.3.

Determination of trace elements and relevant ions

All water samples were analyzed in triplicates for the total concentration of selected heavy metals, calcium and magnesium. For this, the unfiltered water samples were stirred and equally split into sub-samples. For arsenic and metal analysis each sub-sample was acidified to pH 2 using nitric acid (Suprapur, Merck) to stabilize the solution until analysis. For the determination of ammonium and selected anions the sub-samples were transferred to polyethylene bottles

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559

Fig. 1 – Location of the sample sites (grey dots), main towns and rivers and the former mining area (Mansfeld region).

and cooled to 4 °C. The analyses were realized within 24 h after sampling. Because of the elevated concentrations of the considered elements, ICP, atomic emission spectrometry (CIROS, Spectro A.I.) with pneumatic nebulization (cross flow), was used for the determination of metals. Depending on their concentrations, the elements were analyzed in undiluted or diluted samples (sample + deionized water: 1 + 9). The calibration was done with the standard addition technique. Arsenic was analyzed after hydride generation and in situ trapping in an iridium-coated graphite furnace using a 4100 ZL atomic absorption spectrometer equipped with a FIAS-400 flow injection device (both Perkin-Elmer). Mercury was analyzed using the cold vapour technique (FIMS, Perkin-Elmer) with NaBH4 for reduction of the mercury ions. Ion chromatography was used to determine the anions chloride, nitrite, nitrate, and sulphate. The ion chromatograph DX 500 (Dionex, Sunnyvale, USA) was equipped with an autosampler AS3500, a gradient pump GP 40 and a conductivity detector CD20 with a thermostated conductivity cell (35 °C). The common anions were separated using an anion exchange guard column IonPac AG11 in series with the analytical column IonPac AS11 (Dionex) and a NaOH gradient. Data acquisition was performed with the software PeakNet using peak areas for calibration. To analyze ammonium (indophenol blue reaction, at 819 nm) and o-phosphate (molybdenum blue reaction, at 690 nm) photometric methods were used using an EPOS Analyzer 5060 (Eppendorf AG, Hamburg, Germany). Ammonium determination was based on the Berthelot's Reaction

(reaction with indophenol blue, detection at wavelength 691 nm). For the o-phosphate determination the reaction with isopolymolybdic acid to finally form polyheteromolybdenum blue (detection wavelength 819 nm) was applied.

2.4.

Fungal diversity and ergosterol analyses

To determine the fungal inventory at each sampling location, five nylon mesh bags containing leaf disks (25 leaf disks each) of senescent air dried and sterilized leaves of Alnus glutinosa (L.) Gaertn. were immersed in the water column (for a detailed description see Krauss et al., 2003b). The mesh bags were deployed at each site at depths of 10 to 25 cm in surface water and 1.5 to 2.5 m in groundwater. After two weeks of immersion (time generally required to reach the peaks of fungal biomass and sporulation in these habitats, Sridhar et al. 2001, 2005), bags were recovered and transferred to the lab. Conidia and ergosterol analyses were performed in five replicates of five leaf disks. For the determination of fungal species composition, 75 ml sterile water containing the leaf disks were continuously aerated in order to induce sporulation of aquatic hyphomycetes. Then, conidial suspension were filtered through an 8 μm membrane filter (Millipore) and stained with Aniline Blue in Lactophenol, identified to the lowest taxonomic level and counted under a microscope. All counts were then adjusted to number of conidia per mg leaf dry mass. Finally, the relative abundance of aquatic hyphomycete species was calculated as the average percentage of contribution of single species to the total number of conidia produced

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Table 1 – Hydrogeological and hydrochemical characterization (all values [mg l− 1]) of 11 sampling sites located in SaxonyAnhalt, Central Germany Mansfeld Region

Coordinates pH Temperature (°C) O2 Eh Conductivity DOC TOC SO2−IC 4 NO−IC 3 NO−IC 2 −IC Cl Br−IC PO−ph 4 NH+ph 4 a Ca Mga Fea Nia Pba Cda Cua Zna Mna Asb

Saale River

Spittelwasser stream

H4

H8

H9

P1

P10A

UHH2

UHH5

UHH8

UHH9

SpWFL

GWM/2893

51.54° 11.48° 7.5 6.8 8.9 340 5.4 7.9 8.1 3322 149 b 0.25 192 b 0.9 0.19 2.69 448 155 b 1.7 0.76 1.99 9.7 1228 11.6 0.016

51.54° 11.53° 8.3 9.6 8.5 250 2.5 3.3 3.4 764 62 b 0.25 181 b 0.9 0.08 0.02 351 85 b b b b 0.1 0.28 0.01 0.026

51.49° 11.70° 7.4 16.1 7.6 220 1.5 4.4 5.6 375 8 b 0.25 124 b 0.9 0.17 0.06 141 57 b b b b b 0.08 0.01 0.017

51.54° 11.49° 7.5 11 2.5 238 4.3 14.2 14.2 1648 69 0.28 215 1.6 0.04 0.01 587 114 b b b b b 0.60 0.04 0.001

51.54° 11.51° 7.8 9.4 4.6 242 2.6 2.0 2.0 964 31 b 0.25 111 b 0.9 0.06 0.01 342 117 b b b b b b b 0.002

51.52° 11.92° 7 9.6 7.2 105 1.9 12.5 12.5 589 31 b0.25 115 b0.9 0.21 0.10 258 55 b b b b b b 0.23 0.0004

51.50° 11.95° 8.2 15 7.5 140 1.5 4.9 5.2 291 25 b 0.25 174 b 0.9 0.15 0.06 145 45 b b b b b b 0.01 0.001

51.44° 11.95° 8.5 13.7 6.9 106 1.7 3.0 3.7 307 26 b 0.25 195 b 0.9 0.16 0.02 149 49 b b b b b b b 0.001

51.43° 11.97° 7.8 14.7 7.1 110 1.1 2.5 2.6 248 22 0.37 86 b 0.9 0.14 0.86 114 34 b b b b b b 0.02 0.0007

51.72° 12.29° 7.1 12.6 8.8 150 1.8 7.6 7.9 429 6 b0.25 178 b0.9 0.11 1.88 212 31 b b b b b b 0.70 0.002

51.70° 12.29° 7.7 9.7 1 −51 0.5 2.3 2.6 3 b0.6 b0.25 17 b0.9 0.36 0.71 41 10 0.06 b b b b b 0.01 0.0005

The sites are located located in in the the Mansfeld Mansfeld region, region,Saale SaaleRiver Riverand andSpittelwasser Spittelwasserstream. stream.P1, P1,P10A P10Aand andGWM/2893 GWM/2893are arethree threegroundwater groundwaterhabitats. habitats. are given in decimal Lat Lon projection). RedoxRedox potential (Eh) is expressed in mV and is expressed Coordinates of ofthe thesites sites are given in decimal Lat (Mercator Lon (Mercator projection). potential (Eh) is expressed in conductivity mV and conductivity is b −1 b . DOC and TOC abbreviations for Dissolved and Total Organic Carbon. The analytical methods used are: aused ICP-AES, HG-ETV-AAS, in mS cm− 1in . DOCare and TOC are abbreviations for Dissolved and Total Organic Carbon. The analytical methods are: aICP-AES, HGexpressed mS cm IC ph IC ph ion chromatography, photometric. ion chromatography, photometric. ETV-AAS, b b a and CraCr were under the detection level level of theof analytical method used (b0.0005 b 0.06, respectively). Other nonThe concentrations HgHg and were under the detection the analytical method used (band 0.0005 and b 0.06, respectively). concentrationsmeasured measuredfor for detectable measurements were replaced in the table by (b). The detection werethresholds b 0.05, b 0.08, b0.07, 0.07,bb0.06, 0.04, Other non-detectable measurements were replaced inthe theless-than table by sign the less-than sign (b).thresholds The detection were b0.05, 0.08, bb0.07, and the elements Fe,for Ni,the Pb, elements Cd, Cu, ZnFe, and 0.07,b0.01 b 0.06,for b0.04, and b0.01 Ni,Mn, Pb,respectively. Cd, Cu, Zn and Mn, respectively.

by the whole community. Evenness index (E) was calculated according to Pielou (1966) as following: E = H(s) / H(max), where H(s) is the Shannon–Wiener information function and H(max) the theoretical maximum value for H(s) if all species in the sample were equally abundant. The evenness index ranges from 0 to 1. High values characterize populations with an even distribution of species; low values characterize populations dominated by only a few species. Estimates of fungal biomass were based on ergosterol measurements estimated from the leaf disks (modified from Newell et al., 1988 in Sridhar et al., 2001).

2.5.

Statistical analysis

For the interpretation of the relationship between environmental and biological data, a redundancy analysis (RDA) was carried out. RDA is a constrained ordination technique based on linear (Euclidean distance) relationships between variables, which tries to find major compositional variation within datasets by correlating ‘independent’ (explanatory) variables or constraints (i.e. environmental data) to ‘dependent’ (response) variables (i.e. community data). RDA is an enhance-

ment of the commonly applied principal component analysis (PCA) but in contrast to PCA, RDA allows a direct analysis of the biotic-environment components (ter Braak, 1994; van Wijngaarden et al., 1995). To test whether RDA analysis is appropriate for the dataset, the data were previously tested for normality (Kolmogorov– Smirnov test). Constrained eigenvector analysis was then performed to estimate the type (unimodal versus linear) of species relationship along environmental axes (for details see Lepš and Šmilauer, 2003). According to the eigenvectors analysis, a total community change along environmental vectors occurred, pointing to linear community change along the vectors (scores of the constrained eigenvalues b 2, see Lepš and Šmilauer, 2003; McCune and Grace, 2002). Analyses were performed with the statistical software package R Ver. 2.3.1 (R Develop Core Team, 2006) and the R package ‘vegan’ (Oksanen et al., 2006). Previous analysis showed that values for the single anions (except for Cl−) and cations measured converged in strength and direction. For simplification of the plot these parameters were in further analyses combined into common vectors ‘Anions’ and ‘Cations’, respectively. The same applied for

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561

Fig. 2 – Triplot of redundancy analysis (RDA) integrating fungal species, environmental variables and sites. The measured environmental variables and fungal species are shown as arrows. The vector orientations represent the direction of strongest change; vector lengths correspond to relative importance. At all sites the environmental parameters O2, temperature, pH, redox potential (Eh), DOC, TOC, conductivity and concentration of various anions and cations were measured (see Table 1 for details; black arrows). The sites (black dots with labels in framed boxes) are placed as perpendicular projections of the variable vectors according to the environmental conditions measured at each site. The distribution and direction of strongest abundance changes for fungal species in response to the environment are shown by the corresponding species vectors (grey arrows). In the RDA analysis, a positive correlation between two environmental factors is expressed by relatively long vectors roughly pointing into the same direction, whereas a negative correlation is indicated by arrows pointing into opposite directions. The longer the environmental cline, the stronger is the relationship of that parameter with the community. Perpendicular arrows indicate that there is no correlation.

vectors TOC and DOC, which were regrouped into the vector ‘TOC–DOC’.

3.

Results

3.1.

Abiotic environment

The pH values at all sites ranged from neutral (pH 7) to slightly basic (pH 8.5). Concentrations of dissolved oxygen at all sites fluctuated between 1 and 8.9 mg l− 1. The lowest values were

measured in the groundwaters at sites GWM/2893 (1 mg l− 1), P1 (2.5 mg l− 1) and P10A (4.6 mg l− 1). In surface waters, dissolved oxygen concentrations ranged from 6.9 (UHH8) to 8.9 mg l− 1 (H4). In agreement with the O2 concentrations, the redox potential values (Eh) ranged from − 51 mV in the groundwater well GWM/2893 to 340 mV in the surface water from site H4. GWM/2893 had a negative value, indicating the absence of oxygen and a prevailing reducing environment. Redox potential correlated significantly with the measurements of organic carbon (DOC, TOC). The samples showed high variations in DOC and TOC contents regardless of their

562

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origin from either surface or groundwater samples. DOC values ranged from 2 to 14.2 mg C L− 1 in surface waters and from 2.5 to 12.5 mg C L− 1 in groundwaters (Table 1). Conductivities were generally elevated. On average, the concentration of anions in the Mansfeld region waters was much higher than at the other sites. An exceptionally high concentration of sulphate (3320 mg l− 1) was measured at site H4. Additionally, the three samples taken in the Mansfeld region were characterized by very high concentrations of nitrate (H4 = 149 mg l− 1, H8 = 62 mg l− 1, P1 = 69 mg l− 1). Concentrations of all other anions were more or less evenly distributed among all sites. The total concentrations of cations tended to be higher at all sampling sites in the Mansfeld region. The surface water at H4 had the highest concentrations of the elements Ni, Pb, Cd, Cu. Copper was also detected at H8, but only at low concentrations. Zinc was detected only in the Mansfeld region and varied by several orders of magnitude between the sites. The highest concentration (1230 mg l− 1) was measured at H4 and correspond the element Zn. Elevated concentrations of manganese were measured in the water surface sites at H4, UHH2 and SpWFL. All water surface sites from the Mansfeld region (H4, H8, H9) also had slightly elevated arsenic concentrations.

3.2.

Fungal diversity and biomass

After two weeks of immersion, the species richness of aquatic hyphomycetes ranged from 1 to 13 (Table 2). The harsh habitats (H4, P1, P10A, GWM/2893 and UHH5) were characterized by low species diversity and by high evenness indices.

However, sites UHH5 and H4 showed intermediate fungal diversity (9 and 6 species respectively) and the evenness index measured in UHH5 (0.34) was in the range of evenness indices measured in moderately polluted sites (0.15–0.42). Interestingly, both sites H4 and UHH5 had equally low ergosterol contents (0.03 μg per mg dry leaves). The lowest numbers of species were recorded in groundwaters, corresponding to 1, 3 and 4 species at P1, P10A and GWM/2893, respectively (Table 2). The surface water sites H4, H8, UHH2 and UHH5 had intermediate species richness ranging from 5 to 9 species. The highest fungal diversities (N10 species detected) were found in the Mansfeld region at site H9, in the Saale River at sites UHH8 and UHH9 and in the Spittelwasser stream (SpWFL). At the water surface sites, the average evenness of 0.31 (ranging from 0.15 to 0.63) was low. This indicates that relative contribution of aquatic hyphomycete species to the total spore production was unequalled and thus that fungal communities were dominated by few species. We identified the following species as major conidium producers Tetracladium marchalianum, Heliscus lugdunensis, Aguillospora longissima, Tricladium angulatum. These species contributed for 88 to 100% of the total number of spore production at all habitats, except at UHH5 where they represented only 38%. Groundwaters, H4 and UHH5 had the highest evenness indices indicating that their communities had less dominant species than those of the other habitats (evenness indices ranged from 0.34 to 0.83 and from 0.15 to 0.29 respectively). The leaf ergosterol content varied from 0.03 to 0.2 μg per mg dry leaves. The ergosterol content measured in harsh habitats (H4, UHH5, P1, P10A and GWM/2893) was lower than the leaf

Table 2 – Description of aquatic hyphomycete communities on alder leaves after 2 weeks of exposure in polluted groundwaters and surface waters in Central Germany Mansfeld Region H4 Tetracladium marchalianum (De Wild.) Heliscus lugdunensis (Sacc. et Thérry) Anguillospora longissima (Sacc. et Syd.) Tricladium angulatum (De Wild.) Cylindrocarpon sp. Tetracladium setigerum (Grove) Clavariopsis aquatica (De Wild.) Lemonniera terrestris (Tubaki) Alatospora accuminata (Ingold) Alatospora flagellata (Gönzöl Marvanova) Lemonniera aquatica (De Wild.) Flagellospora curvula (Ingold) Tumularia aquatica (Ingold) Clavatospora longibrachiata (Ingold) Lemonniera centrosphaera (Marvanová) Total number of conidia Ergosterol (SDEV) Species richness Evenness

23 21.4 46.7 4

H8

H9

42.4 26.6 0.001 30.8 0.1 0.03

85.35 11.8 1.9 0.01 0.9 0.03

P1 100

Saale River P10A

UHH2

UHH5

10.3 27.6 62.1

85.2 7.6 4.1 2.5 0.1 0.4

27.1 5.5 5.3 0.01 0.1

3.3

1.6 58.7

0.01 0.002 0.002 0.002

1.6

0.1 1.6

0.001

UHH8

UHH9

75.5 14.9 2.9 3 0.002 0.1 1.5 0.8 0.9 0.3 0.002 0.1

13.4 74.6 4.8 0.1

0.01

1.22 0.03 (0.003) 6 0.63

1626 0.12 (0.02) 7 0.42

0.002 1766 0.20 (0.01) 11 0.15

0.01 0.03 (0.01) 1 –

0.58 0.06 (0.01) 3 0.80

1205 0.10 (0.005) 7 0.26

176 0.03 (0.005) 9 0.34

Spittelwasser stream

1133 0.15 (0.03) 12 0.20

0.01 2.5 1.6 0.003 0.002 1 2 0.01 0.002 2670 0.20 (0.04) 13 0.19

SpWFL 4.3 46 38 0.01 0.01

GWM/2893 8.3 25 50 16.7

2.2 9.4 0.01 0.01 0.04 0.01

717 0.10 (0.02) 11 0.29

0.24 0.08 (0.02) 4 0.83

The table shows the average percentage contribution of the individual aquatic hyphomycete species to the total number of conidia (per mg leaf dry mass). Ergosterol is expressed in μg per mg dry leaves and the standard deviation based on 5 replicates is shown in parenthesis (SDEV). The evenness index was calculated according to Pielou (1966).

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ergosterol content measured at all the other sites (0.03 to 0.08 versus 0.10 to 0.20, respectively).

3.3. Matching fungal communities and environmental variables The outcome of the RDA analysis is given as a triplot containing environmental measurements, fungal species and sites (Fig. 2). The RDA showed that 86.2% of the overall variability was explained by the first two axes, while the remaining contributions of all other axes contributed only to the explanation of 3.2% of the variance. The part of the unconstrained scores (unexplained part of the variations) remained at 10.7%. The RDA plot revealed two main radiating directions (or environmental clines) (Fig. 2). Conductivity, anions, cations, oxygen and temperature formed the first cline, with conductivity, anions and cations pointing to a direction opposed to vectors for O2 concentration and temperature. This indicates a negative correlation between these two groups of parameters. The second grouping was made up of the parameters TOC/DOC, Cl− and Eh (Fig. 2), all pointing to the same direction (i.e. they are positively correlated). The highest correlations were observed between anions and cations (r = 0.99), and anions/cations and conductivity (r = 0.92 and r = 0.96, respectively). Strong relationship between the amount of DOC–TOC and Eh could be also detected (r = 0.93). The concentrations of O2 and temperature were negatively correlated to the amounts of anions/cations (r = − 0.65) and shared no relationship to DOC–TOC contents in the samples. Most sampling sites were distributed along the first radiating line spanned by the parameters O2, temperature, cations and anions and their effect on conductivity. The sites H4, P1, P10A and GWM/2893 group together and were characterized by either low temperatures and oxygen content (P1, P10A, GWM/2893) or by a high ion content (H4, P1, P10A) and intermediate to high DOC–TOC values. A second group, made up of H8, UHH8, UHH2 and H9, was characterized by low anion/cation and DOC–TOC concentrations, as well as relatively high water temperature and oxygen contents. Two sampling sites, H9 and UHH9 were clearly distinguished from the general pattern (Fig. 2). These habitats were characterized by the lowest DOC–TOC concentrations and conductivity. The RDA showed that aquatic hyphomycetes species were distributed in two groups positioned on the two environmental clines, and that species abundances follow either the first or the second axis (Fig. 2). The separation occurred mostly according to the parameters DOC, TOC, chloride and Eh. The first group (T. marchalianum, Cylindrocarpon sp., T. angulatum, Tetracladium setigerum, Lemonniera centrosphaera, Alatospora flagellata and Alatospora accuminata) was composed of species that were uncorrelated to the parameters organic carbon (DOC–TOC), chloride and Eh (Fig. 2), whereas a second group (Anguillospora longissima, Clavatospora longibrachiata, Clavariopsis aquatica, Flagellospora curvula, H. lugdunensis, Tumularia aquatica and Lemonniera aquatica) was positioned on the opposite direction of the gradient, and was thus strongly negatively correlated to these parameters.

4.

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Discussion

At the investigated sites, the pollution was mainly caused by increased concentrations of sulphate and heavy metals (Table 1). High concentrations of sulphate are often associated with industrial wastewater input, which is probably the case for sites at the River Saale and Spittelwasser stream. In the Mansfeld district, high concentrations of sulphate near the mining area (e.g. sites H4, P1, P10A) may have resulted from the oxidation of sulphidic mining residues (Strauch et al., 2001), whereas the major source for additional sulphate present in the region (H8, H9) may result from the dissolution of gypsum and anhydrite (Strauch et al., 2001). In moderately polluted habitats, nutrient enrichment has been found to accelerate leaf decomposition by aquatic hyphomycetes (Webster and Benfield, 1986; Gulis and Suberkropp, 2003; Pascoal et al., 2001; Pascoal and Cássio, 2004; Sridhar and Bärlocher, 2000). In our study, the maximal concentrations of ammonium and nitrate measured at H4 were respectively about five- and sixty times higher than in Pascoal and Cássio (2004) and Pascoal et al. (2003, 2005b). Consequently fungal biomass and sporulation rate were clearly inhibited in surface water sites H4, H8, UHH2 and SpWFL compared to the nutrient-poor sites H9 and UHH9 (Table 2), suggesting that the positive role of nutrients on fungal growth might be true up to a certain threshold, beyond which biological activity might be inhibited. The diversity of aquatic hyphomycetes was similar to the diversity usually reported for alder leaves in these habitats (Sridhar et al., 2001; Krauss et al., 2005b). Although the fungal biomass measured at the least polluted site H9 was comparable to that measured in small first-order streams in Canada (Nikolcheva et al., 2003), the corresponding fungal diversity detected was lower compared to that reported at other polluted habitats in Portugal (20–25 species, (Pascoal et al., 2003; Pascoal and Cássio, 2004) and other regions (see Krauss et al., 2005a for a review). This discrepancy might be due to the generally better environmental conditions prevailing in Portuguese streams and rivers that may have ensured higher fungal diversity, but it also points out the need to include reference sites (i.e. sites showing no pollution) in the future. Additionally, at the most impacted sites a significant reduction in fungal biomass and in community structure (i.e. an increase in community evenness) was detected (Table 2). From these observations, we propose that estimate the fungal diversity alone (i.e. as species number) is not sufficient to identify harsh habitats. Measurement of fungal biomass coupled with other diversity indicators taking into account the community structure (e.g. evenness indices) appears to be better for evaluating the degree of stress present in a habitat. The RDA analysis explained 86.2% of the total variation. Although quite different types of habitats (surface water versus groundwater) have been integrated, the RDA did not group the sites according to their geographical or habitat origins (Fig. 2), indicating that this variety of ecosystems did not interfere with the analysis. The general pattern was: the groundwater habitats grouped together with the highly polluted surface water site H4 and the site UHH5 from the Saale River (Fig. 2). The grouping of these sites together can be

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explained by the influence of multiple factors acting on fungal communities like the high level of metals (particularly at H4) or by the low oxygen concentrations measured in groundwaters. In the case of UHH5, located in a side arm of the River Saale, a reduced current velocity combined with sedimentation and low oxygen concentration might be the responsible factors acting on fungal communities like recently shown in Portugal by Pascoal and Cássio (2004) and Pascoal et al. (2005a). Thus, the result of the RDA supports the contention that despite of the different type of stressors (high metal concentrations in the Mansfeld region, low oxygen content in the groundwater systems or low current velocity at the site UHH5 on the Saale River), harsh habitats have similar effects on the community composition of aquatic hyphomycetes. Aquatic hyphomycetes live preferentially in clean and well aerated water habitats (Bärlocher, 1992, 2005). These results were in agreement with the RDA analysis, which showed that aquatic hyphomycetes were generally negatively correlated with the amount of nutrients in the water (anions, cations, conductivity, DOC, TOC) but positively correlated to the concentration of oxygen (Fig. 2). However, these fungi can be associated with high metal and nutrient concentrations (Sridhar et al., 2000; Krauss et al., 2001, 2003b; Pascoal et al., 2003; Pascoal and Cássio, 2004), but no clear preferences of these fungi for particular ecological conditions have been demonstrated up to now. In our study the redundancy analysis clearly separated the aquatic hyphomycete species in two groups (Fig. 2). This clear separation might indicate preferred ecological characteristics of certain aquatic hyphomycete species according to the redox potential and concentrations of chloride and dissolved and total organic carbon in the water (Fig. 2). A first group of species (T. marchalianum, Cylindrocarpon sp, T. angulatum, T. setigerum, L. centrosphaera, A. flagellata, A. accuminata) were not influenced by these parameters, suggesting that this first group of species might represent more ubiquitous fungi, which tolerate a broader range of ecological conditions, like higher concentrations in chloride, anoxic conditions and lower specificity for particular carbon sources. The second group of fungi, made up of the top conidium producers H. lugdunensis and A. longissiama, as well as less abundant species (C. longibrachiata, C. aquatica, F. curvula, T. aquatica and L. aquatica) was clearly negatively correlated to these environmental factors. This result might indicate a higher specificity of these fungi for some carbon sources (e.g. leaf litter) or a preference for water containing less organic matter. However, the concentrations of organic matter measured in situ were rather low (from 2 to 14.2 mg l− 1, Table 1), which did not fully support this hypothesis. In our study, organic matter was estimated by measurements of DOC and TOC, parameters which comprise both natural organic matter as well as organic pollutants. Although acute toxicity of xenobiotic pollutants is uncommon, exposure to small pollutant concentrations might cause disturbance in reproduction and physiology to a wide range of organisms leading to a reduction of their competitive abilities (Moriarty, 1999). We suggest that in the future work the separation between the two groups of fungi observed in the RDA should be addressed from the viewpoint of different capabilities of certain aquatic hyphomycetes to tolerate xenobiotic pollutants. It might turn out that species like the top conidium producers H. lugdunensis

and A. longissima represent excellent candidates for indicating minute changes in the composition of the organic inventory including pollutants in freshwater. To date, the assessment of stream quality has been based on the presence of bioindicator groups, such as diatoms, macroinvertebrates and fishes (Ector and Rimet, 2005; Hering et al., 2006). Previous studies already mentioned the potential use of certain hyphomycetes (e.g. H. lugdunensis) and mosses for the biomonitoring of heavy metals in aquatic habitats (Jaeckel et al., 2005; Bleuel et al., 2005, respectively). A future application of aquatic hyphomycetes as indicators for pollution is further supported by recent studies (Pascoal et al., 2005b; Gulis et al., 2006), showing that leaf litter decomposition by aquatic fungi and invertebrates was sensitive to the levels of nutrient loads. However, as aquatic hyphomycetes undergo seasonal fluctuations (Nikolcheva and Bärlocher, 2005) this has to be taken into account when using these fungi as bioindicators. Finally, further laboratory experiments are needed, in which the response of various attributes of the individual aquatic hyphomycetes (e.g., productivity, composition, distribution) to different concentrations and organic carbon sources, including organic pollutants, are measured under controlled conditions.

Acknowledgments This work was supported by the DFG graduate college: “Adaptive physiological and biochemical reactions to ecologically important substances” at the Martin-Luther-University Halle-Wittenberg (Germany). K.R. Sridhar is indebted to Mangalore University for permission to carry out this study in Germany and to UFZ Leipzig-Halle for a fellowship. We also thank I. Volkmann, J. Steffen, B. Krause and C. Ludwig for the excellent technical support and Dr. K.E.C. Smith for kindly accepting to revise the English of this manuscript.

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