Soil formation and initial microbiological activity on a foreland of an Arctic glacier (SW Svalbard)

Applied Soil Ecology 114 (2017) 34–44

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Soil formation and initial microbiological activity on a foreland of an Arctic glacier (SW Svalbard) Dorota Górniaka,* , Henryk Marszałekb , Monika Kwa
sniak-Kominekc , Grzegorz Rzepac , Maciej Maneckic a Department of Microbiology, Faculty of Biology and Biotechnology, University of Warmia and Mazury in Olsztyn,Oczapowskiego St. 1a, 10-917 Olsztyn, Poland b Department of Applied Hydrogeology, Institute of Geological Sciences, Wrocław University, M. Borna Sq. 9, 50-204 Wrocław, Poland, c Department of Mineralogy, Petrography and Geochemistry, Faculty of Geology, Geophysics and Environmental Protection, AGH University of Science and Technology, A. Mickiewicz Av. 30, 30-059, Kraków, Poland

A R T I C L E I N F O

Article history: Received 26 September 2016 Accepted 17 February 2017 Available online xxx Keywords: Soil formation Soil bacteria PCR-DGGE Arctic

A B S T R A C T

The initial microbiological activity on the forefield of the continuously retreating Werenskiold glacier (West Spitsbergen) along the chronosequence was investigated using both culture-dependent and culture-independent approaches. The prokaryotic cell parameters: total cell number (TCN g
1 d.w.), biomass (mg C g
1 d.w.), average cell volume (ACV, mm3), morphological structure (% cocci, rods, curved cells in TCN) and the contribution of viable cells with intact membrane (% in TCN) were established. The number of opportunistic bacteria (CFU g
1 d.w.) was counted using plate culture methodology. The PCRDGGE of amplified 16S rRNA gene fragments and sequencing were also used to analyse the total (native soil samples) and culturable (plate wash samples) bacterial community structure. A total of 33 partial 16S rRNA gene sequences were obtained from the excised DGGE bands, with the majority of the sequences closely related to Actinobacteria, Bacteroidetes, and Proteobacteria (b and g ) groups. A high proportion of cultured and uncultured Arthrobacter in the studied glacier foreland soil confirms their role in the initiation of soil formation processes. Changes in the structure of both the native soil samples and wash plate samples communities along the chronosequence indicated their participation in young soil formation. Although initial microbial activity is closely associated with a higher proportion of noncultivated bacteria, less numerous cultivated bacterial strains also feature significantly in the biodiversity. The main factors positively affecting TCN, BB, CFU, and the contribution of viable cells were water, nitrogen, carbon and organic matter content in the soil. In our study we have shown that a large share of the finest-particle-size fractions in the soil (dust, clay) negatively affects the BB and CFU. The native soil samples number of operational taxonomic units (OTUs) was mostly dependent on the pore water composition, and the C:N ratio in the soil, the wash plate samples number of OTUs was mostly connected with organic matter and soil water content. © 2017 Elsevier B.V. All rights reserved.

1. Introduction One of the effects of global climate change and the rapid warming of the atmosphere is glacier retreat. A continuous and relatively rapid reduction of glacier mass has been observed worldwide. These changes are particularly visible in the Arctic,

* Corresponding author. E-mail addresses: [email protected] (D. Górniak), [email protected] (H. Marszałek), [email protected] (M. Kwa
sniak-Kominek), [email protected] (G. Rzepa), [email protected] (M. Manecki). http://dx.doi.org/10.1016/j.apsoil.2017.02.017 0929-1393/© 2017 Elsevier B.V. All rights reserved.

where the annual average temperature over the last 100 years has almost doubled compared to the average value in the world (Bernstein et al., 2007; https://nsidc.org/cryosphere/arctic-meteorology). Temperatures at the top of the permafrost layer have generally increased since the 1980s in the Arctic by up to 3  C (Jania and Hagen 1996). The period of 1995–2005 was the warmest decade in the Arctic since at least the 17th century, with temperatures 2  C above the 1951–1990 average (Przybylak 2007). This resulted in an increase in characterizing the biogeochemical development of glacier forelands using a chronosequence approach (Sigler and Zeyer 2002; Noll and Wellinger 2008; Schütte et al., 2009; Mavris et al., 2010; Schütte et al., 2010;

D. Górniak et al. / Applied Soil Ecology 114 (2017) 34–44

Knelman et al., 2014). The forefields of retreating glaciers are extremely heterogeneous in terms of physical landforms, soil structure and environmental conditions, each of which directly impact the composition, activity and function of the microbial community (Sigler et al., 2002; Schütte et al., 2010; Wu et al., 2012; Bradley et al., 2015). The forefields close to the glacier terminus are initially vegetation free, consisting mainly of rock material with high fractions of silt-sized grains with low C and N content and only small amounts of available nutrients (Edwards et al., 2006). Recently uncovered glacigenic sediments and regolith in the foreland of this retreating glaciers have become exposed to existent atmospheric conditions and undergone rapid weathering (Anderson et al., 1997; Hodkinson et al., 2002; Anderson, 2007). Microbial communities stabilize soils and shape the physical and biological development of post-glacial soil ecosystems (Dietrich and Perron 2006). The primary factors affecting the initial steps of soil formation in extremely arid environments, such as glacier forefields are the availability of water, bedrock lithology/ mineralogy, solute composition, nutrient sources, temperature, and time since exposure that limits growth of organisms and are unique to each environment (Sundareshwar et al., 2003; Skidmore et al., 2005; Yoshitake et al., 2007). Primary succession after glacier retreat has been widely studied in plant communities, but bacterial succession requires a closer study. Soil development along glacial chronosequences has often been correlated with the primary succession of soil microorganisms capable of biological weathering (Sigler et al., 2002; Yoshitake et al., 2007; Nemergut et al., 2007). It is recognized that soil establishment is strongly accelerated under plant roots during their primary colonization of rock substrates, but still little is known about how microbiological weathering affects soil ecosystem development before the colonization of the plant. The weathering rates, soil composition, and chemical evolution of glacier melt-waters along glacial chronosequences have been intensively studied in recent years (Bernasconi et al., 2008; Dümig et al., 2011; Montross et al., 2013; Kazemi et al., 2016; Kim et al., 2016). As described, in the early stages of the soil formation, mineral weathering is a key process (Anderson et al., 2000; Mavris et al., 2010). However, microbially-promoted mineral weathering may have greater importance than previously thought. It is known that in nutrient poor oligotrophic environments, mineral weathering initiated by microorganisms may be significant (Banfield et al., 1999; Bennett et al., 2001; Welch et al., 2002; Uroz et al., 2009; Frey et al., 2010; Dahms et al., 2012; Montross et al., 2013; Knelman et al., 2014; Bradley et al., 2015; Kazemi et al., 2016). Dominant processes in the early stages of alteration of rock and glacial sediment in polar climate weathering are the dissolution of carbonates and oxidation of sulphides (Anderson et al., 1997; Anderson et al., 2000; Bukowska-Jania 2007; Kabała and Zapart, 2009). At more mature stages, after most carbonate and sulphide are leached from the soils, silicate dissolution and transformation become important (Taylor and Blum 1995; Anderson et al., 1997; Anderson et al., 2000). While initial stages are dominated by dissolution and removal, more advanced weathering is characterized by crystallization of secondary phases. The significant role of microbes in mediating dissolution and oxidation of minerals in glacial sediments where liquid water is present is still under investigation (Sharp et al., 1999; Skidmore et al., 2000; Tranter et al., 2002; Skidmore et al., 2005; Wadham et al., 2007). To date, many hydrochemical studies have concentrated solely on the evolution of surface waters or bulk composition of the soils. Soil development along glacial chronosequences has often been correlated with primary successional changes in bacterial community composition (Sigler et al., 2002; Yoshitake et al., 2007; Nemergut et al., 2007). Soil microbes play an essential role in the newly-formed environment by contributing to the release of key nutrients from primary minerals required not

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only for their own nutrition, but also for that of plants (Hodkinson et al., 2003). As has been shown deglaciation time and environmental factors (i.e. pH and soil temperature) play key roles in structuring bacterial communities and soil bacterial groups with different ecological strategies occur in different stages of succession in glacier foreland (Kim et al., 2016). Nutrient colimitation is also an important control on microbial primary succession in glacier forefield (Knelman et al., 2014). As shown by Sigler et al. (2002) bacterial succession in the glacier forefield is a dynamic process with adaptation to the differing stages of succession occurring on both the individual and community levels. Nevertheless, the knowledge of microbial community composition and activity relevant to soil establishment in the newly-forming polar soils is still limited and requires in-depth research. A good area for this study is Werenskiold glacier, located in the south-western part of Spitsbergen, which has been retreating since the beginning of the twentieth century with an average velocity of 25 m/year (Bukowska-Jania 2003). In this paper, our principal objective was to characterize microbial abundance, viability, opportunistic growth dynamics and bacterial community diversity with respect to the glacier foreland environment, focusing on initial microbiological activity and soil formation. The aim of this study is to investigate soil composition impact on bacterial communities at sites with different stages of rock weathering. We hypothesized that microbial community is an important contributor to the solute flux from glaciers, and while highly specialised uncultivated bacteria generally dominate early stages of soil formation, their contribution decreases with soil age. This knowledge will enable appreciation of the mechanisms involved in the formation of initial glacial soils in the arctic climate. 2. Materials and methods 2.1. Study area Werenskiold glacier is located in Wedel Jarlsberg Land near the south-western coast of West Spitsbergen. It is a polythermal glacier which terminates on land covering an area of 27 km2. The area is under the influence of a sub-oceanic arctic climate with an  average annual temperature of
4.4 C and precipitation of
ska, 2007). Soils currently forming 430 mm (Marsz and Styczyn in the forefield of Werenskiold glacier are in the initial stage of development. According to Skiba et al. (2002) these soils have poorly-developed horizons due to excessive frost-induced mixing of the surface layer and low intensity of mineral weathering. The till, in most cases, is structureless in a pedological sense and is often greenish-grey and gleyed due to continuous saturation with water (Kabała and Zapart, 2009). The rocks exposed by Werenskiold glacier include polymetamorphic metasediments and metavolcanics, mostly phyllites, carbonate-mica schists, chlorite schists, conglomerates, amphibolites, greenschists and marbles (Czerny et al., 1993). They contain sulphites (mostly pyrite, locally Cu, Pb and Zn sulphites) as well as carbonate minerals, including
ski calcite, dolomite, ankerite and siderite (Kieres and Piestrzyn 1992; Czerny et al., 1992). The methodology of soil characteristics and soil water analysis is described in details in Kwa
sniak-Kominek et al. (2016). 2.2. Sample collection Soil samples were taken twice in the middle of August 2010 and 2011 along the chronosequence of the Werenskiold glacier foreland. Four sampling points in a transect parallel to the forefield were established beginning at the glacier terminus. The total time period covered was 150 years, with sites 1–4 uncovered

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5, 35, 70, and 150 years after glacier retreat, respectively. Approximately 0.5-kg of soil was collected from each of the four sites along a transect by pooling at least five sub-samples harvested within a 10 m diameter circle surrounding the given sampling point (Fig. 1). To avoid vertical heterogeneity imparted by soil horizon development, only surface soils to a depth of approximately 5 cm were harvested. Larger gravel was removed before samples were taken. A total of 20 samples were collected, placed in sterile plastic bags and kept on ice during transport. The soils were processed within 2 h upon return to the field laboratory. Cultivation technique and samples preparation for microscopic examination (fluorescent staining and deposition prokaryotic cells on the membranes by vacuum filtration) were performed in the field laboratory. After filtration, the membrane was dried in the dark and mounted on slides and was then frozen at
20  C until microscopic analysis. Soil for molecular investigation was stored for two weeks at
20  C until analysed. 2.3. Total direct counts and measuring The total cell number (TCN) in the soil samples was estimated using direct epifluorescent filter technique. The average values of three measurements using three independently prepared filters were calculated. The number of bacterial cells was counted in soil suspension (water:soil 100:1 v/w) shaken gently at 120 rpm for 10 min in 10  C and then stored at the same temperature for 10– 20 min to allow larger particles to settle. Sub-samples were fixed with buffered formalin to a final concentration of 1%. Fluorescent

staining was performed according to Bloem et al. (1999). Subsamples were stained with DAPI (40 6-diamidino-2-phenolindole to a final concentration of 1 mg ml
1) and filtered through 0.2-mm pore-size black polycarbonate membrane filters (Millipore GTBP). Stained bacterial cells in at least 20 images of each filter were counted and measured by the automated image analysis system. Microscopic analysis was effected using an epifluorescence microscope (Olympus BX41) equipped with highly sensitive digital camera (Nikon DS-Fi1c) linked to a PC computer with scanning software NIS-Elements F 3.0 and MultiScan v. 14.02 (CSS). Images of stained cells were taken and processed by the image analysis software. The total count was expressed as the number of cells per gram of dry soil weight (dry weight
d. w.). Cell volume and total bacterial biomass were evaluated through
˛tecki, 1997). The volume image analysis (Sieracki et al., 1985; Swia of each cell was calculated from its length and width, assuming a spherical shape for cocci and a cylindrical shape for rods and filamentous cells, as follows: V = (P/4) x W2 x (L-W/3), where V is the cell volume, W is the cell width, and L is the cell length (Bratbak 1985). Cell volumes were converted to bacterial carbon content using the equation given by Norland (1993). Biomass (mg C g
1 d. w.) was calculated from the cell carbon content and number of cells. Average cell volume (ACV) was calculated by multiplying the number of cells by the cell volume. A cell morphotype diversity analysis describing the frequency of morphological forms of bacteria in soil samples was performed based on cell shape: cocci, rods and curved forms (Nübel et al., 1999).

Fig. 1. Locations of the sample sites at the foreland of Werenskiold glacier (1–3) and at Hyttevika (4), North-West of Hornsund (the map after Karczewski et al., 1984 and Pulina et al., 2003).

D. Górniak et al. / Applied Soil Ecology 114 (2017) 34–44

2.4. Percentage contribution of viable cells with intact membrane (Live/Dead) A Live/Dead BacLight Bacterial Viability Kit (L-7012, Invitrogen, Life Technologies, UK) was used to estimate the number of cells with intact membranes (Quéric et al., 2004). The assay consists of mixtures of SYTO 9 green-fluorescent nucleic acid stain and the red-fluorescent nucleic acid stain, propidium iodide. With an appropriate mixture of the SYTO 9 and propidium iodide, bacteria with intact cell membranes stain fluorescent green, whereas bacteria with damaged membranes stain fluorescent red. Samples taken directly from soil were decimally diluted in 50 mM K2HPO4 and 0.03% sodium pyrophosphate (NaPPi) and gently mixed by vortexing. Suspensions were then stored for 10 min at 10  C to allow larger particles to settle. The staining procedure was processed immediately without prior preservation in triplicate (Schumann et al., 2003). A mixture of two BacLight Kit’s stains was added to 250 ml sub-samples (with stains in 1:1 ratio, and a final concentration of 0.15%). The treated sub-samples were then incubated for 15 min at 10  C in the dark, filtered through 0.2 mm pore-size, black polycarbonate membrane filters (Millipore GTBP) and enumerated by epifluorescence microscopy. The BacLight mounting oil, which is part of the viability kit, was used as mounting solution because standard immersion oils may permeabilise cells on the filter. For all other stains, Citifluor AF1 (Citifluor, UK) was used as the embedding medium. The percentage of alive cells was calculated as the ratio of alive cells to the sum of alive and dead prokaryotic cells. 2.5. Plate culture, colony forming units count, and plate wash samples The number of culturable bacteria (CFU) was counted by the plate culture method. Each 1 g wet weight soil sample was dispersed in 9 ml of sterile saline (0.85%) and subjected to shaking for 2 h at 10  C. Suspensions were then stored at that temperature for 15 min to allow larger particles to settle. The obtained soil solutions were decimally diluted to 10
4 and 100 ml and then plated on medium [soil extract, prepared by autoclaving 200 g of each soil samples in 1 l water (Zdanowski et al., 2005), peptone (0.5%, w/v), yeast extract (0.2%, w/ v), agar (2%, w/v), pH depending on the station], in five replicates each. Plates containing between 30 and 300 colonies of bacteria were counted following 12 days of growth in the dark at 10  C. The number of opportunistic bacteria in soil samples was calculated from the number of colonies as colony forming units (CFU). Then bacterial colonies were washed from the plates and bacterial DNA was extracted for PCR-DGGE analyse. Wash plate samples (WPS) were prepared as follows: five ml of sterile 1xPBS buffer was poured onto the agar plate and all colonies were scraped from the surface of the medium with a disposable inoculating needle. 2.6. Extraction of total DNA and PCR amplification of 16S rRNA gene Total DNA from soil samples was extracted using 10 g wet weight and MegaSoil DNA isolation Kit (MoBio, Carlsbad, CA) in accordance with the manufacturer’s protocol. Culturable bacterial DNA from 200 ml wash plate sample suspensions were extracted by DNeasy Blood and Tissue Kit (Qiagen, Germany) using the protocol for gram-positive bacteria. DNA quality and yield were measured with a NanoVueTM spectrophotometer (GE Healthcare Life Science, Germany). The extracted DNA was stored at
20  C for further use. 2.7. Denaturing gradient gel electrophoresis (DGGE) Bacterial populations were distinguished by community similarity using DGGE analysis and electrophoresis was performed

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with a D-Code Universal Mutation Detection System (BioRad Laboratories, USA). The detailed procedure was described in an earlier paper (Zdanowski et al., 2013). The primers used were 341f with a GC clamp (bold) 50 -GCCCTACGGGAGGCAGCAG-30 and 907r 50 -CCGTCAATTCMTTTGAGTTT-30 (Muyzer et al., 1993; Muyzer et al., 1998). The PCR products were loaded in 6% acrylamide gel with a denaturing gradient of 35–70% (where 100% denaturant is 7 M urea and 40% formamide). The gels were run at 60 V for 17 h at 60  C. The products of electrophoreses were stained by gently agitating the gel for 30 min in 100 ml of 1  TAE containing 5 ml 1:10,000 dilution of SYBR Gold nucleic acid stain (Invitrogen, Life Technologies, UK) in DMSO. DGGE banding patterns were visualized with UV transillumination and photographed using the Gel Doc 2000 gel documentation system (BioRad Laboratories, USA). At least three DGGE profile-replicates per each sample was run. DGGE bands from both culture-based and culture-independent approaches were compared and well-defined were sequenced. 2.8. Sequencing of DGGE bands Well-defined bands in the DGGE were excised using a flamesterilized scalpel blade. DNA was eluted from the gel in a 1.5 ml tube containing 100 ml sterile PCR water by heating briefly (30s) in a microwave oven and then stored at 4  C overnight before reamplification. The positions of the excised bands in DGGE gel were confirmed with repeated DGGE. Bands showing the expected melting position were amplified with the primers without GCclamp (341f, 907r). The PCR products were purified using a CleanUp PCR Product Purification Kit (A&A Biotechnology, Poland), dissolved in 25 ml of sterile water and sequenced with DYEnamic ET Terminator Cycle Sequencing Kit (GE Healthcare Life Science). Taxonomic identities of the partial 16S rRNA gene sequences or complete genome were obtained using the BioEdit Sequence Alignment Editor (Ibis Biosciences Carlsbad, CA), SILVA and RDP classifier search database (Wang et al., 2007; Yilmaz et al., 2014). 2.9. Statistical analysis The results were reported as averages and standard deviations over the replications described above. Statistical analysis was used to evaluate interdependences between studied microbial traits and environmental factors. Two–way ANOVA determined repetitive measurements of the microbial community parameters: abundance, biomass, viable cell number, cell volume and the biomass of the three cell fractions (rods, cocci, curved) and sampling position. Multiple stepwise regression analyses were conducted for major microbiological parameters as dependent variables, including abundance, biomass (total and for rod, coccoid, and curved cell morphologies), cell volume and viable cell number. The analysis identified the explaining variable for a model whose correlation with the explained variable was the strongest and determined a model with significant parameters. DGGE gel images were analysed using the Quantity One software on a GelDoc gel documentation system (BioRad Laboratories, USA). Gel bands were identified using GelCompar software to create a presence-absence matrix as described by Crump and Hobbie (2005). Each band represents an OTU (Operational Taxonomic Unit) of bacteria. The presence or absence of a band in each lane was converted to a binary (1 or 0) matrix to make the data accessible for statistical analysis. The similarity between the DGGE band patterns was assessed by the Dice coefficient, and clustering analysis was performed using the unweighted pair-group method and arithmetic averages (UPGMA) for dendrogram construction. Species richness was determined by

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the number of bands resolved by PCR-DGGE in one sample line. Canoco for Windows v. 4.5 software (ter Braak and Šmilauer, 2002) was applied for canonical correspondence analysis (CCA). 3. Results and discussion 3.1. Sampling sites characteristics The surface sediments and soils described at sites 1, 2 and 3 approximate the soil profiles 1, 2 and 3 characterized by Kabała and Zapart (2009). Briefly; (1) sample site 1 (closest to the glacier front) has a relatively thin (up to 50 cm) mixture of moraine till and glaciofluvial gravels and sands resting directly on bedrock schists. The sediment is saturated with melting water and is gleyed and structureless. Although organic matter accumulation is observed on some areas of the surface, vegetation is absent; (2) sample site 2 has poorly-sorted gravely till which is approximately 25% covered with lichens and mosses. An initial humic A horizon (ca. 3 cm) is observed on top of a thicker greenish-grey gleyic layer (over 50 cm) in most cases resting directly on the bedrock; (3) the much older sample site 3 is composed of cryoturbated soils developed from recent tills on buried paleosoils, with permafrost in the subsoil. Horizon A is 6–8 cm thick and an initial sub-surface B horizon is evident. While 40% of this surface supports higher plants, moss coverage is also present. This profile resembles the soils observed on the frontal moraine. Station 4 located the furthest from the head

of the glacier. Soil characteristics were angular rock debris covered with a layer of soil about 20 cm thick, peat soil with a high content of organic debris mixed with quartz sand, well-hydrated, over 80% of the vegetation cover consisting mostly of higher plants (tundra). The mineral composition of soils and sediments from sampling sites is described by Kwa
sniak-Kominek et al. (2016). Typical of moraine deposits, the sediments here are poorly sorted and consist of fragments of angular rocks, gravel, sand and clay. Similar to the results reported by Kabała and Zapart (2009), we also observed a decreasing clay fraction with increasing soil age. The content of stones and gravel accounted for 6.7–60.3% (mean 18.4  3.9), sand from 35.2 to 68.7% (mean 63.2  2.6); dust and silt from 4.5 to 25.6% (mean 18.6  1.8) (Kwa
sniak-Kominek et al., 2016). The content of organic matter at the analysed sites varied widely: 3.5% at site 1, 1.5% at site 2, 1.3% at site 3, and 43.9% at site 4 (Table 1). 3.2. Mineral composition The mineral composition of the soils and sediments is dominated by primary rock-forming minerals derived from native rocks by mechanical weathering: quartz, micas, carbonate minerals, plagioclases, amphiboles and chlorites (Table 1). Secondary kaolinite, vermiculite, illite and smectite clays were determined by X-ray diffraction only in the oldest sediment at site 3. This indicates that the fine fraction at sites 1 and 2 consists mostly of mechanically-pulverized primary minerals. The content

Table 1 Selected parameters characterizing soils at sampling sites. Data after Kabała and Zapart (2009), Kwa
sniak-Kominek et al. (2016), and based on own data and direct observations. Site 1

Site 2

Site 3

Site 4

Close to the glacier

Middle

Far from the glacier

Far from the glacier

a

5 years s. exp.

35 years s. exp.

70 years s. exp.

150 years s. exp.

Location (GPS position) Primary minerals

77 040 33.3“N 15140 05.2“E quartz, carbonate minerals, micas, feldspars, amphiboles, chlorites

77 040 37.2“N 1514015.1“E quartz, carbonate minerals, micas, feldspars, amphiboles, chlorites

77 040 34.9“N 15100 22.7“E quartz, carbonate minerals, micas, feldspars, amphiboles, chlorites

77 030 02.4“N 15 080 45.0“E mostly quartz, sparse micas, chlorites, amphiboles, epidotes, feldspars

Secondary minerals

iron (oxy)hydroxides (e.g. goethite), traces of unidentified products of Weathering

iron (oxy)hydroxides (e.g. goethite), traces of unidentified products of Weathering

iron (oxy)hydroxides (e.g. goethite) and clays (illite, kaolinite, smectite)

Soil characteristics

thin mixture of moraine till and glaciofluvial gravel and sand resting directly on bedrock schists, gleyed, nearly absent Vegetation

poorly sorted gravelly till covered in 25% with lichens and mosses, initial humic A horizon on top of gleyic layer

cryoturbated soils developed from recent tills, horizon A is 6–8 cm thick and initial subsurface B horizon may be distinguished, surface is mostly covered with moss and in up to 40% with higher plants.

angular rock debris covered with a layer of soil about 20 cm thick, peat soil with high content of organic debris mixed with quartz sand, well-hydrated, over 80% vegetation cover consisting mostly of higher plants (tundra)

Soil water content (%) Granulation (mm) Organic matter (%) N (%) C (%) Ratio (C/N)

23.0b 3.6c 0.054  2.59 3.48  0.19 0.147  0.001 1.889  0.04 12.8  0.20

10.4  1.1 0.048  3.08 1.54  0.02 0.032  0.001 1.423  0.04 44.4  0.26

13.2  0.1 0.047  1.84 1.30  0.01 0.032  0.002 1.206  0.05 37.7  3.68

38.0  2.5 not determinedd 43.87  0.04 1.627  0.072 23.473  0.97 14.4  0.04

a b c d

Since exposure. Average. Standard deviation. Due to the high content of organic matter granulation was not measured.

below detection

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of clay minerals there is below the detection limit of XRD (in this case equal to approximately 3 wt%). This is probably the effect of relatively slow transformation of primary aluminosilicate minerals into clay phases. Iron oxides and hydroxides, mostly goethite, were also noted among the secondary minerals. Progressive weathering of sulphide minerals is responsible for the presence of SO42
ion in pore waters which increases with distance from the glacier front. Carbonate minerals include a wide variety of phases, including primarily calcite, dolomite, ankerite and siderite. Since the carbonate minerals are the most soluble phases in the system, they strongly affect pore water chemistry. The carbonate content determined in soils by Kabała and Zapart (2009) using Scheibler’s gasometric method was 3.5%, between 2.6% and 5.6%, and approximately 2% CaCO3 at sites 1, 2 and 3, respectively. Bukowska-Jania (2007) also reported decreased carbonate phase content in the sediment with increased distance from the glacier. Site 4 has primary minerals, mostly quartz, sparse micas, chlorites, amphiboles, epidotes and feldspars. Secondary minerals were below detection. 3.3. Pore water composition The evolution of the chemical composition of pore waters saturating the sediments at studied sites in the Werenskiold glacier foreland was investigated by Kwa
sniak-Kominek et al. (2016). This was supplemented by water chemistry determination at Hyttevika (site 4). Table 2 summarizes the relative changes in water composition sampled at various distances from the glacier. These changes are explained by equilibration of the solution with a mineral skeleton in the processes of dissolution and crystallization of minerals, accompanied by the oxidation of certain elements; mainly Fe and S. The following systematic changes from sites 1–3 correlate with the distance from the glacier front: pH decreases from 8.6 to 7.7, mineralization expressed as total dissolved solids (TDS) increases from 123 to 748 mg L
1 while redox potential (Eh) decreases from 270 to 174 mV. Regular changes in ion concentration are also apparent. The evolution of bicarbonate HCO3
correlates with that of magnesium ion, generally confirming both results from the dissolution of carbonates. Equilibrium calculations using the PHREEQC hydrochemical model indicate that the pore water at locality 1 is close to saturation with atmospheric CO2, while localities 2, 3 and 4 are oversaturated. In addition, the increase in calcium concentration correlates with that of sulphate SO42
, and water gypsum saturation increases with soil age. Although gypsum presence was not detected, a significant concentration of Ca2+ and SO42
ions in the pore solutions may result from dissolution of secondary sulphate salts, formed on the surface by a freezing concentration in winter. Such formation of secondary sulphates on the surface of the moraine was observed

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not only in the foreland of Werenskiold glacier but also near Finsterwalder glacier (Wadham et al., 2007). 3.4. Total microbial abundance, biovolume, biomass and cell morphological structure Direct prokaryotic cell counts (TCN) along the chronosequence ranged from 6.2  107 to 2.9  109 cells g
1 d. w. Cell abundance was at its lowest level in the 35-year old soil site 2. Although the total bacteria number increased to 8.0  107 cells g
1 d. w. in the 70-year old soil, the highest number of bacteria in the glacier foreland was recorded at 1.1 108 cells g
1 d. w. in the youngest 5year-old soil near the glacier front (Table 3). However, bacterial numbers were much higher in the oldest soil at site 4, characterized by rich vegetation and relatively constant water content, than in all other sites, registering 2.9  109 cells g
1 d. w. On average, the prokaryotic cell biovolume (ACV) in the studied soils was varied depending on the station; sites 1 and 2 closest to the glacier head had ACV 0.21  0.02 and 0.30  0.02 mm3, respectively, while the oldest soils (70 and 150 years) had ACV 0.13  0.03 and 0.15  0.01 mm3 (Table 3). Although prokaryotes in oligotrophic environments usually optimise the surface area-tovolume ratio by decreasing size (Sigler et al., 2002), here, in contrast, decreases in cell volumes accompanied by older soils (70 and 150 years). As described by Bakken and Olsen (1987) in oligotrophic soils small volume of prokaryotic cells is the consequence of starvation. The authors showed that in these environments bacteria respond to nutrient input by cell enlargement, followed by size reduction, when the nutrients were exhausted. There is also a possibility that some of the very small cells in soil represent a kind of swarmer cell produced by asymmetric cell division as a survival strategy during starvation. On the forefield of rapidly retreating glaciers, as described Skidmore et al. (2005), and Stibal et al. (2008), the area closest to the glacier head is supply by nutrients and DOC of glacial origin. DOC concentrations indicating that an available organic carbon source exist in these same environments. This may explain the higher biovolume prokaryotic cells recorded at the station 1 and 2 in comparison to station 3. Bacterial biomass in terms of carbon content changed from 89.1 17.1 at site 2–120.5  22.9 mg C g
1 d. w. at site 1 and this result was similar to previous Arctic polar desert findings (Bekku et al., 2004). The site 4 bacterial carbon level was high at 663.9  39.2 mg C g
1 d. w., and thus comparable with alpine tundra (King et al., 2008). The consistently lower prokaryotic cell biomass levels in soils poorly covered by plants confirms the notion that carbon inputs from plants determine the size and activity of soil microbial communities (Bekku et al., 1999; Zdanowski et al., 2013). Glacial recession chronosequences clearly demonstrate a build-up of greater microbial biomass associated

Table 2 Selected soil pore water characteristics at studied sites. Data for sites 1–3 from (Kwa
sniak-Kominek et al., 2016) and for site 4 from (Płonka et al., 2008), ysince exposure.

pH Ca2+ (mg l
1) Mg2+ (mg l
1) Na+ (mg l
1) K+ (mg l
1) HCO3
(mg l
1) SO42
(mg l
1) Cl
(mg l
1) TDS (mg l
1) Eh (mV)

Site 1

Site 2

Site 3

Site 4

Close to the glacier

Middle

Far from the glacier

Hyttevika

5 years s. exp.y

35 years s. exp.

70 years s. exp.

150 years s. exp.

8.6 20.8 8.7 0.5 2.5 64.8 15.0 8.5 123.0 270.0

7.7 91.2 40.0 5.5 4.5 226.8 188.0 14.2 573.0 330.0

7.7 131.2 45.1 6.3 4.8 236.5 300.0 21.3 748.0 175.0

6.6 4.21 1.24 5.96 1.87 18.0 1.0 10.71 47.1 145.0

40

D. Górniak et al. / Applied Soil Ecology 114 (2017) 34–44

Table 3 Structure of microbial populations on the studied sites (DAPI and Live/Dead staining, DGGE bands), culturable bacteria, index of opportunism”, Operational Taxonomic Units (OTUs) in total soil (TSS) and wash plate samples (WPS). Site

TCNa

ACVb

Biomass

Cell morphological structure

Viable cells

CFUc

Index of ‘opportunism

OTUs

No

(g
1 d.w.)

(mm3)

(mg C g
1 d. w.)

(% in TCN)

(% in TCN)

(x105 g
1 d. w.)

(CFU/TCN ratio)

TSS/ Unique

WPS/ Unique

WPS/ TSS

Site 1 Site 2 Site 3 Site 4

1.15  108  0.33

0.21 120.5  22.9 86.3  3.8  0.02 0.30  0.02 89.1  17.1 90.4  11.2

Rods

8.62  2.97

0.0075

30/2

15/3

0.50

6.2  1.9

3.4  1.1

1.17  0.38

0.0019

36/4

8/0

0.22

0.61  0.34

0.0002

37/3

21/3

0.57

48.3  11.2 12.7  3.17

0.0004

30/1

15/3

0.50

7.96  10  1.21 0.13  0.03

91.7  12.8

82.3  16.3 5.9  1.6

2.86  109  0.66 0.15  0.01

663.9  39.2 78.5  18.9 20.5  9.4 1.0  0.3

11.2  1.3

11.8  6.4 4.6  0.9

Total Cell Number. Average Cell Volume. Culturable bacteria number (CFU), TCN, ACV, Biomass, Cell morphological structure, Viable cells, CFU data: average and standard deviation, dry weight
d. w.

with increasing soil organic matter and plant cover (Tscherko et al., 2003). However, our study indicates that bacterial total count and biomass are greater in soils near the glacier head than in the older site 2 and 3 soils on the glacier foreland (Table 3). This may result from the small, but permanent, input of dissolved organic and inorganic carbon (DOC, DIC) and nitrogen (DIN, DON) from the melt water and soluble reactive phosphorus (SRP) from the glacier (Schmidt et al., 2008; Stibal et al., 2008; Uroz et al., 2009). In our studies% organic matter, the content of C and N in the soil decreased along a chronosequence, but the ratio C:N increased. This suggests that similar relationships exist on Werenskiold glacier forefield. As described by Göransson et al. (2011) on the forefield of the Damma glacier, the availability of soil organic matter with soil age decreased and bacterial growth per unit soil carbon decreased with increasing soil development. Soil nutrient contents, rates of nitrogen fixation and microbial activity all vary with stage of soil development and, in turn, alter the microbial community structure and composition (Bradley et al., 2015). With regard to other environmental factors, a statistically significant positive relationship was established between both total cell number (TCN) and biomass (BB) and the soil water content (r = 0.89, p  0.05), organic matter content (r = 0.86, p  0.05) and a significant negative correlation was recorded between these community parameters and soil granulation at r =
0.9, (p  0.05). CCA was performed on the whole set of environmental and microbiological data. The eigenvalues for CCA axis 1 and axis 2 explained 91,43% of the variance in the microbial parameters. CCA analysis showed that in the early stages of the soil development (5 and 35 years) the microorganisms affect pH, Eh, the C:N ratio and soil granulation. ACV, % rods in the TCN and the ratio CFU:TCN remain under the influence of these factors (Fig. 2). The microbial parameters of the oldest soil (150 years) clearly were shaped by water, carbon, nitrogen and organic matter content. These factors affect the total number of cells (TCN), the percentage of viable cells in total cell number, biomass, the cultivable bacteria (CFU) and morphological structure
% cocci in TCN. In the 70-years-old soil there was a clear influence of the soil pore water composition, TDS and C:N ratio on the morphological structure of prokaryotes (especially% curved cells in the TCN). These parameters affect also the number of OTUs in TSS and unique OTUs. The number of wash plate sample OTUs showed a relationship with the water content, carbon, nitrogen and organic matter in the soil. As was demonstrated by the CCA analysis, the key factors positively affecting the bacterial biomass (BB), the total cell number (TCN), cultivable bacteria number (CFU) and living cells percentage in TCN were water, nitrogen, carbon and the organic

1.0

c

4.6  0.8 26.1  3.1

Cl-

Na+

70 years SO42- Ca2+

Axis 2 23.11%

b

7

Curved

9.1  2.2

N [%] OM [%] C [%] Soil water

TDS %Curved K+ Mg2+ WPS-Unic C/N ratio 150 years WPS HCO3TCN PWS/TSS BB TSS Sand TSS-Unic %Cocci %Rods CFU Dust ACV Viable pH Clay CFU/TCN 35 years 5 years

-1.0

a

6.22  107  1.10

Cocci

-1.5

Axis 1 68.32%

Eh

1.5

Fig. 2. Constrained ordination determined by CCA analysis of prokaryotic community structure and main soil parameters for four studied sites, i.e. 5, 35, 70 and 150 years since exposure. TCN – Total cell number, ACV – Average cell volume, CFU – Culturable bacteria number, Cell morphological structure (% in TCN): Rods, Cocci, Curved, Viable cells (% in TCN), Index of ‘opportunism’: CFU/TCN ratio, Operational Taxonomic Units (OTUs) in total soil (TSS) and wash plate samples (WPS) and WPS/TSS ratio, Soil water (%), TDS – total dissolved solids, Organic matter (LOI [%]), Nitrogen (N [%]) and Carbon content (C [%]), Ratio [C/N]. Granulation (mm): Sand 2.0–0.05; Dust 0.05– 0.002; Clay 0.002.

matter content in the soil. All these parameters showed an inverse relationship with soil granulation (dust/clay). Axes 1 and 2 represent 68.32% and 23.11% of the variation in the data, respectively (Fig. 2). Prokaryotic community of stations 1, 2 seem to form one cluster, defined mainly by the CFU/TCN ratio (index of ‘opportunism’) whereas station 4 differed greatly from younger soils. 3.5. Live cells and cultivated bacteria abundance and distribution The contribution of live cells to the TCN varied across sample sites; this was surprisingly high in the youngest soil at 26.1%, followed by 11.2%. and 4.6% for sites 3 and 2, respectively. Meanwhile, live bacteria in the oldest soil (80% covered with vegetation) registered the very high level of 48.3% (Table 3). Along the chronosequence the% of viable cells in TCN positively correlated with soil water content and negatively with the fine dust and clay fraction in the soil, at r = 0.78 and r =
0.82, (p  0.001) respectively. The percentage of viable cells in the

D. Górniak et al. / Applied Soil Ecology 114 (2017) 34–44

TCN and the CFU numbers also showed a strong relationship at r = 0.82 (p < 0.001). The higher total, viable and opportunistic cells numbers in coarse soil is likely due to the increased number of isolated water films in soils with large pores, suggesting that porescale hydrologic regime constrains bacterial abundances in soil. Thus the observed increase of bacterial biomass and viability with increasing sand and gravel content and decrease with dust/clay fraction may be a consequence of the higher number of isolated hydrated microhabitats in coarser soil (Chau et al., 2011). Cultivated bacteria counts shoved a similar trend to TCN along the chronosequence, with the highest number recorded in the freshly-exposed soil of site 1 and the lowest at site 3. A similar phenomenon was observed in the foreland of the Ecology glacier in Antarctic soils (Zdanowski et al., 2013). In comparison, a much higher number of cultured bacteria were registered in the 150year-old soil at site 4 than in the foreland soils (Table 3). Sigler et al. (2002) reported that “opportunistic growth” and community structure are useful indicators of the successional state of a bacterial population, and the ratio of culturable to total cells (CFU: TCN) herein was relatively high in the younger soils but decreased as succession age increased (Table 3). Specifically, within the first 25 years of deglaciation, the CFU:TCN ratio decreased from 0.0075 in the 5-y soil to 0.0019 in 35-y soil and to 0.0002 in 70-y old soil; with this latter value increasing slightly to 0.0004 in the 150-y old soil. This indicates an alteration in the life strategy of bacterial communities from r to K and, hence, successional changes (Sigler et al., 2002). Organisms with a predominant K-strategy can live near the carrying capacity of the environment. They have relatively low growth rates, but compensate this by competitive advantages such as high affinity for substrates, low maintenance energy, the ability to uncouple growth from transport, and accumulation of storage polymers. In contrast, r-selected organisms have the potential of rapid proliferation and fast response to abundant and readily available substrates. 3.6. Total and cultivated bacterial community analysis (DGGE) Initial microbial activity in young soil formation can be characterized by taxonomic structure analysis. DGGE is a useful way of detecting differences in community structure even if it is limited to dominant phylotype detection only (Nakatsu et al., 2000; Kozdroj and van Elsas, 2000). The total bacterial diversity in a soil sample (TSS) comparison with cultivable bacteria growth (WPS) is also a good indicator of changes in bacterial populations. The comparison between TSS and WPS could be a good indicator of changes in bacterial populations because the opportunistic

41

heterotrophic bacteria reveal their presence with increasing availability of easily digestible food substrates and could change between sites and over the time (Sigler et al., 2002). Here, the bacterial communities in 20 soil samples and 20 wash plate samples were compared by DGGE analysis of 16S rRNA genes. Each well-defined DNA fragment in the DGGE profiles was considered a distinct operational taxonomic unit (OTU) and the relative fluorescence of each OTU was assumed to reflect its true proportional abundance. By using the spread-plate method to identify cultivated bacteria undetected in DGGE profiles, we were able to estimate absolute species richness, as a sum of OTUs TSS and WPS. In addition, wash plate PCR proved useful in detecting bacterial community differences, allowing identification of heterotrophic bacteria in total soil samples undetected by DGGE rare phylotypes due to low turnout. Our analysis by DGGE in both the total and wash plate samples highlighted differences in taxonomic structure in the studied soils. The following numbers of OTUs were defined in the transect of total soil samples (TSS): 30, 36, 37 and 39, respectively, for 5-y, 35-y and 70-y and 150-y old soil. From the wash plate samples (WPS): 15, 8, 21 and 15 OTU-s were defined, respectively to 5-y, 35-y and 70-y and 150-y old soil. The cultivation and wash plate PCR/DGGE technique (WPS) identified the additional presence of 6, 2, 7 and 5 OTUs in sites 1, 2, 3, and 4, respectively. Collectively, the sum of TSS and WPS samples numbered 61 OTUs. DGGE fingerprinting indicated that several OTUs were present in each of the foreland soils and also that the community structure changed as successional age increased. Only 3 OTUs were present in all sites and samples, 19 OTUs were noncultivated and 10 OTUs were obtained after culture. Although some studies of bacterial community composition based on analysis of 16S rRNA gene sequences have shown an increase in phylotype diversity over time following glacier retreat (Nemergut et al., 2007; Zdanowski et al., 2013), other studies have reported a decrease (Sigler and Zeyer 2002; Sigler et al., 2002). We indicated that unique OTUs of samples WPS were concerned with the oldest soil and soil water content although TSS-unique OTUs were related to the ionic composition of water (mineralization). This suggests that the development of bacterial species richness is quite disparate to that observed in plant succession, where species richness increases over time (del Moral and Jones 2002; Hodkinson et al., 2003). Our data established that phylotype diversity increases along the chronosequence, but in the oldest soil (150 years), it was relatively low. Simultaneously, it was observed that the lesser bacterial biomass did not coincide with a simplification of bacterial community composition structure or a reduction in biodiversity. It is also apparent that while the youngest (5-y) and the oldest

WPS

TSS

5-y s.exp.

5-y s.exp.

35-y s.exp.

150-y s.exp.

70-y s.exp.

35-y s.exp.

150-y s.exp.

100

70-y s.exp.

95

90

85

80

75

Similarity

70

65

60

55

100

95

90

85

80

75

70

65

60

55

50

45

40

Similarity

Fig. 3. Hierarchical clustering of bacterial communities along the chronosequence based on data from DGGE analysis. Banding patterns were subjected to GelCompar cluster analysis (UPGMA; Dice correlation coefficient). TSS – total soil samples OTUs, WPS – wash plate samples OTUs (s. exp. – since exposure).

42

D. Górniak et al. / Applied Soil Ecology 114 (2017) 34–44

(150-y) sites exhibited similar lowest total phylotype diversity, culturable bacteria diversity was the lowest in the 35-y age soil at site 2. We presume that, in general, similar factors created the same situation in sites 1 and 4. It is most likely that organic matter content originates in the youngest soil from the glacial supply and in the oldest soil from higher plants. At the same time, site 3 had the highest richness. Comparison of bacterial community banding patterns TSS and WPS using canonical analysis (CA) revealed that each soil contains both common and unique OTUs. The number of unique OTUs in total soil samples (TSS) was 2, 4, 3 and 1 in the 5-y, 35-y, 70-y and 150-y old sites, respectively. In cultivated samples (WPS), the number of unique OTUs was the same in sites 1, 3 and 4, with their significant absence at site 2. The similarity of banding patterns of the foreland soils determined by hierarchical clustering illustrated that the 35-y soil was most similar to the 70-y soil and that similarities between the 5-y and 150-y old soil were quite surprisingly high. Similarity relationships in the cultivated bacteria DGGE banding patterns showed that 1 and 2 are the most similar sites and that site 3 is most dissimilar (Fig. 3). The 61 DGGE products of 16S rRNA genes (25 from WPS, and 36 from TSS) were partly-sequenced and provided 33 OTUs at the 97% sequence identity level (17 from WPS, and 16 from TSS) (Table 4). Actinobacteria were the most numerous cultured bacteria with 8 OTUs from the Arthrobacter spp. One OTU was Isoptericola sp., 4 OTUs were Bacteroidetes comprising Flavobacterium sp. and Sphingobacteriales, 2 OTUs were Betaproteobacteria, with Collimonas fungivorans and Gallionella capsiferriformans, 2-OTUs were

Gammaproteobacteria composed of Pseudomonas sp. and Shewanella halifaxensis, while one OTU was described as an uncultured Bacteroidetes bacterium strain. The TSS contained 5 Actinobacteria OTUs with Arthrobacter oxydans, Arthrobacter sulfonivorans one Arthrobacter bacterium strain and two OTUs uncultured Arthrobacter sp., three OTUs were uncultured Acidobacteria, four uncultured Gemmatimonadaceae (Gemmatimonas bacteria). Three OTUs were identified as uncultured Alphaproteobacteria (Sphingomonadales bacterium ), Acidimicrobiia (Acidimicrobineae) and Gammaproteobacteria (Stenotrophomonas bacterium). The most numerous OTUs in TSS were uncultured bacteria. The nearest neighbours in the SILVA search database and RDP classifier were from cold environments, such as Antarctica, the Arctic, Alps, Himalayas, Tibetan Plateau, Riverbank soil, Iceland and the Tianshan Mountains. The most interesting were bacteria closely related to the biological weathering of rocks. These included; Actinobacteria from the apatite surface under a Norway spruce stand, Betaproteobacteria from iron-contaminated groundwater in Michigan, Actinobacteria from epilithic biofilms growing on gravel, mineral-weathering Actinobacteria in Taihu paddy soil profile and bacteria from unvegetated, perhumid, recently-deglaciated soils. It was established that the Collimonas genus is especially welladapted to young, oligotrophic postglacial soils (Leveau et al., 2010; Borin et al., 2010). Many strains of Arthrobacter are connected with rock weathering. Members of this genus are ubiquitously present and these have been routinely associated with hydrocarbon-rich environments (Tennessee and Li, 2010). These microorganisms

Table 4 Identity from SILVA search database and RDP classifier (16S ribosomal RNA gene, partial sequence or complete genome). y wash plate samples, yy total soil samples. Band

Source Nearest match

Homology (%)

Accession no.

Phylum/Class/Family

Origin of GenBank sequence

1. 2. 3.

WPSy WPS WPS

Flavobacterium sp. HME6015 Arthrobacter sp. EA25 Flavobacterium sp. K22-02

99 99 97

HM149212.1 JN819637.1 EU326490.1

Bacteroidetes Actinobacteria Bacteroidetes

4. 5. 6. 7. 8. 9. 10. 11. 12.

WPS WPS WPS WPS WPS WPS WPS WPS WPS

Arthrobacter sp. Dza9 Collimonas fungivorans Pseudomonas sp. UA-JF4006 Gallionella capsiferriformans ES-2, Shewanella halifaxensis HAW-EB4, Uncultured Sphingobacteriales bacterium Isoptericola sp. EBKC42 Uncultured Bacteroidetes bacterium Arthrobacter sp. A1032

99 100 98 100 100 100 97 98 99

13. 14. 15. 16. 17. 18.

WPS WPS WPS WPS WPS TSSyy

Arthrobacter sp. UA-JF3701 Arthrobacter sp. PF2M2 Arthrobacter pascens strain A8 Z-7 Arthrobacter sp. TMT2-54 Actinobacteridae bacterium 12-01PB Arthrobacter oxydans strain 63

99 99 99 100 100 100

19. 20. 21. 22. 23. 24. 25. 26.

TSS TSS TSS TSS TSS TSS TSS TSS

99 99 97 98 99 98 98 100

27. 28. 29. 30. 31. 32.

TSS TSS TSS TSS TSS TSS

99 100 99 99 97 100

FM865681.1 JF966914.1 FJ570461.1 JN662538.1 GQ366400.1 JQ999120.1

Alphaproteobacteria Actinobacteria Actinobacteria Gemmatimonadetes Actinobacteria Acidimicrobiia

33.

TSS

Uncultured Acidobacterium Uncultured Acidobacterium Uncultured Acidobacterium Uncultured Gemmatimonas bacterium Arthrobacter bacterium JP33 Uncultured Gemmatimonas bacterium Uncultured Gemmatimonas bacterium Uncultured soil bacterium Sphingomonadales Uncultured Arthrobacter sp. Uncultured Bacteroidetes bacterium Uncultured Gemmatimonadetes bacterium Arthrobacter sulfonivorans Uncultured Arthrobacter sp. RUGL6-4 Uncultured Acidimicrobineae GKJWQY101ACFF3 Unidentified Stenotrophomonas bacterium

Mesotrophic artificial lake Apatite surface under Norway spruce stand l from cold desert in Himalayas, Lahaul-Spiti valley, India JQ977650.1 Actinobacteria Tianshan Mountains CP002745.1 Betaproteobacteria GenBank, complete genome KC108974.1 Gammaproteobacteria Riverbank soil, Iceland, Herdubreidarlindir CP002159.1 Betaproteobacteria Iron contaminated groundwater in Michigan CP000931.1 Gammaproteobacteria GenBank, complete genome HM527805.1 Bacteroidetes Bioreactor simulating a low temperature GU581100.1 Actinobacteria Epilithic biofilms growing on gravel HF674434.1 Bacteroidetes Atlantic salmon gut microbiota, Norway KC236715.1 Actinobacteria Mineral-weathering bacteria in Taihu paddy soil profile KC108914.1 Actinobacteria Glacial river in Iceland, riverbank sand KC311577.1 Actinobacteria Deeper permafrost soils of Western Spitsbergen KC788105.1 Actinobacteria Soil from Ladahk, Nubra valley, India, altitude 4850 m JX949854.1 Actinobacteria Glacier, China JX491418.1 Actinobacteria Glacier forefield soil, East Antarctica JX122175.1 Actinobacteria Soil bacteria participated in nitrogen and phosphorous cycles JX967665.1 Acidobacteria Soil, Tibetan Plateau GU598835.1 Acidobacteria Mineral horizon of Hubbard Brook forest HQ629076.1 Acidobacteria Forest soil Vosges Mountains, France JF420774.1 Subgroup 2 Glacier sedyment, Northern Schneeferner, Germany KC602267.1 Gemmatimonadaceae Heavy metal contaminated soil, Canada GQ396912.1 Actinobacteria Unvegetated, perhumid, recently-deglaciated soils GQ336949.1 Gemmatimonadaceae Soil, Antarctica, King George Island JF393266.1 Gemmatimonadaceae Petroleum-Contaminated Arctic Soil, Canada

97

KC002360.1

Gammaproteobacteria Surface seawater samples from China

Glacial snow on the Tibetan Plateau Hai River sediment in the season of the autumn Soil early snow melt site, Alpes Tianshan No. 1 Glacier foreland Soil from Roopkund Glacier, Himalayan mountain Lake Vostok accretion ice (Antarctica)

D. Górniak et al. / Applied Soil Ecology 114 (2017) 34–44

contribute to precipitation of new minerals and to carbonate production and also to bicalcification in calcite formation (Welch et al., 2002). As described by Frey et al. (2010), laboratory experiments (Ullman et al., 1996; Welch and Ullman, 1999) have shown that the Arthrobacter strains under limited-nutrient conditions could produce organic acids (acetate, gluconic acid, citrate and oxalate) that are involved in rock dissolution. This confirms bacteria’s significant role in early soil formation; even with organic substrate limitation. The CCA analysis showed that the TSS number of OTUs was dependent on the soil pore water composition, TDS content and the C:N ratio, but the WPS number of OTUs depended on organic matter and soil water content. 3.7. Summary and conclusions It has been shown that the following factors are associated with changes in bacterial viability, growth and community structure in young postglacial soils: the time period after glacier retreat, horizontal variations due to the distance between the sites in the chronosequence and bacteria-induced weathering. Prokaryotic community structure (abundance, biomass, biovolume, viability and “opportunistic” bacteria number) correlates with the environmental parameters: soil age, granulation, water and organic matter content. When environmental conditions are variable (unsteady) to be a broad niche specialist tolerating a wide range of conditions is the best survival strategy. Bacteria with low relative abundance and broad niche specialization inhabit the early stage of soil formation and although the 150-year-old relatively nutrient–rich late succession soil exhibited a 100-fold increase in bacterial abundance compared to the 35-year-old soil, it decreased in species richness. Meanwhile, the CFU:TCN ratio may simply indicate changes in environmental resources and bacterial metabolic activity. The results of molecular fingerprinting suggested that community-level changes were associated with the amount and availability of nutrients, soil water content, granulation and soil age. It can be concluded that the initial microbial activity is closely associated with a higher proportion of highly-specialised non-cultivated bacteria and their significant biodiversity. Using the plate wash technique allowed us to expand knowledge on the participation of low abundance taxa in post-glacial soil bacterial communities. The significant participation of the Arthrobacter genus of Actinobacteria in young soils confirms their important role in the initiation of soils and biological weathering. Based on the results of our research, we conclude that abundance, activity, opportunistic growth dynamics and diversity of the bacterial community were prime instigators of initial microbiological activity and soil formation. Along the chronosequence, the greatest abundance of OTUs was detected at the middle-aged 70-y soil site 3, although it registered the lowest number of cultured bacteria. While the youngest (site 1) soil formation, located on the foreland directly in front of the glacier foot, recorded both the highest TCN and cultivated bacteria levels, the total bacterial diversity there was the lowest. Microscopic abundance analysis and band-based estimation of bacterial species’ richness suggested that community richness increased along the chronosequence despite a decrease in the total bacteria count. These results are consistent with the hypothesis that microbial activity is an important contributor to the solute flux from glaciers. Bacterial communities are key determinants of Arctic ecosystem stability and function because of their important role in soil development. It is concluded that while highly specialised uncultivated bacteria generally dominate early stages of soil formation, their contribution decreases with soil age. This research highlights that early soil formation processes should be related to the composition of bacterial communities, the primary substrate structure and the abundance of available water.

43

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