Folia Microbiol DOI 10.1007/s12223-014-0352-0

Seasonal changes of microbial communities in two shallow peat bog lakes Sylwia Lew & Michal Koblížek & Marcin Lew & Hana Medová & Katarzyna Glińska-Lewczuk & Paweł Michał Owsianny

Received: 16 January 2014 / Accepted: 24 September 2014 # Institute of Microbiology, Academy of Sciences of the Czech Republic, v.v.i. 2014

Abstract Peat bog lakes represent important ecosystems in temperate and boreal zones. We investigated the seasonal dynamics of the microbial community in two small peat bog lakes, Kuźnik Olsowy and Kuźnik Bagienny, located in western Poland. Fluorescence in situ hybridization analyses revealed that the bacterial community was dominated by Proteobacteria and Actinobacteria, in addition to a substantial number of archaea. An infrared epifluorescence analysis demonstrated that aerobic anoxygenic phototrophs (AAPs)

constituted a significant fraction of bacterial plankton (1– 19 %). All the bacterial groups exhibited large seasonal changes whose course differed between the studied lakes. While chlorophyll had its maximum during winter or early summer, AAPs peaked in summer, when the growth of this group was stimulated by higher irradiance and elevated water temperatures.

Introduction S. Lew (*) Faculty of Biology and Biotechnology, University of Warmia and Mazury in Olsztyn, Oczapowskiego 1a, 10-957 Olsztyn, Poland e-mail: [email protected] M. Koblížek : H. Medová Institute of Microbiology CAS, Department of Phototrophic Microorganisms, Algatech, 379 81 Třeboň, Czech Republic M. Koblížek e-mail: [email protected] M. Lew Faculty of Veterinary Medicine, University of Warmia and Mazury in Olsztyn, Oczapowskiego 2, 10-957 Olsztyn, Poland e-mail: [email protected] K. Glińska-Lewczuk Department of Land Reclamation and Management, University of Warmia and Mazury in Olsztyn, Plac Łódzki 2, 10-719 Olsztyn, Poland e-mail: [email protected] P. M. Owsianny Institute of Geoecology and Geoinformation, Faculty of Geography and Geology, University of Adam Mickiewicz, Dzięgielowa 27, 61-680 Poznań, Poland e-mail: [email protected] P. M. Owsianny Didactic and Scientific Branch in Piła, Kołobrzeska 15, 64-920 Piła, Poland

Peat bog lakes are one of the most common types of inland waterbodies in the temperate zones of Eurasia and North America (Dedysh et al. 2006). They are dystrophic water reservoirs characterized by a neutral to acidic pH, a low buffer capacity due to a limited amount of dissolved salts, and a low concentration of nutrients (Dedysh et al. 1998, 2006). In spite of their smaller size, peat bog lakes represent a globally significant reservoir of fresh water (Pankratov et al. 2006). They have an important role in ecosystem water balance, accumulating large quantities of water and preventing floods during wet periods, and returning the accumulated water during droughts. In spite of their large water retention capacity, peat bog lakes are very sensitive to all changes related to human pressure on the environment. Changes in temperature and water regime can significantly affect their proper function, facilitating degradative processes or eventually causing the drying of the bogs. In this scenario, they can lose their capacity to accumulate organic carbon and eventually become a net source of methane released from accumulated peat (Blodau et al. 2004). The water in peat bog lakes is brown due to the high content of colored dissolved organic matter (CDOM) (Klavnis et al. 2003). The decomposition of dissolved organic matter (DOM) in these lakes is very slow, and therefore, the water in these lakes does not undergo eutrophication. The

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DOM composition changes over time (Pankratov et al. 2005); only approx. 15 % of DOM is available to bacteria and is used as a source of carbon (Tranvik 1998), whereas the majority of DOM is inaccessible to bacteria and accumulates in the environment (Haukka et al. 2005). Peat bog lakes support unique communities of organisms (Andersen et al. 2013). The trophic network in shallow dystrophic peat reservoirs is simplified. These lakes are characterized by a low phytoplankton biomass and low production (Jansson et al. 2000), as well as a limited diversity of zooplankton (Druvietis et al. 1998). Most of the production is carried out by bacteria processing the DOM and facilitating the carbon flow between water and the terrestrial environment (Newton et al. 2007; Taipale et al. 2009). However, our knowledge of the composition and functioning of microcenoses in these ecosystems is only limited. A lot of interest was attracted by microorganisms involved in methane production and consumption—methanotrophic bacteria (Dedysh et al. 1998; Raghoebarsing et al. 2005) and methanogenic archaea (Basiliko et al. 2003; Kotsyurbenko et al. 2004). In fact, most of the recent studies focused on microorganisms associated exclusively with Sphagnum (Høj et al. 2008; Pankratov and Dedysh 2009; Preston et al. 2012) and originated from areas with low environmental temperatures (Arctic, Siberia). There are only a limited number of reports on the composition and functions of such microorganisms from lowland areas, e.g., from central Europe and, in particular, from shallow dystrophic peat bog lakes where the number, composition, and activity of microorganisms are influenced by environmental factors related to yearly seasonal changes (Hutalle-Schmelzer et al. 2010). Little is known on the distribution of anoxygenic phototrophs in peat bog lakes. Traditionally, anoxygenic phototrophs were considered to represent mostly anaerobic species inhabiting anoxic parts of the water column. Recently, it was found that anoxygenic phototrophs are also widespread in aerobic aquatic habitats (Mašín et al. 2012). It was shown that bacteriochlorophyll-containing bacteria constitute a large fraction of microbial communities inhabiting euphotic layers of the oceans (Kolber et al. 2001; Koblížek 2011) and aerobic zones of freshwater lakes (Mašín et al. 2008). These organisms, called aerobic anoxygenic phototrophs (AAPs), are photoheterotrophic bacteria which require organic carbon for their metabolism and growth; however, they can supplement their energy requirements using light harvested by bacterial reaction centers (Yurkov and Csotonyi 2009; Hauruseu and Koblížek 2012). To shed more light on the microbial community composition and functioning in peat bog lakes, we decided to follow the seasonal dynamics of major bacterial groups in two shallow peat bog lakes located in northern Poland. The changes in community composition were correlated with basic environmental and microbiological parameters to establish the main

factors driving the seasonal succession pattern of local microbial communities.

Materials and methods Study sites and sampling The study was conducted at two humic, peat bog lakes, Kuźnik Olsowy (lat. 16° 43′ 5″ N, long. 53° 12′ 4″ E) and Lake Kuźnik Bagienny (16° 44′ 0″ N, 53° 12′ 5″ E), located in the mesoregion of the Gwda River Valley, Poland. The lake area for Kuźnik Olsowy and Kuźnik Bagienny is 0.5 and 1.0 ha, respectively. The maximum depth was 1.1 m for Kuźnik Olsowy and 1.9 m for Kuźnik Bagienny. The lakes have forested catchment areas populated by stonewort communities, with adjacent transitional peat moss bogs. The samples were collected four times in 2008 and 2009 from each lake: in winter (January, February), when the water temperature did not exceed 4 °C; in spring (April, May), when the water temperature was from 10 to 17 °C); in summer (July, August), when the water temperature was higher than 18 °C (up to 22 °C); and in autumn (October, November), when the water temperature was from 7.5 to 9.5 °C. Water was sampled in three repetitions (N=12 per season) from the surface zone (5–15 cm beneath the surface) in the central area of the lakes. Temperature (T; °C), dissolved oxygen concentration (DO; mg/L), water color (mg Pt-Co/L), and pH were recorded using a multiparameter YSI 6600 probe (YSI Inc., Yellow Springs, USA). The chlorophyll (Chl) concentration was determined spectrophotometrically in acetone extracts with correction for phaeopigments (Gąbka and Owsianny 2006). Epifluorescence microscopy The total bacterial numbers (TBN) were determined by epifluorescence microscopy (Porter and Feig 1980). Triplicate subsamples were fixed with neutralized formaldehyde (pH 7.4) at a final concentration of 4 %. In the laboratory, the samples were stained with 4′,6-diamidino-2-phenylindole (DAPI) (final concentration 0.01 μg/mL) for 15 min in the dark and gently filtered through 0.2-μm black Nuclepore filters. The bacteria were counted under an Olympus BX41 epifluorescence microscope. More than 1000 bacterial cells in 20 objective fields were counted. The samples for determination of anoxygenic phototrophs (bacteriochlorophyll-containing cells) were fixed with 2 % formaldehyde and stored in a freezer at −20 °C. After thawing, the samples were collected onto 0.2-μm polycarbonate filters, dried, and stained with DAPI (1 μg/mL) mixed with Citifluor AF1 and Vectashield (3:1 vol:vol). Infrared (IR) epifluorescence microscopy was done with an Olympus BX51TF fluorescence microscope equipped with an

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Olympus Universal Planapochromat 100×/1.35 OIL objective and a B/W CCD camera F-ViewII as described earlier (Mašín et al. 2006). Fluorescence in situ hybridization Samples for community analysis were fixed with freshly prepared buffered paraformaldehyde (pH 7.4) to a final concentration of 2 % (vol:vol) and stored for several hours at 4 °C. The samples were filtered through 0.2-μm white polycarbonate filters, rinsed with sterile water, dried at room temperature, and stored at −20 °C. The structure of the bacterial community was investigated with fluorescence in situ hybridization (FISH) with the use of Cy3labelled oligonucleotide probes in accordance with the hybridization procedure for aquatic microorganisms proposed by Glöckner et al. (1999, 2000) and Pernthaler et al. (2001). The hybridization and wash temperatures were 46 and 48 °C, respectively. The composition of the bacterial population was analyzed with the use of the EUB338 oligonucleotide probe targeting most bacteria (Amann et al. 1990; Lew et al. 2010) and the ARCH915 probe targeting archaea (Stahl and Amann 1991). Within bacteria, the main taxonomic groups were determined using probes ALF968, BET42a, and GAM42a for Alpha, Beta, and Gammaproteobacteria (Manz et al. 1992); probe CF319a for Cytophaga-Flavobacteria (Manz et al. 1992); and HGC69a for Actinobacteria (Roller et al. 1994). Autofluorescence and non-specifically stained cells were determined with the negative control probe NON338 (Wallner et al. 1993). The rRNA-targeted oligonucleotide probes employed in this study are listed in Table 1. Bacterial cells on the filter sections were observed with an epifluorescence microscope equipped with filter sets for DAPI and CY3 (Lew et al. 2010). The fractions of FISHstained bacteria in at least 1000 DAPI-stained cells per sample were quantified in triplicate.

Data analyses Lake samples were taken in triplicate to determine the variability of DAPI counts. Probe-specific cell counts are presented as a percentage of cells visualized by DAPI. The correlation analysis of obtained data was calculated using the Pearson’s correlation algorithm in SigmaPlot for Windows ver. 11.0. The response of the microbiological communities to the environmental conditions was analyzed using multivariate statistical analyses. Detrended correspondence analysis (DCA) and redundancy analysis (RDA) were performed using Canoco 4.5. DCA of the microbiological parameters was used to determine whether linear or unimodal ordination methods should be applied (ter Braak and Šmilauer 2002). DCA was used first to determine the character of variability in the studied assemblages: if a gradient length is over 4 SD, the species in the data show a clear unimodal response along the gradient. The gradient length for Kuźnik Olsowy amounted to SD=0.508, while for Kuźnik Bagienny SD=0.338, which indicated a linear variation, providing justification for the further use of redundancy analysis. RDA is a direct gradient analysis that summarizes relations between bacterioplankton and water quality parameters. The dataset was centered and standardized by species, due to the different units of environmental variables. To rank the importance of the individual explanatory variables, automatic forward selection of environmental variables was used. Before each addition, the explanatory effect of the candidate variable was evaluated using the Monte Carlo permutation test (Lepš and Šmilauer 2003).

Results The seasonal succession of microbial communities was studied in two peat bog lakes, Kuźnik Olsowy and Kuźnik Bagienny, during the years 2008 and 2009. Both of the studied lakes displayed dramatic seasonal changes (Figs. 1 and 2).

Table 1 Oligonucleotide probes used in this work Probe name

Sequence (5′–3′) of probe

Target group

rRNA type

FA [%]a

Reference

EUB338

GCTGCCTCCCGTAGGAGT

Most bacteria

16S RNA

35

Amann et al. 1990 Wallner et al. 1993

NON338

ACTCCTACGGGAGGCAGC

Negative control

23S RNA

35

ALF968

GGTAAGGTTCTGCGCGTT

Alphaproteobacteria

16S RNA

35

Manz et al. 1992

BET42a

GCCTTCCCACTTCGTTT

Betaproteobacteria

23S RNA

35

Manz et al. 1992

GAM42a

GCCTTCCCACATCGTTT

Gammaproteobacteria

23S RNA

35

Manz et al. 1992

CF319a

TGGTCCGTGTCTCAGTAC

Cytophaga-Flavobacterium

16S RNA

35

Manz et al. 1992

HGC69a

TATAGTTACCACCGCCGT

23S RNA

25

Roller et al. 1994

ARCH915

GTGCTCCCCCGCCAATTCCT

Gram-positive bacteria with high GC content Archaea

16S RNA

20

Stahl and Amann 1991

a

FA [%]: formamide concentration in the hybridization buffer to ensure specific detection of target organisms

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The water temperature in the lakes changed from +2 °C in January to 22 °C in August. The water color in Kuźnik Olsowy reached its maxima in spring (162.5±3.57) and summer (122.5±3.53) and dropped to 62±1.41 mg Pt-Co/L during winter (see Table 2). A similar situation was also observed in Kuźnik Bagienny where water color ranged between 102± 2.83 and 117.5±3.54 mg Pt-Co/L in spring and summer and decreased to 63±2.83 and 47±2.83 mg Pt-Co/L in autumn and winter, respectively. The water pH in Kuźnik Olsowy

15

15 10 10 5

Temperature Chlorophyll a

5 Apr

Jul

Oct

Jan

Apr

Jul

0 Jan

Oct

15

20

12

16

9

12

6

8 TBN AAPs

3 0 Jan

Apr

Jul

Oct

Jan

Apr

Jul

Oct

4 0 Jan

Percentage [%]

100 80 60 Bacteria Archaea

40 20 0 Jan

Apr

Jul

Oct

Jan

Apr

Jul

Oct

Jan

Percentage [%]

40 30 20 10 0 Jan

HGC CF Apr

Jul

Oct

Jan

Apr

Jul

Oct

Jan

Oct

Jan

40 Alpha Beta Gamma

30 20 10 0 Jan

Apr

Jul

Oct

Jan

Apr

2008 - 2009

Jul

AAPs [105 cells/mL]

Temperature [°C]

20

0 Jan

TBN [106 cells/mL]

20

Chlorophyll a [µg/L]

Ku nik Olsowy 25

Percentage [%]

Fig. 1 Seasonal changes in water temperature and main microbiological parameters in Kuźnik Olsowy from January 2008 to December 2009. TBN total bacterial numbers, AAPs AAP abundance, HGC Actinobacteria, CF CytophagaFlavobacteria, Alpha Alphaproteobacteria, Beta Betaproteobacteria, Gamma Gammaproteobacteria. Error bars represent standard errors

increased from 6.4±0.14 in spring through 6.6±0.04 in summer and autumn to 7.1±0.07 in winter. In Kuźnik Bagienny, the pH remained remarkably constant during most of the year (7.0±0.17) except for spring when it dropped to 6.8±0.07. The lakes remained aerobic during the entire year; the oxygen concentration (DO) changed in relation to the changes in the water temperature. The seasonal changes in physico-chemical parameters affected largely the planktonic community. Chla concentration

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20

60

15

40

10 5 0 Jan

Temperature Chlorophyll a Apr

Jul

Oct

Jan

Apr

Jul

Oct

20

0 Jan

15

15

12

12

9

9

6

6 TBN AAPs

3 0 Jan

Apr

Jul

Oct

Jan

Apr

Jul

Oct

3 0 Jan

AAPs [105 cells/mL]

Temperature [°C]

80

Chlorophyll a [μg/L]

Kuźnik Bagienny 25

TBN [106 cells/mL]

Fig. 2 Seasonal changes in water temperature and main microbiological parameters in Kuźnik Bagienny from January 2008 to December 2009. TBN total bacterial numbers, AAPs AAP abundance, Bacteria most bacteria, HGC Actinobacteria, CF Cytophaga-Flavobacteria, Alpha Alphaproteobacteria, Beta Betaproteobacteria, Gamma Gammaproteobacteria. Error bars represent standard errors

Percentage [%]

100 80 60 Bacteria Archaea

40 20 0 Jan

Apr

Jul

Oct

Jan

Apr

Jul

Oct

Jan

Percentage [%]

40 HGC CF

30 20 10 0 Jan

Apr

Jul

Oct

Jan

Apr

Jul

Percentage [%]

40

Oct

Jan

Alpha Beta Gamma

30 20 10 0 Jan

Apr

Jul

Oct

Jan

Apr

Jul

Oct

Jan

2008 - 2009

was higher in Kuźnik Bagienny, ranging from 20 to 60 μg Chla/L with the chlorophyll maximum observed during winter (January) and the minimum during summer (Figs. 1 and 2). In Kuźnik Olsowy, chlorophyll varied between 5 and 15 μg Chla/L with the maximum in spring (April) and minimum during winter. A different seasonal pattern was observed for total bacteria (Figs. 1 and 2). The highest TBN was reported in spring and

reached, on average, 13.0×106/mL in Kuźnik Olsowy and 9.0×106/mL in Kuźnik Bagienny (Figs. 1 and 2). In these lakes, the lowest number of organisms was determined in summer. During the autumn and winter seasons, TBN stayed between 6.6 and 9.7×106 cells/mL in both studied reservoirs (Figs. 1 and 2). Special attention was paid to the presence of aerobic anoxygenic phototrophs (AAPs) in peat bog lakes which had

Folia Microbiol Table 2 Seasonal variations of selected hydro-chemical parameters in the tested reservoirs in 2008–2009. Provided values represent mean± standard deviation Lake

Kuźnik Olsowy

pH Spring 6.4±0.14 Summer 6.6±0.04 Autumn 6.6±0.04 Winter 7.1±0.07 Water color (mg Pt-Co/L) Spring 162.5±3.57 Summer 122.5±3.53 Autumn 111.5±2.12 Winter DO (mg/L) Spring Summer Autumn Winter

Kuźnik Bagienny

6.8±0.07 7.0±0.21 7.0±0.14 7.0±0.15 102.0±2.83 117.5±3.54 63.0±2.83

62.0±1.41

47.0±2.83

8.0±0.42 6.9±1.99 8.6±0.35 9.6±0.35

9.4±0.07 6.8±1.91 10.3±0.21 10.0±0.27

DO dissolved oxygen concentration

not been previously studied. Their abundance ranged from approx. 105 cells/mL to 12×105 and 20×105 cells/mL for Kuźnik Bagienny and Kuźnik Olsowy, respectively. Their percentage ranged from 1.2 to 2.6 % up to 15 to 19 % during the summer maxima. The seasonal pattern of anoxygenic phototrophs differed somewhat between the two lakes. While in Kuźnik Olsowy they had their minimum in January, in Kuźnik Bagienny, their minimum was in April. In Kuźnik Bagienny, the maximum numbers were found in August, whereas in Kuźnik Olsowy, there were two distinct maxima, one in May and the second in August. The seasonal changes of bacteria and archaea was analyzed using FISH (Figs. 1 and 2). The studies showed that the contribution of these main groups of prokaryotes varied throughout the year. The EUB338-positive cells were more numerous in summer and autumn, representing approx. 80 % of total prokaryotes, whereas the cells hybridizing with the ARCH915 probe were more abundant during winter (Kuźnik Olsowy) or spring (Kuźnik Bagienny) when they formed up to 40 % of total prokaryotes. The seasonal succession was further studied among the environmentally most relevant bacterial phyla: Actinobacteria, Cytophaga-Flavobacteria, and Proteobacteria. Actinobacteria (Gram-positive HGC group) represented 12 to 34 % of total prokaryotes, and their succession differed between the studied lakes. In Kuźnik Olsowy, the maximum of Actinobacteria was found during August and the minimum in April–May. In Kuźnik Bagienny, the maximum was in April, whereas the minimum was found in October–November. Another dynamics was found for Cytophaga-Flavobacteria. The maximum for

Cytophaga-Flavobacteria was observed between October and February (9.6–19.5 % of total prokaryotes), whereas the minimum was found between April and July (3.4–6.7 %). The last major bacterial phylum, Proteobacteria, represented 16.8–42.6 and 21.3–49.1 % of total prokaryotes in Kuźnik Bagienny and Kuźnik Olsowy, respectively. Proteobacteria did not act as a homogenous group as the main proteobacterial classes largely differed in their seasonal succession. Alphaproteobacteria in both lakes displayed similar seasonal trends with maximum in April and minimum in autumn. This contrasted with the time course of Gammaproteobacteria which had their minimum in August and peaked in October–November. The most variable were the seasonal changes of Betaproteobacteria which differed among the lakes. In Kuźnik Olsowy, the maximum of Betaproteobacteria was observed in October, whereas in Kuźnik Bagienny, the maximum was found to be in May. From the observed pattern, we can deduce the seasonal succession of individual microbial groups for each lake. In Kuźnik Olsowy, the winter period was typical for Archaea. The spring phytoplankton bloom (Chl. max.) occurred in April, together with the maximum of Alphaproteobacteria. It was followed by the maximum of total prokaryotes (TBN) and aerobic anoxygenic phototrophs (AAPs) in May. The summer period was characterized by the maximum of Actinobacteria (HGC) and the second maximum of anoxygenic phototrophs which coincided with the temperature maximum. The maximum of Betaproteobacteria, Gammaproteobacteria, and Cytophaga-Flavobacteria followed in autumn. A somewhat different situation was observed in Kuźnik Bagienny. Here, the phytoplankton bloom occurred during the winter period in January. Interestingly, the difference at the start of the productive season affected only some microbial groups, whereas others showed a similar pattern in both lakes. Archaea, Alphaproteobacteria (max. in spring), and Gammaproteobacteria (max. in autumn) had the same time course as in Kuźnik Olsowy. The maxima of Actinobacteria, Betaproteobacteria, and Cytophaga-Flavobacteria were significantly shifted in the season when compared to the situation in Kuźnik Olsowy. Forward selection in RDA identified five environmental variables (water color, pH, T, DO, and Chla) that explained significant (P≤0.05), independent directions of variation in the microbiological data in both lakes. RDA performed for microbiological parameters and physico-chemical parameters of water for Kuźnik Olsowy (Fig. 3) showed significance of the first and second axes (eigenvalue: λa1 =0.475, λa2 = 0.175), which explained 94.9 % of the cumulative variance in the species-environment relationship, 68.8 % of which was related to axis 1. For Kuźnik Bagienny, RDA axis 1 (eigenvalue: λa1 =0.551) and axis 2 (λa2 =0.105) were both significant (P≤0.05). Axes 1 and 2 explained 91.5 % of the variance in the species-environment relationship and 65.7 % of the total species variance (Fig. 4).

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RDA axes summary Eigenvalues :

Axis 2:17.9%

Species-environment correlations : Cumulative % variance of species data : Cumulative % variance of species-environment relation:

Axis1

Axis2

0.475

0.179

0.964

0.768

47.5

65.4

68.8

94.9

Total variance 1.000

Beta

HGC EUB TBN

AAPs

Chla %AAPs water color

DO

CF Gamma

ARCH

T pH

-0.6

Alpha -1.0

Variables

1.0

Axis 1:47.5% Marginal Effects

Conditional Effects

λ1

λA

P

F-value

water color

0.39

0.39

0.002

25.58

pH

0.38

0.11

0.002

8.48

T

0.32

0.09

0.002

8.03

DO

0.30

0.06

0.004

7.28

Chla

0.24

0.04

0.010

4.03

Fig. 3 Biplot of redundancy analysis (RDA) for microbiological and environmental parameters in Kuźnik Olsowy. The explanatory variables represent significant relations between the species (marginal and conditional effects). Lambda denotes the amount of variability in the species data that would be explained by a constrained ordination model using that variable as the only explanatory variable. TBN total bacterial numbers,

AAPs AAP abundance, %AAPs percentage of AAPs in DAPI-stained cells, EUB most bacteria, HGC Actinobacteria, CF CytophagaFlavobacteria, Alpha Alphaproteobacteria, Beta Betaproteobacteria, Gamma Gammaproteobacteria, ARCH Archaea, DO dissolved oxygen concentration, T water temperature, Chla chlorophyll a concentration

In both lakes, out of the five explanatory environmental variables, water color, pH, and water temperature had the strongest relationships to the primary axis. In Kuźnik Olsowy, they explained 39.0, 38.0, 32.0, 30.0, and 24.0 % of variance, respectively. The variance explained by those variables in Kuźnik Bagienny was lower and amounted to 24.0, 22.0, 19.0, 15.0, and 12.0 %, respectively. In both cases, the environmental variables contributed significantly to the model of already included variables (after Monte Carlo permutations) at P=0.002. Among microbiological variables, AAP abundance in both lakes showed a significant gradient related to the first axis.

et al. 2007), but the number of microorganisms in these reservoirs is usually low and does not exceed 3×106 cells/mL (Druvietis et al. 1998; Taipale et al. 2009). Results similar to our data (approx. 6–7×106 cells/mL) have been reported from the humus zone of Crystal Bog reservoirs (Šimek et al. 1998) and dyseutrophic lakes (Druvietis et al. 1998). The highest numbers of total bacteria were observed in both lakes during the late spring. Several factors may explain this observation: (a) an increase in water temperature which stimulated the growth of bacteria, (b) the thawing of snow and the increase in water level which facilitated the mixing of water bringing microorganisms from Sphagnum into the planktonic phase, and (c) the inflow of easily available organic matter (which originates from surrounding peat moss vegetation) into the lake (Pankratov et al. 2005; Dedysh et al. 2006). The microbiome in the examined peat bog lakes was dominated by Actinobacteria. These organisms are globally distributed throughout a variety of limnetic systems and are the

Discussion The examined water reservoirs are peat bog lakes with a slightly lowered pH and intense water color. Humic (dystrophic) reservoirs are characterized by high bacterial metabolism (Newton

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RDA axes summary Eigenvalues : Species-environment correlations : Cumulative % variance of species data : Cumulative % variance of species-environment relation:

Axis1

Axis2

0.551

0.105

0.996

0.757

55.1

65.7

76.8

91.5

DO

Total variance 1.000

Axis 2:10.5%

Gamma CF EUB TBN

AAPs

HGC

%AAP

Beta

Chla

ARCH

T pH water color

-0.6

Alpha Axis 1: 55.1%

-1.0

Variables

Marginal Effects

1.0

Conditional Effects

λ1

λA

P

F-value

water color

0.24

0.24

0.002

12.77

pH

0.22

0.29

0.002

23.35

T

0.19

0.10

0.002

11.18

DO

0.15

0.05

0.004

5.56

Chla

0.12

0.04

0.002

4.68

Fig. 4 Biplot of redundancy analysis (RDA) for microbiological and environmental parameters in Kuźnik Bagienny. The explanatory variables represent significant relations between the species (marginal and conditional effects). Lambda denotes the amount of variability in the species data that would be explained by a constrained ordination model using that variable as the only explanatory variable. TBN total bacterial

numbers, AAPs AAP abundance, %AAPs percentage of AAPs in DAPIstained cells, EUB most bacteria, HGC Actinobacteria, CF CytophagaFlavobacteria, Alpha Alphaproteobacteria, Beta Betaproteobacteria, Gamma Gammaproteobacteria, ARCH Archaea, DO dissolved oxygen concentration, T water temperature, Chla chlorophyll a concentration

prevalent fraction of heterotrophic bacterial plankton (Allgaier and Grossart 2006; Lew et al. 2011, 2013). This fraction of microorganisms did not drop below 15 % of all DAPI-stained bacteria and even exceeded 30 %. Such results have been reported by many authors (Kirchman et al. 2005; Taipale et al. 2009, 2011). The highest concentration was recorded in spring in Kuźnik Olsowy and summer in Kuźnik Bagienny. This is different from other reports which observed the maximum number of Actinobacteria in late autumn and winter (Glöckner et al. 2000; Burkert et al. 2003). Actinobacteria are capable of utilizing some hard-to-degrade compounds (Burkert et al. 2003) and are capable of digesting cellulose. This ability enables them to colonize peat moss, where peat moss remnants are a source of cellulose (Pankratov and Dedysh 2009). Their presence in an ecosystem fed with this matter from surrounding peat moss Sphagnum is justified, particularly during periods with increased water level, straight

after the thawing of snow after filling of the reservoir from the environment during rainfall. Betaproteobacteria were reported to constitute a significant part of the bacterial population in the superficial layer of eutrophic lakes as well as in humic lakes (Taipale et al. 2009). This group was particularly numerous in Kuźnik Bagienny during the winter-spring period and in autumn and w i n t e r in K u ź n ik O l s o w y. I n p r e v i o u s s t u d i e s , Betaproteobacteria were stimulated by the introduction of allochthonous nutrients into water in spring (Lew et al. 2011; Glöckner et al. 1999). The positive linear correlation between the number of bacteria labelled with a BET42a probe and the DOC concentration was observed by Bouvier and del Giorgio (2002); however, in our study, we did not observe such a clear relationship. In our study, the fraction of Gammaproteobacteria ranged between 5 and 13 % of all DAPI-stained bacteria (TBN). This

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is relatively high, since these organisms are relatively rare in freshwater environments, typically not exceeding 4 % of total bacteria (Glöckner et al. 1999). Gammaproteobacteria may colonize biofilm or river detritus, which indicates that they prefer an environment with a stable, high concentration of nutrients (Kirchman 2002). Alphaproteobacteria was the least numerous group. The numbers exceeding 10 % were only registered in spring, which might be connected with the inflow of these organisms from the surrounding peat moss (Dedysh et al. 2006). The majority of bacteria identified with the CF319a probe are chemoorganotrophic and responsible for the degradation of biopolymers such as cellulose, chitin, and pectin (Bertoni et al. 2008). They decompose high-molecular, dissolved organic matter (DOM) which is intensively released from aggregates and detritus in spring (Kirchman 2002; Bertoni et al. 2008). In Kuźnik Bagienny, the maximum CytophagaFlavobacterium concentration was recorded in winter, which coincided with the peak of chlorophyll a concentration. These observations are compatible with the results reported by Pernthaler et al. (1998) who detected the highest number of the bacterial group after the ice melt. Other studies indicated that the increase in the number of these microorganisms coincided with the phytoplankton bloom (Kirchman 2002). In fresh waters, archaea usually represent from 1 to 5 % of the total bacteria (Pernthaler et al. 1998). However, Auguet et al. (2010) found that planktonic freshwater habitats emerged as the largest reservoirs of archaeal diversity and, consequently, were promising environments for the discovery Table 3 Pearson product-moment correlation coefficients between the abundance of anoxygenic phototrophs (AAPs) and selected environmental and microbial variables. Correlations (r) with P