Abstract Little is known about how various substances from living and decomposing aquatic macrophytes affect the horizontal patterns of planktonic bacterial communities. Study sites were located within Lake Kolon, which is a freshwater marsh and can be characterised by open-water sites and small ponds with different macrovegetation (Phragmites australis, Nymphea alba and Utricularia vulgaris). Our aim was to reveal the impact of these macrophytes on the composition of the planktonic microbial communities using comparative analysis of environmental parameters, microscopy and pyrosequencing data. Bacterial 16S rRNA gene sequences were dominated by members of phyla Proteobacteria (36%–72%), Bacteroidetes (12%–33%) and Actinobacteria (5%–26%), but in the anoxic sample the ratio of Chlorobi (54%) was also remarkable. In the phytoplankton community, Cryptomonas sp., Dinobryon divergens, Euglena acus and chrysoflagellates had the highest proportion. Despite the similarities in most of the measured environmental parameters, the inner ponds had different bacterial and algal communities, suggesting that the presence and quality of macrophytes directly and indirectly controlled the composition of microbial plankton. shallow lake, bacterioplankton, phytoplankton, community composition, aquatic macrophytes INTRODUCTION Planktonic bacterial communities in aquatic ecosystems play a fundamental role in nutrient cycling and energy flow. The composition of the bacterioplankton within a lake can be different due to environmental heterogeneity (e.g. different depths of a stratified water column, littoral versus pelagic zone, inner pond in a lake covered with macrophytes) (Wetzel 2001). The most intensively studied factors that affect the composition of bacterial communities are pH, temperature, nutrients, salinity, UV radiation and trophic status (Sigee 2005), although little is known about how various substances from living and decomposing macrophytes affect the composition of bacterial communities. Vertical changes in bacterioplankton composition were described in many lakes (e.g. Máthé et al.2014). However, only few publications (Wu et al.2007; Ng et al.2010; Zeng et al.2012) provided detailed data about the within-lake horizontal heterogeneity of the bacterial communities, despite the fact that the effect of inhabiting aquatic macrophytes may result in a comparable horizontal pattern as detected on the vertical scale in the case of deep lakes. Plant decomposition is modulated by internal (e.g. plant nutrient content, C/N and C/P ratio; Enriquez, Duarte and Sand-Jensen 1993) and external factors (e.g. water physical and chemical characteristics, composition and abundance of microbial and other decomposer communities; Sollins, Homann and Caldwell 1996). During the decay of algal and plant material, dissolved organic matter is formed, a significant part of which is refractory and gives a yellow-brown colour to natural waters (Wetzel 2001). These macrophyte-derived coloured substances (coloured dissolved organic matter, CDOM) are N-containing organic acids (Schulten 1995). CDOM plays a significant role in freshwater and marine ecosystems, its contribution to the DOC (dissolved organic carbon) pool could be as high as 40%–60% in the majority of aquatic environments (Thurman 1985). CDOM modifies the optical properties of the water by absorbing both visible and ultraviolet radiation. Thus, aquatic macrophyte cover may cause light limitation in lakes due to the shading effect of macrophytes and to the light absorption of macrophyte-derived CDOM. As a result, light limitation may decrease oxygen production of the phytoplankton. In addition, photochemical and biological degradation of CDOM consumes oxygen. Therefore, aquatic vegetation has dual influence on planktonic bacterial communities: an indirect one, by suppressing algal growth (which results lower oxygen concentration and lower algal extracellular release), and a direct one, by supplying carbon and nutrient source for the microbes (Sigee 2005). Furthermore, the presence of the higher plants reduces the wind-induced sediment resuspension in shallow lakes. Over the last decade, the understanding of microbial ecology and diversity has significantly increased due to next-generation DNA sequencing (NGS) methods, like pyrosequencing, as it has been used widely to analyse the bacterial community composition of various environmental samples. In this paper, we studied the impact of different macrophyte stands on the community composition of planktonic microorganisms. In this regard, Lake Kolon (Hungary) represented a suitable model system, since the lake is a reed-covered marsh consisting artificially created inner ponds with bladderwort and water-lily and a relative large open-water area. MATERIALS AND METHODS Study site and sampling Lake Kolon is a freshwater marsh located in the Kiskunság National Park, Hungary, Central Europe (Fig. 1). The lake is mesotrophic and has a neutral or slightly alkaline pH (∼7.0–8.5) and Ca2+-Mg2+-HCO3− ion dominance (Mádl-Szőnyi and Tóth 2009). Lake surface (29 km2) is almost entirely covered by reed (Phragmites australis), in which man-made smaller and larger inner ponds can be found (with a total area of 11 km2) with a minimum depth of 1.0 m and a maximum depth of 2.6 m. Some inner ponds are open-water areas, while others are colonised by aquatic macrophytes such as the leaf-floating water-lily (Nymphea alba) or the submerged bladderwort (Utricularia vulgaris). Figure 1. View largeDownload slide Geographic location and the view of sampling sites. Figure 1. View largeDownload slide Geographic location and the view of sampling sites. Samples were collected after the vegetation period, on 18 November 2014 from four different sites of Lake Kolon (Fig. 1; Table 1): site O (46°45΄38΄΄N, 19°20΄25΄΄E; an open-water site without macrophyte cover), site R (46°46΄23΄΄N, 19°20΄20΄΄E; a sampling site within the reed belt, close to site L), site B (46°48΄06΄΄N, 19°20΄10΄΄E; bladderwort-dominated inner pond) and site L (46°46΄23΄΄N, 19°20΄24΄΄E, water-lily-dominated inner pond). Water samples from different depths collected with Meyer bottle were transferred to the laboratory at 4°C in a thermo box, and processing started within 8 h after sampling. Table 1. Coding of water samples collected from Lake Kolon. Depth values are given in meters. Open-water (O) Reed (R) Bladderwort (B) Water-lily (L) Site Depth Code Depth Code Depth Code Depth Code Surface (S) 0.1 OS 0.1 RS 0.1 BS 0.1 LS Middle (M) 1.0 OM 0.5 BM 1.0 LM Bottom (B) 1.0 BB 2.0 LB Open-water (O) Reed (R) Bladderwort (B) Water-lily (L) Site Depth Code Depth Code Depth Code Depth Code Surface (S) 0.1 OS 0.1 RS 0.1 BS 0.1 LS Middle (M) 1.0 OM 0.5 BM 1.0 LM Bottom (B) 1.0 BB 2.0 LB View Large Physical and chemical analyses Temperature, pH and conductivity values were measured with a WTW pH 315i and a Hanna HI9033 portable field meter, while dissolved oxygen (DO) concentration was measured with a Hach HQ30 portable meter on site. Additional chemical analyses were performed in the laboratory: concentration of total nitrogen (TN) according to Eaton et al. (2005); total phosphorus (TP) and orthophosphate (soluble reactive phosphorus, SRP) according to Murphy and Riley (1962) and Mackereth, Heron and Talling (1989), respectively; TOC, DOC and CDOM according to Balogh, Németh and Vörös (2009); chlorophyll a (Chl) according to Wellburn (1994) and bacteriochlorophyll a (Bchl) according to Biel (1986). Microscopy The abundance and composition of autotrophic picoplankton (APP) was determined according to MacIsaac and Stockner (1993) with an Olympus BX51 epifluorescence microscope at 1000× magnification using blue–violet (U-MWBV2) and green (U-MWG2) excitation light. This allowed us to distinguish between two (phycoerythrin- and phycocyanin-rich) types of picocyanobacteria and pico-sized eukaryotic algae. Twenty fields (∼400 cells) were photographed with an Olympus DP71 colour camera, and cells were counted on the images to avoid fluorescence fading. Abundance of infrared-fluorescent, bacteriochlorophyll-containing cells was determined on the same fields photographed with an Olympus XM10 infrared camera using blue (350–550 nm) excitation light according to Jiao, Zhang and Chen (2006). Nano- and microplankton (abbreviated simply with NP) samples were fixed with Lugol's solution, their abundance and composition (based on morphospecies identification) was determined with an inverted microscope (Utermöhl 1958). Total biovolume of the nano-, micro- and picoplankton was calculated on the basis of cell volume and abundance values. Biomass (wet weight) was estimated from the total biovolume of the fractions assuming a specific gravity of 1.0 g/cm3. Heterotrophic bacteria were enumerated following staining with DAPI according to Hobbie, Daley and Jasper (1977) with an Olympus BX51 epifluorescence microscope at 1000× magnification using ultraviolet (UV-MNU2) excitation light. Twenty fields (∼400 cells) were photographed with an Olympus DP71 colour camera and bacterial cells were counted on the images. Next-generation DNA sequencing From each water sample, 200 ml was filtered through a 0.22 μm pore-size filter (Millipore, Billerica, USA), and the filters were stored at −20°C until the community DNA isolation started. Total genomic DNA extraction, PCR amplification of the 16S rRNA gene and sequencing were performed as described in detail by Szabó et al. (2017). Briefly, the 16S rRNA gene was amplified with universal bacterial primers S-D-Bact-0341-b-S-17 forward (5΄-CCT ACG GGN GGC WGC AG-3΄) and S-D-Bact-0785-a-A-21 reverse (5΄-GAC TAC HVG GGT ATC TAA TCC-3΄) according to Klindworth et al. (2013). Quality control of the amplicons was carried out using a model 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Emulsion PCR, amplicon library processing and pyrosequencing were performed on a GS Junior sequencing platform according to the Lib-L protocol of the manufacturer (Roche/454 Life Sciences). Raw sequence data have been deposited to the NCBI Sequence Read Archive and accessible through the BioProject accession number PRJNA385391. Bioinformatic and statistical analyses Bioinformatic analysis of the resulting sequence reads were carried out with mothur (Schloss et al.2009) as described in detail by Szabó et al. (2017). Cluster analysis (CA) was performed based on operation taxonomic units (OTUs) using the PAST software (Hammer, Harper and Ryan 2001). OTUs were generated using 97% 16S rRNA gene sequence similarity, corresponding to the prokaryotic species-level threshold according to Tindall et al. (2010). Alpha diversity (estimated using the Shannon-Wiener and Inverse Simpsons's (1/D) diversity indices) and species richness values (using the Chao1 and the ACE richness metrics) of the bacterioplankton communities were calculated using mothur, while CA, diversity indices and species richness of algal communities were calculated based on phytoplankton biomass data using the PAST software. Relationships between environmental variables and bacterial or algal community composition were revealed by principal component analysis (PCA) ordination combined with vector fitting. Environmental variables were fitted as vectors with ‘envfit’ function (package vegan, Oksanen et al.2016) onto the PCA ordination of bacterial OTUs or algal biomass data, and the significance of fittings was tested with random permutations in program R (R Development Core Team 2016). Similarity percentage (SIMPER) method (Clarke 1993) was used in the PAST software to identify which bacterial or algal community members have the largest effect on sample separation. RESULTS Physical and chemical characteristics of Lake Kolon water Sampling sites had similar physical and chemical characteristics regarding most of the measured parameters. However, open-water samples (OS and OM) were characterised by higher DO content (Fig. 2), and the sample BB had lower pH, DO concentration and higher concentration of bacteriochlorophyll a and inorganic nutrients, namely TP and SRP (Table 2). The temperature of the water body varied between 8.9°C and 9.9°C (therefore it was omitted from the subsequent statistical analysis), and the pH was around neutral. The water colour value (Pt units) ranged between 124 and 273 mg l−1. Algal biomass was moderately low with chlorophyll a concentration between 5 and 10 μg l−1 excepting the reed sampling site (RS), where higher value was found (Table 2). Figure 2. View largeDownload slide Depth-specific changes of dissolved oxygen content at the sampling sites of Lake Kolon. For site codes, see Table 1. Figure 2. View largeDownload slide Depth-specific changes of dissolved oxygen content at the sampling sites of Lake Kolon. For site codes, see Table 1. Table 2. Limnological characteristics of the water samples collected from Lake Kolon. Sample code OS OM RS BS BM BB LS LM LB Temperature (°C) 9.8 9.7 9.9 9.0 8.9 9.0 9.8 9.0 8.9 pH 7.48 7.62 7.11 7.10 7.26 6.88 7.81 7.55 7.29 Conductivity (μS cm−1) 482 494 388 510 523 769 423 382 363 DO (mg l−1) 7.16 7.05 3.39 3.79 3.53 0.44 3.31 2.43 2.49 TN (mg l−1) 1.17 1.19 1.78 1.33 1.24 1.78 1.75 1.11 1.32 TP (μg l−1) 29.5 20.7 40.2 14.6 30.5 80.8 27.1 25.9 25.3 SRP (μg l−1) 2.97 3.19 4.44 4.21 3.16 13.1 2.96 4.28 3.76 TOC (mg l−1) 20.8 22.5 29.4 28.3 28.0 32.6 25.4 21.3 22.4 DOC (mg l−1) 20.4 21.5 23.2 27.8 25.8 30.1 20.9 19.2 19.8 CDOM (mg l−1) 124 126 163 210 204 272 163 158 154 Chl (μg l−1) 5.96 7.09 21.7 6.67 7.15 67.7* 9.93 5.96 5.10 Bchl (μg l−1) <0.01 <0.01 <0.01 <0.01 <0.01 8.4 <0.01 <0.01 <0.01 NP (μg l−1) 700 647 1493 706 1122 336 859 467 208 APP (μg l−1) 15 12 <0.01 <0.01 <0.01 <0.01 2 8 4 PCya (104 cells ml−1) 2.86 1.43 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 PEuk (104 cells ml−1) <0.01 0.22 0.11 <0.01 <0.01 <0.01 0.09 0.37 0.22 BC (104 cells ml−1) 53.1 58.2 85.3 46.1 41.2 278.7 <0.01 74.3 51.1 DAPI (106 cells ml−1) 1.91 2.86 2.21 1.11 2.06 6.82 2.67 2.65 2.11 Sample code OS OM RS BS BM BB LS LM LB Temperature (°C) 9.8 9.7 9.9 9.0 8.9 9.0 9.8 9.0 8.9 pH 7.48 7.62 7.11 7.10 7.26 6.88 7.81 7.55 7.29 Conductivity (μS cm−1) 482 494 388 510 523 769 423 382 363 DO (mg l−1) 7.16 7.05 3.39 3.79 3.53 0.44 3.31 2.43 2.49 TN (mg l−1) 1.17 1.19 1.78 1.33 1.24 1.78 1.75 1.11 1.32 TP (μg l−1) 29.5 20.7 40.2 14.6 30.5 80.8 27.1 25.9 25.3 SRP (μg l−1) 2.97 3.19 4.44 4.21 3.16 13.1 2.96 4.28 3.76 TOC (mg l−1) 20.8 22.5 29.4 28.3 28.0 32.6 25.4 21.3 22.4 DOC (mg l−1) 20.4 21.5 23.2 27.8 25.8 30.1 20.9 19.2 19.8 CDOM (mg l−1) 124 126 163 210 204 272 163 158 154 Chl (μg l−1) 5.96 7.09 21.7 6.67 7.15 67.7* 9.93 5.96 5.10 Bchl (μg l−1) <0.01 <0.01 <0.01 <0.01 <0.01 8.4 <0.01 <0.01 <0.01 NP (μg l−1) 700 647 1493 706 1122 336 859 467 208 APP (μg l−1) 15 12 <0.01 <0.01 <0.01 <0.01 2 8 4 PCya (104 cells ml−1) 2.86 1.43 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 PEuk (104 cells ml−1) <0.01 0.22 0.11 <0.01 <0.01 <0.01 0.09 0.37 0.22 BC (104 cells ml−1) 53.1 58.2 85.3 46.1 41.2 278.7 <0.01 74.3 51.1 DAPI (106 cells ml−1) 1.91 2.86 2.21 1.11 2.06 6.82 2.67 2.65 2.11 Abbreviations: DO, dissolved oxygen; TN, total nitrogen; TP, total phosphorus; SRP, soluble reactive phosphorus (orthophosphate); TOC, total organic carbon; DOC, dissolved organic carbon; CDOM, coloured dissolved organic matter as colour; Chl, chlorophyll a concentration; Bchl, bacteriohlorophyll a; NP, nano- and microphytoplankton biomass; PCya, abundance of picocyanobacteria; PEuk, abundance of picoplanktonic eukaryotic algae; BC, abundance of bacteriochlorophyll-containing bacteria; DAPI, abundance of total bacteria. Asterisk marks sample where the majority of the measured Chl was bacteriochlorophyll c. For sample codes, see Table 1. View Large Phytoplankton community composition of Lake Kolon Phytoplankton biomass (wet weight) varied between 200 and 1500 μg l−1 (Table 3; Fig. 3B). The highest values were detected at the reed- and at one of the bladderwort-dominated sampling sites (sample RS, BM), while the lowest biomass values were found at the bottom of the bladderwort- and water-lily-dominated sampling sites (samples BB and LB). Vertical decrease of the phytoplankton biomass corresponded well to the DO concentration pattern, particularly at the bladderwort-dominated sampling site. Biomass of APP was negligible in all samples (Table 2). At the majority of the sampling sites, phytoplankton was dominated by small cryptophytes (Cryptomonas sp.); however, significant contribution of heterokont flagellates (Dinobryon divergens) was observed at the open-water and the water-lily-dominated sampling sites (Table 3; Fig. 3). Euglenophytes (Euglena acus, Phacus pyrum and Strombomonas sp.) had also a significant contribution at the surface and middle layers of the bladderwort-dominated sampling sites as well as that of the water-lily-dominated sampling site. Oxygen-depleted, bottom layer of the bladderwort-dominated sampling site (sample BB) differed significantly from the other sites showing almost exclusive dominance of small-sized chrysoflagellates (Heterokontophyta). Table 3. Percentage distribution of major phytoplankton species detected by microscopy in different habitats of Lake Kolon. For site codes, see Table 1. View Large Figure 3. View largeDownload slide Taxonomic composition of phytoplankton communities in Lake Kolon at the phylum (A) and species level (B) based on microscopy data. For sample codes, see Table 1. Figure 3. View largeDownload slide Taxonomic composition of phytoplankton communities in Lake Kolon at the phylum (A) and species level (B) based on microscopy data. For sample codes, see Table 1. Bacterioplankton community composition of Lake Kolon A total of 51 757 high-quality bacterial 16S rRNA gene sequences were obtained from the samples by NGS. Good's coverage values and rarefaction curves (Table 4; Suppl. Fig. 1) showed that sequencing depth was sufficient to recover all major taxa. Table 4. Bacterial species richness (ACE and Chao1) and diversity indices [Inverse Simpsons's (1/D) and Shannon-Wiener] calculated from NGS data, and algal diversity indices [Simpson (1-D), Shannon (H)] calculated from algal biomass data of Lake Kolon water. aNumbers in parentheses stand for the total number of high-quality sequences obtained with NGS; for calculating richness estimators and diversity indices, read numbers were subsampled to the read number of the sample having the lowest sequence count. bNumbers in parentheses stand for the lower and upper limits of 95% confidence intervals. For sample codes, see Table 1. View Large At phylum level, dissimilar bacterial communities were found at the sampling sites (Fig. 4A). All samples were dominated by members of phyla Proteobacteria (36%–72%), Bacteroidetes (12%–33%) and Actinobacteria (5%–26%), but in sample BB the ratio of Chlorobi (54%) was also considerable. Within Proteobacteria, higher percentages of taxa affiliated with classes Beta- and Gammaproteobacteria were present in the open-water samples and in those that were collected from the bladderworth-dominated inner lake, while in addition to these classes, Deltaproteobacteria were also found in high abundance at the water-lily-dominated site, whereas classes Alpha- and Betaproteobacteria were the most numerous in the samples collected from the reed belt. Figure 4. View largeDownload slide Taxonomic composition of bacterioplankton communities in Lake Kolon at the phylum (A) and genus level (B) based on NGS data. Chloroplast reads were excluded from the dataset. Note that, in the case of sample BB, DAPI cell counts were much higher than in the case of other samples (see Table 2) due to the high abundance of genus Chlorobium. In Fig. 4A, class level distribution is shown for phylum Proteobacteria. Taxa not identified at the genus level are indicated by an asterisk and their highest taxonomic identification. For sample codes, see Table 1. Figure 4. View largeDownload slide Taxonomic composition of bacterioplankton communities in Lake Kolon at the phylum (A) and genus level (B) based on NGS data. Chloroplast reads were excluded from the dataset. Note that, in the case of sample BB, DAPI cell counts were much higher than in the case of other samples (see Table 2) due to the high abundance of genus Chlorobium. In Fig. 4A, class level distribution is shown for phylum Proteobacteria. Taxa not identified at the genus level are indicated by an asterisk and their highest taxonomic identification. For sample codes, see Table 1. Table 5 shows the 10 most abundant cultivated genera in the nine samples analysed by NGS, while in Fig. 4A all major detected genera are depicted. Rhodoluna, Polynucleobacter, Limnohabitans, Flavobacterium and ‘unclassified Actinobacteria (hgcl clade)’ were abundant in all samples. Genera Bacteriovorax, Methylobacter and Limnohabitans were detected as characteristic taxa of the water-lily-dominated inner lake. Genera Crenothrix and Methylocaldum were only identified in the open-water samples. ‘Unclassified Methylococcales (CABC2E06)’ were abundant in the upper layers (samples BS and BM) of the bladderwort-dominated inner lake and the water-lily-dominated inner lake. Amount of ‘unclassified Rhizobiales’ was significant in the sample taken from the surface layer of the reed belt (sample RS). Different community was found at the deep region of the bladderwort-dominated sampling sites (sample BB) with representatives of genera Chlorobium, ‘unclassified Chlorobiaceae’, ‘unclassified Desulfuromonadales’, ‘unclassified Parcubacteria (OD1)’ and ‘unclassified Bacteriodetes’. Table 5. Percentage distribution of major bacterial genera having cultured representatives which were detected by NGS in different habitats of Lake Kolon. Metabolic type: CO, chemoorganotrophic; R, respiratory type of metabolism; PR, strong proteolytic activity; M, degradation of macromolecules; LA, lithoautotrophic; ME, methanotrophic/methylotrophic; Relation to oxygen: (s)AN, (strictly) anaerobic; (s)AE, (strictly) aerobic; fAN, facultatively anaerobic. For site codes, see Table 1. View Large Microbial diversity in Lake Kolon Number of observed species and species richness estimators (Chao1 and ACE) showed the highest bacterial and algal α-diversity in sample LM (water-lily, medium depth) and the lowest in sample BM (bladderwort, medium depth). Bacterial diversity indices had the highest values in samples collected from the open-water site (OS and OM), while the highest algal diversity was observed in sample LM. Algal and bacterial communities had the lowest diversity values in sample BB (taken from the anoxic deeper region of the bladderwort-dominated inner lake) (Table 4). Exploratory data analysis Similarity among the bacterioplankton and the phytoplankton communities at different sampling sites was revealed by CA (Fig. 5). CA clearly showed horizontal shifts in the bacterial community composition within the lake, since samples characterised by the same type of macrophyte stand clustered into four major group (45% similarity). Lower dissimilarities were observed by different water depth (Fig. 5A). Furthermore, the composition of algal communities was also determined by the macrophytes (Fig. 5B). The anoxic bladderwort-dominated sample (sample BB) was remarkably distinct from others in the case of both the bacterio- and phytoplankton. Figure 5. View largeDownload slide Comparison of Lake Kolon bacterioplankton (A) and phytoplankton (B) communities with cluster analysis based on NGS and microscopy data. Cluster analysis was calculated using the unweighted-pair group mean averages and the Bray–Curtis similarity index. In the case of NGS data, OTUs used for the analysis were generated with 97% 16S rRNA gene sequence similarity level. Bootstrap values are given at the nodes. For sample codes, see Table 1. Figure 5. View largeDownload slide Comparison of Lake Kolon bacterioplankton (A) and phytoplankton (B) communities with cluster analysis based on NGS and microscopy data. Cluster analysis was calculated using the unweighted-pair group mean averages and the Bray–Curtis similarity index. In the case of NGS data, OTUs used for the analysis were generated with 97% 16S rRNA gene sequence similarity level. Bootstrap values are given at the nodes. For sample codes, see Table 1. PCA (Fig. 6) confirmed the results of CA. Significantly fitted environmental variables were plotted onto the PCA ordinations of the bacterial and algal communities. Figure 6A shows that the most unique community was found in sample BB, which was separated from the other samples along axis PC1. This axis correlated positively with the changes in DAPI, CDOM and SRP. The other bacterioplankton communities were separated along axis PC2 according to their sampling sites. Figure 6B shows that biomass of the three dominant phytoplankton species correlated with the distribution of limnological variables. Algal communities in water-lily-dominated and open-water sites separated from the other samples. Figure 6. View largeDownload slide PCA ordination of the (A) bacterial and (B) algal communities of Lake Kolon based on NGS and microscopy data. Community members, contributing at least 2% or 10% (in case of bacteria or algae, respectively) to sample separation based on SIMPER analysis, are shown with black arrows on the biplot. Fitted environmental variables appear as red arrows, where asterisks denote the significance of fitting (‘***’P < 0.001, ‘**’P < 0.01, ‘*’P < 0.05 ‘.’P < 0.1). For sample codes, see Table 1. Figure 6. View largeDownload slide PCA ordination of the (A) bacterial and (B) algal communities of Lake Kolon based on NGS and microscopy data. Community members, contributing at least 2% or 10% (in case of bacteria or algae, respectively) to sample separation based on SIMPER analysis, are shown with black arrows on the biplot. Fitted environmental variables appear as red arrows, where asterisks denote the significance of fitting (‘***’P < 0.001, ‘**’P < 0.01, ‘*’P < 0.05 ‘.’P < 0.1). For sample codes, see Table 1. DISCUSSION To the best of our knowledge, this is the first work comparing total bacterial and algal communities inhabiting the inner ponds dominated by three different macrophyte stands of the same freshwater lake using high-throughput methods. Based on the observed environmental parameters and obtained microscopy and pyrosequencing data, our results clearly supported that the absence, presence and the type of the macrovegetation determined the planktonic microbial communities. Differences of the bacterial communities within a lake might be explained by several environmental factors, and one of those could be the compounds originating from the macrovegetation (Enriquez, Duarte and Sand-Jensen 1993). Our sampling sites were characterised by three different macrophyte species, which have different nutrient content and C/N, C/P ratios (Table 6). The high nutrient content of plant detritus could decay rapidly because of the associated heterotrophic microbial populations (Enriquez, Duarte and Sand-Jensen 1993). This could contribute significantly to the divergent microbial communities observed at different macrophyte-dominated sites of Lake Kolon. In addition, some of the compounds deriving from vascular plants could change the environmental factors, such as light (chromophoric substances), and affect others, e.g. oxygen conditions (by suppressing algae or stimulating aerobic heterotrophs) (Wetzel 2001). On the other hand, some plant species could release allelochemicals (Wetzel 2001) against microorgansisms (Fossen, Larsen and Andersen 1998; Cisowska, Wojnicz and Hendrich 2011). Table 6. Average elemental composition of aquatic plants characteristic in Lake Kolon (based on literature data). All data are expressed on a dry weight basis. C% N% P% C:N C:P Organ Reference Utricularia vulgaris 41.8 2.5 0.19 17 220 Shoot Adamec (1992), Hornibrook et al. (2000) Nymphea alba 44.5 2.5 0.09 18 494 Leaf Newman et al. (2004), Mackie et al. (2005) Phragmites australis 47.5 0.3 0.03 158 1583 Shoot Van der Valk (1991) C% N% P% C:N C:P Organ Reference Utricularia vulgaris 41.8 2.5 0.19 17 220 Shoot Adamec (1992), Hornibrook et al. (2000) Nymphea alba 44.5 2.5 0.09 18 494 Leaf Newman et al. (2004), Mackie et al. (2005) Phragmites australis 47.5 0.3 0.03 158 1583 Shoot Van der Valk (1991) View Large Average amount of nutrients (TP and TN) and chlorophyll a content of the samples referred to a meso-eutrophic water type (Wetzel 2001). Coloured dissolved organic matter (CDOM) concentration (Pt units) ranged between 124 and 273 mg l−1 at the sites, based on these values, Lake Kolon had highly coloured water (>100 Pt units) according to the classification of Hessen and Tranvik (1998). CDOM most probably originated from decomposing macrophytes, since samples were collected after the vegetation period (however it should be noted that standing stocks of reed are continuously present in the lake). Additionally, Lake Kolon has no inflow, like brooks, therefore DOC present in lake water has almost exclusively autochthonous origin. Balogh et al. (2006) studied a similar environment (Kis-Balaton reservoir) in the same biogeographical region, which had shallow water (1–1.5 m depth) and was covered with reed. Their experiments, using a stable carbon isotopic technique, showed that 1 g of reed leaf produced at least 20 mg DOC and 200 mg Pt-colour under aerobic conditions, while anaerobic decomposition resulted in 30 mg DOC and 200 mg Pt-colour. Since moderate algal biomass was present in the samples collected from Lake Kolon (chlorophyll a concentration ranged from 5 to 10 μg l−1), humic substances (and other compounds from decaying plant material) could be available as the major energy and carbon source for planktonic bacteria (Moran and Hodson 1990). Pyrosequencing results (Fig. 4) showed that samples contained several bacterial taxa which are able to utilise plant degradation products or humic substances. Representatives of phylum Bacteroidetes are mainly chemoorganotrophic bacteria that consume various forms of organic matter (Krieg et al.2010), while freshwater pelagic Actinobacteria were selectively favoured by the addition of allochthonous DOC or humic material (Rosenberg 2013). Common planktonic freshwater genera, such as Rhodoluna, Polynucleobacter, Limnohabitans and ‘unclassified Actinobacteria (hgcl clade)’, were abundant in all samples. Flavobacterium is a typical genus which is capable to degrade macromolecules (Krieg et al.2010). Members of genus Polynuclebacter might utilise photodegradation products of humic substances in aerobic humic-rich habitats (Jezberová et al.2010), but some free-living Polynucleobacter similar to Limnohabitans might rely on substrates derived from algal primary production. Limnohabitans prefer monosaccharides (like fructose, glucose and mannose) and certain amino acids (like L-alanine) contrary to some members of Polynucleobacter (Jezbera et al.2012). Differences in the taxonomic composition of microbial communities among sampling sites were unequivocally observed, which were more conspicuous at the genus level compared to phylum-level differences (Fig. 4). The highest dissimilarities of bacterioplankton communities were detected in the case of comparing the bladderwort-dominated site with the others. The deep region of the bladderwort-dominated sampling site (BB) was found to be different having lower pH and DO concentration, higher concentration of bacteriochlorophyll a and higher nutrient content, namely TP and orthophosphate (Table 3). This latter could be explained with the observation that under experimental conditions Utricularia release its phosphorus content completely within 30 days, and even at low temperature (8°C) 25% of TP from the decomposing plant could be released into the water (Kovács and Istvánovics 1994). Additionally, 60%–80% of its phosphorus content is orthophosphate (Kovács and Istvánovics 1994) which is easily consumed by aquatic microorganisms (Sigee 2005). Furthermore, its relative phosphorus content is the highest among the three major plant species present in Lake Kolon (Table 6). The low oxygen content of sample BB could be explained with the low light intensity (virtually no phytoplanktonic oxygen release, Fig. 2), with the large amount of macrophyte-derived dissolved organic matter (high rate of microbial respiration, Vörös 1994) and possibly with the internal trap structures of Utricularia which are able to consume the O2 rapidly and therefore may cause anoxia (Adamec 2011). The different physical and chemical parameters and the higher P content of Utricularia may explain that the most unique community was found at the deep region of the bladderwort-dominated sampling site (sample BB) with representatives of genera Chlorobium, ‘unclassified Chlorobiaceae’, ‘unclassified Desulfuromonadales’, ‘unclassified Parcubacteria (OD1)’ and ‘unclassified Bacteriodetes’. Sulphate-reducing Desulfuromonadales (Brenner, Krieg and Staley 2005), BChl-a-containing, green sulphur Chlorobiaceae and Chlorobium grow under anoxic conditions (Rosenberg 2013). Parcubacteria and Bacteroidetes are mostly anaerobic; Parcubacteria has small, reduced genomes and possibly a symbiotic lifestyle (Nelson and Stegen 2015), while Bacteroidetes (as mentioned above) may utilise proteins and other substrates (Krieg et al.2010). Methylotrophs (including methanotrophs), such as Crenothrix, Methylocaldum and Methylobacter, represented approximately 10% of the bacterioplankton community in almost all samples (Table 5); however, they were practically absent in the bladderwort-dominated inner pond. A possible explanation for this observation is that the large amount of humic compounds derived from decomposing aquatic macrophytes could be used as terminal electron acceptors in the process of anaerobic microbial respiration which may competitively suppress methane formation (Klüpfel et al.2014). The relative abundance of many genera was below 6% in each sample, implying high bacterial diversity in the samples. Diversity of microbial communities was corresponded with the presence and the type of dominant macrophytes. The availability of carbon sources could have a profound effect on the microbial community structure and biodiversity in humic shallow lakes (Sigee 2005). Sample BB with the lowest bacterial species number had highest level of orthophosphate, and therefore the growth of some bacterial species sensitive to anoxic condition and high levels of orthophosphate might be restrained, which could reduce the bacterial diversity in the samples (Margalef 1958). Similarly, fluctuating environmental conditions (e.g. wind-driven turbulence) and low nutrient content might result an increased diversity in the open-water site (Wu et al.2007). In macrophyte-absent areas of shallow lakes, wind-driven turbulence is more intense than in macrophyte-covered sites (Jeppesen et al.2012) since aquatic higher plants have a calming influence on sediment resuspension and on other wind-driven process. Sediment particles in the water column usually lead to spatial and chemical heterogeneity in the open-water area (Simon et al.2002), which create further ecological niches for planktonic bacteria (Wu et al.2007), and as a result increasing the observed species richness and diversity. The relationship between bacterial communities and aquatic plants has been studied previously, although we found only few detailed research studies, which were performed with mostly low-throughput analyses or were based on microcosm experiments, and focused on other macrophyte species. Huss and Wehr (2004) conducted micro- and mesocosm experiments to study the possible effects of Vallisneria americana (water-celery) on bacterial growth and water chemistry in the mesotrophic Calder Lake (USA). They concluded that the submersed macrophyte exerts a strong, indirect effect on the bacterial community by changing nutrient status and/or suppressing algal communities. The other site studied in this regard was the eutrophic, shallow Lake Taihu (China), where different macrophytes cover distinct parts of the lake, and it has been observed that aquatic plants can influence the total bacterioplankton community (Wu et al.2007; Zeng et al.2012) and the denitrifiers within the bacterioplankton and epiphyton (Fan et al.2016). Zhao et al. (2013) reported from the same lake that submerged macrophytes (Ceratophyllum demersum, Potamogeton crispus and Vallisneria natans) can modify also the bacterial community composition in the sediment. Hempel et al. (2008) compared the composition of epiphytic bacteria on two common aquatic macrophytes (the macroalga Chara aspera and the angiosperm Myriophyllum spicatum) from two habitats: the freshwater Lake Constance (Central Europe) and the brackish Schaproder Bodden (Baltic Sea). Their results showed that the plant (in this case a substrate of bacterial biofilm) and habitat had a combined impact on the bacterial community composition which might be also affected by the polyphenol content of the plant. Nevertheless, macrovegetation could also strongly influence the composition and biomass of phytoplankton (Wetzel 2001), which presumably affect the bacterial communities (Grossart and Simon 2007). In the open-water and the water-lily-dominated samples, Dinobryon, a typical planktonic alga, was the most abundant. Since the majority of water-lily leaves had been decayed until the time of sampling, for algae similar conditions were present there as in the open-water site. At almost all sites, Cryptomonas was a dominant member of the phytoplankton community, this alga prefers habitats with high organic matter content that might derive even from the decomposing macrophytes in our case. Our phytoplankton results could be compared with the microscopy data obtained from Lake Fertő (Lake Neusiedl, Austria/Hungary) (Somogyi et al.2010). Lake Fertő is a large, shallow, alkaline, meso-eutrophic lake with a turbid open-water area, and similarly to Lake Kolon, it also has reed-belt-enclosed brown-water inner ponds. Comparing the taxonomic composition of phytoplankton inhabiting the two lakes, Heterokontophyta and Cryptophyta were characteristic members of the communities, and genus Cryptomonas was also frequent in Lake Fertő. In the case of Lake Fertő, based on the analysis of Somogyi et al. (2010), samples taken from the reed belt (artificial canal) clearly separated from the open-water sites, similarly to the results obtained from Lake Kolon. Unfortunately, no further comparison is possible, since planktonic algal communities in Lake Fertő were dominated by picophytoplankton (representing up to 80% of total phytoplankton biomass) which was negligible in Lake Kolon, and the taxonomic composition of this group could be revealed only with DNA sequencing. Furthermore, the only data available on the composition of Lake Fertő bacterioplankton were obtained by cultivation-based methods (Borsodi, Farkas and Kurdi 1998), which also hinders a detailed comparison. However, it was confirmed that macrophytes are the main carbon source of bacterioplankton in that ecosystem (Reitner, Herzig and Herndl 1999). CONCLUSION This is the first comprehensive study, which demonstrated that the composition of algal and bacterial communities in a meso-eutrophic, shallow freshwater lake was significantly altered by the macrophyte cover. Since most of the measured environmental parameters of the samples were similar, the main difference among sampling sites was the species of the dominant macrophyte stands. We observed that freshwater microbial communities (including both bacteria and algae) are not only determined by the presence or absence of aquatic higher plants, but the type of macrophyte also controls their composition. A higher biogenic nutrient concentration present in macrophytes is associated with higher decomposition rate (Enriquez, Duarte and Sand-Jensen 1993). Bladderwort has higher phosphorus content and lower C/N ratio; therefore, it may be decomposed more quickly than water-lily or reed. The resulted large amount of organic matter caused anoxia in the waterbody at the bladderwort-dominated area, which impacted negatively the diversity of bacterioplankton. Additionally, some compounds derived from aquatic plant species may act as antimicrobial agents against bacteria, e.g. water-lily produces anthocyanins (Fossen, Larsen and Andersen 1998), and due to their selective action (Cisowska, Wojnicz and Hendrich 2011) such compounds could also have structuring effect on the bacterial and algal community in aquatic ecosystems. In spite of the low water temperature, these differences were also clearly observable in Lake Kolon, possibly because of the fact that samples were collected after the vegetation period, i.e. huge amount of decaying plant biomass was available in the water. SUPPLEMENTARY DATA Supplementary data are available at FEMSEC online. Acknowledgements The authors are thankful to Laura Jurecska for her useful advice regarding chemical measurements, and to Tímea Szabó and Balázs Németh for their help during sampling. FUNDING This work was financially supported by the National Research, Development and Innovation Office (grant no. K116275 and PD112449). Purchase of equipment was financed by the National Development Agency (grant no. KMOP-4.2.1/B-10-2011-0002 and TÁMOP-4.2.2/B-10/1-2010-0030). The work of AM was supported through the New National Excellence Program of the Ministry of Human Capacities (Hungary). BS and TF were supported by the Bolyai János Research Grant (Hungarian Academy of Sciences). Conflict of interest. None declared. REFERENCES Adamec L. Mineral nutrition of carnivorous plants: a review. Ekol Pol 1992; 40: 147– 92. Adamec L. The smallest but fastest. Ecophysiological characteristics of traps of aquatic carnivorous Utricularia. Plant Sign Behav 2011; 6: 640– 6. Google Scholar CrossRef Search ADS Balogh KV, Présing M, Vörös L et al. A study of the decomposition of reed (Phragmites australis) as a possible source of aquatic humic substances by measuring the natural abundance of stable carbon isotopes. Internat Rev Hydrobiol 2006; 91: 15– 28. Google Scholar CrossRef Search ADS Balogh KV, Németh B, Vörös L. Specific attenuation coefficients of optically active substances and their contribution to the underwater ultraviolet and visible light climate in shallow lakes and ponds. Hydrobiology 2009; 632: 91– 105. Google Scholar CrossRef Search ADS Biel AJ. Control of bacteriochlorophyll accumulation by light in Rhodobacter capsulatus. J Bacteriol 1986; 168: 655– 9. Google Scholar CrossRef Search ADS PubMed Borsodi AK, Farkas I, Kurdi P. Numerical analysis of planktonic and reed biofilm bacterial communities of Lake Fertő (Neusiedlersee, Hungary/Austria). Water Res 1998; 32: 1831– 40. Google Scholar CrossRef Search ADS Brenner DJ, Krieg NR, Staley JT. The proteobacteria. In: Garrity GM (ed). Bergey's Manual of Systematic Bacteriology , 2nd ed. New York, USA: Springer, 2005. Cisowska A, Wojnicz D, Hendrich AB. Anthocyanins as antimicrobial agents of natural plant origin. Nat Prod Commun 2011; 6: 149– 56. Google Scholar PubMed Clarke KR. Non-parametric multivariate analysis of changes in community structure. Aust J Ecol 1993; 18: 117– 43. Google Scholar CrossRef Search ADS Eaton AD, Clesceri LS, Rice EW et al. Standard Methods for the Examination of Water and Wastewater , 21st ed. Washington, DC, USA: APHA, 2005. Enriquez S, Duarte CM, Sand-Jensen K. Patterns in decomposition rates among photosynthetic organisms: the importance of detritus C:N:P content. Oecologia 1993; 94: 457– 71. Google Scholar CrossRef Search ADS PubMed Fan Z, Han RM, Ma J et al. Submerged macrophytes shape the abundance and diversity of bacterial denitrifiers in bacterioplankton and epiphyton in the shallow fresh Lake Taihu, China. Env Sci Pollut Res 2016; 23: 14102– 14. Google Scholar CrossRef Search ADS Fossen T, Larsen Å, Andersen ØM. Anthocyanins from flowers and leaves of Nymphaéa × marliacea cultivars. Phytochemistry 1998; 48: 823– 7. Google Scholar CrossRef Search ADS Grossart HP, Simon M. Interactions of planktonic algae and bacteria: effects on algal growth and organic matter dynamics. Aquat Microb Ecol 2007; 47: 163– 76. Google Scholar CrossRef Search ADS Hahn MW, Lang E, Brandt U et al. Emended description of the genus Polynucleobacter and the species P. necessarius and proposal of two subspecies, P. necessarius subspecies necessarius subsp. nov. and P. necessarius subsp. a symbioticus subsp. nov. Int J Syst Evol Microbiol 2009; 59: 2002– 9. Google Scholar CrossRef Search ADS PubMed Hahn MW, Schmidt J, Taipale SJ et al. Rhodoluna lacicola gen. nov., sp. nov., a planktonic freshwater bacterium with stream-lined genome. Int J Syst Evol Microbiol 2014; 64: 3254– 63. Google Scholar CrossRef Search ADS PubMed Hammer Ø, Harper DAT, Ryan PD. Past paleontological statistics software package for education and data analysis. Palaeontol Electron 2001; 4: 9. Hempel M, Blume M, Blindow I et al. Epiphytic bacterial community composition on two common submerged macrophytes in brackish water and freshwater. BMC Microbiol 2008; 8: 58. Google Scholar CrossRef Search ADS PubMed Hessen DO, Tranvik LJ. Aquatic Humic Substances: Ecology and Biogeochemistry . Berlin: Springer, 1998. Google Scholar CrossRef Search ADS Hobbie JE, Daley RJ, Jasper S. Use of nucleopore filters for counting bacteria by fluorescence microscopy. Appl Environ Microb 1977; 33: 1225– 8. Hornibrook ERC, Longstaffe FJ, Fyfe WS et al. Carbon-isotope ratios and carbon, nitrogen and sulfur abundances in flora and soil organic matter from a temperate-zone bog and marsh. Geochem J 2000; 34: 237– 45. Google Scholar CrossRef Search ADS Huss AA, Wehr JD. Strong indirect effects of a submersed aquatic macrophyte, Vallisneria americana, on bacterioplankton densities in a mesotrophic lake. Microb Ecol 2004; 47: 305– 15. Google Scholar CrossRef Search ADS PubMed Jeppesen E, Sondergaard M, Sondergaard M et al. (eds). Nutrient dynamics, sedimentation, and resuspension. In: The Structuring Role of Submerged Macrophytes in Lakes , vol. 131. USA, Germany: Springer Science & Business Media, 2012. Jezbera J, Jezberová J, Koll U et al. Contrasting trends in distribution of four major planktonic betaproteobacterial groups along a pH gradient of epilimnion of 72 freshwater habitats. FEMS Microbiol Ecol 2012; 81: 467– 79. Google Scholar CrossRef Search ADS PubMed Jezberová J, Jezbera J, Brandt U et al. Ubiquity of Polynucleobacter necessarius subsp asymbioticus in lentic freshwater habitats of a heterogenous 2000 km2 area. Env Microbiol 2010; 12: 658– 69. Google Scholar CrossRef Search ADS Jiao N, Zhang Y, Chen Y. Time series observation based InfraRed Epifluorescence Microscopic (TIREM) approach for accurate enumeration of bacteriochlorophyll-containing microbes in marine environments. J Microbiol Meth 2006; 65: 442– 52. Google Scholar CrossRef Search ADS Kämpfer P, Busse HJ, Longaric I et al. Pseudarcicella hirudinis gen. nov., sp. nov., isolated from the skin of the medical leech Hirudo medicinalis. Int J Syst Evol Microbiol 2012; 62: 2247– 51 Google Scholar CrossRef Search ADS PubMed Klindworth A, Pruesse E, Schweer T et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res 2013; 41: e1, DOI: 10.1093/nar/gks808. Google Scholar CrossRef Search ADS PubMed Klüpfel L, Piepenbrock A, Kappler A et al. Humic substances as fully regenerable electron acceptors in recurrently anoxic environments. Nat Geosci 2014; 7: 195– 200. Google Scholar CrossRef Search ADS Kovács A, Istvánovics V. A Víz Alá Merült Makrofitonok Szerepe a Kis-Balaton II. Ütemének Foszfor Forgalmában [The Role of Submerged Macrophytes in the Phosphourous Cycle of Kis-Balaton II.] , MHT XII. Siófok: Országos Vándorgyűlése I. kötet, 1994 (in Hungarian). Krieg NR, Staley JT, Brown DR et al. The Bacteroidetes, Spirochaetes, Tenericutes (Mollicutes), Acidobacteria, Fibrobacteres, Fusobacteria, Dictyoglomi, Gemmatimonadetes, Lentisphaerae, Verrucomicrobia, Chlamydiae, and Planctomycetes. In: Garrity GM (ed). Bergey's Manual of Systematic Bacteriology , 2nd ed. New York, USA: Springer, 2010. MacIsaac EA, Stockner JG. Enumeration of phototrophic picoplankton by autofluorescence. In: Kemp PF, Sherr, BF, Sherr, EB et al. (eds). Handbook of Methods in Aquatic Microbial Ecology . Boca Raton, Ann Arbor, London, Tokyo: Lewis Publishers, 1993, 187– 97. Mackereth FJH, Heron J, Talling JF. Water Analysis: Some Revised Methods for Limnologists . Kendal, England: FBA Sci Pub, 1989, 84– 90. Mackie EAV, Leng MJ, Lloyd JM et al. Bulk organic δ13C and C/N ratios as palaeosalinity indicators within a Scottish isolation basin. J Quat Sci 2005; 20: 303– 12. Google Scholar CrossRef Search ADS Mádl-Szőnyi J, Tóth J. A hydrogeological type section for the Duna-Tisza Interfluve, Hungary. Hydrogeol J 2009; 17: 961– 80. Google Scholar CrossRef Search ADS Margalef R. Temporal Succession and Spatial Heterogeneity in Phytoplankton . Berkeley, California, USA: University of California press, 1958. Máthé I, Borsodi AK, Tóth EM et al. Vertical physico-chemical gradients with distinct microbial communities in the hypersaline and heliothermal Lake Ursu (Sovata, Romania). Extremophiles 2014; 18: 501– 14. Google Scholar CrossRef Search ADS PubMed Moran MA, Hodson RE. Bacterial production on humic and nonhumic components of dissolved organic carbon. Limnol Oceanogr 1990; 35: 1744– 56. Google Scholar CrossRef Search ADS Murphy J, Riley JP. A modified single solution method for the determination of phosphate in natural waters. Anal Chim Acta 1962; 27: 31– 36. Google Scholar CrossRef Search ADS Nelson WC, Stegen JC. The reduced genomes of Parcubacteria (OD1) contain signatures of a symbiotic lifestyle. Front Microbiol 2015; 6: 713. Google Scholar CrossRef Search ADS PubMed Newman S, McCormick PV, Miao SL et al. The effect of phosphorus enrichment on the nutrient status of a northern Everglades slough. Wetl Ecol Manag 2004; 12: 63– 79. Google Scholar CrossRef Search ADS Ng HT, Marques DM, Jeppesen E et al. Bacterioplankton in the littoral and pelagic zones of subtropical shallow lakes. Hydrobiologia 2010; 646: 311– 26. Google Scholar CrossRef Search ADS Oksanen J, Blanchet FG, Friendly M et al. vegan: Community Ecology Package . R package version 2.4-0. 2016, https://CRAN.R-project.org/package=vegan (10 October 2016, date last accessed). Paganin P, Chiarini L, Bevivino A et al. Vertical distribution of bacterioplankton in Lake Averno in relation to water chemistry. FEMS Microbiol Ecol 2013; 84: 176– 88. Google Scholar CrossRef Search ADS PubMed R Development Core Team. R. A language and environment for statistical computing . Vienna, Austria: R Foundation for Statistical Computing, 2016. https://www.R-project.org (10 October 2016, date last accessed) Reitner B, Herzig A, Herndl GJ. Dynamics in bacterioplankton production in a shallow, temperate lake (Lake Neusiedl, Austria): evidence for dependence on macrophyte production rather than on phytoplankton. Aquat Microb Ecol 1999; 19: 245– 54. Google Scholar CrossRef Search ADS Rosenberg E. The Prokaryotes , 4th ed. New York, USA: Springer, 2013. Reynolds CS, Huszar V, Kruk C et al. Towards a functional classification of the freshwater phytoplankton. J Plankton Res 2002; 24 (5): 417– 428. Google Scholar CrossRef Search ADS Schloss PD, Westcott SL, Ryabin T et al. Introducing Mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microb 2009; 75: 7537– 41. Google Scholar CrossRef Search ADS Schulten HR. The three-dimensional structure of humic substances and soil organic matter studied by computational analytical chemistry. Fres J Anal Chem , 1995; 351: 62– 73. Google Scholar CrossRef Search ADS Sigee DC. Freshwater Microbiology: Biodiversity and Dynamic Interactions of Microorganisms in the Aquatic Environment . Chichester, UK: John Wiley & Sons, Ltd, 2005. Simon M, Grossart HP, Schweitzer B et al. Microbial ecology of organic aggregates in aquatic ecosystems. Aquat Microb Ecol 2002; 28: 175– 211. Google Scholar CrossRef Search ADS Sollins P, Homann P, Caldwell BA. Stabilization and destabilization of soil organic matter: mechanisms and controls. Geoderma 1996; 74: 65– 105. Google Scholar CrossRef Search ADS Somogyi B, Felföldi T, Dinka M et al. Periodic picophytoplankton predominance in a large, shallow alkaline lake (Lake Fertő/Neusiedlersee). Ann Limnol-Int J Lim 2010; 46: 9– 19. Google Scholar CrossRef Search ADS Stoecker K, Bendinger B, Schöning B et al. Cohn's Crenothrix is a filamentous methane oxidizer with an unusual methane monooxygenase. P Natl Acad Sci USA 2006; 103: 2363– 7. Google Scholar CrossRef Search ADS Szabó A, Korponai K, Kerepesi Cs et al. Soda pans of the Pannonian steppe harbor unique bacterial communities adapted to multiple extreme conditions. Extremophiles 2017; 21: 639– 49. Google Scholar CrossRef Search ADS PubMed Thurman EM. Aquatic humic substances. In: Organic Geochemistry of Natural Waters . Netherlands: Springer, 1985. Google Scholar CrossRef Search ADS Tindall BJ, Rossello-Mora R, Busse H-J et al. Notes on the characterization of prokaryote strains for taxonomic purposes. Int J Syst Evol Microbiol 2010; 60: 249– 66. Google Scholar CrossRef Search ADS PubMed Utermöhl H. Zur Vervolkommnung der quantitativen Phytoplankton Methodik. Mitt Int Ver Theor Angew Limnol 1958; 9: 1– 38. Van der Valk AG. Flooding and the decomposition of litter of four emergent plant species in a prairie wetland. Wetlands 1991; 11: 1– 16. Google Scholar CrossRef Search ADS Vörös L. A fitoplankton és a hínárnövényzet elsődleges termelése a Kis-Balatonban [Primary production of phytoplankton and tangles in Kis-Balaton] , Siófok, Hungary: MHT: XII. Országos Vándorgyűlés kiadványa , 1994. (in Hungarian) Wellburn AR. The spectral determination of chlorophylls a and b, as well as total carotenoids, using various solvents with spectrophotometers of different resolution. J Plant Physiol 1994; 144: 307– 13. Google Scholar CrossRef Search ADS Wetzel RG. Limnology: Lake and River Ecosystems , 3rd ed. San Diego, CA: Academic Press. 2001. Wu QL, Zwart G, Wu J et al. Submersed macrophytes play a key role in structuring bacterioplankton community composition in the large, shallow, subtropical Taihu Lake, China. Env Microbiol 2007; 9: 2765– 74. Google Scholar CrossRef Search ADS Zeng J, Bian Y, Xing P et al. Macrophyte species drive the variation of bacterioplankton community composition in a shallow freshwater lake. Appl Environ Microb 2012; 78: 177– 84. Google Scholar CrossRef Search ADS Zhao DY, Liu P, Fang C et al. Submerged macrophytes modify bacterial community composition in sediments in a large, shallow, freshwater lake. Can J Microbiol 2013; 59: 237– 44. Google Scholar CrossRef Search ADS PubMed © FEMS 2017. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org
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