Integrating Decomposers, Methane-Cycling Microbes and Ecosystem Carbon Fluxes Along a Peatland Successional Gradient in a Land Uplift Region

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Integrating Decomposers, Methane-Cycling Microbes and Ecosystem Carbon Fluxes Along a Peatland Successional Gradient in a Land Uplift Region © Authors, 2021 Published version Juottonen, Heli; Kieman, Mirkka; Fritze, Hannu; Hamberg, Leena; Laine, Anna M.; Merilä, Päivi; Peltoniemi, Krista; Putkinen, Anuliina; Tuittila, Eeva-Stiina Juottonen, H., Kieman, M., Fritze, H., Hamberg, L., Laine, A. M., Merilä, P., Peltoniemi, K., Putkinen, A., & Tuittila, E.-S. (2022). Integrating Decomposers, Methane-Cycling Microbes and Ecosystem Carbon Fluxes Along a Peatland Successional Gradient in a Land Uplift Region. Ecosystems, 25(6), 1249-1264. https://doi.org/10.1007/s10021-021-00713-w 2022 Integrating Decomposers, MethaneCycling Microbes and Ecosystem Carbon Fluxes Along a Peatland Successional Gradient in a Land Uplift Region Heli Juottonen, 1,2 * Mirkka Kieman, 3 Hannu Fritze, 4 Leena Hamberg, 4 Anna M. Laine, 3,5,6 Pa ¨ivi Merila ¨, 7 Krista Peltoniemi, 4 Anuliina Putkinen, 2,8,9 and Eeva-Stiina Tuittila 3,6 1 Department of Biological and Environmental Science, University of Jyva ¨skyla ¨, P.O. Box 35, 40014 Jyva ¨skyla ¨, Finland; 2 Department of Biosciences, General Microbiology, University of Helsinki, P.O. Box 56, 00014 Helsinki, Finland; 3 Peatland Ecology Group, Department of Forest Sciences, University of Helsinki, P.O. Box 27, 00014 Helsinki, Finland; 4 Natural Resources Institute Finland (Luke), P.O. Box 2, 00791 Helsinki, Finland; 5 Present Address: Geological Survey of Finland, Neulaniementie 5, P.O. Box 1237, 70211 Kuopio, Finland; 6 Present Address: School of Forest Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland; 7 Natural Resources Institute Finland (Luke), Paavo Havaksen tie 3, 90570 Oulu, Finland; 8 Environmental Soil Science, Department of Agriculture, University of Helsinki, P.O. Box 56, 00014 Helsinki, Finland; 9 Institute of Atmospheric and Earth System Research (INAR)/ Forest Sciences, University of Helsinki, P.O. Box 56, 00014 Helsinki, Finland ABSTRACT Peatlands are carbon dioxide (CO 2 ) sinks that, in parallel, release methane (CH 4 ). The peatland carbon (C) balance depends on the interplay of decomposer and CH 4 -cycling microbes, vegetation, and environmental conditions. These interactions are susceptible to the changes that occur along a successional gradient from vascular plant-dominated systems to Sphagnum moss-dominated systems. Changes similar to this succession are predicted to occur from climate change. Here, we investigated how microbial and plant communities are interlinked with each other and with ecosystem C cycling along a successional gradient on a boreal land uplift coast. The gradient ranged from shoreline to meadows and fens, and further to bogs. Potential microbial activity (aerobic CO 2 production; CH 4 production and oxidation) and biomass were greatest in the early successional meadows, although their communities of aerobic decomposers (fungi, actinobacteria), methanogens, and methanotrophs did not differ from the older fens. Instead, the functional microbial communities shifted at the fen–bog transition concurrent with a sudden decrease in C fluxes. The successional patterns of decomposer versus CH 4 -cycling communities diverged at the bog stage, indicating strong but distinct microbial responses to Sphagnum dominance and acidity. We highlight young meadows as dynamic sites with the greatest microbial potential for C release. These hot spots of C turnover with dense sedge cover may represent a Received 5 May 2021; accepted 16 September 2021 Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1007/s10021-021-0071 3-w. EST and HF conceived the study; EST, PM and AML performed field sampling and flux measurements; MK, HJ, KP and AP performed research in the lab; LH, MK, AML and HJ analyzed data; HJ, MK, HF, AML, LH and EST wrote the paper and all authors commented on it. *Corresponding author; e-mail: heli.[email protected] Ecosystems https://doi.org/10.1007/s10021-021-00713-w 2021 The Author(s) sensitive bottleneck in succession, which is necessary for eventual long-term peat accumulation. The distinctive microbes in bogs could serve as indicators of the C sink function in restoration measures that aim to stabilize the C in the peat. Key words: ecosystem respiration; methane emission; fungi; actinobacteria; methanogens; methanotrophs; microbial biomass; microbial community; primary paludification; peatland development. HIGHLIGHTS Early successional meadows were hot spots of microbial activity and carbon turnover. Microbial community shifted at the fen–bog transition with decreasing carbon flux. Microbes in bogs could be indicators for the carbon sink function of a peatland. INTRODUCTION About 30% of the global soil carbon (C) is stored in peatlands (Gorham 1991). Consequently, peatland ecosystems play a key role in controlling atmospheric carbon dioxide (CO 2 ) and methane (CH 4 ) concentrations (Yu 2012). They are unique habitats of largely water-logged organic soils, where changes in environmental conditions affect the interplay of primary producers and decomposers, which can turn the system into a C sink or source (for example, Laiho 2006). This interplay includes plants, fungi, bacteria, and CH 4 -producing archaea (methanogens) and CH 4 -oxidizing bacteria (MOB) especially, which are present under specific environmental conditions that are determined by moisture content and fertility level (Sottocornola and others 2009; Andersen and others 2011,2013). Climate change is likely to disrupt the complex interplay that determines the peatland C balance. In peatlands, the impacts of warming are expected to be coupled with drying due to increased evaporation (Roulet and others 1992; Monier and others 2013; Helbig and others 2020). Warming and drying are advantageous for the activity of most decomposers, thereby increasing the rates of mineralization (for example, Dieleman and others 2016). In addition, the community composition responds to environmental changes: vascular plants have an advantage over Sphagnum mosses in warmer and drier conditions (Weltzin and others 2000; Breeuwer and others 2009; Dieleman and others 2015). The community response of fungi, actinobacteria, methanogens, and MOB to warming and drying appears to depend on peatland fertility (Jaatinen and others 2005; Peltoniemi and others 2009,2015,2016; Urbanova ´and Ba ´rta 2016). Such community changes have been linked with alterations in several ecosystem functions, such as decreased C accumulation (Riutta and others 2007; Bragazza and others 2016; Laine and others 2019b) and increased decomposition of organic matter (Strakova ´and others 2012). In general, drying appears to have a stronger impact on peatland communities and functions than warming (Peltoniemi and others 2016;Ma ¨kiranta and others 2018; Laine and others 2019a,2019b). Although the responses of individual communities (plants or microbes) to environmental changes have been studied to some extent, very few studies have linked the concurrent responses of multiple communities to ecosystem functions, such as CO 2 and CH 4 exchange (however, see Jassey and others 2013,2018; Robroek and others 2015). Northern peatlands are dynamic systems that typically have undergone succession from vasculardominated to Sphagnum moss-dominated systems during their development (for example, Bauer and others 2003). Similar rapid directional change has been reported as a response to altered hydrology as part of climate change (Gunnarsson and others 2002; Tahvanainen 2011). Concurrent with the plant community, the microbial communities also undergo successional change (Merila ¨and others 2006; Putkinen and others 2014). Peatland primary succession leads to changes in ecosystem functions, such as CO 2 and CH 4 exchange (Leppa ¨la ¨and others 2008,2011a,2011b). Primary succession gradients make it possible to assess how tightly the different communities are linked and to predict changes in microbial composition based on the change in plant community structure. Peatland chronosequences at land uplift coasts (Glaser and others 2004; Tuittila and others 2013; Harris and others 2020; Laine and others 2021) offer excellent settings to study how the community changes are interlinked with ecosystem functions, as communities and functions can be studied under similar climatic and weather conditions. The aim of this study was (1) to quantify how successional patterns in different functional groups (plants, fungi, actinobacteria, methanogens, MOB) are interlinked, and (2) to link the change in communities with the change in ecosystem functions (CO 2 production potential, CH 4 production H. Juottonen and others and oxidation potential, ecosystem respiration, CH 4 emissions). We expected that as broad groups of aerobic litter decomposers, fungi and actinobacteria succession would closely follow that of vegetation because litter type appears to be a more important determinant of fungal and actinobacterial communities in boreal peatlands than hydrology (Peltoniemi and others 2009,2012). Methanogens and MOB, on the other hand, were expected to follow the position of the water level (WL), which controls the aeration of the peat (Urbanova ´and others 2011;Yrja ¨la ¨and others 2011), as well as the prevalence of sedges and Sphagnum mosses, which are substrate sources and habitats for CH 4 -cycling microbes, respectively (Stro ¨m and others 2003; Putkinen and others 2014). MATERIALS AND METHODS Study Sites The study area is located on the Finnish coast of the Gulf of Bothnia (6445¢N, 2442¢E), where new land is exposed from the sea due to post-glacial isostatic rising. On a 10-km transect that extends from the shore inland, the sites comprise seven near natural peatlands (SJ0–SJ6), with successional stages that ranged from the onset of primary peat formation to a bog stage, which is considered as the final stage of succession (Table 1, Figure S1). The early stages (SJ0–SJ2) have a rather flat surface, while in the later stages (SJ3–SJ6) the peatland surface is patterned by microforms (dry raised hummocks, intermediate lawns, wet flarks with peat surface at or below water level (WL)). Typical microforms were lawns (Sphagnum covered) and flarks in SJ3 and SJ4, hummocks, lawns and flarks in SJ5, and shrubby hummocks, hummocks, and lawns in SJ6. Field Measurements From June to September 2007, CH 4 and CO 2 fluxes (ecosystem respiration, RE) were measured at weekly to biweekly intervals from 54 permanent sample plots (0.56 m 90.56 m) established to cover the site-specific variation in vegetation (Tables 1and S1). Gas fluxes were measured with the static chamber method (see supplementary material for details). Water level and peat temperature at 5, 10, and 20 cm depths were measured close to each plot during the flux measurements. Plant species cover was inventoried from the same plots at the end of July 2007 (Table S1). Percentage cover of vascular and moss species was estimated visually using the scale 0.25, 0.5, 1, 2, 3–100%. Peat Sampling and Physicochemical Analyses In August 2007, we collected two parallel sets of soil cores (one for microbiological and one for physicochemical analysis) with a box sampler (8 989100 cm) or with a cylinder sampler (4.5 cm diameter, 50 cm length) from each site along the transect. The cores were taken within 2 m of each gas flux sample plot from areas with similar vegetation to avoid disturbance on the plots. In addition to the sites with gas flux measurements (SJ0–SJ6), we took four cores from the sandy submerged littoral zone (SJm1) near SJ0 to represent the soil before the land was exposed. Table 1. Characteristics of Successional Stages Along the Peatland Gradient Site Successional stage Terrestrial age (y) a Peat thickness (cm) a Typical vegetation Number of sample plots SJm1 Under the sea level 0 0 Phragmites 4 SJ0 Exposed shore 70 0 Grasses 6 SJ1 Epilobium meadow 100–180 £10 Grasses, sedges, brown mosses 6 SJ2 Equisetum meadow 150–200 £10 Grasses, sedges, brown mosses 6 SJ3 Mesotrophic fen 500–700 50 Sedges, Sphagnum sp. 10 SJ4 Oligotrophic fen 1070 ±70 75 Sedges, shrubs, Sphagnum sp. 9 SJ5 Fen–bog transition 2520 ±50 180 Sedges, shrubs, Sphagnum sp., S. fuscum 8 SJ6 Bog 3000 170–230 Shrubs, S. fuscum 9 a The values for terrestrial age and peat thickness are summarized from Merila ¨and others (2006) and Leppa ¨la ¨and others (2008). Microbes and C Fluxes in Peatland Succession The sampling procedure covered the variation in moisture and vegetation typical of each site. The cores (n= 58), which reached depths of 30, 45, or 60 cm, were cut at even intervals (10, 15, or 20 cm) resulting in three peat layers: uppermost, middle, and deepest layer (174 samples in total). The length of the interval depended on the peat depth and WL: longer sections were used for sites with deeper peat and WL. Varying the interval (that is, thickness of the three peat layers) allowed us to cover the peat above, around and below WL at each site despite their widely different peat depths (Table 1). Portions of the samples were used for measuring pH (soil:water 1:5 v/v) and to determine the potential rates of CO 2 and CH 4 production and CH 4 oxidation. The remainder of the samples were frozen (-20 C) for molecular and phospholipid fatty acid (PLFA) analyses. Parallel volumetric soil cores were used to determine bulk density, organic matter (OM; loss in weight on ignition, 500 C, 4 h), and total C and nitrogen (N; LECO CHN-2000 analyzer). Results were calculated by volume based on the bulk density of the volumetric sample slices (g dm -3 ). Potential CO 2 Production, CH 4 Production, and CH 4 Oxidation Potential activity measurements for the three peat layers (uppermost, middle, deepest) were carried out in 120-ml flasks with 15 ml of peat (see supplementary material for further details). The flasks for CH 4 production contained 30 ml of water and were flushed with nitrogen. The flasks for CH 4 oxidation received 100 llofCH 4 as substrate. The flasks were incubated at 15 C in the dark for 4 days (CH 4 production) or 1–2 days (CO 2 production and CH 4 oxidation). Gas concentrations were followed by gas chromatography as described in Perkio ¨ma ¨ki and Fritze (2002; aerobic CO 2 production), Jaatinen and others (2005;CH 4 oxidation), and Merila ¨and others (2006;CH 4 production). Production or oxidation rates were calculated from the slope of the linear regression of gas concentration change over time. The rates are given per sample volume (mg or lgdm -3 h -1 ). Phospholipid Fatty Acid (PLFA) Analysis Fungal and bacterial biomass was analyzed by quantifying PLFAs from 1.5 to 4 g wet weight of peat or 4–6 g wet weight of mineral soil (Frostega ˚rd and others 1993; Jaatinen and others 2007). Relative fungal abundance (F-PLFA) was quantified from the amount of PLFA 18:2x6 (Frostega ˚rd and Ba ˚a ˚th 1996; Kaiser and others 2010). The sum of twelve PLFAs (i15:0, a15:0, 15:0, i16:0, 16:1x9, 16:1x7t, i17:0, a17:0, 17:0, cy17:0, 18:1x7 and cy19:0) was considered to represent bacterial abundance (B-PLFA) (Frostega ˚rd and Ba ˚a ˚th 1996). PLFAs 10Me17 and 10Me18 were considered to represent actinobacteria (Act-PLFA) (Kroppenstedt 1985). The quantity of the PLFAs was determined in relation to the sample volume (lmol dm -3 )by calculating the results per dry weight (lmol g -1 ) and multiplying with the sample-specific bulk density (g dm -3 ). Molecular Analyses of Microbial Groups Total DNA was extracted from the soil with a Power Soil DNA extraction kit (MoBio Laboratories, Inc., Carlsbad, CA, USA). Fungi were amplified with primers ITS1F and ITS2 for the internal transcribed spacer region (Gardes and Bruns 1993). Actinobacterial primers were S-C-Act-0235-a-S-20 and S-C-Act-0878-a-A-19 for actinobacterial 16S ribosomal RNA gene (Stach and others 2003). Type II methanotrophs (tII-MOB) were detected with primers A189f and A621r (Holmes and others 1995; Tuomivirta and others 2009) for methanotrophspecific pmoA gene for particulate methane monooxygenase. Methanogens were detected with the primers of Luton and others (2002) that amplify methanogen-specific mcrA gene for methylcoenzyme M reductase. Fungal, actinobacterial, and type II MOB communities were analyzed by denaturing gradient gel electrophoresis (DGGE) and sequencing of DGGE bands. Methanogens were analyzed by terminal fragment length polymorphism (T-RFLP) and sequencing of clones. The details of PCR, DGGE, and T-RFLP are described in the supplementary material. The DGGE banding patterns of fungi, actinobacteria, and tII-MOB were compiled into presence-absence matrices. DGGE bands with divergent mobility were considered as operational taxonomic units (OTUs). For methanogens, T-RFs of different lengths were considered as OTUs and relative peak areas were used as relative abundances. The OTUs that appeared at least twice in a dataset were included in the community composition data. To determine taxonomic affiliations, we constructed phylogenetic trees of DGGE band sequences (fungi, actinobacteria, tII-MOB) and clone sequences (methanogens; see supplementary material for details). DNA sequences were submitted to the European Nucleotide Archive under accession numbers LN681001-LN681094 (fungi), LN681095-LN681133 (actinobacteria), H. Juottonen and others LN681148-LN681172 (tII-MOB), and LR999478LR999518 and HG993108-HG993123 (methanogens). Statistical Analyses The effects of soil properties on potential microbial activities and biomass were investigated using generalized additive mixed models (GAMMs) in package mgcv with function gamm (Wood 2006)in R (v. 3.1.1, R Core Team 2014). Normal distribution was assumed but response variables were logtransformed when needed to achieve normality. All sample plots in SJ0–SJ6 were included in the analyses (n= 54). Models were estimated separately for each soil layer. Because many of the variables that describe soil properties were strongly correlated (Table S2), only the most important (that is, WL, OM, and pH) were included in the models. Water level, as the mean of the measurements up to the sampling date, was included in the model as a categorical variable with values 0 (the vertical middle point of a sample below the mean WL) and 1 (the vertical middle point of a sample above the mean WL). We considered this an acceptable estimation of the differences in the moisture conditions at a rather small spatial scale (Figure S2). Organic matter and pH were smoothed when the models were estimated. In addition to these fixed effect variables, site was included as a random factor in the models. Response curves were drawn based on GAMMs using mean values for the other explanatory variables rather than those of interest in the models. Global non-metric multidimensional scaling (GNMDS) was performed for the vegetation and each microbial group to investigate changes in these communities along the successional gradient, using the vegan package (v. 2.3-0, Oksanen and others 2015) in R. The Bray–Curtis dissimilarity measure was used for vegetation (cover data), Raup–Crick for fungi, actinobacteria and tII-MOB (binary data), and Gower for methanogens (numeric data). Separate MetaMDS runs were performed 50 times to ensure the best possible solution (that is, to avoid local optima). The solution with the lowest stress value was chosen. Environmental variables were fitted using permutation tests. Species that occurred in at least in five samples were drawn to species ordination figures. The effect of successional stage and peat layer on microbial communities was tested with permutational analysis of variance (PERMANOVA) (Anderson 2001) with the function adonis2 in the vegan package. Procrustes analysis with the functions procrustes and protest in the vegan package based on the first four NMDS dimensions was used to compare the successional patterns of different functional groups (Peres-Neto and Jackson 2001; Lisboa and others 2014). The Procrustes analysis between vegetation and microbial groups only included the uppermost and middle layers to focus on the layers influenced by the surface vegetation. The analyses between microbial groups included all layers. The distance measures in PERMANOVA and Procrustes analysis were the same as in GNMDS. Finally, we used the Procrustes residuals to compare the strength of correlation among microbial groups along the peatland succession (Lisboa and others 2014). Differences between successional stages were determined with analysis of variance and Tukey’s post hoc tests. RESULTS Vegetation, Soil Chemical Variables, Gas Fluxes and Microbial Biomass Along the Peatland Succession Along the successional gradient, total vegetation cover increased from <20% in recently exposed shore SJ0 to nearly 150% in bog SJ6 (Figure 1a, Table S3). From the fen SJ3 onward, the increasing vegetation cover was due to the increase in shrubs (Figure 1b) and Sphagnum mosses (Figure 1c). Sedge cover was highest in the fen SJ3. Organic matter density tripled from meadow SJ2 to fen SJ3, indicating the start of peat accumulation (Figure 1f). Although OM, C, and N densities were greatest in the fen sites SJ3 and SJ4, C:N increased throughout the gradient (SJ0–SJ6) (Figure 1g). Acidity increased along the gradient from pH 6.1 in SJ0 to 4.2. in SJ6 (Figure 1e). Water level was lowest in the bog SJ6 (Figure 1e). Ecosystem respiration peaked in fen SJ3 (Figure 1d). CH 4 emissions showed rather similar levels in sites SJ1–SJ5 and were lowest at the end points of the gradient (Figure 1d). The greatest microbial activity potential, as indicated by the rates of aerobic CO 2 and anaerobic CH 4 production, was measured at the meadow sites, especially SJ2 (Figure 1h). In contrast, potential CH 4 oxidation increased from SJ0 to SJ2 and then remained at this elevated level along the whole gradient. Fungal, bacterial, and actinobacterial biomass peaked in the meadow sites and were greatest in SJ2. The ratio of fungi to bacteria (F:B) was greatest in the oldest sites SJ5 and SJ6 (Figure 1i). Microbes and C Fluxes in Peatland Succession Within-Site Variation in Relation to Microform and Peat Layer To capture the pronounced vertical variation and horizontal patterning typical of boreal peatlands, our sampling strategy covered three peat layers and the different microforms in the stages where microforms were present. The young meadow sites SJ0–SJ2 showed no horizontal patterns of vegetation cover, C fluxes, soil properties, or microbial variables. These sites had a thin organic surface layer that covered the mineral soil (Table 1). Vertically, this layer showed the greatest CO 2 and CH 4 production and CH 4 oxidation rates and microbial biomass at these sites (Table S4). In the older sites SJ3–SJ6 with thicker peat layer and microforms, the cover of Sphagnum mosses and shrubs was greater in drier microforms (lawns in SJ3 and SJ4, hummocks in SJ5 and SJ6) (Table S5). Microformrelated variation in RE was low, whereas CH 4 emissions were generally greater in the moister microforms within the sites SJ3–SJ6. Potential CO 2 production in the older sites did not vary with depth or microform. Potential CH 4 production in SJ3–SJ6 was generally greater below WL and in the moister microforms (Tables S4–S6). CH 4 oxidation rates were generally greater below the uppermost layer, especially in the drier microforms. Fungal Figure 1. Variables describing peatland succession (SJ0–SJ6) with land uplift from the sea (SJm1): a–cplant functional type cover, decosystem respiration (RE) and methane (CH 4 ) emissions, e–gwater level (WL) and soil properties, h potential rates of carbon dioxide (CO 2 ) (aerobic) and CH 4 production and CH 4 oxidation, and imicrobial biomass: B-PLFA, bacterial phospholipid fatty acids (PLFAs); F-PLFA, fungal PLFAs; Act-PLFA, actinobacterial PLFAs; F:B is the ratio of fungal to bacterial PLFAs. Values are site means including three peat layers (SJm1 n= 12; SJ0–SJ2 n= 18; SJ3 n= 30; SJ4 n= 27: SJ5 n= 24; SJ6 n= 27). To fit the scale, F:B and CH 4 emissions are presented 100 times larger, organic matter (OM) and nitrogen (N) 10 times larger, and CO 2 production 10 times smaller than the initial values. H. Juottonen and others biomass decreased with depth in SJ3–SJ6, whereas bacterial and actinobacterial biomass were mainly greatest in the middle layer (Table S6). Relationship of Microbial Activity Potentials to Soil Variables Based on Generalized Additive Mixed Models (GAMMs) Potential CO 2 production increased with increasing OM density in all layers (Figure 2a–c). In the middle layer, CO 2 production leveled at an OM density of about 70 g dm -3 and greater (Figure 2b). The deepest layer showed greater CO 2 production when the layer was above the WL (Figure 2c). Similarly, potential CH 4 production was affected by the position of the WL (Figure 2d– f). In the surface layer, CH 4 production increased with higher pH (>5) but only when the layer was below the WL (Figure 2d). In the middle layer, none of the selected soil properties explained the CH 4 production rate, with the possible exception of WL (p= 0.059). In the deepest layer, only a weak link was observed between CH 4 production and increasing OM density, but only if this layer was above the WL (Figure 2f). The response of potential CH 4 oxidation depended on the peat layer. In the surface layer, CH 4 oxidation increased with increasing OM density, especially under the WL and at pH 5 (Figure 2g). In the middle layer, CH 4 Figure 2. Effects of water level (WL), organic matter (OM) density, and pH on the microbial activity potentials (aerobic CO 2 production, CH 4 production, and oxidation) for three peat layers. Sites SJ0–SJ6 were included in the model for each layer (n= 54). Response curves were drawn based on generalized additive mixed models (GAMMs) so that explanatory variables other than the presented variable were retained as their mean value. The effects of OM and pH are presented only when p<0.05. All effects of the WL categories (above, below) are shown (pvalues in bold when p<0.05). Empty subfigure e had no significant soil properties. In figures d–i: black denotes OM density; gray denotes pH. Note the different axis scales. R 2adj. = adjusted R 2 value of the model. Microbes and C Fluxes in Peatland Succession oxidation varied strongly with OM density and peaked at an OM density of about 50 g dm -3 (Figure 2h). In the deepest layer, CH 4 oxidation was accentuated, especially above the WL, by increasing acidity and OM (Figure 2i). Plant and Microbial Communities Along the Peatland Gradient Vegetation formed a clear gradient from SJ0 to SJ6 (Figure 3); from grassto sedge-dominated communities, and finally to Sphagnum-dominated vegetation (including dwarf shrubs). Bulk density, pH, C:N, and the cover of Sphagnum and shrubs showed the greatest correlation (r‡0.74) with plant community change (Table S7). Overall microbial community structure based on PLFAs showed a similar, though less differentiated, successional gradient and separated the young meadows (SJ1, SJ2), midsuccessional fens (SJ3, SJ4), and the oldest bog sites (SJ5, SJ6) from each other (Figure 4). At the level of microbial functional groups, successional stage explained a larger proportion of community variation than peat layer for all the groups (Table 2). The community structure of fungi, actinobacteria, and methanogens showed a common pattern where the late stages (SJ5, SJ6) were separated from the other stages, and the early (SJ0–SJ2) and mid-successional (SJ3, SJ4) stages were grouped together (Figure 5a–i, Figure S3). Methanotrophs were not detected in the youngest sites (SJ0, SJ1). The tII-MOB community in the oldest sites (SJ5, SJ6) was separated from the younger sites, but tIIMOB also differed more clearly with peat layer than the other groups (Figure 5j–l). Changes in the fungal, actinobacterial, and tII-MOB communities correlated best with C:N, pH and the cover of Sphagnum and shrubs, and the methanogen communities with C, N, and OM density and Sphagnum cover (Table S8). We used Procrustes analysis, which superimposes two ordinations, to compare the successional patterns of vegetation and microbial functional groups. Fungal community showed the greatest correlation with vegetation composition, and actinobacteria the lowest (Table 2). When comparing the successional patterns of the different functional groups, the strongest correlations were seen between actinobacteria and fungi, and between actinobacteria and methanogens, and lowest between methanogens and tII-MOB (Table 2). Procrustes residuals showed a fairly uniform correlation of actinobacteria vs. fungi and methanogens vs. tII-MOB along the gradient (Figure 6). Procrustes residuals of actinobacteria and fungi with CH 4 -cycling microbes increased toward the bog sites, particularly the oldest site SJ6, indicating decreasing correlation of community patterns. Phylogenetic Affiliation of the Microbial Groups The majority of fungal sequences clustered with Ascomycota and Pezizomycotina, including genera Penicillium (SJ0), Articulospora (SJ0, SJ1, SJ4), Figure 3. Global non-metric multidimensional scaling (GNMDS) ordination of avegetation in sites SJ0–SJ6, and bplant species scores. Ovals represent 95% confidence intervals. The vectors in arepresent environmental variables with correlation ‡0.5. H. Juottonen and others Jaatinen K, Tuittila ES, Laine J, Yrja ¨la ¨K, Fritze H. 2005. Methane-oxidizing bacteria in a Finnish raised mire complex: effects of site fertility and drainage. Microb Ecol 50:429–439. Jaatinen K, Fritze H, Laine J, Laiho R. 2007. 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