Northern acidic peatlands are important sources of atmospheric methane, yet the methanogens in them are poorly characterized. We examined methanogenic activities and methanogen populations at different depths in two peatlands, McLean bog (MB) and Chicago bog (CB). Both have acidic (pH 3.5-4.5) peat soils, but the pH of the deeper layers of CB is near-neutral, reflecting its previous existence as a neutral-pH fen. Acetotrophic and hydrogenotrophic methanogenesis could be stimulated in upper samples from both bogs, and phylotypes of methanogens using H2/CO2 (Methanomicrobiales) or acetate (Methanosarcinales) were identified in 16S rRNA gene clone libraries and by terminal restriction fragment length polymorphism (T-RFLP) analyses using a novel primer/restriction enzyme set that we developed. Particularly dominant in the upper layers was a clade in the Methanomicrobiales, called E2 here and the R10 or fen group elsewhere, estimated by quantitative polymerase chain reaction to be present at approximately 10(8) cells per gram of dry peat. Methanogenic activity was considerably lower in deeper samples from both bogs. The methanogen populations detected by T-RFLP in deeper portions of MB were mainly E2 and the uncultured euryarchaeal rice cluster (RC)-II group, whereas populations in the less acidic CB deep layers were considerably different, and included a Methanomicrobiales clade we call E1-E1', as well as RC-I, RC-II, marine benthic group D, and a new cluster that we call the subaqueous cluster. E2 was barely detectable in the deeper samples from CB, further evidence for the associations of most organisms in this group with acidic habitats.

Mountain ecosystems are characterized by a diverse range of climatic and topographic conditions over short distances and are known to shelter a high biodiversity. Despite important progress, still little is known on bacterial diversity in mountain areas. Here, we investigated soil bacterial biogeography at more than 100 sampling sites randomly stratified across a 700-km 2 area with 2,200-m elevation gradient in the western Swiss Alps. Bacterial grassland communities were highly diverse, with 12,741 total operational taxonomic units (OTUs) across 100 sites and an average of 2,918 OTUs per site. Bacterial community structure was correlated with local climatic, topographic, and soil physicochemical parameters with high statistical significance. We found pH (correlated with % CaO and % mineral carbon), hydrogen index (correlated with bulk gravimetric water content), and annual average number of frost days during the growing season to be among the groups of the most important environmental drivers of bacterial community structure. In contrast, bacterial community structure was only weakly stratified as a function of elevation. Contrasting patterns were discovered for individual bacterial taxa. Acidobacteria responded both positively and negatively to pH extremes. Various families within the Bacteroidetes responded to available phosphorus levels. Different verrucomicrobial groups responded to electrical conductivity, total organic carbon, water content, and mineral carbon contents. Alpine grassland bacterial communities are thus highly diverse, which is likely due to the large variety of different environmental conditions. These results shed new light on the biodiversity of mountain ecosystems, which were already identified as potentially fragile to anthropogenic influences and climate change. IMPORTANCEThis article addresses the question of how microbial communities in alpine regions are dependent on local climatic and soil physicochemical variables. We benefit from a unique 700-km 2 study region in the western Swiss Alps region, which has been exhaustively studied for macro-organismal and fungal ecology, and for topoclimatic modeling of future ecological trends, but without taking into account soil bacterial diversity. Here, we present an in-depth biogeographical characterization of the bacterial community diversity in this alpine region across 100 randomly stratified sites, using 56 environmental variables. Our exhaustive sampling ensured the detection of ecological trends with high statistical robustness. Our data both confirm previously observed general trends and show many new detailed trends for a wide range of bacterial taxonomic groups and environmental parameters.

High-throughput 16S rRNA gene amplicon sequencing is an essential method for studying the diversity and dynamics of microbial communities. However, this method is presently hampered by the lack of high-identity reference sequences for many environmental microbes in the public 16S rRNA gene reference databases and by the absence of a systematic and comprehensive taxonomy for the uncultured majority. Here, we demonstrate how high-throughput synthetic long-read sequencing can be applied to create ecosystem-specific full-length 16S rRNA gene amplicon sequence variant (FL-ASV) resolved reference databases that include high-identity references (>98.7% identity) for nearly all abundant bacteria (>0.01% relative abundance) using Danish wastewater treatment systems and anaerobic digesters as an example. In addition, we introduce a novel sequence identity-based approach for automated taxonomy assignment (AutoTax) that provides a complete seven-rank taxonomy for all reference sequences, using the SILVA taxonomy as a backbone, with stable placeholder names for unclassified taxa. The FL-ASVs are perfectly suited for the evaluation of taxonomic resolution and bias associated with primers commonly used for amplicon sequencing, allowing researchers to choose those that are ideal for their ecosystem. Reference databases processed with AutoTax greatly improves the classification of short-read 16S rRNA ASVs at the genus- and species-level, compared with the commonly used universal reference databases. Importantly, the placeholder names provide a way to explore the unclassified environmental taxa at different taxonomic ranks, which in combination with in situ analyses can be used to uncover their ecological roles.

Minerotrophic fen peatlands are widely distributed in northern latitudes and, because of their rapid turnover of organic matter, are potentially larger sources of atmospheric methane than bog peatlands per unit area. However, studies of the archaeal community composition in fens are scarce particularly in minerotrophic sites. Several 16S rRNA-based primer sets were used to obtain a broad characterization of the archaeal community in a minerotrophic fen in central New York State. A wide archaeal diversity was observed in the site: 11 euryarchaeal and 2 crenarchaeal groups, most of which were uncultured. The E1 group, a novel cluster in the order Methanomicrobiales, and Methanosaetaceae were the codominant groups in all libraries and results of terminal restriction fragment length polymorphism (T-RFLP) analysis. Given its abundance and potential hydrogenotrophic methane contribution, the E1 group was targeted for culture attempts with a low-ionic-strength medium (PM1). Initial attempts yielded Methanospirillumdominated cultures. However, by incorporating a T-RFLP analysis as a quick selection tool for treatments and replicates, we were able to select an enrichment dominated by E1. Further dilutions to 10 ؊9 and tracking with T-RFLP yielded a strain named E1-9c. E1-9c is a novel coccoid hydrogenotrophic, mesophilic, slightly acidophilic methanogen and is highly sensitive to Na 2 S concentrations (requires <0.12 mM for growth). We propose E1-9c as the first representative of a novel genus in the Methanomicrobiales order.Peatlands are wetlands where the rate of accumulation of organic matter exceeds its rate of decomposition (26), producing organic peat soil. On a global basis, these ecosystems are estimated to store more than 30% of all terrestrial soil carbon (28), and their anoxic and reducing conditions are suitable for CH 4 production by methanogenic Archaea (67). It is important to gain a better understanding of the processes and microorganisms involved in CH 4 production in peatlands because these ecosystems represent the largest natural sources of CH 4 for the atmosphere, levels of which have more than doubled in the past 200 years (17). Moreover, peatlands are not homogeneous ecosystems but include a wide range of sites that can substantially differ in vegetation, hydrology, and chemistry (9, 62). The distinctions between bogs and fens include many of these differences.Bogs (ombrotrophic or rain-fed sites) are dominated by Sphagnum mosses (27); receive only atmospheric inputs of water, cations, and nutrients; and are nutrient-poor, low-pH (Յ4) ecosystems (26). In contrast, fens have a greater plant diversity, are commonly dominated by sedges and woody plants, receive the inputs of groundwater and runoff from surrounding uplands, and exhibit higher alkalinity and pH levels (5.5 to 7 in moderate minerotrophic fens; Ͼ7 in calcareous fens) (26, 64).Bogs are abundant in boreal regions and have been the focus of many studies of methanogenic processes, environmental controls, and methanogenic Archaea (2, 3, 9, 11, ...

Acidic peatlands are among the largest natural sources of atmospheric methane and harbour a large diversity of methanogenic Archaea. Despite the ubiquity of methanogens in these peatlands, indigenous methanogens capable of growth at acidic pH values have resisted culture and isolation; these recalcitrant methanogens include members of an uncultured family-level clade in the Methanomicrobiales prevalent in many acidic peat bogs in the Northern Hemisphere. However, we recently succeeded in obtaining a mixed enrichment culture of a member of this clade. Here we describe its isolation and initial characterization. We demonstrate that the optimum pH for methanogenesis by this organism is lower than that of any previously described methanogen.

Aims:  Bacterial communities in the apple phyllosphere were examined quantitatively and qualitatively by applying culture‐dependent and culture‐independent methods. Methods and Results:  Populations estimated by viewing cells stained with 4′,6‐diamidino‐2‐phenylindole generally were at least 100–1000 times greater than populations estimated by culturing on tryptic soy agar (TSA). Of the 44 operational taxonomic units (OTUs; cut‐off threshold of 97%) detected in total, five bacterial orders containing 23 OTUs were identified by culturing on TSA, whereas nine orders containing 33 OTUs were identified by 16S rRNA gene cloning of DNA extracted from apple leaf surfaces. Twelve of the 44 OTUs were shared between cultured isolates and 16S rRNA gene clones and included the orders Burkholderiales, Pseudomonadales, Rhizobiales and Sphingomonadales. Three OTUs within the genus Sphingomonas accounted for 40% of isolates and 68% of clones. The Actinomycetales were found only among isolates, whereas the Bacteroidales, Enterobacteriales, Myxococales and Sphingobacteriales were represented in the 16S rRNA gene clone libraries but were absent among isolates. Conclusions:  Culture‐independent methods revealed greater numbers and greater richness of bacteria on apple leaves than found by culturing. Significance and Impact of the Study:  This is the first study to directly compare culture‐dependent and independent approaches for assessing bacterial communities in the phyllosphere. The biases introduced by different methods will have a significant impact on studies related to phyllosphere ecology, biological control of plant diseases, reservoirs of antibiotic resistance genes and food safety.

Explanatory studies suggest that using very high resolution (VHR, 1–5 m resolution) topo-climatic predictors may improve the predictive power of plant species distribution models (SDMs). However, the use of VHR topo-climatic data alone was recently shown not to significantly improve SDM predictions. This suggests that new ecologically-meaningful VHR variables based on more direct field measurements are needed, especially since non topo-climatic variables, such as soil parameters, are important for plants. In this study, we investigated the effects of adding mapped VHR predictors at a 5 m resolution, including field measurements of temperature, carbon isotope composition of soil organic matter (δ13CSOM values) and soil pH, to topo-climatic predictors in SDMs for the Swiss Alps. We used data from field temperature loggers to construct temperature maps, and we modelled the geographic variation in δ13CSOM and soil pH values. We then tested the effect of adding these VHR mapped variables as predictors into 154 plant SDMs and assessed the improvement in spatial predictions across the study area. Our results demonstrate that the use of VHR predictors based on more proximal field measurements, particularly soil parameters, can significantly increase the predictive power of models. Predicted soil pH was the second most important predictor after temperature, and predicted δ13CSOM was fourth. The greatest increase in model performance was for species found at high elevation (i.e. 1500–2000 m a.s.l.). Addition of predicted soil factors thus allowed better capturing of plant requirements in our models, showing that these can explain species distributions in ways complementary to topo-climatic variables. Modelling techniques to generalize edaphic information in space and then predict plant species distributions revealed a great potential in complex landscapes such as the mountain region considered in this study.

Methanogenic archaea are ubiquitous in peat soils; however, their diversity and distributions within and among peatland ecosystems are not well known. We used comprehensive clone libraries of 16S rRNA gene sequences to investigate spatial patterns in diversity (richness, evenness of taxa) and composition (taxonomic, phylogenetic) of the methanogenic community in six peatlands arrayed 775 km from eastern Ontario, Canada to West Virginia, USA. Five sites were Sphagnum (moss) and shrub dominated; one site was sedge dominated; and, potential rates of methane (CH 4 ) production ranged from 15 to 450 nmol/g day. The gradient allowed us to examine influences of site conditions, site history, and climate on community composition. The region had representatives of methanogens from four taxonomic orders. We observed 29 operationally defined units (OTUs) based on [97% sequence identity. One OTU accounted for 43% of all clones, whereas 15 OTUs were rare with \1% of the total number of clones. The number of OTUs per site ranged from 4 to 21, and statistical analysis suggested diversity of 4-43 per site. Eighteen of the OTUs were endemic to one site; albeit, most endemics occurred in the sedge dominated site. One OTU was cosmopolitan, occurring in all six sites. We found a positive relationship between methanogen diversity and rates of CH 4 production per site (Pearson r = 0.93). Turnover in community composition between sites was weakly related to geographic distance between sites, whereas variation in soil pH and annual temperature played larger roles. About 50% of the variation in community composition was unexplained by distance, pH, mean climate, and site age. We conclude that methanogen diversity in peatlands of the central Appalachian region is shaped by present-day environmental conditions, suggesting an influence of impending climatic and environmental changes.