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      Effects of Spartina alterniflora Invasion on the Abundance, Diversity, and Community Structure of Sulfate Reducing Bacteria along a Successional Gradient of Coastal Salt Marshes in China

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          Fast UniFrac: Facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data

          Next-generation sequencing techniques, and PhyloChip, have made simultaneous phylogenetic analyses of hundreds of microbial communities possible. Insight into community structure has been limited by the inability to integrate and visualize such vast datasets. Fast UniFrac overcomes these issues, allowing integration of larger numbers of sequences and samples into a single analysis. Its new array-based implementation offers orders of magnitude improvements over the original version. New 3D visualization of principal coordinates analysis (PCoA) results, with the option to view multiple coordinate axes simultaneously, provides a powerful way to quickly identify patterns that relate vast numbers of microbial communities. We demonstrate the potential of Fast UniFrac using examples from three data types: Sanger-sequencing studies of diverse free-living and animal-associated bacterial assemblages and from the gut of obese humans as they diet, pyrosequencing data integrated from studies of the human hand and gut, and PhyloChip data from a study of citrus pathogens. We show that a Fast UniFrac analysis using a reference tree recaptures patterns that could not be detected without considering phylogenetic relationships and that Fast UniFrac, coupled with BLAST-based sequence assignment, can be used to quickly analyze pyrosequencing runs containing hundreds of thousands of sequences, revealing patterns relating human and gut samples. Finally, we show that the application of Fast UniFrac to PhyloChip data could identify well-defined subcategories associated with infection. Together, these case studies point the way towards a broad range of applications and demonstrate some of the new features of Fast UniFrac.
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            Methane emissions from wetlands: biogeochemical, microbial, and modeling perspectives from local to global scales.

            Understanding the dynamics of methane (CH4 ) emissions is of paramount importance because CH4 has 25 times the global warming potential of carbon dioxide (CO2 ) and is currently the second most important anthropogenic greenhouse gas. Wetlands are the single largest natural CH4 source with median emissions from published studies of 164 Tg yr(-1) , which is about a third of total global emissions. We provide a perspective on important new frontiers in obtaining a better understanding of CH4 dynamics in natural systems, with a focus on wetlands. One of the most exciting recent developments in this field is the attempt to integrate the different methodologies and spatial scales of biogeochemistry, molecular microbiology, and modeling, and thus this is a major focus of this review. Our specific objectives are to provide an up-to-date synthesis of estimates of global CH4 emissions from wetlands and other freshwater aquatic ecosystems, briefly summarize major biogeophysical controls over CH4 emissions from wetlands, suggest new frontiers in CH4 biogeochemistry, examine relationships between methanogen community structure and CH4 dynamics in situ, and to review the current generation of CH4 models. We highlight throughout some of the most pressing issues concerning global change and feedbacks on CH4 emissions from natural ecosystems. Major uncertainties in estimating current and future CH4 emissions from natural ecosystems include the following: (i) A number of important controls over CH4 production, consumption, and transport have not been, or are inadequately, incorporated into existing CH4 biogeochemistry models. (ii) Significant errors in regional and global emission estimates are derived from large spatial-scale extrapolations from highly heterogeneous and often poorly mapped wetland complexes. (iii) The limited number of observations of CH4 fluxes and their associated environmental variables loosely constrains the parameterization of process-based biogeochemistry models. © 2012 Blackwell Publishing Ltd.
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              Salinity Influence on Methane Emissions from Tidal Marshes

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                Author and article information

                Journal
                Wetlands
                Wetlands
                Springer Nature
                0277-5212
                1943-6246
                April 2017
                January 6 2017
                : 37
                : 2
                : 221-232
                Article
                10.1007/s13157-016-0860-6
                c5ecaad4-9e65-4689-ad64-8a213ab9ae52
                © 2017

                http://www.springer.com/tdm

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