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The decomposition of large stocks of soil organic carbon in thawing permafrost might depend on more than climate change-induced temperature increases: indirect effects of thawing via altered bacterial community structure (BCS) or rooting patterns are largely unexplored. We used a 10-year in situ permafrost thaw experiment and aerobic incubations to investigate alterations in BCS and potential respiration at different depths, and the extent to which they are related with each other and with root density. Active layer and permafrost BCS strongly differed, and the BCS in formerly frozen soils (below the natural thawfront) converged under induced deep thaw to strongly resemble the active layer BCS, possibly as a result of colonization by overlying microorganisms. Overall, respiration rates decreased with depth and soils showed lower potential respiration when subjected to deeper thaw, which we attributed to gradual labile carbon pool depletion. Despite deeper rooting under induced deep thaw, root density measurements did not improve soil chemistry-based models of potential respiration. However, BCS explained an additional unique portion of variation in respiration, particularly when accounting for differences in organic matter content. Our results suggest that by measuring bacterial community composition, we can improve both our understanding and the modeling of the permafrost carbon feedback.
Pubmed ID: 29875436
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Software package that provides a graphical summary of linkage disequilibrium in human genetic data. The graphical summary is well suited to the analysis of dense genetic maps, where contingency tables are cumbersome to interpret. An interface to the Simwalk2 application allows for the analysis of family data.
View all literature mentionsAn algorithm for detecting chimeric sequences.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.
View all literature mentionsSource code that infers approximately-maximum-likelihood phylogenetic trees from alignments of nucleotide or protein sequences. It uses the Jukes-Cantor or generalized time-reversible (GTR) models of nucleotide evolution and the JTT, WAG, or LG models of amino acid evolution.
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