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    Author(s): Swathi A. Turlapati; Rakesh Minocha; Premsai S. Bhiravarasa; Louise S. Tisa; William K. Thomas; Subhash C. Minocha
    Date: 2013
    Source: FEMS Microbiology Ecology. 83: 478-493.
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: Download Publication  (699.14 KB)


    At the Harvard Forest, Petersham, MA, the impact of 20 years of annual ammonium nitrate application to the mixed hardwood stand on soil bacterial communities was studied using 16S rRNA genes pyrosequencing. Amplification of 16S rRNA genes was done using DNA extracted from 30 soil samples (three treatments x two horizons x five subplots) collected from untreated (control), low N-amended (50 kg ha-1 year-1) and high N-amended (150 kg ha-1 year-1) plots. A total of 1.3 million sequences were processed using QIIME. Although Acidobacteria represented the most abundant phylum based on the number of sequences, Proteobacteria were the most diverse in terms of operational taxonomic units (OTUs). UniFrac analyses revealed that the bacterial communities differed significantly among soil horizons and treatments. Microsite variability among the five subplots was also evident. Nonmetric multidimensional scaling ordination of normalized OTU data followed by permutational MANOVA further confirmed these observations. Richness indicators and indicator species analyses revealed higher bacterial diversity associated with N amendment. Differences in bacterial diversity and community composition associated with the N treatments were also observed at lower phylogenetic levels. Only 28-35% of the 6 936 total OTUs identified were common to three treatments, while the rest were specific to one treatment or common to two.

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    Turlapati, Swathi A.; Minocha, Rakesh; Bhiravarasa, Premsai S.; Tisa, Louise S.; Thomas, William K.; Minocha, Subhash C. 2013. Chronic N-amended soils exhibit an altered bacterial community structure in Harvard Forest, MA, USA. FEMS Microbiology Ecology. 83: 478-493.


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    bacterial composition, forest soils, indicator species, pyrosequencing, QIIME software, unique operational taxonomic units

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