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Ammonia-oxidizing archaea and bacteria are structured by geography

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TLDR
In this paper, the authors used clone libraries and quantitative PCR targeting the amoA gene, which codes for the ammonia monooxygenase enzyme, universally present in ammonia-oxidizing microbes.
Abstract
IntroductionBiological soil crusts (BSCs) can dominate surface cover in dry lands worldwide, playing an integral role in arid land biogeochemistry, particularly in N fertilization through fixation and cycling. Nitrification is a characteristic and universal N transformation in BSCs that becomes important for the export of N beyond the microscopic bounds of the crust itself. The contribution of ammonia-oxidizing bacteria (AOB) in BSCs has been shown, but the role and extent of the recently discovered ammonia-oxidizing archaea (AOA) have not.MethodsWe sampled various types of crusts in four desert regions across the western United States and characterized the composition and size of ammonia-oxidizing communities using clone libraries and quantitative PCR targeting the amoA gene, which codes for the ammonia monooxygenase enzyme, universally present in ammonia-oxidizing microbes.ResultsAll archaeal amoA sequences retrieved from BSCs belonged to the Thaumarchaeota (Nitrososphaera associated Group I.1b). Sequences from the Sonoran Desert, Colorado Plateau, and Great Basin were indistinguishable from each other but distinct from those of the Chihuahuan Desert. Based on amoA gene abundances, archaeal and bacterial ammonia oxidizers were ubiquitous in our survey, but the ratios of archaeal to bacterial ammonia oxidizers shifted from bacterially dominated in northern, cooler deserts to archaeally dominated in southern, warmer deserts.ConclusionsArchaea are shown to be potentially important biogeochemical agents of biological soil crust N cycling. Conditions associated with different types of BSCs and biogeographical factors reveal a niche differentiation between AOA and AOB, possibly driven by temperature.

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Erratum to The chemical and functional characterization of soil N and its biotic components

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Photoautotrophic organisms control microbial abundance, diversity, and physiology in different types of biological soil crusts.

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Patterns and Controls on Nitrogen Cycling of Biological Soil Crusts

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Differences in thallus chemistry are related to species-specific effects of biocrust-forming lichens on soil nutrients and microbial communities

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Microbial nursery production of high-quality biological soil crust biomass for restoration of degraded dryland soils

TL;DR: The results constitute an advance in the quest to actively restore biological soil covers by providing a means to obtain high-quality inoculum within a reasonable time (a few months), thereby allowing land managers to recover essential, but damaged, ecosystem services in a sustainable, self-perpetuating way as provided by biocrust communities.
References
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MEGA5: Molecular Evolutionary Genetics Analysis using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods

TL;DR: The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models, inferring ancestral states and sequences, and estimating evolutionary rates site-by-site.
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Past: paleontological statistical software package for education and data analysis

TL;DR: PAST (PAleontological STatistics) as discussed by the authors is a simple-to-use software package for executing a range of standard numerical analysis and operations used in quantitative paleontology.
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MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform

TL;DR: A simplified scoring system is proposed that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length.
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Canonical Correspondence Analysis: A New Eigenvector Technique for Multivariate Direct Gradient Analysis

TL;DR: In this article, a new multivariate analysis technique, called canonical correspondence analysis (CCA), was developed to relate community composition to known variation in the environment, where ordination axes are chosen in the light of known environmental variables by imposing the extra restriction that the axes be linear combinations of environmental variables.
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