Climate controls prokaryotic community composition in desert soils of the southwestern United States.

Theresa A McHugh,Zacchaeus Compson,Natasja van Gestel,Michaela Hayer, Lisa Ballard, Matthew Haverty, Jeffrey Hines, Nick Irvine, David Krassner, Ted Lyons, Emily Julien Musta, Michele Schiff, Patricia Zint,Egbert Schwartz

FEMS MICROBIOLOGY ECOLOGY(2017)

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摘要
Aridisols are the dominant soil type in drylands, which occupy one-third of Earth's terrestrial surface. We examined controls on biogeographical patterns of Aridisol prokaryotic (bacterial and archaeal) communities at a regional scale by comparing communities from 100 Aridisols throughout the southwestern United States using high-throughput sequencing of the 16S rRNA gene. We found that microbial communities differed among global biomes and deserts of the Southwest. Differences among biomes were driven by differences in taxonomic identities, whereas differences among deserts of the Southwest were driven by differences in relative sequence abundance. Desert communities were dominated by Actinobacteria, Proteobacteria and Crenarchaeota, supporting the notion of a core set of abundant taxa in desert soils. Our findings contrast with studies showing little taxonomic overlap at the OTU level (97% sequence similarity) across large spatial scales, as we found similar to 90% of taxa in at least two of the three deserts. Geographic distance structured prokaryotic communities indirectly through the influence of climate and soil properties. Structural equation modeling suggests that climate exerts a stronger influence than soil properties in shaping the composition of Aridisol microbial communities, with annual heat moisture index (an aridity metric) being the strongest climate driver. Annual heat moisture index was associated with decreased microbial diversity and richness. If the Desert Southwest becomes hotter and drier as predicted, these findings suggest that prokaryotic diversity and richness in Aridisols will decline.
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关键词
Aridisols,biodiversity,biogeography,16S rRNA gene,structural equation model,climate
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