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V4 16S sequencing of coastal marsh sediment in Mobile Bay

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NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1051103
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Here we describe soil physicochemical and microbial diversity along a vegetation and salinity gradient in the Mobile Bay estuary, AL, USA and discuss how these factors feedback on ecosystem characteristics and the delivery of ecological functions. We incorporated microbial biomass, diversity, and community composition into patterns of dominant vegetation cover type and soil properties. Stepwise model selection using permutation tests indicated that vegetation type >> soil horizon > and salinity strongly influenced microbe-soil relationships. The dominant variables governing microbial content were total sulfur concentration in surface soils and nitrate and nitrite (NOx) for subsurface soils. All biotic and abiotic variables indicated that seasonally inundated forested wetlands represented a distinct microbial biome within the Mobile Bay estuary compared to more frequently flooded and increasingly salt-tolerant Typha, tidal shrub, and Juncus wetland types. Compared with the other wetland types examined for this study, forested wetlands contained ~80% less organic carbon content, ~75% less nitrogen, ~33% less phosphorus, and ~95% less sulfur. Our results show the benefit of incorporating microbial trait data, including metataxonomics, enzymatics, and biomass, with other ecosystem properties such as vegetation and soil characterization data.
创建时间:
2023-12-11
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