Final Technical Report [electronic resource] : DOE-Biological Ocean Margins Program. Microbial Ecology of Denitrifying Bacteria in the Coastal Ocean.

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Ngôn ngữ: eng

Ký hiệu phân loại: 662.8 Other fuels

Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. Dept. of Energy. Office of Science and Technology ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2013

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The focus of our research was to provide a comprehensive study of the bacterioplankton populations off the coast of New Jersey near the Rutgers University marine field station using terminal restriction fragment polymorphism analysis (TRFLP) coupled to 16S rRNA genes for large data set studies. Our three revised objectives to this study became: (1) to describe bacterioplankton population dynamics in the Mid Atlantic Bight using TRFLP analysis of 16S rRNA genes. (2) to determine whether spatial and temporal factors are driving bacterioplankton community dynamics in the MAB using monthly samping along our transect line over a 2-year period. (3) to identify dominant members of a coastal bacterioplankton population by clonal library analysis of 16S rDNA genes and sequencing of PCR product corresponding to specific TRFLP peaks in the data set. Although open ocean time-series sites have been areas of microbial research for years, relatively little was known about the population dynamics of bacterioplankton communities in the coastal ocean on kilometer spatial and seasonal temporal scales. To gain a better understanding of microbial community variability, monthly samples of bacterial biomass were collected in 1995-1996 along a 34-km transect near the Long-Term Ecosystem Observatory (LEO-15) off the New Jersey coast. Surface and bottom sampling was performed at seven stations along a transect line with depths ranging from 1 to 35m (n=178). The data revealed distinct temporal patterns among the bacterioplankton communities in the Mid-Atlantic Bight rather than grouping by sample location or depth (figure 2-next page). Principal components analysis models supported the temporal patterns. In addition, partial least squares regression modeling could not discern a significant correlation from traditional oceanographic physical and phytoplankton nutrient parameters on overall bacterial community variability patterns at LEO-15. These results suggest factors not traditionally measured during oceanographic studies are structuring coastal microbial communities.
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