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Aquatic Microbial Ecology

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AME 53:69-81 (2008)  -  DOI:

Community structure of marine bacterioplankton: patterns, networks, and relationships to function

Jed A. Fuhrman*, Joshua A. Steele

Department of Biological Sciences and Wrigley Institute for Environmental Studies, University of Southern California, Los Angeles, California 90089-0371, USA

ABSTRACT: Major challenges in marine microbial ecology include determining patterns of community structure and structure–function relationships. Progress has occurred by a combination of molecular and classical techniques. An example for this is work on the marine Crenarchaeota, extremely abundant organisms that we now think play important roles both as autotrophic ammonium oxidizers and as heterotrophs. Another involves the recently discovered Proteorhodopsins, pigments that are potentially important in solar energy capture, yet often do not seem to confer a clear growth benefit to organisms that possess them. Proteorhodopsins occur in numerous phylogenetic groups and may have multiple roles, complicating the linking of these proteins to a well-defined function. Community fingerprinting is a powerful tool for examining community structure and for examining spatial and temporal distribution patterns. Using fingerprinting, we found that ocean communities tend to occur in patches with horizontal dimensions of several km, while samples 10s of km or more apart can be quite different. Temporal analyses such as the San Pedro Ocean Time Series (SPOT) show that near-surface communities are somewhat similar from month to month, then change significantly over several months, and finally return to a similar community annually. Near-surface communities can also be predicted from environmental parameters like temperature, salinity, nutrients, and chlorophyll. Time series data show co-occurrence of organisms (resembling a succession of communities) under particular conditions, or conversely can show which organisms are significantly negatively correlated, indicative perhaps of competition, resource partitioning, or allelopathy. These relationships are visualized here as mathematical interaction networks to map out the ‘niche space’ of microbial taxa and their correlations, displaying complex ecological interactions. Observations indicate that ecological relatedness does not necessarily closely follow phylogenetic relatedness.

KEY WORDS: Bacteria · Archaea · ARISA · Proteorhodopsin · Patchiness · Time series · Networks

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Cite this article as: Fuhrman JA, Steele JA (2008) Community structure of marine bacterioplankton: patterns, networks, and relationships to function. Aquat Microb Ecol 53:69-81.

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