Document Detail


Emergent biogeography of microbial communities in a model ocean.
MedLine Citation:
PMID:  17395828     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
A marine ecosystem model seeded with many phytoplankton types, whose physiological traits were randomly assigned from ranges defined by field and laboratory data, generated an emergent community structure and biogeography consistent with observed global phytoplankton distributions. The modeled organisms included types analogous to the marine cyanobacterium Prochlorococcus. Their emergent global distributions and physiological properties simultaneously correspond to observations. This flexible representation of community structure can be used to explore relations between ecosystems, biogeochemical cycles, and climate change.
Authors:
Michael J Follows; Stephanie Dutkiewicz; Scott Grant; Sallie W Chisholm
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Science (New York, N.Y.)     Volume:  315     ISSN:  1095-9203     ISO Abbreviation:  Science     Publication Date:  2007 Mar 
Date Detail:
Created Date:  2007-03-30     Completed Date:  2007-04-12     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0404511     Medline TA:  Science     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1843-6     Citation Subset:  IM    
Affiliation:
Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 54-1514 MIT, Cambridge, MA 02139, USA. mick@mit.edu
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MeSH Terms
Descriptor/Qualifier:
Biomass
Computer Simulation
Ecosystem*
Geography
Light
Mathematics
Models, Biological
Oceans and Seas
Phytoplankton / growth & development,  physiology*
Prochlorococcus / growth & development,  physiology*
Seawater / microbiology*
Temperature

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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