Multivariate analyses in microbial ecology
Многомерный анализ в микробной экологии
2007-09-24
SCID: 54.1/a8vqw26s
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diversity patternsenvironmental microbiologyenvironmental parametersmicrobial ecologymultivariate statistical analyses
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Abstract (AI)
Environmental microbiology is undergoing a dramatic revolution due to the increasing accumulation of biological information and contextual environmental parameters. This will not only enable a better identification of diversity patterns, but will also shed more light on the associated environmental conditions, spatial locations, and seasonal fluctuations, which could explain such patterns. Complex ecological questions may now be addressed using multivariate statistical analyses, which represent a vast potential of techniques that are still underexploited. Here, well-established exploratory and hypothesis-driven approaches are reviewed, so as to foster their addition to the microbial ecologist toolbox. Because such tools aim at reducing data set complexity, at identifying major patterns and putative causal factors, they will certainly find many applications in microbial ecology.
Key Findings
1
Both exploratory and hypothesis-driven multivariate approaches are established but remain underexploited in microbial ecology.
2
Multivariate statistical analyses can address complex ecological questions by integrating diverse biological and contextual environmental parameters.
3
The accumulation of biological and environmental data enables improved identification of microbial diversity patterns and their environmental, spatial, and seasonal associations.
4
These methods reduce dataset complexity, reveal major ecological patterns, and identify putative causal factors, expanding the microbial ecologist’s analytical toolbox.
Research Object
Multivariate statistical analyses applied to microbial ecology data
Research Subject
diversity patterns and their environmental, spatial, and seasonal drivers
Publication Details
Publication Date
2007-09-24
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