Biodiversity and Microbial Ecosystems Functioning
8
Philippe Normand, Robert Duran, Xavier Le Roux, Cindy Morris,
and Jean-Christophe Poggiale
Abstract
All ecosystems are composed of multiple species performing numerous functions. This
plurality identified as biodiversity has become a research topic of general importance for
understanding how ecosystems function. The word “biodiversity” has subsequently
received different interpretations we aim to describe. Microbial systems can be used to
illustrate these definitions and to clarify paradigms that have emerged in general ecology.
Microbial biodiversity can be characterized by the kind of biodiversity (taxa or functional
groups present), the representativeness of samples, and the culturability of samples or taxa,
in terms of genetic, functional, or physiological characteristics. Biodiversity is a major
driver of ecosystem functioning, and this relation is described in the case of several
biotopes. Several mathematical approaches have been used to quantify microbial diversity,
and the various indices are described and discussed.
Keywords
Alpha diversity Beta diversity Biodiversity Canonical correspondence
analysis Chimeras Cluster analysis Community structure Cultural
approach Denaturing gradient gel electrophoresis (DGGE) Diversity
indices DNA arrays DNA reassociation Fingerprints Functional
groups Identification Linkage disequilibrium analysis Lipids Metabolic capacities
of communities Metabolites Microbial communities Multivariate analysis Nei
index Nonparametric test OTU (operational taxonomic unit) Parametric
test Phylotype Pigment Principal component analysis Rarefaction
curve Ribosomal intergenic spacer analysis (RISA) Richness Saturation
analysis Shannon alpha diversity index Simpson index Single-strand conformational
polymorphism (SSCP) Spearman correlation tests Species richness index Temperature
gradient gel electrophoresis (TGGE) Terminal-restriction fragment length polymorphism
(T-RFLP) Variables
P. Normand* (*) X. Le Roux
Microbial Ecology Center, UMR CNRS 5557 / USC INRA 1364,
Universite ´ Lyon 1, 69622 Villeurbanne, France
e-mail: philippe.normand@univ-lyon1.fr
R. Duran
Institut des Sciences Analytiques et de Physico-chimie pour
l’Environnement et les Mate ´riaux (IPREM), UMR CNRS 5254,
Universite ´ de Pau et des Pays de l’Adour, B.P. 1155,
64013 Pau Cedex, France
* Chapter Coordinator
C. Morris
Unite ´ de Recherches de Pathologie Ve ´ge ´tale, INRA, Domaine
St-Maurice, BP 94, 84143 Montfavet Cedex, France
J.-C. Poggiale
Institut Me ´diterrane ´en d’Oce ´anologie (MIO), UM 110, CNRS 7294
IRD 235, Universite ´ de Toulon, Aix-Marseille Universite ´,
Campus de Luminy, 13288 Marseille Cedex 9, France
J.-C. Bertrand et al. (eds.), Environmental Microbiology: Fundamentals and Applications: Microbial Ecology,
DOI 10.1007/978-94-017-9118-2_8, # Springer Science+Business Media Dordrecht 2015
261
8
Philippe Normand, Robert Duran, Xavier Le Roux, Cindy Morris,
and Jean-Christophe Poggiale
Abstract
All ecosystems are composed of multiple species performing numerous functions. This
plurality identified as biodiversity has become a research topic of general importance for
understanding how ecosystems function. The word “biodiversity” has subsequently
received different interpretations we aim to describe. Microbial systems can be used to
illustrate these definitions and to clarify paradigms that have emerged in general ecology.
Microbial biodiversity can be characterized by the kind of biodiversity (taxa or functional
groups present), the representativeness of samples, and the culturability of samples or taxa,
in terms of genetic, functional, or physiological characteristics. Biodiversity is a major
driver of ecosystem functioning, and this relation is described in the case of several
biotopes. Several mathematical approaches have been used to quantify microbial diversity,
and the various indices are described and discussed.
Keywords
Alpha diversity Beta diversity Biodiversity Canonical correspondence
analysis Chimeras Cluster analysis Community structure Cultural
approach Denaturing gradient gel electrophoresis (DGGE) Diversity
indices DNA arrays DNA reassociation Fingerprints Functional
groups Identification Linkage disequilibrium analysis Lipids Metabolic capacities
of communities Metabolites Microbial communities Multivariate analysis Nei
index Nonparametric test OTU (operational taxonomic unit) Parametric
test Phylotype Pigment Principal component analysis Rarefaction
curve Ribosomal intergenic spacer analysis (RISA) Richness Saturation
analysis Shannon alpha diversity index Simpson index Single-strand conformational
polymorphism (SSCP) Spearman correlation tests Species richness index Temperature
gradient gel electrophoresis (TGGE) Terminal-restriction fragment length polymorphism
(T-RFLP) Variables
P. Normand* (*) X. Le Roux
Microbial Ecology Center, UMR CNRS 5557 / USC INRA 1364,
Universite ´ Lyon 1, 69622 Villeurbanne, France
e-mail: philippe.normand@univ-lyon1.fr
R. Duran
Institut des Sciences Analytiques et de Physico-chimie pour
l’Environnement et les Mate ´riaux (IPREM), UMR CNRS 5254,
Universite ´ de Pau et des Pays de l’Adour, B.P. 1155,
64013 Pau Cedex, France
* Chapter Coordinator
C. Morris
Unite ´ de Recherches de Pathologie Ve ´ge ´tale, INRA, Domaine
St-Maurice, BP 94, 84143 Montfavet Cedex, France
J.-C. Poggiale
Institut Me ´diterrane ´en d’Oce ´anologie (MIO), UM 110, CNRS 7294
IRD 235, Universite ´ de Toulon, Aix-Marseille Universite ´,
Campus de Luminy, 13288 Marseille Cedex 9, France
J.-C. Bertrand et al. (eds.), Environmental Microbiology: Fundamentals and Applications: Microbial Ecology,
DOI 10.1007/978-94-017-9118-2_8, # Springer Science+Business Media Dordrecht 2015
261