Other aspects of ecological theory have been studied in
microbiology, e.g., eutrophication and algal blooms clearly
contributed to our understanding of the concept of
biological carrying capacity of the habitat. Obviously,
in plant ecology, for example, the important parameter
for explaining ecosystem productivity in large-scale
experiments such as those conducted in Jena (Roscher
et al. 2007) is not so much the number of plant species
but rather the functional groups defined a posteriori
(dinitrogen fixers, small herbs, etc.) to which they belong
(Le Roux et al. 2013). A comparable question for
microorganisms would address functional groups such as
photosynthetic organisms, dinitrogen fixers, cellulolytic
ones, antibiotic producers, as well as others that will
emerge as a result of research on microbial ecology such
as those described here. Even within a given microbial
functional group, microbial functional traits are better
predictors of functional complementarity and ecosystem
functioning than taxonomic diversity (Salles et al. 2012).
Clearly, microbial ecological research can help to test
hypotheses developed in general ecological theory. A
major and current motivation for the study of microbial
diversity is to understand the role that biodiversity plays in
the functioning of microbial communities to better manage,
protect, or handle them. Some examples of goals of microbial biodiversity studies are to:
(i) Identify the role of community complexity in the degradation and chemical modifications of chemicals in
biogeochemical cycles of elements in general
(ii) Describe the biogeography of microorganisms to highlight the limits to their dissemination and the importance of their adaptation to habitats
(iii) Discover organisms playing key roles in environmental processes or with a strong potential for industrial
utility
(iv) Assess the impact of human activities on microbial
biodiversity, especially to avoid the destruction of useful diversity (i.e., beneficial to the environment) or to
manage negative organisms (limit the emergence of
harmful organisms: pathogens, hypercompetitive
organisms, etc.)
Despite the relevance of these objectives to contemporary
issues of environmental protection, most studies in microbial
diversity have long referred to the simple description of
biodiversity and have spotlighted species or variants that
were previously unknown (Morris et al. 2002). The
biological richness revealed in these studies has occasionally
found practical applications in the development of diagnostic tools (e.g., medical or plant health assessment) and in
industrial processes or biotechnology. The thermostable
DNA polymerase from Thermus aquaticus used in PCR
reactions, discovered during a study of microbial diversity
in extreme environments, is the archetypal example of such
an application. Several DNA polymerases were known
before, but it was the discovery of a thermostable enzyme
which has made chain reaction possible and opened the
market for PCR, which is now an industrial product that
represents a 300 million dollar market.
8.3
Mathematical Approaches and Tools for
the Study of Microbial Biodiversity
A large proportion of studies on microbial biodiversity have
been mainly descriptive. In reading the literature, a novice
student could easily get the impression that the motto “look
and see” is the accepted approach to the study of microbial
diversity. This trend was revealed by a systematic study of
the literature on microbial biodiversity for the period
1977–2002 (Morris et al. 2002). A major challenge for
research on microbial biodiversity that has been partially
addressed in recent years is the conceptualization and implementation of experimental design.
Despite recent calls to do descriptive, hypotheses-free
ecological studies, we feel that the implementation of appropriate experimental designs for the study of microbial biodiversity involves the application of the scientific method
common to all research in the natural sciences. This implies:
(i) Formulating hypotheses relevant to the objectives
(ii) Developing sampling procedures to distinguish experimental error from effects due to the environmental
processes studied
(iii) Demonstrating the repeatability of the results obtained
(iv) The use of nonsubjective (statistical) tests of hypotheses
The nature of microbial communities makes sampling
especially critical for studies of biodiversity. In addition,
advances in molecular biology have rendered a wide variety
of techniques for characterizing microorganisms and microbial communities more available to researchers, thereby
facilitating the elucidation of subtle differences between
members of the same species. All this leads to a paradox
faced by many researchers in the field of microbial biodiversity: the relatively small number of samples that can be
characterized reveals a level of diversity that effectively
and severely limits the power of statistical analyses. Some
of the steps for defining experimental design for the study of
microbial biodiversity that can help resolve this paradox will
be presented in details later in this chapter.
Formulating clear objectives and identifying the underlying assumptions are one of the first steps in any research
project. The hypotheses to be tested will be crucial to determine the choice of methods, the nature of the experimental
setup, and the type of statistical analyses to be used. However, microbial biodiversity studies often face trade-offs
between the optimal size of samples and the limits of
time and labor necessary for characterizing the samples.
264
P. Normand et al.
microbiology, e.g., eutrophication and algal blooms clearly
contributed to our understanding of the concept of
biological carrying capacity of the habitat. Obviously,
in plant ecology, for example, the important parameter
for explaining ecosystem productivity in large-scale
experiments such as those conducted in Jena (Roscher
et al. 2007) is not so much the number of plant species
but rather the functional groups defined a posteriori
(dinitrogen fixers, small herbs, etc.) to which they belong
(Le Roux et al. 2013). A comparable question for
microorganisms would address functional groups such as
photosynthetic organisms, dinitrogen fixers, cellulolytic
ones, antibiotic producers, as well as others that will
emerge as a result of research on microbial ecology such
as those described here. Even within a given microbial
functional group, microbial functional traits are better
predictors of functional complementarity and ecosystem
functioning than taxonomic diversity (Salles et al. 2012).
Clearly, microbial ecological research can help to test
hypotheses developed in general ecological theory. A
major and current motivation for the study of microbial
diversity is to understand the role that biodiversity plays in
the functioning of microbial communities to better manage,
protect, or handle them. Some examples of goals of microbial biodiversity studies are to:
(i) Identify the role of community complexity in the degradation and chemical modifications of chemicals in
biogeochemical cycles of elements in general
(ii) Describe the biogeography of microorganisms to highlight the limits to their dissemination and the importance of their adaptation to habitats
(iii) Discover organisms playing key roles in environmental processes or with a strong potential for industrial
utility
(iv) Assess the impact of human activities on microbial
biodiversity, especially to avoid the destruction of useful diversity (i.e., beneficial to the environment) or to
manage negative organisms (limit the emergence of
harmful organisms: pathogens, hypercompetitive
organisms, etc.)
Despite the relevance of these objectives to contemporary
issues of environmental protection, most studies in microbial
diversity have long referred to the simple description of
biodiversity and have spotlighted species or variants that
were previously unknown (Morris et al. 2002). The
biological richness revealed in these studies has occasionally
found practical applications in the development of diagnostic tools (e.g., medical or plant health assessment) and in
industrial processes or biotechnology. The thermostable
DNA polymerase from Thermus aquaticus used in PCR
reactions, discovered during a study of microbial diversity
in extreme environments, is the archetypal example of such
an application. Several DNA polymerases were known
before, but it was the discovery of a thermostable enzyme
which has made chain reaction possible and opened the
market for PCR, which is now an industrial product that
represents a 300 million dollar market.
8.3
Mathematical Approaches and Tools for
the Study of Microbial Biodiversity
A large proportion of studies on microbial biodiversity have
been mainly descriptive. In reading the literature, a novice
student could easily get the impression that the motto “look
and see” is the accepted approach to the study of microbial
diversity. This trend was revealed by a systematic study of
the literature on microbial biodiversity for the period
1977–2002 (Morris et al. 2002). A major challenge for
research on microbial biodiversity that has been partially
addressed in recent years is the conceptualization and implementation of experimental design.
Despite recent calls to do descriptive, hypotheses-free
ecological studies, we feel that the implementation of appropriate experimental designs for the study of microbial biodiversity involves the application of the scientific method
common to all research in the natural sciences. This implies:
(i) Formulating hypotheses relevant to the objectives
(ii) Developing sampling procedures to distinguish experimental error from effects due to the environmental
processes studied
(iii) Demonstrating the repeatability of the results obtained
(iv) The use of nonsubjective (statistical) tests of hypotheses
The nature of microbial communities makes sampling
especially critical for studies of biodiversity. In addition,
advances in molecular biology have rendered a wide variety
of techniques for characterizing microorganisms and microbial communities more available to researchers, thereby
facilitating the elucidation of subtle differences between
members of the same species. All this leads to a paradox
faced by many researchers in the field of microbial biodiversity: the relatively small number of samples that can be
characterized reveals a level of diversity that effectively
and severely limits the power of statistical analyses. Some
of the steps for defining experimental design for the study of
microbial biodiversity that can help resolve this paradox will
be presented in details later in this chapter.
Formulating clear objectives and identifying the underlying assumptions are one of the first steps in any research
project. The hypotheses to be tested will be crucial to determine the choice of methods, the nature of the experimental
setup, and the type of statistical analyses to be used. However, microbial biodiversity studies often face trade-offs
between the optimal size of samples and the limits of
time and labor necessary for characterizing the samples.
264
P. Normand et al.