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Combe, M., Bouvier, T., Pringault, olivier., Rochelle-Newall, E., Bouvier, C., Agis, M., et al. (2013). Freshwater prokaryote and virus communities can adapt to a controlled increase in salinity through changes in their structure and interactions. Estuarine Coastal and Shelf Science, 133, 58–66.
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Joux, F., Bertrand, J. - C., De Wit, R., Grossi, V., Intertaglia, L., Lebaron, P., et al. (2015). Methods for Studying Microorganisms in the Environment. In J. - C. Bertrand, P. Caumette, P. Lebaron, R. Matheron, P. Normand, & T. Sime-Ngando (Eds.), (pp. 757–829). Environmental Microbiology: Fundamentals and Applications. Springer Netherlands.
Résumé: The main methods for the study of microorganisms in the environment (water, soil, sediment, biofilms), the different techniques of sampling for measuring biomass, the activities, and the diversity of the microorganisms are presented. To respond to these various issues, techniques as varied as those of flow cytometry, molecular biology, biochemistry, molecular isotopic tools, or electrochemistry are implemented. These different techniques are described with their advantages and disadvantages for different types of biotopes. The question of the isolation, culture, and conservation of microorganisms from the environment are also addressed. Without being exhaustive, this chapter emphasizes the importance of using appropriate and efficient methodological tools to properly explore the still mysterious compartment of microorganisms in the environment.
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KIVELA, M., ARNAUD-HAOND, S., & SARAMAKI, J. (2015). EDENetworks: A user-friendly software to build and analyse networks in biogeography, ecology and population genetics. Molecular Ecology Resources, 15(1), 117–122.
Résumé: The recent application of graph-based network theory analysis to biogeography, community ecology and population genetics has created a need for user-friendly software, which would allow a wider accessibility to and adaptation of these methods. EDENetworks aims to fill this void by providing an easy-to-use interface for the whole analysis pipeline of ecological and evolutionary networks starting from matrices of species distributions, genotypes, bacterial OTUs or populations characterized genetically. The user can choose between several different ecological distance metrics, such as Bray-Curtis or Sorensen distance, or population genetic metrics such as FST or Goldstein distances, to turn the raw data into a distance/dissimilarity matrix. This matrix is then transformed into a network by manual or automatic thresholding based on percolation theory or by building the minimum spanning tree. The networks can be visualized along with auxiliary data and analysed with various metrics such as degree, clustering coefficient, assortativity and betweenness centrality. The statistical significance of the results can be estimated either by resampling the original biological data or by null models based on permutations of the data.
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Mostajir, B., Amblard, C., Buffan-Dubau, E., De Wit, R., Lensi, R., & Sime-Ngando, T. (2015). Microbial Food Webs in Aquatic and Terrestrial Ecosystems. In J. - C. Bertrand, P. Caumette, P. Lebaron, R. Matheron, P. Normand, & T. Sime-Ngando (Eds.), (pp. 485–509). Environmental Microbiology: Fundamentals and Applications. Springer Netherlands.
Résumé: In microbial food webs, different types of interactions occur between microorganisms themselves and with meio- and macroorganisms. After an historical and general introduction, the biological components of the microbial food webs in the pelagic and benthic marine and lake ecosystems, as well as in the terrestrial ecosystems, are presented. The functioning of the microbial food webs in different ecosystems is illustrated and explained, including the trophic pathways and transfer of matter from microbial food webs toward meio- and macroorganisms of the superior trophic levels, the nutrient recycling in the aquatic environments, and the decomposition of organic matter in soils. Finally, the factors regulating microbial food webs, primarily “top-down” and “bottom-up” controls, are described with a special focus on the role of viruses in the aquatic microbial food webs.
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Poggiale, J. - C., Dantigny, P., De Wit, R., & Steinberg, C. (2015). Modeling in Microbial Ecology. In J. - C. Bertrand, P. Caumette, P. Lebaron, R. Matheron, P. Normand, & T. Sime-Ngando (Eds.), (pp. 847–882). Environmental Microbiology: Fundamentals and Applications. Springer Netherlands.
Résumé: The bases and the principles of modeling in microbial community ecology and biogeochemistry are presented and discussed. Several examples are given. Among them, the fermentation process is largely developed, thus demonstrating how the model allows determining the microbial population growth rate, the death rate, and the maintenance rate. More generally, these models have been used to increase the development of bioenergetic formulations which are presently used in biogeochemical models (Monod, Droop, DEB models). Different types of interactions (competition, predation, and virus–bacteria) are also developed. For each topic, a complete view of the models used in the literature cannot be presented. Consequently, the focus has been done on the demonstration how to build a model instead of providing a long list of existing models. Some recent results in sediment biogeochemistry are provided to illustrate the application of such models.
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