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  • Review Article
  • Published:

Visualization, modelling and prediction in soil microbiology

Nature Reviews Microbiology volume 5, pages 689–699 (2007)Cite this article

Key Points

  • Soil microbiology is enjoying a period of challenge and discovery made possible by the availability of new approaches for characterizing microbial communities and for imaging the soil environment.

  • Soils are highly complex and the development of soil microbiology as a systems science requires that microbial ecologists take full account of the spatio–temporal heterogeneity of microbial communities and their physical environments. The evolution of microbial communities (diversity) and their response in space and time (function) can be seen as emergent properties of this physicochemical environment.

  • The introduction of imaging techniques such as fluorescence in situ hybridization (FISH), FISH-microautoradiography (MAR), nano-secondary ion mass spectrometry (Nano-SIMS) and X-ray tomography offer new opportunities for locating microorganisms in their three-dimensional (3D) environment and for relating this to selected functions. However, none of the current analytical approaches offer an ideal solution for quantitatively imaging microorganisms in their physical environment, and further developments are needed.

  • Innovations in modelling are providing the tools needed to tackle the twin problems of integrating the physical heterogeneity of the soil environment with the dynamics of microbial communities. These methods have all been derived from developments in physics and have the advantage of enabling the stochastic behaviour of individual components of these complex, spatially segregated systems to be modelled.

  • Three modelling approaches are described. The first of these, individual based (IB) models, makes it possible to deal with individual particles and simulate their behaviours stochastically. General IB models are used when variability in individual components are deemed important in governing system processes. However, IB models are limited in their application to soils as they cannot model the dynamic impacts of microbial activity on the physical environment.

  • The lattice Boltzmann (LBM) method can be used to describe the multiphase transport processes typical of soil environments and is itself an IB model that simulates the 3D environment by tracking individual particles. It has the advantage over general IB models in that it uses interaction rules to reproduce surface tension and viscosity effects and can accommodate how these are modified by microbial growth and activity.

  • Network models are based on graph theory and, like IB and LBM, can be used to model individual components such as colonies of individual cells in a biological system. They differ in their application from IB and LBM in that the interactions between individual components are modelled as individual entities rather than as emergent properties. An important limitation of network models is that they currently do not explicitly address space.

Abstract

The introduction of new approaches for characterizing microbial communities and imaging soil environments has benefited soil microbiology by providing new ways of detecting and locating microorganisms. Consequently, soil microbiology is poised to progress from simply cataloguing microbial complexity to becoming a systems science. A systems approach will enable the structures of microbial communities to be characterized and will inform how microbial communities affect soil function. Systems approaches require accurate analyses of the spatio–temporal properties of the different microenvironments present in soil. In this Review we advocate the need for the convergence of the experimental and theoretical approaches that are used to characterize and model the development of microbial communities in soils.

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Figure 1: FISH-MAR for analysis of bacterial activity.
Figure 2: Secondary ion mass spectrometry.
Figure 3: Soil aggregates visualized using X-ray computer tomography.

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Acknowledgements

We are grateful to the anonymous reviewers for helpful and constructive comments on the manuscript. Our work in this area is supported by a range of sponsors, but in particular by the Biotechnology and Biological Sciences Research Council (BBSRC), the Natural Environment Research Council (NERC) and the Engineering and Physical Sciences Research Council (EPSRC), UK.

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  1. Institute for Research on Environment and Sustainability, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK

    Anthony G. O'Donnell, Steven P. Rushton & Mark D. Shirley

  2. SIMBIOS Centre, University of Abertay, Bell Street, Dundee, DD1 1HG, Dundee, UK

    Iain M. Young & John W. Crawford

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DATABASES

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Glossary

Soil porosity

Although there is no sharp demarcation, macropores allow the movement of air and percolating water, whereas micropores, under normal field conditions, are generally filled with water and limit the movement of air. Water movement in micropores is usually restricted to slow capillary movement. A good illustration of the importance of pore-size distribution is a sandy soil, where despite a low total porosity the movement of air and water is rapid because macropores dominate.

Capillary force

As used in this Review, a capillary force enables water to move against gravity and is the net effect of the attractive force of water for the solid matrix through which it moves (adhesion) and the surface tension of water. Surface tension of water is largely a consequence of the attraction of polar water molecules for each other (cohesion).

Gravimetric force

Refers to the movement of soil water under the force of gravity. Gravitational water drains easily from soils and is not influenced by interactions with the solid matrix.

Soil microbial biomass

The soil microbial biomass concept assumes that the entire soil microbial population (bacteria, fungi, protozoa and so on) can be treated as a single entity. It is easy to measure and has been used extensively in soil science to assess and predict the impact of management, climate, pollution and other factors on the soil biota.

Ecophysiology

Refers to the adaptation of microorganisms to growth in natural environments. In soils, the physiology of individual members of a population can change according to the individual biotic and abiotic environments. It is the distribution of these physiologies in space and time that delivers soil functions.

Kriging

Kriging is a set of geostatistical methods that are used to interpolate values of spatial patterns at unsampled points. Kriging recognizes that in any set of samples or measurements there may be underlying and systematic spatial patterning of the data.

Mean field theory

Mean field theory deals with multiple system components by replacing the complexity of interactions with an average interaction. The accuracy of mean field analyses is dependent on the number of interacting systems. High dimension systems are more accurate.

Graph theory

Graph theory is the study of graphs, which in mathematics and computer sciences are used to model pair-wise relationships between objects. The interactions (edges) between each pair of objects (vertices) can be directed (for example, vertex A predates vertex B), or undirected (for example, vertices A and B are in competition).

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O'Donnell, A., Young, I., Rushton, S. et al. Visualization, modelling and prediction in soil microbiology. Nat Rev Microbiol 5, 689–699 (2007). https://doi.org/10.1038/nrmicro1714

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