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  • Review Article
  • Published:

Microbial biogeography: putting microorganisms on the map

Nature Reviews Microbiology volume 4, pages 102–112 (2006)Cite this article

Key Points

  • Since the eighteenth century, biologists have investigated plant and animal biogeography, but only recently have the distributions of microorganisms been examined.

  • We consider microbial biogeography in light of habitats types (the contemporary environment) and provinces (legacies of historical events such as dispersal limitation). This framework is useful for addressing whether the distributions of microbial taxa, like those of macroorganisms, reflect the influences of both contemporary environmental conditions and past events.

  • We review a growing body of literature that suggests that microbial assemblages are not only influenced by their current environment, but that some display a degree of provincialism — evidence that these microbial assemblages have diverged and are maintained by genetic isolation. We also find that the relative influence of historical versus environmental factors appears to be related to the scale of sampling.

  • As a first hypothesis, we suggest that the same processes that influence macroorganism biogeography (colonization, diversification and extinction) also apply to microbial life, but that their rates scale with body size, or for single-celled organisms, cell size. Therefore, we use the idea of allometry as a structure for discussing the rates of biogeographic processes in microorganisms.

  • We conclude that the rates of biogeographic processes probably vary more widely for microorganisms of a given size than for macroorganisms of a given size.

  • To tackle the mechanisms generating microbial biogeographic patterns, we recommend that new microbial biogeography studies should systematically sample and record data from various distances, habitats and environmental conditions.

Abstract

We review the biogeography of microorganisms in light of the biogeography of macroorganisms. A large body of research supports the idea that free-living microbial taxa exhibit biogeographic patterns. Current evidence confirms that, as proposed by the Baas-Becking hypothesis, 'the environment selects' and is, in part, responsible for spatial variation in microbial diversity. However, recent studies also dispute the idea that 'everything is everywhere'. We also consider how the processes that generate and maintain biogeographic patterns in macroorganisms could operate in the microbial world.

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Figure 1: Assessing the contributions of environmental and historical effects on microbial biogeography.
Figure 2: Hypothetical relationship between body mass (at an organism's largest life stage) and lifetime dispersal capability.
Figure 3: Hypothetical dispersal distribution of a typical passively dispersed macroorganism.
Figure 4: Hypothesized constraints on a taxon's population density in a given body-size class.
Figure 5: Hypothesized constraints on an organism's geographic-range size for a given body mass.
Figure 6: Hypothesized relationships between number of species and body mass.

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Acknowledgements

This work was conducted as part of the Patterns in Microbial Biodiversity Working Group supported by the National Center for Ecological Analysis and Synthesis, a centre funded by the National Science Foundation, the University of California at Santa Barbara and the State of California. We thank M. Liebold, G. Muyzer, O. Petchey and D. Ward for useful and lively discussions, and C. van der Gast for comments on the manuscript. Any opinions, findings and conclusions or recommendations expressed in this study are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Authors and Affiliations

  1. Department of Ecology and Evolutionary Biology, 80 Waterman Street, BOX G-W, Brown University, Providence, 02912, Rhode Island, USA

    Jennifer B. Hughes Martiny

  2. Department of Biological Sciences, Stanford University, 94305, California, USA

    Brendan J.M. Bohannan

  3. Department of Biology, University of New Mexico, New Mexico, 87131, USA

    James H. Brown

  4. Department of Ecology and Evolutionary Biology, University of Connecticut, Connecticut, 06269, USA

    Robert K. Colwell

  5. Department of Biological Sciences, University of Southern California, 90089, California, USA

    Jed A. Fuhrman

  6. School of Natural Sciences, University of California, Merced, 95344, California, USA

    Jessica L. Green

  7. School of Aquatic and Fishery Science, University of Washington, 98195, Washington, USA

    M. Claire Horner-Devine

  8. Division of Molecular and Cellular Biosciences, National Science Foundation, 22230, Virginia, USA

    Matthew Kane

  9. Department of Ecology and Evolution, Rutgers University, New Jersey, 08901, USA

    Jennifer Adams Krumins & Peter J. Morin

  10. Bioscience Division, Los Alamos National Laboratory, New Mexico, 87545, USA

    Cheryl R. Kuske

  11. Department of Ecology, Evolution and Environmental Biology, Columbia University, New York, 10027, USA

    Shahid Naeem

  12. Department of Biology, University of Bergen, Norway

    Lise Øvreås

  13. Department of Biology, Portland State University, Oregon, 97207, USA

    Anna-Louise Reysenbach

  14. Department of Ecology and Evolutionary Biology, University of Kansas, Kansas, 66045, USA

    Val H. Smith

  15. Department of Microbiology, University of Washington, 98195, Washington, USA

    James T. Staley

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Corresponding author

Correspondence to Jennifer B. Hughes Martiny.

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NCEAS

Glossary

Province

A region the biotic composition of which reflects the legacies of historical events.

Habitat type

An environment defined by the suite of its abiotic and biotic characteristics.

Beta diversity

Taxonomic diversity due to turnover in composition between assemblages.

Distance effect

The influence of isolation on biotic composition after controlling for the influence of the contemporary environment.

Genetic drift

Changes in gene frequencies in a population caused solely by chance.

Allometry

The relationship between organismal attributes and body size of the form Y = Y0 Mb, in which Y is a variable such as metabolic rate, lifespan or population density, Y0 is a normalization constant (the y-intercept on a logarithmic graph), M is body mass (or other measure of body size) and b is the scaling exponent (the slope on the graph).

Ecological drift

The influence of random demographic variability (such as birth, death and migration rates) on biotic composition.

Propagule

The smallest unit of dispersal that is necessary to colonize a new population.

Geographic range

The area encompassing the extent of a taxon's distribution.

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Martiny, J., Bohannan, B., Brown, J. et al. Microbial biogeography: putting microorganisms on the map. Nat Rev Microbiol 4, 102–112 (2006). https://doi.org/10.1038/nrmicro1341

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