Microbial biogeography: putting microorganisms on the map
Jennifer B. Hughes Martiny, Brendan J. M. Bohannan, James Brown, Robert K Colwell, Jed A. Fuhrman, Jessica L. Green, M. Claire Horner-Devine, Matthew Kane, Jennifer Adams Krumins, Cheryl R. Kuske, Peter J. Morin, Shahid Naeem, Lise Øvreås, Anna-Louise Reysenbach, V. H. Smith, James T Staley
NATURE REVIEWS - MICROBIOLOGY - FEBRUARY 2006 - VOLUME 4 -pp 102 - 112
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.
Biogeography is the study of the distribution of biodiversity over space and time. It aims to reveal where organisms live, at what abundance, and why. The study of biogeography offers insights into the mechanisms that generate and maintain diversity, such as speciation, extinction, dispersal and species interactions1 . Since the eighteenth century, biologists have investigated the geographic distribution of plant and animal diversity. More recently, the geographic distributions of microorganisms have been examined. Genetic methodologies have revealed that past culture-based studies missed most microbial diversity2–4, and have allowed recent studies to sample microbial diversity more deeply and widely than ever before5,6. Microbial biogeography stands to benefit tremendously from these advances, although there is still debate as to whether microorganisms exhibit any biogeographic patterns7–10
Although traditionally confined to separate academic disciplines, ecologists who study microorganisms and those who study macroorganisms have been interacting more often in recent years. Indeed, this article is a result of a National Center for Ecological Analysis and Synthesis (NCEAS) working group composed of scientists from both specialties. Our goal here is to review what is known regarding the biogeography of microorganisms in light of that of macroorganisms. This inquiry is not driven by the expectation that microorganisms simply follow the patterns of macroorganisms, but rather by the fact that the biogeography of macroorganisms is much better studied. Furthermore, micro- and macroorganisms are often involved in intimate associations that affect each other’s geographic distributions11,12. Therefore, a logical first hypothesis is that the biogeography of microorganisms is similar to the biogeography of macroorganisms. To the extent that microorganisms conform to the relationships documented for macroorganisms, they will extend the generality of empirical patterns and support mechanistic hypotheses that all living entities share universal attributes. Alternatively, if microorganisms can be shown to represent clear exceptions to the biogeographic patterns of plants and animals, then this will call attention to unique features of microbial life that have influenced the generation and maintenance of its diversity.
As an initial step towards distinguishing between these hypotheses, we suggest a framework for investigating whether microbial assemblages differ in different places and the extent to which this spatial variation is due to contemporary environmental factors and historical contingencies. We then discuss the mechanistic processes that generate and maintain biogeographic patterns in macroorganisms and consider their relevance to microbial biogeography
There is no universal definition of a ‘micro organism’. The term generally denotes members of the domains Bacteria and Archaea, as well as microscopic members of the domain Eukarya (for example, unicellular algae, some fungi and protists). For convenience, we further define a microorganism as having a mass of less than 10–5 g and a length of less than 500 µm.
We do not consider the question of whether viruses have bio geography, as their biology adds further complications and, in most cases, far less is known about their distribution than that of other microorganisms (for a recent discussion see REF. 13).
Figure 1 | Assessing the contributions of environmental and historical effects on microbial biogeography. Four alternative hypotheses about environmental and historical influences on communities and the general results that would support them, using (a) samples (shown in circles) from discrete predefined habitat types (A, B and C) and locations (green versus white) or (b) samples from continuous habitat variables and geographic distances. The axes in (a) are dimensionless; samples that contain similar assemblages are mapped closer to one another relative to pairs of samples with different assemblages. In b, lack of a correlation between environmental similarity or geographic distance and biotic similarity (BOX 1) indicates no biogeographic patterning. Alternatively, to the extent that environmental and historical factors have influenced the assemblages sampled, biotic similarity should be correlated with environmental similarity and geographic distance, respectively. Standard correlation tests are not appropriate to distinguish between these hypotheses because of non-independence; therefore, randomization tests such as a bootstrapped regression analysis25 or Mantel tests87,88 are required. Further tests, such as a partial Mantel test, can disentangle the effects of geographic distance versus environment on assemblage composition89.
Table 1 | Examples of studies that have found non-random distributions of free-living microbial taxa
Table 2 | Studies of the effects of distance (dist.) and environment (env.) on microbial composition
Figure 2 | Hypothetical relationship between body mass (at an organism’s largest life stage) and lifetime dispersal capability. The relationship varies depending on whether the organism disperses actively or passively (by its own propulsion). The range of active (a) dispersal is a subset of the range of passive (b) dispersal. It is convenient to think of the log(mass) axis as representing three qualitative groups: first, microorganisms, which span about 8 orders of magnitude from bacteria to eukaryotic algae and protozoa (10–13–10–5 g); second, large plants and animals, which span about 8 orders of magnitude from herbs and small vertebrates to whales and trees (101–109 g); and third, intermediatesized organisms, which span the intervening 6 or so orders of magnitude and include the small metazoans, such as nematodes, annelids and arthropod
Figure 3 | Hypothetical dispersal distribution of a typical passively dispersed macroorganism. Population density influences the probability that an individual from that population will disperse over very long distances (solid line). For taxa with relatively low densities (dashed line), dispersal might be effectively restricted, even though long-distance movement is theoretically possible. Based on REF. 41.
Figure 4 | Hypothesized constraints on a taxon’s population density in a given body-size class. The thick green line on the diagonal is a known physiological constraint. The gradient in shading from the diagonal to the bottom-left corner represents the idea that fewer taxa are thought to fall in the bottom left of the figure; however, we hypothesize that some taxa do fall in this region. The inset plots log (body mass, g) of North American birds versus log (population density, individuals per route). The data set falls within a well-defined quadrilateral with a constant minimum density and a maximum density for birds of an intermediate size. Individual data points are not shown. The outline of these data is also sketched on the constraint figure. The approximate range of marine phytoplankton data from Li48 is also sketched (assuming that cell volume is proportional to body mass). The X-axis categories are defined in FIG. 2. Inset adapted with permission from REF. 43 © (1987) University of Chicago.
Figure 5 | Hypothesized constraints on an organism’s geographic-range size for a given body mass. The inset graph is log (body size, g) versus log (geographic-range size, 106 km2) for terrestrial bird species of North America. Individual data points are not shown. The combined data set forms an approximate triangle. The outline of these data is also sketched on the constraint figure. The X-axis categories are defined in FIG. 2. Inset adapted with permission from REF. 43 © (1987) University of Chicago.
Figure 6 | Hypothesized relationships between number of species and body mass. For larger macroorganisms (approximately larger than insects), it is clear that the number of species increases as body mass decreases. For smaller macroorganisms and microorganisms, the number of species might continue to increase (dashed line) or begin to decrease (dotted line) as body mass decreases. The inset plots the number of invertebrate species by log(mass) on Marion Island64. The X-axis categories are defined in FIG. 2. Inset reproduced with permission from REF. 64 © (2001) National Academy of Sciences, USA.
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