The microbial contribution to macroecology

Abstract

There has been a recent explosion of research within the field of microbial ecology that has been fueled, in part, by methodological improvements that make it feasible to characterize microbial communities to an extent that was inconceivable only a few years ago. Furthermore, there is increasing recognition within the field of ecology that microorganisms play a critical role in the health of organisms and ecosystems. Despite these developments, an important gap still persists between the theoretical framework of macroecology and microbial ecology. We highlight two idiosyncrasies of microorganisms that are fundamental to understanding macroecological patterns and their mechanistic drivers. First, high dispersal rates provide novel opportunities to test the relative importance of niche, stochastic, and historical processes in structuring biological communities. Second, high speciation rates potentially lead to the convergence of ecological and evolutionary time scales. After reviewing these unique aspects, we discuss strategies for improving the conceptual integration of microbes into macroecology. As examples, we discuss the use of phylogenetic ecology as an integrative approach to explore patterns across the tree of life. Then we demonstrate how two general theories of biodiversity (i.e., the recently developed theory of stochastic geometry and the neutral theory) can be adapted to microorganisms. We demonstrate how conceptual models that integrate evolutionary and ecological mechanisms can contribute to the unification of microbial ecology and macroecology.

Keywords: dispersal; macroecology; microbial ecology; neutral theory; speciation; stochastic geometry.

FIGURE 1

Conceptual summary of the main processes influencing community composition, structure, and diversity at different spatial scales. All ecological and evolutionary processes considered have been encapsulated in three perspectives: deterministic (i.e., the biotic and abiotic niche), stochastic, and historic. It can be argued that each one of the processes may have deterministic, stochastic, and historic components. For example, dispersal may be stochastic when rates depend solely on population size, deterministic when traits that affect arrival and establishment are considered, and also historic if the information of past events is available. Additionally, although the same process can operate at different scales, in this simplistic model as spatial scale increases historical processes tend to be more relevant, while at small local scale stochasticity can play an important role. As follows, speciation often requires geographic barriers, diverse niches and/or large population sizes to take place. On the contrary, the stochastic change in the abundance of organisms (drift) that can eventually result in extinction is more important at small population sizes. The demarcation of discrete spatial scales is arbitrary and will be dependent on the study system in question.

FIGURE 2

Model simulation results of the stochastic geometry theory (McGill, 2010) as applied to either macroorganisms (top left) or microorganisms (bottom left). The only difference between both simulations is the “dispersal” parameter (i.e., larger spread of the spatial distributions for microbial species). For simplicity, the number of species (represented as different colors) has been set to fifteen for both macroorganisms and microorganisms. Axes represent the two spatial dimensions, while color intensity indicates relative abundance. As explained in McGill (2010), species abundance distributions (top right) are generated by sampling at one point in the spatial grid, species-area relationships (mid right) are created by sampling increasingly large areas, while the decrease of community similarity with spatial distance (bottom right) is derived by sampling areas of the same size at different distances. The tendency of microorganisms to be better dispersers (larger spatial distributions) is sufficient to reproduce the observed qualitative differences of macroecological patterns between macroorganisms and microorganisms. For microbes, the key differences observed for microorganisms versus macroorganisms include: richer species abundance distributions with longer tails of rare taxa (Curtis et al., 2006), species-area relationships with a higher total number of species and with lower slopes (Lennon and Jones, 2011), and a more moderate decay of community similarity with distance (Soininen, 2012). That is, microbial communities would tend to have a higher number of species (richness, or alpha-diversity) but lower turnover (beta-diversity).

FIGURE 3

A schematic representation of two neutral models: Hubbell’s original two-level spatially implicit model (Hubbell, 2001) for macroorganisms (above), and a suggested model for microorganisms (below). Both models are based on the same mechanistic processes operating at different scales. The main differences are that, in the neutral model for microorganisms, global scale dynamics become more important with the incorporation of long-distance dispersal to the global pool due to high dispersibility, and high speciation introduced by placing this process at the local scale. As in Figure 1, the demarcation of discrete spatial scales is arbitrary.