The diversity of prokaryotes on Earth is unfathomable, with some estimates as high as ~1017 total species.1
This mind-numbing statistic is reinforced by work in comparative genomics that has shown remarkable diversity between and within species. Despite the wealth of information that has been gathered to document microbial diversity, the evolutionary and ecological processes leading to the emergence and maintenance of this diversity are largely unknown.
The high microbial diversity found in spatially heterogeneous environments such as soil can be attributed in part to niche separation, but microorganisms that are ecologically similar have been found to coexist in close proximity to each other in many habitats. Gradients of nutrients, redox conditions, pH, and other environmental factors are common in microbial systems, and their effects can be readily seen in the formation of bacterial mats and the three-dimensional structure of biofilms. In natural systems, the spatial structure that mediates these gradients is nearly ubiquitous and is often heavily influenced by growth of the microbial organisms themselves. The resulting fine-scale environmental heterogeneity can provide the conditions that can lead to the apparent coexistence of strains, often referred to as ecotypes, that have similar physiological characteristics, but differ in subtle yet ecologically significant ways. A better understanding of the factors that lead to the coexistence of ecotypes has implications for processes that lead to adaptive radiation, speciation and the maintenance of diversity in bacterial populations and communities.
Previous studies on the experimental evolution of bacterial populations have demonstrated that habitat heterogeneity and spatial isolation can lead to the production and maintenance of diversity. Our research is focused on documenting the extent of diversity that exists in spatially structured environments and developing conceptual and mathematical models that account for the observed diversity. These include investigations to understand circumstances that drive diversification as well as modeling the evolutionary dynamics of adaptive evolution.