Evolution in heterogeneous environments
The world is heterogeneous across many spatial and temporal scales, and these complexities have important implications for the dynamics of evolution. The particular evolutionary outcome that is realized depends on a number of factors, both ecological – e.g. strength and type of competition, and genetic – e.g. trade-offs in adaptation to multiple niches. I examine the effects of a number of these factors using both theoretical models and evolution experiments in the lab, aiming to better understand the processes that play important roles in populations living and evolving in the complex natural world.
I use evolution experiments with Pseudomonas fluorescens to explore the effects of environmental heterogeneity on adaptation and diversification. Previous experiments have shown that the type and arrangement of resources can drive the rate of adaptation and degree of specialization (Bailey & Kassen 2012) and have characterized underlying fitness trade-offs (Schick et al 2015). I have also explored the potential for both intra- and
inter-specific competition to further drive or impede adaptation and diversification in spatially heterogeneous environments (Bailey et al 2013).
Future experiments will be focused on understanding the interplay between local adaptation and dispersal evolution. I am currently developing an experimental system to explore these evolutionary dynamics in P. fluorescens populations grown on spatially heterogeneous agar surfaces. This experimental setup will allow for dispersal traits to evolve in concert with local adaptation to resources, something that most previous evolution experiments cannot do.
Modelling adaptation and dispersal in heterogeneous environments
I am interested in the role of dispersal and location adaptation specifically in response to shifting habitat ranges and have explored these processes using simulation models in collaboration with Anna Hargreaves and Robert Laird. Our theoretical models and others have given rise to a number of predictions about how populations are expected to evolve in response to a shifting climate, e.g.
increased rates of dispersal at the expanding edges of species ranges (Hargreaves et al 2015). Many of these predictions are difficult to test in natural populations and so the empirical support is not always clear. However within a microbial evolution experiment setup like the one discussed above, there is great potential for tackling these questions.
Evolution experiments in spatially structured environments