Ecological and evolutionary dynamics have been historically regarded as unfolding at broadly separated timescales. However, these two types of processes are nowadays well-documented to intermingle much more tightly than traditionally assumed, especially in communities of microorganisms. Improving the existing approches to these problems and developing novel analytical and computational frameworks is a challenge of utmost theoretical and practical relevance.
Within this context, in this talk I present an introduction to some relevant concepts such as "bet-hedging", optimal strategies, evolutionary tradoffs, diversification, etc. Then, I discuss recent experimental results showing empirical evidence of very rapid evolution of tolerance by lag in bacterial communities that are periodically exposed to antibiotic stress in laboratory conditions. In particular, the communities evolve to develop a broad distribution of lag times —i.e. the times that individual bacteria typically remain in a dormant state to cope with stress— whose statistics are determined by those of the environments, thus creating a sort of collective memory in the community. Finally, I will discuss a general analytical and computational framework that we have developed to model and shed light onto this specific example as well as on more general eco-evolutionary problems and discuss further directions and open problems.
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