Evolutionary Biology

, Volume 38, Issue 1, pp 3–14

Many Possible Worlds: Expanding the Ecological Scenarios in Experimental Evolution

Synthesis Paper

DOI: 10.1007/s11692-010-9106-3

Cite this article as:
Collins, S. Evol Biol (2011) 38: 3. doi:10.1007/s11692-010-9106-3

Abstract

Experimental microbial evolution has focused on the particular ecological scenario where a population is placed suddenly in an environment where its fitness is low, and then adapts while the environment remains stable. In line with this, most microbial evolution studies use fitness measures that report how evolved genotypes fare when competed directly against their own distant ancestor while other studies compare life history traits (such as growth rates) of ancestral and evolved genotypes. This standard way of measuring and reporting changes in fitness has resulted in a consistent body of literature that explains adaptation when populations evolve in this “standard ecological scenario.” Here, I suggest that for experimental evolution to investigate adaptation in other ecological scenarios, such as fluctuating or persistently changing environments, measures of fitness must be expanded such that they not only continue to be comparable between experiments, but also account for evolution and demographic effects in all environments that an evolving lineage experiences. I examine two non-standard measures of fitness—fitness flux and the total number of reproductive events—as potential ways to quantify adaptation by integrating historical information about selection over many environments. This approach could allow us to make quantitative and biologically-meaningful comparisons of adaptation across diverse ecological scenarios. I use the case study of understanding how phytoplankton communities may respond to global change, where environmental variables change continuously, to explore concrete ways of using non-standard fitness measures that consider both demographic effects and selection in changing, rather than in changed, environments.

Keywords

AdaptationFitness measuresExperimental evolutionMicrobes

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Institute of Evolutionary Biology, School of Biological SciencesUniversity of EdinburghEdinburghScotland, UK