Paul Hohenlohe

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  A coevolutionary resolution to the paradox of concave selection?
  Paul Hohenlohe
  The adaptive landscape, long a useful metaphor, is also a rigorous tool for understanding evolution when it is linked to empirical measurements of fitness. However, empirical estimates of fitness surfaces are often concave, implying an evolutionarily unstable situation under general conditions in the short term, and untenable extrapolations to longer-term evolution under the traditional adaptive landscape model. Incorporating the multivariate genetic and ecological context of concave selection would lead to a more robust adaptive landscape model. The several non-exclusive hypotheses for the prevalence of concave selection fall roughly into two groups: static and dynamic. Coevolution lies at the heart of dynamic solutions and is thus critical to resolving the paradox of concave selection. In this talk I will discuss the basic hypotheses and empirical evidence for the prevalence of concave selection and explore its relationship to coevolution. I will propose a revised adaptive landscape model that can account for concave selection, yet maintain the adaptive landscape's heuristic value for understanding multivariate phenotypic evolution.