Data from: Multidimensional (co)evolutionary stability

The complexity of biotic and abiotic environmental conditions is such that
the fitness of individuals is likely to depend on multiple traits. Using a
synthetic framework of phenotypic evolution that draws from adaptive
dynamics and quantitative genetics approaches, we explore how the number
of traits under selection influences convergence stability and
evolutionary stability in models for coevolution in multidimensional
phenotype spaces. Our results allow us to identify three different effects
of trait dimensionality on stability. First are (i) a “combinatorial
effect”: without epistasis and genetic correlations, a higher number of
trait dimensions offers more opportunities for equilibria to be unstable;
and (ii) epistatic interactions, that is, fitness interactions between
traits, which tend to destabilize evolutionary equilibria; this effect
increases with the dimension of phenotype space. These first two effects
influence both convergence stability and evolutionary stability, while
(iii) genetic correlations (due, e.g., to pleiotropy or linkage
disequilibrium) can affect only convergence stability. We illustrate the
general prediction that increased dimensionality destabilizes evolutionary
equilibria using examples drawn from well-studied classical models of
frequency-dependent competition for resources, adaptation to a spatially
heterogeneous environment, and antagonistic coevolution. In addition, our
analyses show that increased dimensionality can favor diversification, for
example, in the form of local adaptation, as well as evolutionary escape.