A Quantitative Genetic Theory of Life History Evolution

Abstract

Dynamic models of quantitative (polygenic) characters are more generally applicable in the analysis of life history evolution than are static optimization methods or one and two locus genetic models. A dynamic theory of life history evolution is derived by synthesizing population demography with quantitative genetics. In a population under weak selection with a nearly stable age distribution, the relative fitness of individuals with a particular life history phenotype can be approximated as an average of age—specific relative fecundity and mortality rates, weighted respectively by the present productivity and future reproductive value of each age—class. An adaptive topography is constructed showing that, with phenotype— and age—specific fecundity and mortality rates constant in time, evolution of the mean life history maximizes the intrinsic rate of increase of a population. However, the rate and direction of evolution in response to selection are strongly influenced by genetic correlations among characters. Negative genetic correlations among major components of fitness are often obscured phenotypically by positive environmental correlations, but commonly constitute the ultimate constraint on life history evolution, as illustrated by artificial selection experiments. Methods are suggested for measuring selective forces and evolutionary constraints that effect life history characters in natural populations.