STABILIZING SELECTION AND THE COMPARATIVE ANALYSIS OF ADAPTATION

TLDR

Comparative studies differ from optimality studies in their treatment of adaptation, with comparative approaches focusing on trait origins and changes while optimality studies assume stabilizing selection maintains traits at an optimum; comparative methods are also used to examine evolutionary trends. The paper introduces a macroevolutionary model that incorporates stabilizing selection as the dominant force maintaining traits at adaptive optima and derives a statistical comparative method to estimate selective factor effects on these optima. The model treats interspecific variation as shifts in the positions of adaptive optima and uses this framework to develop the comparative method. The model demonstrates that phylogenetic constraints generate correlations among related species and lead to imperfect adaptations, and the method is applied to analyze dental evolution in fossil horses.

Abstract

Comparative studies tend to differ from optimality and functionality studies in how they treat adaptation. While the comparative approach focuses on the origin and change of traits, optimality studies assume that adaptations are maintained at an optimum by stabilizing selection. This paper presents a model of adaptive evolution on a macroevolutionary time scale that includes the maintenance of traits at adaptive optima by stabilizing selection as the dominant evolutionary force. Interspecific variation is treated as variation in the position of adaptive optima. The model illustrates how phylogenetic constraints not only lead to correlations between phylogenetically related species, but also to imperfect adaptations. From this model, a statistical comparative method is derived that can be used to estimate the effect of a selective factor on adaptive optima in a way that would be consistent with an optimality study of adaptation to this factor. The method is illustrated with an analysis of dental evolution in fossil horses. The use of comparative methods to study evolutionary trends is also discussed.