Adaptive Diversification

Adaptive Diversification

Adaptive Diversification

Adaptive Diversification

Synopsis

Understanding the mechanisms driving biological diversity remains a central problem in ecology and evolutionary biology. Traditional explanations assume that differences in selection pressures lead to different adaptations in geographically separated locations. This book takes a different approach and explores adaptive diversification--diversification rooted in ecological interactions and frequency-dependent selection. In any ecosystem, birth and death rates of individuals are affected by interactions with other individuals. What is an advantageous phenotype therefore depends on the phenotype of other individuals, and it may often be best to be ecologically different from the majority phenotype. Such rare-type advantage is a hallmark of frequency-dependent selection and opens the scope for processes of diversification that require ecological contact rather than geographical isolation.


Michael Doebeli investigates adaptive diversification using the mathematical framework of adaptive dynamics. Evolutionary branching is a paradigmatic feature of adaptive dynamics that serves as a basic metaphor for adaptive diversification, and Doebeli explores the scope of evolutionary branching in many different ecological scenarios, including models of coevolution, cooperation, and cultural evolution. He also uses alternative modeling approaches. Stochastic, individual-based models are particularly useful for studying adaptive speciation in sexual populations, and partial differential equation models confirm the pervasiveness of adaptive diversification.


Showing that frequency-dependent interactions are an important driver of biological diversity, Adaptive Diversification provides a comprehensive theoretical treatment of adaptive diversification.

Excerpt

Evolution occurs when organisms reproduce so that their offspring inherit certain characteristics, or traits. Variation in heritable traits, together with variation in reproductive success, generates evolutionary change in trait distributions. If the correlation between heritable variation and reproductive variation is (close to) zero, evolutionary change is neutral, and the trait distribution performs an evolutionary random walk. in contrast, evolution is adaptive if the correlation between heritable variation and reproductive variation is significantly different from zero.

Adaptive evolution is generally thought to be of central importance for the history of life on earth. the process of adaptation, whereby types that are better adapted to the prevalent circumstances leave more offspring than types that are less well adapted, is, for example, believed to have been the main driving force generating major evolutionary transitions (Szathmáry & Maynard Smith, 1995). By far the most widespread view of adaptation, both among experts and laymen, is that of an optimization process: Given a set of environmental conditions, the type that is best adapted to these conditions prevails. Determining the optimal type in a given situation, and understanding how genetic and developmental constraints impinge on the evolutionary trajectory toward such optimal types, have been among the main objectives in evolutionary theory.

One of the problems with viewing evolution as an optimization process is that this perspective leaves little room for diversity: the optimally adapted type has more offspring than all other types, and so eventually, all other types will go extinct, leaving the optimal type as the single type present. of course, recurring mutations may constantly introduce genetic variation into a population, but optimization essentially generates uniformity. in particular, evolution of distinct ecological types out of a uniform ancestral lineage at the same physical location is precluded under the tenet of evolutionary optimization.

Yet understanding the evolution of diversity is one of the central and most fundamental problems in biology. To explain the evolution of diversity in the realm of the traditional optimization perspective, one needs to . . .

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