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The Theory of EvolutionPrinciples, Concepts, and Assumptions$
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Samuel M. Scheiner and David P. Mindell

Print publication date: 2020

Print ISBN-13: 9780226671024

Published to Chicago Scholarship Online: September 2020

DOI: 10.7208/chicago/9780226671338.001.0001

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PRINTED FROM CHICAGO SCHOLARSHIP ONLINE (www.chicago.universitypressscholarship.com). (c) Copyright University of Chicago Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in CHSO for personal use.date: 15 October 2021

Modeling Evolutionary Theories

Modeling Evolutionary Theories

Chapter:
(p.64) Four Modeling Evolutionary Theories
Source:
The Theory of Evolution
Author(s):

Patrick C. Phillips

Publisher:
University of Chicago Press
DOI:10.7208/chicago/9780226671338.003.0004

Models are a critical component of nearly every theory in evolutionary biology. Over the last 100 years, most models in evolutionary biology have transitioned from verbal approaches, as exemplified by Darwin, to precise mathematical models, usually based upon our increasing understanding of underlying genetic processes. This chapter explores two phases of the transition to increasingly quantitative approaches to evolutionary theory. The first phase was the focus on understanding general evolutionary mechanisms, such as natural selection, mutation, recombination, and migration. The second phase was the recent shift from abstract models of mechanism to concrete statistical models being used to analyze the emerging onslaught of genetic and genomic data being generated across the tree of life. No matter how precise the model, however, tests of specific hypotheses will nearly always be limited by the historical nature of evolution and the dependence of statistical tests of evolutionary change on assumptions about the underlying structure of the evolutionary processes. The role of explicit mathematical models in evolutionary biology is now unassailable, and their sophistication is likely to continue to increase over the foreseeable future.

Keywords:   genetics, genomics, hypothesis test, mathematical model, natural selection, statistics

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