Mathematical and statistical approaches to elucidate recent human evolutionary history

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Abstract/Contents

Abstract
Reconstructing human evolutionary history is of central importance to many fields, from medical genetics and biological anthropology to archaeology and environmental studies. Human population histories, such as where and when people move, and how populations grow or adapt to their environments, affect human genetic and phenotypic variation, and disease risk. The past decade has reinforced the importance of recent human population history for the distributions of variation; over the past fifteen thousand years, populations around the world have undergone dramatic demographic changes related to environmental and cultural adaptation. This thesis develops multiple new methods to leverage genetic and archaeological evidence to reconstruct past human demography during the past ~15,000. Chapters 2-4 derive a set of mechanistic models describing the impact of sex-biased admixture on distributions of genetic ancestry in an admixed population. Chapters 3 and 4 infer the sex-specific admixture history of major human migrations during the last ten thousand years. Finally, Chapter 5 leverages models from ecological statistics and demographic archaeology to test the relationship between human population growth, local environments, and agricultural development. Together, these chapters interrogate the impact of environmental and cultural change on human demography during the last fifteen thousand years using new mathematical and statistical methods.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2017
Issuance monographic
Language English

Creators/Contributors

Associated with Goldberg, Amy
Associated with Stanford University, Department of Biology.
Primary advisor Rosenberg, Noah
Thesis advisor Rosenberg, Noah
Thesis advisor Bustamante, Carlos
Thesis advisor Feldman, Marcus W
Advisor Bustamante, Carlos
Advisor Feldman, Marcus W

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Amy Goldberg.
Note Submitted to the Department of Biology.
Thesis Thesis (Ph.D.)--Stanford University, 2017.
Location electronic resource

Access conditions

Copyright
© 2017 by Amy Goldberg

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