An authoritative introduction to the latest comparative methods in evolutionary biology
Phylogenetic comparative methods are a suite of statistical approaches that enable biologists to analyze and better understand the evolutionary tree of life, and shed vital new light on patterns of divergence and common ancestry among all species on Earth. This textbook shows how to carry out phylogenetic comparative analyses in the R statistical computing environment. Liam Revell and Luke Harmon provide an incisive conceptual overview of each method along with worked examples using real data and challenge problems that encourage students to learn by doing. By working through this book, students will gain a solid foundation in these methods and develop the skills they need to interpret patterns in the tree of life.
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Liam J. Revell is associate professor of biology at the University of Massachusetts, Boston, and an adjunct researcher at the Universidad Católica de la Santísima Concepción in Chile. Luke J. Harmon is professor of biological sciences at the University of Idaho and the author of Phylogenetic Comparative Methods: Learning from Trees.
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Hardback. Condición: New. An authoritative introduction to the latest comparative methods in evolutionary biologyPhylogenetic comparative methods are a suite of statistical approaches that enable biologists to analyze and better understand the evolutionary tree of life, and shed vital new light on patterns of divergence and common ancestry among all species on Earth. This textbook shows how to carry out phylogenetic comparative analyses in the R statistical computing environment. Liam Revell and Luke Harmon provide an incisive conceptual overview of each method along with worked examples using real data and challenge problems that encourage students to learn by doing. By working through this book, students will gain a solid foundation in these methods and develop the skills they need to interpret patterns in the tree of life.Covers every major method of modern phylogenetic comparative analysis in RExplains the basics of R and discusses topics such as trait evolution, diversification, trait-dependent diversification, biogeography, and visualizationFeatures a wealth of exercises and challenge problemsServes as an invaluable resource for students and researchers, with applications in ecology, evolution, anthropology, disease transmission, conservation biology, and a host of other areasWritten by two of today's leading developers of phylogenetic comparative methods. Nº de ref. del artículo: LU-9780691219028
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Hardcover. Condición: new. Hardcover. An authoritative introduction to the latest comparative methods in evolutionary biologyPhylogenetic comparative methods are a suite of statistical approaches that enable biologists to analyze and better understand the evolutionary tree of life, and shed vital new light on patterns of divergence and common ancestry among all species on Earth. This textbook shows how to carry out phylogenetic comparative analyses in the R statistical computing environment. Liam Revell and Luke Harmon provide an incisive conceptual overview of each method along with worked examples using real data and challenge problems that encourage students to learn by doing. By working through this book, students will gain a solid foundation in these methods and develop the skills they need to interpret patterns in the tree of life.Covers every major method of modern phylogenetic comparative analysis in RExplains the basics of R and discusses topics such as trait evolution, diversification, trait-dependent diversification, biogeography, and visualizationFeatures a wealth of exercises and challenge problemsServes as an invaluable resource for students and researchers, with applications in ecology, evolution, anthropology, disease transmission, conservation biology, and a host of other areasWritten by two of today's leading developers of phylogenetic comparative methods Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9780691219028
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