Phylogenetic comparative methods in R
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. Covers every major method of modern phylogenetic comparative analysis in R. Explains the basics of R and discusses topics such as trait evolution, diversification, trait-dependent diversification, biogeography, and visualization. Features a wealth of exercises and challenge problems. Serves as an invaluable resource for students and researchers, with applications in ecology, evolution, anthropology, disease transmission, conservation biology, and a host of other areas. Written by two of today’s leading developers of phylogenetic comparative methods.
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Princeton, New Jersey, United States Princeton University Press
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Filogenética Método comparativo Filogenética Método comparativo Liam J. Revell, Liam J. autor Harmon, Luke J. autor Phylogenetic comparative methods in R |
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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. Covers every major method of modern phylogenetic comparative analysis in R. Explains the basics of R and discusses topics such as trait evolution, diversification, trait-dependent diversification, biogeography, and visualization. Features a wealth of exercises and challenge problems. Serves as an invaluable resource for students and researchers, with applications in ecology, evolution, anthropology, disease transmission, conservation biology, and a host of other areas. Written by two of today’s leading developers of phylogenetic comparative methods. |
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Liam J. Revell, Liam J. autor Harmon, Luke J. autor |
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Liam J. Revell, Liam J. autor Harmon, Luke J. autor |
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Phylogenetic comparative methods in R |
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Phylogenetic comparative methods in R |
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Phylogenetic comparative methods in R |
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phylogenetic comparative methods in r |
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Princeton, New Jersey, United States Princeton University Press |
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c202 |
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KOHA-OAI-ECOSUR:631372022-11-18T19:27:07ZPhylogenetic comparative methods in R Liam J. Revell, Liam J. autor Harmon, Luke J. autor textPrinceton, New Jersey, United States Princeton University Pressc2022engPhylogenetic 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 R. Explains the basics of R and discusses topics such as trait evolution, diversification, trait-dependent diversification, biogeography, and visualization. Features a wealth of exercises and challenge problems. Serves as an invaluable resource for students and researchers, with applications in ecology, evolution, anthropology, disease transmission, conservation biology, and a host of other areas. Written by two of today’s leading developers of phylogenetic comparative methods.Incluye bibliografía: páginas 413-420 e índice: páginas 421-4261 A brief introduction to phylogenetics in R.. 1.1 Introduction.. 1.2 Preliminaries.. 1.3 R phylogenetics.. 1.4 ape and the “phylo” object in R.. 1.5 The internal structure of a tree in R.. 1.6 Reading and writing phylogenetic trees.. 1.7 Plotting and manipulating trees.. 1.8 Multiple trees in a single object.. 1.9 Managing trees and comparative data.. 1.10 A simple comparative analysis: Phylogenetic principal components analysis.. 1.11 Practice problems.. 2 Phylogenetically independent contrasts.. 2.1 Introduction.. 2.2 Phylogenetic nonindependence.. 2.3 Phylogenetically independent contrasts.. 2.4 What happens if we ignore the tree?.. 2.5 Practice problems.. 3 Phylogenetic generalized least squares.. 3.1 Introduction.. 3.2 Statistical nonindependence of phylogenetic data.. 3.3 Equivalence of contrasts regression and PGLS.. 3.4 Assumptions of PGLS.. 3.5 Phylogenetic ANOVA and ANCOVA.. 3.6 Practice problems.. 4 Modeling continuous character evolution on a phylogeny.. 4.1 Introduction.. 4.2 The Brownian motion model.. 4.3 Brownian motion on a phylogeny.. 4.4 Properties of Brownian motion.. 4.5 Fitting a Brownian model to data.. 4.6 Phylogenetic signal.. 4.7 Other models of continuous character evolution on phylogenies.. 4.8 Fitting and comparing alternative continuous character models.. 4.9 Practice problems.. 5 Multi-rate, multi-regime, and multivariate models for continuous traits.. 5.1 Multi-rate Brownian evolution.. 5.2 Multi-optimum Ornstein–Uhlenbeck evolution.. 5.3 Multivariate Brownian evolution.. 5.4 Exploring evolutionary heterogeneity.. 5.5 Practice problems.. 6 Modeling discrete character evolution on a phylogeny.. 6.1 Introduction.. 6.2 The Mk model.. 6.3 Fitting the Mk model to data.. 6.4 Comparing alternative discrete character models.. 6.5 Practice problems.. 7 Other models of discrete character evolution.. 7.1 Introduction.. 7.2 Correlated binary traits.. 7.3 Modeling heterogeneity in the evolutionary rate for a discrete trait.. 7.4 Modeling rate variation using the hidden-rates model.. 7.5 A polymorphic trait model.. 7.6 The threshold model for studying discrete and continuous character traits.. 7.7 Practice problems.. 8 Reconstructing ancestral states.. 8.1 Introduction.. 8.2 Ancestral states for continuous characters.. 8.3 Properties of ancestral state estimation for continuous traits.. 8.4 Discrete characters.. 8.5 Joint ancestral state reconstruction.. 8.6 Marginal ancestral state reconstruction.. 8.7 Stochastic character mapping.. 8.8 What about parsimony?.. 8.9 Practice problems.. 9 Analysis of diversification with phylogenies.. 9.1 Introduction.. 9.2 Lineage-through-time plots and the Γ statistic.. 9.3 Estimating speciation and extinction rates from a reconstructed phylogeny.. 9.4 The effect of incomplete sampling on diversification rates.. 9.5 Likelihood surface of a birth-death model.. 9.6 Analyzing diversification using diversitree.. 9.7 Practice problems.. 10 Time- and density-dependent diversification.. 10.1 Introduction.. 10.2 Time-varying diversification.. 10.3 Fitting time-variable diversification models to data.. 10.4 Diversity-dependent diversification.. 10.5 Testing for variation in diversification rates among clades.. 10.6 Practice problems.. 11 Character-dependent diversification.. 11.1 Introduction.. 11.2 Binary-state speciation and extinction (BiSSE) model.. 11.3 Multi-state speciation and extinction (MuSSE) model.. 11.4 Hidden-state speciation and extinction (HiSSE) model.. 11.5 Quantitative-trait speciation and extinction (QuaSSE) model.. 11.6 Practice problems.. 12 Biogeography and phylogenetic community ecology.. 12.1 Introduction.. 12.2 Ancestral area reconstruction.. 12.3 Phylogenetic community ecology.. 12.4 Practice problems.. 13 Plotting phylogenies and comparative data.. 13.1 Introduction.. 13.2 Phylogenies in the R plotting environment.. 13.3 Plotting phylogenies without actually plotting them.. 13.4 Algorithms for drawing trees.. 13.5 Practice problems.. References.. Index.. Index of R functionsPhylogenetic 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 R. Explains the basics of R and discusses topics such as trait evolution, diversification, trait-dependent diversification, biogeography, and visualization. Features a wealth of exercises and challenge problems. Serves as an invaluable resource for students and researchers, with applications in ecology, evolution, anthropology, disease transmission, conservation biology, and a host of other areas. Written by two of today’s leading developers of phylogenetic comparative methods.FilogenéticaMétodo comparativoURN:ISBN:0691219028URN:ISBN:9780691219035 |