{"product_id":"systematics-9780470671702","title":"Systematics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSystematics: A Course of Lectures\u003c\/i\u003e is designed for use in an advanced undergraduate or introductory graduate level course in systematics and is meant to present core systematic concepts and literature. The book covers topics such as the history of systematic thinking and fundamental concepts in the field including species concepts, homology, and hypothesis testing. Analytical methods are covered in detail with chapters devoted to sequence alignment, optimality criteria, and methods such as distance, parsimony, maximum likelihood and Bayesian approaches. Trees and tree searching, consensus and super-tree methods, support measures, and other relevant topics are each covered in their own sections.  \u003cp\u003eThe work is not a bleeding-edge statement or in-depth review of the entirety of systematics, but covers the basics as broadly as could be handled in a one semester course. Most chapters are designed to be a single 1.5 hour class, with those on parsimony, likelihood, posterior probabili\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e“Viewed as a series of lectures, this is clearly aimed at graduate level courses in systematics, although some elements would prove useful at undergraduate level.”  (\u003ci\u003eBritish Ecological Society Bulletin\u003c\/i\u003e, 1 August 2013)\u003c\/p\u003e \u003cp\u003e“If you want to teach yourself systematics, this book is for you. It’s just a series of lectures and exercises compiled by Wheeler, one of the top systematic biologists.”  (\u003ci\u003eTeaching Biology\u003c\/i\u003e, 20 December 2012)\u003c\/p\u003e \u003cp\u003e“All things considered, I strongly recommend this work as a textbook for those teaching in systematics, biologists and palaeontologists alike . . . I would advise this book to graduate students – MSc and above.”  (\u003ci\u003eJournal of Zoological Systematics and Evolutionary Research\u003c\/i\u003e, 1 February 2013)\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cb\u003ePreface xv\u003c\/b\u003e  \u003cp\u003eUsing these notes xv\u003c\/p\u003e \u003cp\u003eAcknowledgments  xvi\u003c\/p\u003e \u003cp\u003e\u003cb\u003eList of algorithms xix\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eI Fundamentals 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 History 2\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Aristotle  2\u003c\/p\u003e \u003cp\u003e1.2 Theophrastus 3\u003c\/p\u003e \u003cp\u003e1.3 Pierre Belon 4\u003c\/p\u003e \u003cp\u003e1.4 Carolus Linnaeus 4\u003c\/p\u003e \u003cp\u003e1.5 Georges Louis Leclerc, Comte de Buffon  6\u003c\/p\u003e \u003cp\u003e1.6 Jean-Baptiste Lamarck 7\u003c\/p\u003e \u003cp\u003e1.7 Georges Cuvier  8\u003c\/p\u003e \u003cp\u003e1.8 ´Etienne Geoffroy Saint-Hilaire  8\u003c\/p\u003e \u003cp\u003e1.9 JohannWolfgang von Goethe 8\u003c\/p\u003e \u003cp\u003e1.10 Lorenz Oken9\u003c\/p\u003e \u003cp\u003e1.11 Richard Owen 9\u003c\/p\u003e \u003cp\u003e1.12 Charles Darwin  9\u003c\/p\u003e \u003cp\u003e1.13 Stammbäume  12\u003c\/p\u003e \u003cp\u003e1.14 Evolutionary Taxonomy 14\u003c\/p\u003e \u003cp\u003e1.15 Phenetics 15\u003c\/p\u003e \u003cp\u003e1.16 Phylogenetic Systematics  16\u003c\/p\u003e \u003cp\u003e1.16.1 Hennig’s Three Questions 16\u003c\/p\u003e \u003cp\u003e1.17 Molecules and Morphology  18\u003c\/p\u003e \u003cp\u003e1.18 We are all Cladists 18\u003c\/p\u003e \u003cp\u003e1.19 Exercises 19\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Fundamental Concepts 20\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Characters 20\u003c\/p\u003e \u003cp\u003e2.1.1 Classes of Characters and Total Evidence  22\u003c\/p\u003e \u003cp\u003e2.1.2 Ontogeny, Tokogeny, and Phylogeny  23\u003c\/p\u003e \u003cp\u003e2.1.3 Characters and Character States 23\u003c\/p\u003e \u003cp\u003e2.2 Taxa 26\u003c\/p\u003e \u003cp\u003e2.3 Graphs, Trees, and Networks 28\u003c\/p\u003e \u003cp\u003e2.3.1 Graphs and Trees 30\u003c\/p\u003e \u003cp\u003e2.3.2 Enumeration 31\u003c\/p\u003e \u003cp\u003e2.3.3 Networks  33\u003c\/p\u003e \u003cp\u003e2.3.4 Mono-, Para-, and Polyphyly 33\u003c\/p\u003e \u003cp\u003e2.3.5 Splits and Convexity  38\u003c\/p\u003e \u003cp\u003e2.3.6 Apomorphy, Plesiomorphy, and Homoplasy  39\u003c\/p\u003e \u003cp\u003e2.3.7 Gene Trees and Species Trees 41\u003c\/p\u003e \u003cp\u003e2.4 Polarity and Rooting 43\u003c\/p\u003e \u003cp\u003e2.4.1 Stratigraphy  43\u003c\/p\u003e \u003cp\u003e2.4.2 Ontogeny  43\u003c\/p\u003e \u003cp\u003e2.4.3 Outgroups  45\u003c\/p\u003e \u003cp\u003e2.5 Optimality 49\u003c\/p\u003e \u003cp\u003e2.6 Homology  49\u003c\/p\u003e \u003cp\u003e2.7 Exercises  50\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Species Concepts, Definitions, and Issues 53\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Typological or Taxonomic Species Concept  54\u003c\/p\u003e \u003cp\u003e3.2 Biological Species Concept  54\u003c\/p\u003e \u003cp\u003e3.2.1 Criticisms of the BSC 55\u003c\/p\u003e \u003cp\u003e3.3 Phylogenetic Species Concept(s) 56\u003c\/p\u003e \u003cp\u003e3.3.1 Autapomorphic\/Monophyletic Species Concept 56\u003c\/p\u003e \u003cp\u003e3.3.2 Diagnostic\/Phylogenetic Species Concept  58\u003c\/p\u003e \u003cp\u003e3.4 Lineage Species Concepts  59\u003c\/p\u003e \u003cp\u003e3.4.1 Hennigian Species  59\u003c\/p\u003e \u003cp\u003e3.4.2 Evolutionary Species  60\u003c\/p\u003e \u003cp\u003e3.4.3 Criticisms of Lineage-Based Species  61\u003c\/p\u003e \u003cp\u003e3.5 Species as Individuals or Classes  62\u003c\/p\u003e \u003cp\u003e3.6 Monoism and Pluralism  63\u003c\/p\u003e \u003cp\u003e3.7 Pattern and Process  63\u003c\/p\u003e \u003cp\u003e3.8 Species Nominalism  64\u003c\/p\u003e \u003cp\u003e3.9 Do Species Concepts Matter?  65\u003c\/p\u003e \u003cp\u003e3.10 Exercises  65\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Hypothesis Testing and the Philosophy of Science 67\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Forms of Scientific Reasoning 67\u003c\/p\u003e \u003cp\u003e4.1.1 The Ancients  67\u003c\/p\u003e \u003cp\u003e4.1.2 Ockham’s Razor  68\u003c\/p\u003e \u003cp\u003e4.1.3 Modes of Scientific Inference  69\u003c\/p\u003e \u003cp\u003e4.1.4 Induction 69\u003c\/p\u003e \u003cp\u003e4.1.5 Deduction 69\u003c\/p\u003e \u003cp\u003e4.1.6 Abduction 70\u003c\/p\u003e \u003cp\u003e4.1.7 Hypothetico-Deduction  71\u003c\/p\u003e \u003cp\u003e4.2 Other Philosophical Issues 75\u003c\/p\u003e \u003cp\u003e4.2.1 Minimization, Transformation, and Weighting 75\u003c\/p\u003e \u003cp\u003e4.3 Quotidian Importance  76\u003c\/p\u003e \u003cp\u003e4.4 Exercises  76\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Computational Concepts 77\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Problems, Algorithms, and Complexity 77\u003c\/p\u003e \u003cp\u003e5.1.1 Computer Science Basics  77\u003c\/p\u003e \u003cp\u003e5.1.2 Algorithms  79\u003c\/p\u003e \u003cp\u003e5.1.3 Asymptotic Notation 79\u003c\/p\u003e \u003cp\u003e5.1.4 Complexity  80\u003c\/p\u003e \u003cp\u003e5.1.5 Non-Deterministic Complexity  82\u003c\/p\u003e \u003cp\u003e5.1.6 Complexity Classes: \u003ci\u003eP\u003c\/i\u003e and \u003ci\u003eNP \u003c\/i\u003e 82\u003c\/p\u003e \u003cp\u003e5.2 An Example: The Traveling Salesman Problem  84\u003c\/p\u003e \u003cp\u003e5.3 Heuristic Solutions  85\u003c\/p\u003e \u003cp\u003e5.4 Metricity, and Untrametricity  86\u003c\/p\u003e \u003cp\u003e5.5 NP–Complete Problems in Systematics  87\u003c\/p\u003e \u003cp\u003e5.6 Exercises 88\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Statistical and Mathematical Basics 89\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Theory of Statistics  89\u003c\/p\u003e \u003cp\u003e6.1.1 Probability  89\u003c\/p\u003e \u003cp\u003e6.1.2 Conditional Probability  91\u003c\/p\u003e \u003cp\u003e6.1.3 Distributions 92\u003c\/p\u003e \u003cp\u003e6.1.4 Statistical Inference  98\u003c\/p\u003e \u003cp\u003e6.1.5 Prior and Posterior Distributions  99\u003c\/p\u003e \u003cp\u003e6.1.6 Bayes Estimators 100\u003c\/p\u003e \u003cp\u003e6.1.7 Maximum Likelihood Estimators  101\u003c\/p\u003e \u003cp\u003e6.1.8 Properties of Estimators 101\u003c\/p\u003e \u003cp\u003e6.2 Matrix Algebra, Differential Equations, and Markov Models 102\u003c\/p\u003e \u003cp\u003e6.2.1 Basics  102\u003c\/p\u003e \u003cp\u003e6.2.2 Gaussian Elimination 102\u003c\/p\u003e \u003cp\u003e6.2.3 Differential Equations  104\u003c\/p\u003e \u003cp\u003e6.2.4 Determining Eigenvalues  105\u003c\/p\u003e \u003cp\u003e6.2.5 MarkovMatrices  106\u003c\/p\u003e \u003cp\u003e6.3 Exercises  107\u003c\/p\u003e \u003cp\u003e\u003cb\u003eII Homology 109\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Homology 110\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Pre-Evolutionary Concepts110\u003c\/p\u003e \u003cp\u003e7.1.1 Aristotle  110\u003c\/p\u003e \u003cp\u003e7.1.2 Pierre Belon  110\u003c\/p\u003e \u003cp\u003e7.1.3 ´Etienne Geoffroy Saint-Hilaire  111\u003c\/p\u003e \u003cp\u003e7.1.4 Richard Owen 112\u003c\/p\u003e \u003cp\u003e7.2 Charles Darwin  113\u003c\/p\u003e \u003cp\u003e7.3 E. Ray Lankester  114\u003c\/p\u003e \u003cp\u003e7.4 Adolf Remane  114\u003c\/p\u003e \u003cp\u003e7.5 Four Types of Homology  115\u003c\/p\u003e \u003cp\u003e7.5.1 Classical View  115\u003c\/p\u003e \u003cp\u003e7.5.2 Evolutionary Taxonomy  115\u003c\/p\u003e \u003cp\u003e7.5.3 Phenetic Homology  116\u003c\/p\u003e \u003cp\u003e7.5.4 Cladistic Homology  116\u003c\/p\u003e \u003cp\u003e7.5.5 Types of Homology  117\u003c\/p\u003e \u003cp\u003e7.6 Dynamic and Static Homology  118\u003c\/p\u003e \u003cp\u003e7.7 Exercises  120\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Sequence Alignment 121\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Background  121\u003c\/p\u003e \u003cp\u003e8.2 “Informal” Alignment  121\u003c\/p\u003e \u003cp\u003e8.3 Sequences  121\u003c\/p\u003e \u003cp\u003e8.3.1 Alphabets  122\u003c\/p\u003e \u003cp\u003e8.3.2 Transformations  123\u003c\/p\u003e \u003cp\u003e8.3.3 Distances  123\u003c\/p\u003e \u003cp\u003e8.4 Pairwise StringMatching 123\u003c\/p\u003e \u003cp\u003e8.4.1 An Example  127\u003c\/p\u003e \u003cp\u003e8.4.2 Reducing Complexity  129\u003c\/p\u003e \u003cp\u003e8.4.3 Other Indel Weights  130\u003c\/p\u003e \u003cp\u003e8.5 Multiple Sequence Alignment  131\u003c\/p\u003e \u003cp\u003e8.5.1 The Tree Alignment Problem  133\u003c\/p\u003e \u003cp\u003e8.5.2 Trees and Alignment  133\u003c\/p\u003e \u003cp\u003e8.5.3 Exact Solutions 134\u003c\/p\u003e \u003cp\u003e8.5.4 Polynomial Time Approximate Schemes  134\u003c\/p\u003e \u003cp\u003e8.5.5 Heuristic Multiple Sequence Alignment  134\u003c\/p\u003e \u003cp\u003e8.5.6 Implementations  135\u003c\/p\u003e \u003cp\u003e8.5.7 Structural Alignment  139\u003c\/p\u003e \u003cp\u003e8.6 Exercises 145\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIII Optimality Criteria 147\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Optimality Criteria\u003c\/b\u003e\u003ci\u003e-\u003c\/i\u003e\u003cb\u003eDistance 148\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Why Distance? 148\u003c\/p\u003e \u003cp\u003e9.1.1 Benefits  149\u003c\/p\u003e \u003cp\u003e9.1.2 Drawbacks 149\u003c\/p\u003e \u003cp\u003e9.2 Distance Functions  150\u003c\/p\u003e \u003cp\u003e9.2.1 Metricity  150\u003c\/p\u003e \u003cp\u003e9.3 Ultrametric Trees  150\u003c\/p\u003e \u003cp\u003e9.4 Additive Trees  152\u003c\/p\u003e \u003cp\u003e9.4.1 Farris Transform  153\u003c\/p\u003e \u003cp\u003e9.4.2 Buneman Trees  154\u003c\/p\u003e \u003cp\u003e9.5 General Distances  156\u003c\/p\u003e \u003cp\u003e9.5.1 Phenetic Clustering 157\u003c\/p\u003e \u003cp\u003e9.5.2 Percent Standard Deviation 160\u003c\/p\u003e \u003cp\u003e9.5.3 Minimizing Length  163\u003c\/p\u003e \u003cp\u003e9.6 Comparisons 170\u003c\/p\u003e \u003cp\u003e9.7 Exercises  171\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Optimality Criteria\u003c\/b\u003e\u003ci\u003e-\u003c\/i\u003e\u003cb\u003eParsimony 173\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Perfect Phylogeny  174\u003c\/p\u003e \u003cp\u003e10.2 Static Homology Characters  174\u003c\/p\u003e \u003cp\u003e10.2.1 Additive Characters  175\u003c\/p\u003e \u003cp\u003e10.2.2 Non-Additive Characters  179\u003c\/p\u003e \u003cp\u003e10.2.3 Matrix Characters  182\u003c\/p\u003e \u003cp\u003e10.3 Missing Data  184\u003c\/p\u003e \u003cp\u003e10.4 Edge Transformation Assignments  187\u003c\/p\u003e \u003cp\u003e10.5 Collapsing Branches  188\u003c\/p\u003e \u003cp\u003e10.6 Dynamic Homology  188\u003c\/p\u003e \u003cp\u003e10.7 Dynamic and Static Homology  189\u003c\/p\u003e \u003cp\u003e10.8 Sequences as Characters 190\u003c\/p\u003e \u003cp\u003e10.9 The Tree Alignment Problem on Trees  191\u003c\/p\u003e \u003cp\u003e10.9.1 Exact Solutions  191\u003c\/p\u003e \u003cp\u003e10.9.2 Heuristic Solutions 191\u003c\/p\u003e \u003cp\u003e10.9.3 Lifted Alignments, Fixed-States, and Search-Based Heuristics  193\u003c\/p\u003e \u003cp\u003e10.9.4 Iterative Improvement  197\u003c\/p\u003e \u003cp\u003e10.10 Performance of Heuristic Solutions 198\u003c\/p\u003e \u003cp\u003e10.11 Parameter Sensitivity  198\u003c\/p\u003e \u003cp\u003e10.11.1 Sensitivity Analysis  199\u003c\/p\u003e \u003cp\u003e10.12 Implied Alignment  199\u003c\/p\u003e \u003cp\u003e10.13 Rearrangement  204\u003c\/p\u003e \u003cp\u003e10.13.1 Sequence Characters with Moves  204\u003c\/p\u003e \u003cp\u003e10.13.2Gene Order Rearrangement 205\u003c\/p\u003e \u003cp\u003e10.13.3Median Evaluation  207\u003c\/p\u003e \u003cp\u003e10.13.4Combination ofMethods 207\u003c\/p\u003e \u003cp\u003e10.14 Horizontal Gene Transfer, Hybridization, and Phylogenetic Networks  209\u003c\/p\u003e \u003cp\u003e10.15 Exercises  210\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Optimality Criteria\u003c\/b\u003e\u003ci\u003e-\u003c\/i\u003e\u003cb\u003eLikelihood 213\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Motivation  213\u003c\/p\u003e \u003cp\u003e11.1.1 Felsenstein’s Example  213\u003c\/p\u003e \u003cp\u003e11.2 Maximum Likelihood and Trees  216\u003c\/p\u003e \u003cp\u003e11.2.1 Nuisance Parameters  216\u003c\/p\u003e \u003cp\u003e11.3 Types of Likelihood  217\u003c\/p\u003e \u003cp\u003e11.3.1 Flavors ofMaximum Relative Likelihood 217\u003c\/p\u003e \u003cp\u003e11.4 Static-Homology Characters  218\u003c\/p\u003e \u003cp\u003e11.4.1 Models  218\u003c\/p\u003e \u003cp\u003e11.4.2 Rate Variation  219\u003c\/p\u003e \u003cp\u003e11.4.3 Calculating \u003ci\u003ep\u003c\/i\u003e(\u003ci\u003eD|T, ?\u003c\/i\u003e)  221\u003c\/p\u003e \u003cp\u003e11.4.4 Links Between Likelihood and Parsimony  222\u003c\/p\u003e \u003cp\u003e11.4.5 A Note onMissing Data 224\u003c\/p\u003e \u003cp\u003e11.5 Dynamic-Homology Characters  224\u003c\/p\u003e \u003cp\u003e11.5.1 Sequence Characters  225\u003c\/p\u003e \u003cp\u003e11.5.2 CalculatingML Pairwise Alignment  227\u003c\/p\u003e \u003cp\u003e11.5.3 MLMultiple Alignment  230\u003c\/p\u003e \u003cp\u003e11.5.4 Maximum Likelihood Tree Alignment Problem 230\u003c\/p\u003e \u003cp\u003e11.5.5 Genomic Rearrangement  232\u003c\/p\u003e \u003cp\u003e11.5.6 Phylogenetic Networks  234\u003c\/p\u003e \u003cp\u003e11.6 Hypothesis Testing  234\u003c\/p\u003e \u003cp\u003e11.6.1 Likelihood Ratios  234\u003c\/p\u003e \u003cp\u003e11.6.2 Parameters and Fit  236\u003c\/p\u003e \u003cp\u003e11.7 Exercises  238\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Optimality Criteria\u003c\/b\u003e\u003ci\u003e-\u003c\/i\u003e\u003cb\u003ePosterior Probability 240\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Bayes in Systematics  240\u003c\/p\u003e \u003cp\u003e12.2 Priors  241\u003c\/p\u003e \u003cp\u003e12.2.1 Trees  241\u003c\/p\u003e \u003cp\u003e12.2.2 Nuisance Parameters  242\u003c\/p\u003e \u003cp\u003e12.3 Techniques 246\u003c\/p\u003e \u003cp\u003e12.3.1 Markov ChainMonte Carlo  246\u003c\/p\u003e \u003cp\u003e12.3.2 Metropolis–Hastings Algorithm 246\u003c\/p\u003e \u003cp\u003e12.3.3 Single Component 248\u003c\/p\u003e \u003cp\u003e12.3.4 Gibbs Sampler  249\u003c\/p\u003e \u003cp\u003e12.3.5 Bayesian MC3 249\u003c\/p\u003e \u003cp\u003e12.3.6 Summary of Posterior  250\u003c\/p\u003e \u003cp\u003e12.4 Topologies and Clades  252\u003c\/p\u003e \u003cp\u003e12.5 Optimality versus Support  254\u003c\/p\u003e \u003cp\u003e12.6 Dynamic Homology  254\u003c\/p\u003e \u003cp\u003e12.6.1 Hidden Markov Models  255\u003c\/p\u003e \u003cp\u003e12.6.2 An Example 256\u003c\/p\u003e \u003cp\u003e12.6.3 Three Questions—Three Algorithms  258\u003c\/p\u003e \u003cp\u003e12.6.4 HMMAlignment  262\u003c\/p\u003e \u003cp\u003e12.6.5 Bayesian Tree Alignment  264\u003c\/p\u003e \u003cp\u003e12.6.6 Implementations  264\u003c\/p\u003e \u003cp\u003e12.7 Rearrangement  266\u003c\/p\u003e \u003cp\u003e12.8 Criticisms of BayesianMethods  267\u003c\/p\u003e \u003cp\u003e12.9 Exercises  267\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Comparison of Optimality Criteria 269\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Distance and CharacterMethods  269\u003c\/p\u003e \u003cp\u003e13.2 Epistemology 270\u003c\/p\u003e \u003cp\u003e13.2.1 Ockham’s Razor and Popperian Argumentation  271\u003c\/p\u003e \u003cp\u003e13.2.2 Parsimony and the Evolutionary Process  272\u003c\/p\u003e \u003cp\u003e13.2.3 Induction and Statistical Estimation  272\u003c\/p\u003e \u003cp\u003e13.2.4 Hypothesis Testing and Optimality Criteria  272\u003c\/p\u003e \u003cp\u003e13.3 Statistical Behavior  273\u003c\/p\u003e \u003cp\u003e13.3.1 Probability  273\u003c\/p\u003e \u003cp\u003e13.3.2 Consistency  274\u003c\/p\u003e \u003cp\u003e13.3.3 Efficiency  281\u003c\/p\u003e \u003cp\u003e13.3.4 Robustness  282\u003c\/p\u003e \u003cp\u003e13.4 Performance 282\u003c\/p\u003e \u003cp\u003e13.4.1 Long-Branch Attraction 283\u003c\/p\u003e \u003cp\u003e13.4.2 Congruence  285\u003c\/p\u003e \u003cp\u003e13.5 Convergence  285\u003c\/p\u003e \u003cp\u003e13.6 CanWe Argue Optimality Criteria? 286\u003c\/p\u003e \u003cp\u003e13.7 Exercises 287\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIV Trees 289\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Tree Searching 290\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Exact Solutions  290\u003c\/p\u003e \u003cp\u003e14.1.1 Explicit Enumeration 290\u003c\/p\u003e \u003cp\u003e14.1.2 Implicit Enumeration—Branch-and-Bound  292\u003c\/p\u003e \u003cp\u003e14.2 Heuristic Solutions 294\u003c\/p\u003e \u003cp\u003e14.2.1 Local versus Global Optima 294\u003c\/p\u003e \u003cp\u003e14.3 Trajectory Search 296\u003c\/p\u003e \u003cp\u003e14.3.1 Wagner Algorithm 296\u003c\/p\u003e \u003cp\u003e14.3.2 Branch-Swapping Refinement  298\u003c\/p\u003e \u003cp\u003e14.3.3 Swapping as Distance 301\u003c\/p\u003e \u003cp\u003e14.3.4 Depth-First versus Breadth-First Searching  302\u003c\/p\u003e \u003cp\u003e14.4 Randomization  304\u003c\/p\u003e \u003cp\u003e14.5 Perturbation  305\u003c\/p\u003e \u003cp\u003e14.6 Sectorial Searches and Disc-Covering Methods  309\u003c\/p\u003e \u003cp\u003e14.6.1 Sectorial Searches  309\u003c\/p\u003e \u003cp\u003e14.6.2 Disc-CoveringMethods  310\u003c\/p\u003e \u003cp\u003e14.7 Simulated Annealing  312\u003c\/p\u003e \u003cp\u003e14.8 Genetic Algorithm  316\u003c\/p\u003e \u003cp\u003e14.9 Synthesis and Stopping 318\u003c\/p\u003e \u003cp\u003e14.10 Empirical Examples  319\u003c\/p\u003e \u003cp\u003e14.11 Exercises 323\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Support 324\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 ResamplingMeasures 324\u003c\/p\u003e \u003cp\u003e15.1.1 Bootstrap  325\u003c\/p\u003e \u003cp\u003e15.1.2 Criticisms of the Bootstrap  326\u003c\/p\u003e \u003cp\u003e15.1.3 Jackknife  328\u003c\/p\u003e \u003cp\u003e15.1.4 Resampling and Dynamic Homology Characters  329\u003c\/p\u003e \u003cp\u003e15.2 Optimality-BasedMeasures  329\u003c\/p\u003e \u003cp\u003e15.2.1 Parsimony  330\u003c\/p\u003e \u003cp\u003e15.2.2 Likelihood 332\u003c\/p\u003e \u003cp\u003e15.2.3 Bayesian Posterior Probability  334\u003c\/p\u003e \u003cp\u003e15.2.4 Strengths of Optimality-Based Support  335\u003c\/p\u003e \u003cp\u003e15.3 Parameter-BasedMeasures 336\u003c\/p\u003e \u003cp\u003e15.4 Comparison of Support Measures—Optimal and Average  336\u003c\/p\u003e \u003cp\u003e15.5 Which to Choose?  339\u003c\/p\u003e \u003cp\u003e15.6 Exercises  339\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Consensus, Congruence, and Supertrees 341\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Consensus TreeMethods  341\u003c\/p\u003e \u003cp\u003e16.1.1 Motivations  341\u003c\/p\u003e \u003cp\u003e16.1.2 Adams I and II  341\u003c\/p\u003e \u003cp\u003e16.1.3 Gareth Nelson  344\u003c\/p\u003e \u003cp\u003e16.1.4 Majority Rule  347\u003c\/p\u003e \u003cp\u003e16.1.5 Strict  347\u003c\/p\u003e \u003cp\u003e16.1.6 Semi-Strict\/Combinable Components  348\u003c\/p\u003e \u003cp\u003e16.1.7 Minimally Pruned 348\u003c\/p\u003e \u003cp\u003e16.1.8 When to UseWhat?  350\u003c\/p\u003e \u003cp\u003e16.2 Supertrees 350\u003c\/p\u003e \u003cp\u003e16.2.1 Overview  350\u003c\/p\u003e \u003cp\u003e16.2.2 The Impossibility of the Reasonable  350\u003c\/p\u003e \u003cp\u003e16.2.3 Graph-BasedMethods 353\u003c\/p\u003e \u003cp\u003e16.2.4 Strict Consensus Supertree  355\u003c\/p\u003e \u003cp\u003e16.2.5 MR-Based  355\u003c\/p\u003e \u003cp\u003e16.2.6 Distance-Based Method  358\u003c\/p\u003e \u003cp\u003e16.2.7 Supertrees or Supermatrices?  360\u003c\/p\u003e \u003cp\u003e16.3 Exercises  361\u003c\/p\u003e \u003cp\u003e\u003cb\u003eV Applications 363\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Clocks and Rates 364\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 The Molecular Clock  364\u003c\/p\u003e \u003cp\u003e17.2 Dating  365\u003c\/p\u003e \u003cp\u003e17.3 Testing Clocks  365\u003c\/p\u003e \u003cp\u003e17.3.1 Langley–Fitch  365\u003c\/p\u003e \u003cp\u003e17.3.2 Farris  366\u003c\/p\u003e \u003cp\u003e17.3.3 Felsenstein  367\u003c\/p\u003e \u003cp\u003e17.4 Relaxed ClockModels  368\u003c\/p\u003e \u003cp\u003e17.4.1 Local Clocks  368\u003c\/p\u003e \u003cp\u003e17.4.2 Rate Smoothing  368\u003c\/p\u003e \u003cp\u003e17.4.3 Bayesian Clock  369\u003c\/p\u003e \u003cp\u003e17.5 Implementations  369\u003c\/p\u003e \u003cp\u003e17.5.1 r8s  369\u003c\/p\u003e \u003cp\u003e17.5.2 MULTIDIVTIME 370\u003c\/p\u003e \u003cp\u003e17.5.3 BEAST  370\u003c\/p\u003e \u003cp\u003e17.6 Criticisms  370\u003c\/p\u003e \u003cp\u003e17.7 Molecular Dates?  373\u003c\/p\u003e \u003cp\u003e17.8 Exercises  373\u003c\/p\u003e \u003cp\u003e\u003cb\u003eA Mathematical Notation 374\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eBibliography 376\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex 415\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eColor plate section between pp. 76 and 77\u003c\/i\u003e ?\u003c\/p\u003e","brand":"John Wiley and Sons Ltd","offers":[{"title":"Default Title","offer_id":49525386608983,"sku":"9780470671702","price":138.53,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780470671702.jpg?v=1731860319","url":"https:\/\/bookcurl.com\/products\/systematics-9780470671702","provider":"Book Curl","version":"1.0","type":"link"}