Systematics

Ward Wheeler is Professor in the Richard Gilder Graduate School and Curator of Invertebrate Zoology at the American Museum of Natural History. He is the author of several books, software packages, and over 100 technical papers in empirical and theoretical systematics.

• Preface xv Using these notes xvAcknowledgments  xviList of algorithms xixI Fundamentals 11 History 21.1 Aristotle  21.2 Theophrastus 31.3 Pierre Belon 41.4 Carolus Linnaeus 41.5 Georges Louis Leclerc, Comte de Buffon  61.6 Jean-Baptiste Lamarck 71.7 Georges Cuvier  81.8 ´Etienne Geoffroy Saint-Hilaire  81.9 JohannWolfgang von Goethe 81.10 Lorenz Oken 91.11 Richard Owen 91.12 Charles Darwin  91.13 Stammb¨aume  121.14 Evolutionary Taxonomy 141.15 Phenetics 151.16 Phylogenetic Systematics  161.16.1 Hennig’s Three Questions 161.17 Molecules and Morphology  181.18 We are all Cladists 181.19 Exercises 192 Fundamental Concepts 202.1 Characters 202.1.1 Classes of Characters and Total Evidence  222.1.2 Ontogeny, Tokogeny, and Phylogeny  232.1.3 Characters and Character States 232.2 Taxa 262.3 Graphs, Trees, and Networks 282.3.1 Graphs and Trees 302.3.2 Enumeration 312.3.3 Networks  332.3.4 Mono-, Para-, and Polyphyly 332.3.5 Splits and Convexity  382.3.6 Apomorphy, Plesiomorphy, and Homoplasy  392.3.7 Gene Trees and Species Trees 412.4 Polarity and Rooting 432.4.1 Stratigraphy  432.4.2 Ontogeny  432.4.3 Outgroups  452.5 Optimality 492.6 Homology  492.7 Exercises  503 Species Concepts, Definitions, and Issues 533.1 Typological or Taxonomic Species Concept  543.2 Biological Species Concept  543.2.1 Criticisms of the BSC 553.3 Phylogenetic Species Concept(s) 563.3.1 Autapomorphic/Monophyletic Species Concept 563.3.2 Diagnostic/Phylogenetic Species Concept  583.4 Lineage Species Concepts  593.4.1 Hennigian Species  593.4.2 Evolutionary Species  603.4.3 Criticisms of Lineage-Based Species  613.5 Species as Individuals or Classes  623.6 Monoism and Pluralism  633.7 Pattern and Process  633.8 Species Nominalism  643.9 Do Species Concepts Matter?  653.10 Exercises  654 Hypothesis Testing and the Philosophy of Science 674.1 Forms of Scientific Reasoning 674.1.1 The Ancients  674.1.2 Ockham’s Razor  684.1.3 Modes of Scientific Inference  694.1.4 Induction 694.1.5 Deduction 694.1.6 Abduction 704.1.7 Hypothetico-Deduction  714.2 Other Philosophical Issues 754.2.1 Minimization, Transformation, and Weighting 754.3 Quotidian Importance  764.4 Exercises  765 Computational Concepts 775.1 Problems, Algorithms, and Complexity 775.1.1 Computer Science Basics  775.1.2 Algorithms  795.1.3 Asymptotic Notation 795.1.4 Complexity  805.1.5 Non-Deterministic Complexity  825.1.6 Complexity Classes: P and NP  825.2 An Example: The Traveling Salesman Problem  845.3 Heuristic Solutions  855.4 Metricity, and Untrametricity  865.5 NP–Complete Problems in Systematics  875.6 Exercises 886 Statistical and Mathematical Basics 896.1 Theory of Statistics  896.1.1 Probability  896.1.2 Conditional Probability  916.1.3 Distributions 926.1.4 Statistical Inference  986.1.5 Prior and Posterior Distributions  996.1.6 Bayes Estimators 1006.1.7 Maximum Likelihood Estimators  1016.1.8 Properties of Estimators 1016.2 Matrix Algebra, Differential Equations, and Markov Models 1026.2.1 Basics  1026.2.2 Gaussian Elimination 1026.2.3 Differential Equations  1046.2.4 Determining Eigenvalues  1056.2.5 MarkovMatrices  1066.3 Exercises  107II Homology 1097 Homology 1107.1 Pre-Evolutionary Concepts1107.1.1 Aristotle  1107.1.2 Pierre Belon  1107.1.3 ´Etienne Geoffroy Saint-Hilaire  1117.1.4 Richard Owen 1127.2 Charles Darwin  1137.3 E. Ray Lankester  1147.4 Adolf Remane  1147.5 Four Types of Homology  1157.5.1 Classical View  1157.5.2 Evolutionary Taxonomy  1157.5.3 Phenetic Homology  1167.5.4 Cladistic Homology  1167.5.5 Types of Homology  1177.6 Dynamic and Static Homology  1187.7 Exercises  1208 Sequence Alignment 1218.1 Background  1218.2 “Informal” Alignment  1218.3 Sequences  1218.3.1 Alphabets  1228.3.2 Transformations  1238.3.3 Distances  1238.4 Pairwise StringMatching 1238.4.1 An Example  1278.4.2 Reducing Complexity  1298.4.3 Other Indel Weights  1308.5 Multiple Sequence Alignment  1318.5.1 The Tree Alignment Problem  1338.5.2 Trees and Alignment  1338.5.3 Exact Solutions 1348.5.4 Polynomial Time Approximate Schemes  1348.5.5 Heuristic Multiple Sequence Alignment  1348.5.6 Implementations  1358.5.7 Structural Alignment  1398.6 Exercises 145III Optimality Criteria 1479 Optimality Criteria−Distance 1489.1 Why Distance? 1489.1.1 Benefits  1499.1.2 Drawbacks 1499.2 Distance Functions  1509.2.1 Metricity  1509.3 Ultrametric Trees  1509.4 Additive Trees  1529.4.1 Farris Transform  1539.4.2 Buneman Trees  1549.5 General Distances  1569.5.1 Phenetic Clustering 1579.5.2 Percent Standard Deviation 1609.5.3 Minimizing Length  1639.6 Comparisons 1709.7 Exercises  17110 Optimality Criteria−Parsimony 17310.1 Perfect Phylogeny  17410.2 Static Homology Characters  17410.2.1 Additive Characters  17510.2.2 Non-Additive Characters  17910.2.3 Matrix Characters  18210.3 Missing Data  18410.4 Edge Transformation Assignments  18710.5 Collapsing Branches  18810.6 Dynamic Homology  18810.7 Dynamic and Static Homology  18910.8 Sequences as Characters 19010.9 The Tree Alignment Problem on Trees  19110.9.1 Exact Solutions  19110.9.2 Heuristic Solutions 19110.9.3 Lifted Alignments, Fixed-States, and Search-Based Heuristics  19310.9.4 Iterative Improvement  19710.10 Performance of Heuristic Solutions 19810.11 Parameter Sensitivity  19810.11.1 Sensitivity Analysis  19910.12 Implied Alignment  19910.13 Rearrangement  20410.13.1 Sequence Characters with Moves  20410.13.2Gene Order Rearrangement 20510.13.3Median Evaluation  20710.13.4Combination ofMethods 20710.14 Horizontal Gene Transfer, Hybridization, and Phylogenetic Networks  20910.15 Exercises  21011 Optimality Criteria−Likelihood 21311.1 Motivation  21311.1.1 Felsenstein’s Example  21311.2 Maximum Likelihood and Trees  21611.2.1 Nuisance Parameters  21611.3 Types of Likelihood  21711.3.1 Flavors ofMaximum Relative Likelihood 21711.4 Static-Homology Characters  21811.4.1 Models  21811.4.2 Rate Variation  21911.4.3 Calculating p(D|T, θ)  22111.4.4 Links Between Likelihood and Parsimony  22211.4.5 A Note onMissing Data 22411.5 Dynamic-Homology Characters  22411.5.1 Sequence Characters  22511.5.2 CalculatingML Pairwise Alignment  22711.5.3 MLMultiple Alignment  23011.5.4 Maximum Likelihood Tree Alignment Problem 23011.5.5 Genomic Rearrangement  23211.5.6 Phylogenetic Networks  23411.6 Hypothesis Testing  23411.6.1 Likelihood Ratios  23411.6.2 Parameters and Fit  23611.7 Exercises  23812 Optimality Criteria−Posterior Probability 24012.1 Bayes in Systematics  24012.2 Priors  24112.2.1 Trees  24112.2.2 Nuisance Parameters  24212.3 Techniques 24612.3.1 Markov ChainMonte Carlo  24612.3.2 Metropolis–Hastings Algorithm 24612.3.3 Single Component 24812.3.4 Gibbs Sampler  24912.3.5 Bayesian MC3 24912.3.6 Summary of Posterior  25012.4 Topologies and Clades  25212.5 Optimality versus Support  25412.6 Dynamic Homology  25412.6.1 Hidden Markov Models  25512.6.2 An Example 25612.6.3 Three Questions—Three Algorithms  25812.6.4 HMMAlignment  26212.6.5 Bayesian Tree Alignment  26412.6.6 Implementations  26412.7 Rearrangement  26612.8 Criticisms of BayesianMethods  26712.9 Exercises  26713 Comparison of Optimality Criteria 26913.1 Distance and CharacterMethods  26913.2 Epistemology 27013.2.1 Ockham’s Razor and Popperian Argumentation  27113.2.2 Parsimony and the Evolutionary Process  27213.2.3 Induction and Statistical Estimation  27213.2.4 Hypothesis Testing and Optimality Criteria  27213.3 Statistical Behavior  27313.3.1 Probability  27313.3.2 Consistency  27413.3.3 Efficiency  28113.3.4 Robustness  28213.4 Performance 28213.4.1 Long-Branch Attraction 28313.4.2 Congruence  28513.5 Convergence  28513.6 CanWe Argue Optimality Criteria? 28613.7 Exercises 287IV Trees 28914 Tree Searching 29014.1 Exact Solutions  29014.1.1 Explicit Enumeration 29014.1.2 Implicit Enumeration—Branch-and-Bound  29214.2 Heuristic Solutions 29414.2.1 Local versus Global Optima 29414.3 Trajectory Search 29614.3.1 Wagner Algorithm 29614.3.2 Branch-Swapping Refinement  29814.3.3 Swapping as Distance 30114.3.4 Depth-First versus Breadth-First Searching  30214.4 Randomization  30414.5 Perturbation  30514.6 Sectorial Searches and Disc-Covering Methods  30914.6.1 Sectorial Searches  30914.6.2 Disc-CoveringMethods  31014.7 Simulated Annealing  31214.8 Genetic Algorithm  31614.9 Synthesis and Stopping 31814.10 Empirical Examples  31914.11 Exercises 32315 Support 32415.1 ResamplingMeasures 32415.1.1 Bootstrap  32515.1.2 Criticisms of the Bootstrap  32615.1.3 Jackknife  32815.1.4 Resampling and Dynamic Homology Characters  32915.2 Optimality-BasedMeasures  32915.2.1 Parsimony  33015.2.2 Likelihood 33215.2.3 Bayesian Posterior Probability  33415.2.4 Strengths of Optimality-Based Support  33515.3 Parameter-BasedMeasures 33615.4 Comparison of Support Measures—Optimal and Average  33615.5 Which to Choose?  33915.6 Exercises  33916 Consensus, Congruence, and Supertrees 34116.1 Consensus TreeMethods  34116.1.1 Motivations  34116.1.2 Adams I and II  34116.1.3 Gareth Nelson  34416.1.4 Majority Rule  34716.1.5 Strict  34716.1.6 Semi-Strict/Combinable Components  34816.1.7 Minimally Pruned 34816.1.8 When to UseWhat?  35016.2 Supertrees 35016.2.1 Overview  35016.2.2 The Impossibility of the Reasonable  35016.2.3 Graph-BasedMethods 35316.2.4 Strict Consensus Supertree  35516.2.5 MR-Based  35516.2.6 Distance-Based Method  35816.2.7 Supertrees or Supermatrices?  36016.3 Exercises  361V Applications 36317 Clocks and Rates 36417.1 The Molecular Clock  36417.2 Dating  36517.3 Testing Clocks  36517.3.1 Langley–Fitch  36517.3.2 Farris  36617.3.3 Felsenstein  36717.4 Relaxed ClockModels  36817.4.1 Local Clocks  36817.4.2 Rate Smoothing  36817.4.3 Bayesian Clock  36917.5 Implementations  36917.5.1 r8s  36917.5.2 MULTIDIVTIME 37017.5.3 BEAST  37017.6 Criticisms  37017.7 Molecular Dates?  37317.8 Exercises  373A Mathematical Notation 374Bibliography 376Index 415Color plate section between pp. 76 and 77

“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.”  (British Ecological Society Bulletin, 1 August 2013)“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.”  (Teaching Biology, 20 December 2012)“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.”  (Journal of Zoological Systematics and Evolutionary Research, 1 February 2013)