Systematics: a course of lectures / Ward C. Wheeler

Incluye bibliografía: páginas 377-413 e índice: páginas 415-426

Preface.. Using these notes.. Acknowledgments.. List of algorithms.. I Fundamentals.. 1 History.. 1.1 Aristotle.. 1.2 Theophrastus.. 1.3 Pierre Belon.. 1.4 Carolus Linnaeus.. 1.5 Georges Louis Leclerc, Comte de Buffon.. 1.6 Jean-Baptiste Lamarck.. 1.7 Georges Cuvier.. 1.8 Étienne Geoffroy Saint-Hilaire.. 1.9 Johann Wolfgang von Goethe.. 1.10 Lorenz Oken.. 1.11 Richard Owen.. 1.12 Charles Darwin.. 1.13 Stammbäume.. 1.14 Evolutionary Taxonomy.. 1.15 Phenetics.. 1.16 Phylogenetic Systematics.. 1.16.1 Hennig's Three Questions.. 1.17 Molecules and Morphology.. 1.18 We are all Cladists.. 1.19 Exercises.. 2 Fundamental Concepts.. 2.1 Characters.. 2.1.1 Classes of Characters and Total Evidence.. 2.1.2 Ontogeny, Tokogeny, and Phylogeny.. 2.1.3 Characters and Character States.. 2.2 Taxa.. 2.3 Graphs, Trees, and Networks.. 2.3.1 Graphs and Trees.. 2.3.2 Enumeration.. 2.3.3 Networks.. 2.3.4 Mono-, Para-, and Polyphyly.. 2.3.5 Splits and Convexity.. 2.3.6 Apomorphy, Plesiomorphy, and Homoplasy.. 2.3.7 Gene Trees and Species Trees.. 2.4 Polarity and Rooting.. 2.4.1 Stratigraphy.. 2.4.2 Ontogeny.. 2.4.3 Outgroups.. 2.5 Optimality.. 2.6 Homology.. 2.7 Exercises.. 3 Species Concepts, Definitions, and Issues.. 3.1 Typological or Taxonomic Species Concept.. 3.2 Biological Species Concept.. 3.2.1 Criticisms of the BSC.. 3.3 Phylogenetic Species Concept(s.. 3.3.1 Autapomorphic/Monophyletic Species Concept.. 3.3.2 Diagnostic/Phylogenetic Species Concept.. 3.4 Lineage Species Concepts.. 3.4.1 Hennigian Species.. 3.4.2 Evolutionary Species.. 3.4.3 Criticisms of Lineage-Based Species.. 3.5 Species as Individuals or Classes.. 3.6 Monoism and Pluralism.. 3.7 Pattern and Process.. 3.8 Species Nominalism.. 3.9 Do Species Concepts Matter?.. 3.10 Exercises.. 4 Hypothesis Testing and the Philosophy of Science.. 4.1 Forms of Scientific Reasoning.. 4.1.1 The Ancients.. 4.1.2 Ockham's Razor.. 4.1.3 Modes of Scientific Inference.. 4.1.4 Induction

4.1.5 Deduction.. 4.1.6 Abduction.. 4.1.7 Hypothetico-Deduction.. 4.2 Other Philosophical Issues.. 4.2.1 Minimization, Transformation, and Weighting.. 4.3 Quotidian Importance.. 4.4 Exercises.. 5 Computational Concepts.. 5.1 Problems, Algorithms, and Complexity.. 5.1.1 Computer Science Basics.. 5.1.2 Algorithms.. 5.1.3 Asymptotic Notation.. 5.1.4 Complexity.. 5.1.5 Non-Deterministic Complexity.. 5.1.6 Complexity Classes: P and NP.. 5.2 An Example: The Traveling Salesman Problem.. 5.3 Heuristic Solutions.. 5.4 Metricity, and Untrametricity.. 5.5 NP-Complete Problems in Systematics.. 5.6 Exercises.. 6 Statistical and Mathematical Basics.. 6.1 Theory of Statistics.. 6.1.1 Probability.. 6.1.2 Conditional Probability.. 6.1.3 Distributions.. 6.1.4 Statistical Inference.. 6.1.5 Prior and Posterior Distributions.. 6.1.6 Bayes Estimators.. 6.1.7 Maximum Likelihood Estimators.. 6.1.8 Properties of Estimators.. 6.2 Matrix Algebra, Differential Equations, and Markov Models.. 6.2.1 Basics.. 6.2.2 Gaussian Elimination.. 6.2.3 Differential Equations.. 6.2.4 Determining Eigenvalues.. 6.2.5 Markov Matrices.. 6.3 Exercises.. II Homology.. 7 Homology.. 7.1 Pre-Evolutionary Concepts.. 7.1.1 Aristotle.. 7.1.2 Pierre Belon.. 7.1.3 ´Etienne Geoffroy Saint-Hilaire.. 7.1.4 Richard Owen.. 7.2 Charles Darwin.. 7.3 E. Ray Lankester.. 7.4 Adolf Remane.. 7.5 Four Types of Homology.. 7.5.1 Classical View.. 7.5.2 Evolutionary Taxonomy.. 7.5.3 Phenetic Homology.. 7.5.4 Cladistic Homology.. 7.5.5 Types of Homology.. 7.6 Dynamic and Static Homology.. 7.7 Exercises.. 8 Sequence Alignment.. 8.1 Background.. 8.2 "Informal" Alignment.. 8.3 Sequences.. 8.3.1 Alphabets.. 8.3.2 Transformations.. 8.3.3 Distances.. 8.4 Pairwise String Matching.. 8.4.1 An Example.. 8.4.2 Reducing Complexity.. 8.4.3 Other Indel Weights.. 8.5 Multiple Sequence Alignment.. 8.5.1 The Tree Alignment Problem.. 8.5.2 Trees and Alignment.. 8.5.3 Exact Solutions

8.5.4 Polynomial Time Approximate Schemes.. 8.5.5 Heuristic Multiple Sequence Alignment.. 8.5.6 Implementations.. 8.5.7 Structural Alignment.. 8.6 Exercises.. III Optimality Criteria.. 9 Optimality Criteria−Distance.. 9.1 Why Distance?.. 9.1.1 Benefits.. 9.1.2 Drawbacks.. 9.2 Distance Functions.. 9.2.1 Metricity.. 9.3 Ultrametric Trees.. 9.4 Additive Trees.. 9.4.1 Farris Transform.. 9.4.2 Buneman Trees.. 9.5 General Distances.. 9.5.1 Phenetic Clustering.. 9.5.2 Percent Standard Deviation.. 9.5.3 Minimizing Length.. 9.6 Comparisons.. 9.7 Exercises.. 10 Optimality Criteria−Parsimony.. 10.1 Perfect Phylogeny.. 10.2 Static Homology Characters.. 10.2.1 Additive Characters.. 10.2.2 Non-Additive Characters.. 10.2.3 Matrix Characters.. 10.3 Missing Data.. 10.4 Edge Transformation Assignments.. 10.5 Collapsing Branches.. 10.6 Dynamic Homology.. 10.7 Dynamic and Static Homology.. 10.8 Sequences as Characters.. 10.9 The Tree Alignment Problem on Trees.. 10.9.1 Exact Solutions.. 10.9.2 Heuristic Solutions.. 10.9.3 Lifted Alignments, Fixed-States, and Search-Based Heuristics.. 10.9.4 Iterative Improvement.. 10.10 Performance of Heuristic Solutions.. 10.11 Parameter Sensitivity.. 10.11.1 Sensitivity Analysis.. 10.12 Implied Alignment.. 10.13 Rearrangement.. 10.13.1 Sequence Characters with Moves.. 10.13.2 Gene Order Rearrangement.. 10.13.3 Median Evaluation.. 10.13.4 Combination of Methods.. 10.14 Horizontal Gene Transfer, Hybridization, and Phylogenetic Networks.. 10.15 Exercises.. 11 Optimality Criteria−Likelihood.. 11.1 Motivation.. 11.1.1 Felsenstein's Example.. 11.2 Maximum Likelihood and Trees.. 11.2.1 Nuisance Parameters.. 11.3 Types of Likelihood.. 11.3.1 Flavors of Maximum Relative Likelihood.. 11.4 Static-Homology Characters.. 11.4.1 Models.. 11.4.2 Rate Variation.. 11.4.3 Calculating p(D|T, θ.. 11.4.4 Links Between Likelihood and Parsimony.. 11.4.5 A Note on Missing Data.. 11.5 Dynamic-Homology Characters

11.5.1 Sequence Characters.. 11.5.2 Calculating ML Pairwise Alignment.. 11.5.3 ML Multiple Alignment.. 11.5.4 Maximum Likelihood Tree Alignment Problem.. 11.5.5 Genomic Rearrangement.. 11.5.6 Phylogenetic Networks.. 11.6 Hypothesis Testing.. 11.6.1 Likelihood Ratios.. 11.6.2 Parameters and Fit.. 11.7 Exercises.. 12 Optimality Criteria−Posterior Probability.. 12.1 Bayes in Systematics.. 12.2 Priors.. 12.2.1 Trees.. 12.2.2 Nuisance Parameters.. 12.3 Techniques.. 12.3.1 Markov Chain Monte Carlo.. 12.3.2 Metropolis-Hastings Algorithm.. 12.3.3 Single Component.. 12.3.4 Gibbs Sampler.. 12.3.5 Bayesian MC3.. 12.3.6 Summary of Posterior.. 12.4 Topologies and Clades.. 12.5 Optimality versus Support.. 12.6 Dynamic Homology.. 12.6.1 Hidden Markov Models.. 12.6.2 An Example.. 12.6.3 Three Questions-Three Algorithms.. 12.6.4 HMM Alignment.. 12.6.5 Bayesian Tree Alignment.. 12.6.6 Implementations.. 12.7 Rearrangement.. 12.8 Criticisms of Bayesian Methods.. 12.9 Exercises.. 13 Comparison of Optimality Criteria.. 13.1 Distance and Character Methods.. 13.2 Epistemology.. 13.2.1 Ockham's Razor and Popperian Argumentation.. 13.2.2 Parsimony and the Evolutionary Process.. 13.2.3 Induction and Statistical Estimation.. 13.2.4 Hypothesis Testing and Optimality Criteria.. 13.3 Statistical Behavior.. 13.3.1 Probability.. 13.3.2 Consistency.. 13.3.3 Efficiency.. 13.3.4 Robustness.. 13.4 Performance.. 13.4.1 Long-Branch Attraction.. 13.4.2 Congruence.. 13.5 Convergence.. 13.6 Can We Argue Optimality Criteria?.. 13.7 Exercises.. IV Trees.. 14 Tree Searching.. 14.1 Exact Solutions.. 14.1.1 Explicit Enumeration.. 14.1.2 Implicit Enumeration-Branch-and-Bound.. 14.2 Heuristic Solutions.. 14.2.1 Local versus Global Optima.. 14.3 Trajectory Search.. 14.3.1 Wagner Algorithm.. 14.3.2 Branch-Swapping Refinement.. 14.3.3 Swapping as Distance.. 14.3.4 Depth-First versus Breadth-First Searching.. 14.4 Randomization.. 14.5 Perturbation

14.6 Sectorial Searches and Disc-Covering Methods.. 14.6.1 Sectorial Searches.. 14.6.2 Disc-Covering Methods.. 14.7 Simulated Annealing.. 14.8 Genetic Algorithm.. 14.9 Synthesis and Stopping.. 14.10 Empirical Examples.. 14.11 Exercises.. 15 Support.. 15.1 ResamplingMeasures.. 15.1.1 Bootstrap.. 15.1.2 Criticisms of the Bootstrap.. 15.1.3 Jackknife.. 15.1.4 Resampling and Dynamic Homology Characters.. 15.2 Optimality-Based Measures.. 15.2.1 Parsimony.. 15.2.2 Likelihood.. 15.2.3 Bayesian Posterior Probability.. 15.2.4 Strengths of Optimality-Based Support.. 15.3 Parameter-Based Measures.. 15.4 Comparison of Support Measures-Optimal and Average.. 15.5 Which to Choose?.. 15.6 Exercises.. 16 Consensus, Congruence, and Supertrees.. 16.1 Consensus Tree Methods.. 16.1.1 Motivations.. 16.1.2 Adams I and II.. 16.1.3 Gareth Nelson.. 16.1.4 Majority Rule.. 16.1.5 Strict.. 16.1.6 Semi-Strict/Combinable Components.. 16.1.7 Minimally Pruned.. 16.1.8 When to Use What?.. 16.2 Supertrees.. 16.2.1 Overview.. 16.2.2 The Impossibility of the Reasonable.. 16.2.3 Graph-Based Methods.. 16.2.4 Strict Consensus Supertree.. 16.2.5 MR-Based.. 16.2.6 Distance-Based Method.. 16.2.7 Supertrees or Supermatrices?.. 16.3 Exercises.. V Applications.. 17 Clocks and Rates.. 17.1 The Molecular Clock.. 17.2 Dating.. 17.3 Testing Clocks.. 17.3.1 Langley-Fitch.. 17.3.2 Farris.. 17.3.3 Felsenstein.. 17.4 Relaxed Clock Models.. 17.4.1 Local Clocks.. 17.4.2 Rate Smoothing.. 17.4.3 Bayesian Clock.. 17.5 Implementations.. 17.5.1 r8s.. 17.5.2 MULTIDIVTIME.. 17.5.3 BEAST.. 17.6 Criticisms.. 17.7 Molecular Dates?.. 17.8 Exercises.. A Mathematical Notation.. Bibliography.. Index.. Color plate section between pp.76 and 77

Systematics: A Course of Lectures 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. The 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 probability, and tree searching two classes (2 x 1.5 hours). eng