Systematics A Course of Lectures

by Wheeler, Ward C.

• ISBN13: 9780470671702
• ISBN10: 047067170X
• Edition: 1st
• Format: Hardcover
• Copyright: 2012-05-29
• Publisher: Wiley-Blackwell

Summary

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).

Author Biography

Ward Wheeler is Professor 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.

Table of Contents

Preface	p. xv
Using these notes	p. xv
Acknowledgments	p. xvi
List of algorithms	p. xix
Fundamentals	p. 1
History	p. 2
Aristotle	p. 2
Theophrastus	p. 3
Pierre Belon	p. 4
Carolus Linnaeus	p. 4
Georges Louis Leclerc, Comte de Buffon	p. 6
Jean-Baptiste Lamarck	p. 7
Georges Cuvier	p. 8
'Etienne Geoffroy Saint-Hilaire	p. 8
JohannWolfgang von Goethe	p. 8
Lorenz Oken	p. 9
Richard Owen	p. 9
Charles Darwin	p. 9
Stammbäume	p. 12
Evolutionary Taxonomy	p. 14
Phenetics	p. 15
Phylogenetic Systematics	p. 16
Hennig's Three Questions	p. 16
Molecules and Morphology	p. 18
We are all Cladists	p. 18
Exercises	p. 19
Fundamental Concepts	p. 20
Characters	p. 20
Classes of Characters and Total Evidence	p. 22
Ontogeny, Tokogeny, and Phylogeny	p. 23
Characters and Character States	p. 23
Taxa	p. 26
Graphs, Trees, and Networks	p. 28
Graphs and Trees	p. 30
Enumeration	p. 31
Networks	p. 33
Mono-, Para-, and Polyphyly	p. 33
Splits and Convexity	p. 38
Apomorphy, Plesiomorphy, and Homoplasy	p. 39
Gene Trees and Species Trees	p. 41
Polarity and Rooting	p. 43
Stratigraphy	p. 43
Ontogeny	p. 43
Outgroups	p. 45
Optimality	p. 49
Homology	p. 49
Exercises	p. 50
Species Concepts, Definitions, and Issues	p. 53
Typological or Taxonomic Species Concept	p. 54
Biological Species Concept	p. 54
Criticisms of the BSC	p. 55
Phylogenetic Species Concept(s)	p. 56
Autapomorphic/Monophyletic Species Concept	p. 56
Diagnostic/Phylogenetic Species Concept	p. 58
Lineage Species Concepts	p. 59
Hennigian Species	p. 59
Evolutionary Species	p. 60
Criticisms of Lineage-Based Species	p. 61
Species as Individuals or Classes	p. 62
Monoism and Pluralism	p. 63
Pattern and Process	p. 63
Species Nominalism	p. 64
Do Species Concepts Matter?	p. 65
Exercises	p. 65
Hypothesis Testing and the Philosophy of Science	p. 67
Forms of Scientific Reasoning	p. 67
The Ancients	p. 67
Ockham's Razor	p. 68
Modes of Scientific Inference	p. 69
Induction	p. 69
Deduction	p. 69
Abduction	p. 70
Hypothetico-Deduction	p. 71
Other Philosophical Issues	p. 75
Minimization, Transformation, and Weighting	p. 75
Quotidian Importance	p. 76
Exercises	p. 76
Computational Concepts	p. 77
Problems, Algorithms, and Complexity	p. 77
Computer Science Basics	p. 77
Algorithms	p. 79
Asymptotic Notation	p. 79
Complexity	p. 80
Non-Deterministic Complexity	p. 82
Complexity Classes: P and NP	p. 82
An Example: The Traveling Salesman Problem	p. 84
Heuristic Solutions	p. 85
Metricity, and Untrametricity	p. 86
NP-Complete Problems in Systematics	p. 87
Exercises	p. 88
Statistical and Mathematical Basics	p. 89
Theory of Statistics	p. 89
Probability	p. 89
Conditional Probability	p. 91
Distributions	p. 92
Statistical Inference	p. 98
Prior and Posterior Distributions	p. 99
Bayes Estimators	p. 100
Maximum Likelihood Estimators	p. 101
Properties of Estimators	p. 101
Matrix Algebra, Differential Equations, and Markov Models	p. 102
Basics	p. 102
Gaussian Elimination	p. 102
Differential Equations	p. 104
Determining Eigenvalues	p. 105
MarkovMatrices	p. 106
Exercises	p. 107
Homology	p. 109
Homology	p. 110
Pre-Evolutionary Concepts	p. 110
Aristotle	p. 110
Pierre Belon	p. 110
'Etienne Geoffroy Saint-Hilaire	p. 111
Richard Owen	p. 112
Charles Darwin	p. 113
E. Ray Lankester	p. 114
Adolf Remane	p. 114
Four Types of Homology	p. 115
Classical View	p. 115
Evolutionary Taxonomy	p. 115
Phenetic Homology	p. 116
Cladistic Homology	p. 116
Types of Homology	p. 117
Dynamic and Static Homology	p. 118
Exercises	p. 120
Sequence Alignment	p. 121
Background	p. 121
"Informal" Alignment	p. 121
Sequences	p. 121
Alphabets	p. 122
Transformations	p. 123
Distances	p. 123
Pairwise StringMatching	p. 123
An Example	p. 127
Reducing Complexity	p. 129
Other Indel Weights	p. 130
Multiple Sequence Alignment	p. 131
The Tree Alignment Problem	p. 133
Trees and Alignment	p. 133
Exact Solutions	p. 134
Polynomial Time Approximate Schemes	p. 134
Heuristic Multiple Sequence Alignment	p. 134
Implementations	p. 135
Structural Alignment	p. 139
Exercises	p. 145
Optimality Criteria	p. 147
Optimality Criteria-Distance	p. 148
Why Distance?	p. 148
Benefits	p. 149
Drawbacks	p. 149
Distance Functions	p. 150
Metricity	p. 150
Ultrametric Trees	p. 150
Additive Trees	p. 152
Farris Transform	p. 153
Buneman Trees	p. 154
General Distances	p. 156
Phenetic Clustering	p. 157
Percent Standard Deviation	p. 160
Minimizing Length	p. 163
Comparisons	p. 170
Exercises	p. 171
Optimality Criteria-Parsimony	p. 173
Perfect Phylogeny	p. 174
Static Homology Characters	p. 174
Additive Characters	p. 175
Non-Additive Characters	p. 179
Matrix Characters	p. 182
Missing Data	p. 184
Edge Transformation Assignments	p. 187
Collapsing Branches	p. 188
Dynamic Homology	p. 188
Dynamic and Static Homology	p. 189
Sequences as Characters	p. 190
The Tree Alignment Problem on Trees	p. 191
Exact Solutions	p. 191
Heuristic Solutions	p. 191
Lifted Alignments, Fixed-States, and Search-Based Heuristics	p. 193
Iterative Improvement	p. 197
Performance of Heuristic Solutions	p. 198
Parameter Sensitivity	p. 198
Sensitivity Analysis	p. 199
Implied Alignment	p. 199
Rearrangement	p. 204
Sequence Characters with Moves	p. 204
Gene Order Rearrangement	p. 205
Median Evaluation	p. 207
Combination ofMethods	p. 207
Horizontal Gene Transfer, Hybridization, and Phylogenetic Networks	p. 209
Exercises	p. 210
Optimality Criteria-Likelihood	p. 213
Motivation	p. 213
Felsenstein's Example	p. 213
Maximum Likelihood and Trees	p. 216
Nuisance Parameters	p. 216
Types of Likelihood	p. 217
Flavors ofMaximum Relative Likelihood	p. 217
Static-Homology Characters	p. 218
Models	p. 218
Rate Variation	p. 219
Calculating p(D T, ?)	p. 221
Links Between Likelihood and Parsimony	p. 222
A Note onMissing Data	p. 224
Dynamic-Homology Characters	p. 224
Sequence Characters	p. 225
CalculatingML Pairwise Alignment	p. 227
MLMultiple Alignment	p. 230
Maximum Likelihood Tree Alignment Problem	p. 230
Genomic Rearrangement	p. 232
Phylogenetic Networks	p. 234
Hypothesis Testing	p. 234
Likelihood Ratios	p. 234
Parameters and Fit	p. 236
Exercises	p. 238
Optimality Criteria-Posterior Probability	p. 240
Bayes in Systematics	p. 240
Priors	p. 241
Trees	p. 241
Nuisance Parameters	p. 242
Techniques	p. 246
Markov ChainMonte Carlo	p. 246
Metropolis-Hastings Algorithm	p. 246
Single Component	p. 248
Gibbs Sampler	p. 249
Bayesian MC3	p. 249
Summary of Posterior	p. 250
Topologies and Clades	p. 252
Optimality versus Support	p. 254
Dynamic Homology	p. 254
Hidden Markov Models	p. 255
An Example	p. 256
Three Questions-Three Algorithms	p. 258
HMMAlignment	p. 262
Bayesian Tree Alignment	p. 264
Implementations	p. 264
Rearrangement	p. 266
Criticisms of BayesianMethods	p. 267
Exercises	p. 267
Comparison of Optimality Criteria	p. 269
Distance and CharacterMethods	p. 269
Epistemology	p. 270
Ockham's Razor and Popperian Argumentation	p. 271
Parsimony and the Evolutionary Process	p. 272
Induction and Statistical Estimation	p. 272
Hypothesis Testing and Optimality Criteria	p. 272
Statistical Behavior	p. 273
Probability	p. 273
Consistency	p. 274
Efficiency	p. 281
Robustness	p. 282
Performance	p. 282
Long-Branch Attraction	p. 283
Congruence	p. 285
Convergence	p. 285
CanWe Argue Optimality Criteria?	p. 286
Exercises 287 IV Trees	p. 289
Tree Searching	p. 290
Exact Solutions	p. 290
Explicit Enumeration	p. 290
Implicit Enumeration-Branch-and-Bound	p. 292
Heuristic Solutions	p. 294
Local versus Global Optima	p. 294
Trajectory Search	p. 296
Wagner Algorithm	p. 296
Branch-Swapping Refinement	p. 298
Swapping as Distance	p. 301
Depth-First versus Breadth-First Searching	p. 302
Randomization	p. 304
Perturbation	p. 305
Sectorial Searches and Disc-Covering Methods	p. 309
Sectorial Searches	p. 309
Disc-CoveringMethods	p. 310
Simulated Annealing	p. 312
Genetic Algorithm	p. 316
Synthesis and Stopping	p. 318
Empirical Examples	p. 319
Exercises	p. 323
Support	p. 324
ResamplingMeasures	p. 324
Bootstrap	p. 325
Criticisms of the Bootstrap	p. 326
Jackknife	p. 328
Resampling and Dynamic Homology Characters	p. 329
Optimality-BasedMeasures	p. 329
Parsimony	p. 330
Likelihood	p. 332
Bayesian Posterior Probability	p. 334
Strengths of Optimality-Based Support	p. 335
Parameter-BasedMeasures	p. 336
Comparison of Support Measures-Optimal and Average	p. 336
Which to Choose?	p. 339
Exercises	p. 339
Consensus, Congruence, and Supertrees	p. 341
Consensus TreeMethods	p. 341
Motivations	p. 341
Adams I and II	p. 341
Gareth Nelson	p. 344
Majority Rule	p. 347
Strict	p. 347
Semi-Strict/Combinable Components	p. 348
Minimally Pruned	p. 348
When to UseWhat?	p. 350
Supertrees	p. 350
Overview	p. 350
The Impossibility of the Reasonable	p. 350
Graph-BasedMethods	p. 353
Strict Consensus Supertree	p. 355
MR-Based	p. 355
Distance-Based Method	p. 358
Supertrees or Supermatrices?	p. 360
Exercises 361 V Applications	p. 363
Clocks and Rates	p. 364
The Molecular Clock	p. 364
Dating	p. 365
Testing Clocks	p. 365
Langley-Fitch	p. 365
Farris	p. 366
Felsenstein	p. 367
Relaxed ClockModels	p. 368
Local Clocks	p. 368
Rate Smoothing	p. 368
Bayesian Clock	p. 369
Implementations	p. 369
r8s	p. 369
Multidivtime	p. 370
BEAST	p. 370
Criticisms	p. 370
Molecular Dates?	p. 373
Exercises	p. 373
A Mathematical Notation	p. 374
Bibliography	p. 376
Index	p. 415
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