Foundations of Phylogenetic Systematics

Introduction 9
1. Metaphysical foundations of science 11
1.1 What is knowledge? 11
1.2 Classification and the function of language 12
1.3 What is there outside of our cognition apparatus? What is “really existing”? 16
1.3.1 Objects of nature, the “thing per se” 17
1.3.2 Systems 18
1.3.3 Thing and system 19
1.3.4 What is a “system in the animal kingdom”? 20
1.3.5 What is “information”? 21
1.3.6 Quantifying information 24
1.3.7 What is a character? 25
1.4 Acquisition of knowledge in sciences 29
1.4.1 What is a “truth”? 29
1.4.2 Deduction and induction 30
1.4.3 The hypothetico-deductive method 32
1.4.4 Laws and theories 34
1.4.5 Probability and the principle of parsimony 34
1.4.6 Phenomenology 40
1.4.7 The role of logic 41
1.4.8 Algorithms and gaining knowledge 41
1.5 Evolutionary epistemology 42
2. The subject of phylogenetic systematics 44
2.1 Transfer of genetic information between organisms 45
2.1.1 Horizontal gene transfer 45
2.1.2 Clonal reproduction 45
2.1.3 Bisexual reproduction 46
2.1.4 The special case of endosymbionts which evolved to organelles (mitochondria and plastids) 47
2.2 The population 48
2.3 The “biological species” 52
2.3.1 The species concept as a tool of phylogenetics 56
2.3.2 Recognition of species 63
2.4 The transitional field between species 65
2.5 Speciation as a “key event” 68
2.5.1 Notions and real processes 68
2.5.2 Dichotomy and polytomy 68
2.6 Monophyla 69
2.7 Evolutionary theory and models of evolution as basis for systematics 73
2.7.1 Variability and evolution of morphological structures 75
2.7.2 Variability and evolution of molecules 81
2.7.2.1 Changes in populations 81
2.7.2.2 The theory of neutral evolution 83
2.7.2.3 The molecular clock 85
2.7.2.4 Evolutionary rates 89
2.8 Summary: Constructs, processes and systems 97
3. Phylogenetic graphs 98
3.1 Ontology and terms 98
3.2 Topology 100
3.2.1 Visualization of compatible hypotheses of monophyly 100
3.2.2 Visualization of incompatible hypotheses of monophyly 103
3.2.3 Visualization of hypotheses of character polarity and of apomorphy 103
3.3 Consensus dendrograms 104
3.3.1 Supertrees and “democratic voting” 106
3.4 Number of elements of a dendrogram and number of topologies 107
3.5 The taxon 108
3.6 The stem lineage 111
3.7 Linnéan categories 113
4. The search for evidence of monophyly 177
4.1 What is information in systematics? 177
4.2 Classes of characters 119
4.2.1 Similarities 119
4.2.2 Classes of homologies 124
4.2.3 Forming groups with different classes of characters 132
4.2.4 Homologous genes 133
4.3 Principles of character analysis 134
4.3.1 Processes and patterns, or what we can learn from Leonardo’s Mona Lisa 135
4.4 Delimitation and identification of monophyla 137
4.4.1 The delimitation 137
4.4.2 The identification 139
4.4.3 Recommended procedure for practical analyses 139
4.5 Analysis of fossils 139
4.5.1 Character analysis 139
4.5.2 Transformation series of populations as evidence for monophyly 141
5. Phenomenological character analysis 142
5.1 The estimation of the probability of homology and character weighting 142
5.1.1 The probability of homology and criteria for its evaluation 142
5.1.2 Weighting 152
5.2 The search for morphological and molecular homologies 155
5.2.1 Criteria of homology for morphological characters 155
5.2.2 Homologization of molecular characters 164
5.2.2.1 Sequence alignment 164
5.2.2.2 Determination of the homology of nucleotides and of sequence sections 169
5.2.2.3 Homology of genes, gene arrangements, sequence duplications 171
5.2.2.4 Homology of restriction fragments 172
5.2.2.5 Immunology 174
5.2.2.6 Homologization of isoenzymes 175
5.2.2.7 Cytogenetics 177
5.2.2.8 DNA-Hybridization 177
5.2.2.9 RAPD and AFLP 179
5.2.2.10 Amino acid sequences 180
5.3 Determination of character polarity 181
5.3.1 Ingroup and outgroup 181
5.3.2 Phylogenetic character analysis with outgroup comparison, reconstruction of ground patterns 182
5.3.3 Cladistic outgroup addition 187
5.3.4 Increase of complexity 188
5.3.5 The ontogenetic criterion 189
5.3.6 The paleontological criterion 192
5.3.7 Phenomenological determination of character state polarity in nucleic acid sequences and asymmetry of split-supporting patterns 193
6. Reconstruction of phylogeny: the phenomenological method 195
6.1 Phenetic cladistics 196
6.1.1. Character coding 198
6.1.2. The MP-method for tree construction 201
6.1.2.1 Wagner parsimony 203
6.1.2.2 Fitch parsimony 204
6.1.2.3 Dollo parsimony 204
6.1.2.4 Generalized parsimony 205
6.1.2.5 Nucleic acids and amino acid sequences 206
6.1.3 Weighting and the MP-method 207
6.1.4 Iterative weighting 208
6.1.5 Homoplasy 209
6.1.6 Manipulation of the data matrix 210
6.1.7 Cladistic reconstruction of ground patterns 210
6.1.8 Rooting of unpolarized dendrograms 212
6.1.9 Cladistic statistics and tests of reliability 213
6.1.9.1 Consistency index, retention-index, F-ratio 213
6.1.9.2 Resampling tests 215
6.1.9.3 Distribution of tree lengths, randomization tests 217
6.1.10 Can homologies be identified with the MP-method? 218
6.1.11 Sources of errors of phenetic cladistics 220
6.2 Hennig’s method (phylogenetic cladistics) 222
6.2.1 Comparison of phenetic and phylogenetic cladistics 224
6.3 Cladistic analysis of DNA-sequences 225
6.3.1 Model-dependent weighting 225
6.3.2 The analogy problem: the creation of polyphyletic groups 228
6.3.3 The symplesiomorphy trap: paraphyletic groups 230
6.3.4 Using alignment gaps 231
6.3.5 Potential apomorphies 236
6.3.6 Lake’s method 236
6.4 Split-decomposition 236
6.5 Spectra 238
6.5.1 Basics 238
6.5.2 Analysis of spectra of supporting positions 238
6.6 Combined analyses, data partitioning, total evidence 242
7. Process-based character analysis 245
8. Reconstruction of phylogeny: model-dependent methods 248
8.1 Substitution models 248
8.2 Distance methods 254
8.2.1 The principle of distance analyses 255
8.2.2 Visible distances 257
8.2.3 Falsifying effects 259
8.2.4 Effect of invariable positions, positions with different variability, alignment gaps 260
8.2.5 Effects of nucleotide frequencies 262
8.2.6 Distance corrections 262
8.2.7 Tree construction with distance data 264
8.3 Maximum Likelihood: Estimation of the probability of events 265
8.4 Bayesian phylogeny inference 267
8.5 Hendy-Penny spectral analysis 270
8.6 The role of simulations 272
9. Sources of error 273
9.1 Overview of common sources of error 273
9.2 Criteria for the evaluation of the quality of datasets 275
10. Comparison of topologies and plausibility tests 277
10.1 Plausibility 277
10.2 Comparison of topologies 287
11. The importance of results of phylogenetics for other studies 289
12. Systematization and classification 290
12.1 Systematization 290
12.2 Hierarchy 291
12.3 Formal classification 292
12.3.1 Traditional Linnéan nomenclature 292
12.3.2 Phylogenetic nomenclature 294
12.4 Artifacts of the formal classification 295
12.5 Taxonomy 296
12.6 Evolutionary taxonomy 296
13. General laws of phylogenetic systematics 298
14. Appendix: Methods and terms 299
14.1 Models of sequence evolution 299
14.1.1 Jukes-Cantor (JC) model 299
14.1.2 Tajima-Nei-(TjN-)model 301
14.1.3 Kimura’s two-parameter-Model (K2P) 301
14.1.4 Tamura-Nei-model (TrN) 302
14.1.5 Position-dependent variability of substitution rates 302
14.1.6 Log-det distance transformation 304
14.1.7 Protein coding sequences 305
14.2 Maximum parsimony: the search for the shortest topology 305
14.2.1 Construction of topologies 306
14.2.2 Combinatorial weighting 308
14.2.3 Comparison of MP and ML 309
14.3 Distance methods 309
14.3.1 Definition of the Hamming distance 310
14.3.2 Transformation of distances 310
14.3.3 Additive distances 312
14.3.4 Ultrametric distances 313
14.3.5 Transformation of frequency data to distance data: geometric distances 313
14.3.6 Nei’s genetic distance: allele frequencies, restriction fragments 314
14.3.7 Construction of dendrograms with clustering methods 315
14.3.8 Construction of dendrograms with minimum evolution methods 317
14.4 Construction of networks: split-decomposition 317
14.5 Clique analyses 323
14.6 Maximum likelihood methods: analysis of DNA sequences 324
14.7 Hadamard conjugation and Hendy-Penny spectra 328
14.8 Relative rate test 333
14.9 Evaluation of the information content of datasets using permutations 335
14.10 F-ratio 337
14.11 PAM-matrix 338
14.12 Optimization alignment 339
15. Available computer programs, web sites 343
16. References 344
17. Index 359

Johann-Wolfgang Wägele was until recently head of the Department for Animal Systematics (Lehrstuhl für Spezielle Zoologie) at the University of Bochum and is now director of the Museum Alexander Koenig in Bonn (Germany). His main research interests are the taxonomy, phylogeny and biodiversity of Isopoda, which implies observations of life history, biogeography and ecology in combination with phylogeny inference. Further subjects include arthropod phylogeny and tools for explorative data analyses. The author is president of the Gesellschaft für Biologische Systematik, a Central European society of systematists, and he is actively promoting biodiversity research.