Principles of Evolution (eBook)

Hildegard Meyer-Ortmanns is full professor and head of the statistical physics group at Jacobs University in Bremen, Germany. Her area of expertise ranges from general relativity and theoretical particle physics to  statistical physics and its applications to complex systems. Stefan Thurner is Professor of Science of Complex Systems at the Medical  University of Vienna and external professor at the Santa Fe institute.  His area of interest extends from theoretical physics and applied  mathematics to complex systems theory and its applications in  life science and economics.

Preface 7
Contents 8
Contributors 10
1 Introduction 12
Hildegard Meyer-Ortmanns 12
1.1 A Short Chronology of Evolution 13
1.2 Scientific Reductionism 16
1.3 Universal Features, Universal Processes, and Striving for Universal Laws 19
1.4 The Concept of Self-Organization 22
1.5 Chicken-and-Egg Problems in Many Facets 24
1.6 A Quick Look into the Nanoworld 26
1.7 Playing the Tape Again 26
1.8 There is More than Intuition 28
1.9 Reduction of Complexity 29
1.10 How This Book Is Organized 30
1.10.1 Background 30
1.10.2 Rationale 30
1.10.3 About the Articles 32
References 51
Part I Principles of Evolution 53
2 Physical Principles of Evolution 54
Peter Schuster 54
2.1 Mathematics and Biology 55
2.2 Darwin's Theory in Mathematical Language 58
2.3 Evolution in Genotype Space 62
2.4 Modeling Genotype--Phenotype Mappings 65
2.5 Chemical Kinetics of Evolution 71
2.6 Evolution as a Stochastic Process 78
2.7 Concluding Remarks 85
References 86
3 The Interplay of Replication, Variation and Selection in the Dynamics of Evolving Populations 89
Richard A. Blythe 89
3.1 Hull's General Analysis of Selection 91
3.1.1 Instances of Hull's General Analysis of Selection 92
3.2 A Mathematical Analysis of Selection: The Price Equation 94
3.2.1 Derivation of the Price Equation 95
3.2.2 Applications of the Price Equation 96
3.3 Neutral Demographic Fluctuations: Genetic Drift 99
3.3.1 Models of Purely Neutral Evolution 100
3.3.2 Fixation Probability 101
3.3.3 Mean Fixation Time 102
3.3.4 Experimental Observation of Genetic Drift: Effective Population Size 103
3.4 Immigration and Mutation in Neutral Models 104
3.4.1 Recurrent Immigration 105
3.4.2 Nonrecurrent Immigration 108
3.4.3 Applications in Ecology and Cultural Evolution 116
3.5 Population Subdivision 117
3.5.1 Voter-Type Models on Heterogeneous Networks 120
3.5.2 Application to Theories for Language Change 123
3.6 Summary and Outlook 124
References 125
4 A Simple General Model of Evolutionary Dynamics 127
Stefan Thurner 127
4.1 Introduction 128
4.2 A General Model for Evolution Dynamics 131
4.2.1 A Notion for Species, Goods, Things, or Elements 132
4.2.2 Recombination and Production of New Elements 132
4.2.3 Selection, Competition, Destruction 133
4.2.4 The Active Production or Recombination Network 135
4.2.5 Spontaneous Creations, Innovations, Ideas, and Disasters 136
4.2.6 Formal Summary of the Model 136
4.2.7 An Evolutionary Algorithm 137
4.2.8 Random Interactions 137
4.3 Predictions of the Model 138
4.4 Model Variants 140
4.5 Understanding Evolutionary Dynamics 141
4.5.1 Evolutionary Dynamics as a Self-Organized Critical System 141
4.5.2 Eigenvalues and Keystone Productions 141
4.6 Toward a Unified Mathematical Framework 144
4.6.1 Variational Principle for Deterministic Diversity Dynamics 144
4.6.2 Mean-Field Approximation 145
4.7 Applicability to Specific Evolutionary Systems 147
4.7.1 Macroeconomic Instruments 148
4.7.2 Chemical Reaction Networks 148
4.7.3 Lifetime Distributions of Species 148
4.8 Conclusions 150
References 151
5 Can We Recognize an Innovation? Perspective from an Evolving Network Model 153
Sanjay Jain and Sandeep Krishna 153
5.1 Introduction 153
5.2 A Framework for Modeling Innovation: Graph Theoryand Dynamical Systems 154
5.3 Definition of the Model System 156
5.4 Time Evolution of the System 157
5.5 Innovation 163
5.6 Six Categories of Innovation 164
5.6.1 A Short-Lived Innovation: Uncaring and Unviable Winners 164
5.6.2 Birth of an Organization: Cooperation Begets Stability 165
5.6.3 Expansion of the Organization at Its Periphery: Incremental Innovations 166
5.6.4 Growth of the Core of the Organization: Parasites Become Symbionts 167
5.6.5 Core-Shift 1: Takeover by a New Competitor 168
5.6.6 Core-Shift 2: Takeover by a Dormant Innovation 169
5.7 Recognizing Innovations: A Structural Classification 170
5.8 Some Possible General Lessons 172
5.9 Discussion 173
References 179
Part II From Random to Complex Structures:The Concept of Self-Organization for Galaxies,Asters, and Spindles 181
6 How Stochastic Dynamics Far from Equilibrium Can Create Nonrandom Patterns 182
Gunter M. Schütz 182
6.1 Some Very Small Numbers 182
6.2 Some Models for Nonequilibrium Dynamics 186
6.2.1 Model 1: The Totally Asymmetric Simple Exclusion Process 186
6.2.2 Model 2: The TASEP with Random Sequential Update 188
6.2.3 Model 3: TASEP with Sublattice Parallel Update 189
6.2.4 Model 4: TASEP with Next-Nearest-Neighbor Interaction 189
6.2.5 Emergence of Order and Relaxation to Disorder 190
6.3 Some Conclusions 192
References 194
7 Structure Formation in the Universe 195
Matthias Bartelmann 195
7.1 The Framework 195
7.1.1 Concepts 195
7.1.2 Isotropy on Average 196
7.1.3 The Cosmic Expansion 197
7.1.4 Origin of the Light Elements and the CosmicMicrowave Background 198
7.1.5 Structures in the Cosmic Microwave Background 199
7.1.6 Cosmic Consistency 202
7.2 Structure Formation in the Universe 203
7.2.1 Concepts and Assumptions 203
7.2.2 Linear Structure Growth 204
7.2.3 Cold Dark Matter 205
7.2.4 Nonlinear Structure Growth 208
7.2.5 The Origin of Structures 209
References 209
8 The Need for Quantum Cosmology 211
Claus Kiefer 211
8.1 Introduction 211
8.2 Quantum Gravity 212
8.3 Quantum Cosmology 215
8.4 Boundary Conditions 216
8.4.1 No-Boundary Proposal 216
8.4.2 Tunneling Proposal 218
8.5 Inclusion of Inhomogeneities and the Semiclassical Picture 218
8.6 Arrow of Time and Structure Formation 220
References 223
9 Self-Organization in Cells 224
Leif Dehmelt and Philippe Bastiaens 224
9.1 The Origin of Cellular Organization 224
9.2 Self-Organization and Other Organizational Principlesin Cells 225
9.3 Emergence of Spatio-Temporal Gradients via Dynamic Feedback Systems 229
9.4 Stigmergy and Feedback Regulation in Directional Morphogenetic Growth or Transport Processes 232
9.5 Emergence of Complex Structures via Self-Organizationof Microtubules and Associated Motors 235
9.6 Emergence of Dynamic Structures in Actin Filament Treadmill Systems 238
9.7 Limits of Self-Organization in Cells 240
References 242
Part III Protocells In Silico and In Vitro 244
10 Approach of Complex-Systems Biology to Reproduction and Evolution 245
Kunihiko Kaneko 245
10.1 A Bridge Between Catalytic Reaction Networks and Reproducing Cells 246
10.1.1 Catalytic Reaction Network for a Protocell 246
10.1.2 Long-Term Sustainment of Nonequilibrium State 247
10.1.3 Consistency Between Cell Reproduction and Molecule Replication 249
10.1.4 Minority Control: Origin of Genetic Information 251
10.2 Evolution 254
10.2.1 Fluctuations and Robustness 254
10.2.2 Evolutionary Fluctuation--Response Relationship 255
10.2.3 Relationship Between Fluctuations by Noise and by Mutation 256
10.2.4 Phenomenological Distribution Theory 259
10.2.5 Discussion 261
References 262
11 Wet Artificial Life: The Construction of Artificial Living Systems 264
Harold Fellermann 264
11.1 Introduction 264
11.2 Bits and Pieces 266
11.2.1 Chemical Information 266
11.2.2 Protocell Containers 268
11.2.3 Protocell Metabolisms 270
11.3 Bottom-Up Approaches to Artificial Cells 271
11.4 The Minimal Protocell 274
11.4.1 Design Principles 274
11.4.2 Building Blocks 275
11.4.3 Life Cycle of the Protocell 275
11.4.4 The Metabolism of the Protocell 277
11.4.5 Toward Inheritable Information and Darwinian Evolution 279
11.5 The Evolutionary Potential of Protocells 280
References 281
12 Towards a Minimal System for Cell Division 284
Petra Schwille 284
12.1 Two Concepts of Synthetic Biology 285
12.2 The Concept of a Minimal Cell 286
12.3 Minimal Systems for Cell Division: An Attempt 287
12.3.1 Step One: Modeling Membrane Morphogenesis -- Nature`s Solution to Compartmentation 288
12.3.2 Step Two: Adding Mechanical Stability -- Creation of an Artificial Cortex/Cytoskeleton 291
12.3.3 Step Three: How Should the Division Site Be Defined? Pattern Formation and Self-Organization in Minimal Systems 293
12.4 Outlook 295
References 296
Part IV From Cells to Societies 297
13 Bacterial Games 298
Erwin Frey and Tobias Reichenbach 298
13.1 Introduction 299
13.2 The Language of Game Theory 300
13.2.1 Strategic Games and Social Dilemmas 300
13.2.2 Evolutionary Game Theory 302
13.2.3 Nonlinear Dynamics of Two-Player Games 305
13.3 Games in Microbial Metapopulations 307
13.3.1 Cooperation 307
13.3.2 Pattern Formation 309
13.3.3 The Escherichia coli Col E2 System 309
13.4 Stochastic Dynamics in Well-Mixed Populations 311
13.4.1 Extinction Times and Classification of Coexistence Stability 311
13.4.2 Cyclic Three-Strategy Games 315
13.5 Spatial Games with Cyclic Dominance 316
13.5.1 The Role of Mobility in Ecosystems 316
13.5.2 Cyclic Dominance in Ecosystems 317
13.5.3 The May--Leonard Model 317
13.5.4 The Spatially Extended May--Leonard Model 319
13.5.5 Pattern Formation and Reaction--Diffusion Equations 321
13.6 Conclusions and Outlook 325
References 328
14 Darwin and the Evolution of Human Cooperation 331
Karl Sigmund and Christian Hilbe 331
14.1 Darwin on Complexity 331
14.2 The Riddle of Cooperation 332
14.3 Kin Selection 334
14.4 Relatedness and Assortment 335
14.5 Darwin on Kin Selection 336
14.6 Political Animals 337
14.7 Reciprocal Altruism 338
14.8 Indirect Reciprocity 341
14.9 Competition of Moral Systems 342
14.10 Exceptionalism 344
14.11 Team Efforts 345
14.12 Group Selection 346
References 347
15 Similarities Between Biological and Social Networks in Their Structural Organization 348
Byungnam Kahng, Deokjae Lee, and Pureun Kim 348
15.1 Introduction 348
15.2 Branching Tree and Fractal Structure 349
15.2.1 Scale-Free and Critical Branching Structure 349
15.2.2 Fractality 350
15.3 The Phylogenetic Tree 352
15.3.1 Database 352
15.3.2 Structural Features 352
15.4 Evolution of Protein Interaction Networks 353
15.4.1 The Solé Model 353
15.4.2 Numerical Results 354
15.5 Evolution of a Coauthorship Network 357
15.5.1 Data Collection 357
15.5.2 Evolution of a Large-Scale Structure 358
15.5.3 Fractal Structure and Critical Branching Tree 360
15.6 Conclusions 363
References 363
16 From Swarms to Societies: Origins of Social Organization 365
Alexander S. Mikhailov 365
16.1 What Is a Society? 365
16.2 Swarms and Active Fluids 366
16.3 Internal Dynamics and Communication 367
16.4 Synchronization 368
16.5 Clustering 368
16.6 Hierarchies 370
16.7 Networks 372
16.8 Coherent Patterns and Turbulence 373
16.9 Feedback and Control 374
16.10 Social Evolution 376
16.11 Open Questions and Perspectives 376
References 377
Index 379