Self-organization In Complex Ecosystems. (mpb-42) (ebook)

Argumento de Self-organization In Complex Ecosystems. (mpb-42) (ebook)

Can physics be an appropriate framework for the understanding of ecological science? Most ecologists would probably agree that there is little relation between the complexity of natural ecosystems and the simplicity of any example derived from Newtonian physics. Though ecologists have long been interested in concepts originally developed by statistical physicists and later applied to explain everything from why stock markets crash to why rivers develop particular branching patterns, applying such concepts to ecosystems has remained a challenge.

Self-Organization in Complex Ecosystems is the first book to clearly synthesize what we have learned about the usefulness of tools from statistical physics in ecology. Ricard Solé and Jordi Bascompte provide a comprehensive introduction to complex systems theory, and ask: do universal laws shape the structure of ecosystems, at least at some scales? They offer the most compelling array of theoretical evidence to date of the potential of nonlinear ecological interactions to generate nonrandom, self-organized patterns at all levels.

Tackling classic ecological questions--from population dynamics to biodiversity to macroevolution--the book's novel presentation of theories and data shows the power of statistical physics and complexity in ecology. Self-Organization in Complex Ecosystems will be a staple resource for years to come for ecologists interested in complex systems theory as well as mathematicians and physicists interested in ecology.

"Throughout the volume, the authors provide examples of rigorous mathematical treatment and ecological problems of local and global significance using concepts and tools of statistical physics. These examples, as well as a solid background on the applicability of fundamental laws of physics in ecology, could provide excellent supplemental formation for theoretical ecology courses."--Igor Linkov, Quarterly Review of Biology

"A great book. Self-organization in Complex Ecosystems brings a whole new set of tools from statistical physics into the realm of studying ecological systems. Most, if not all, of these tools have been floating around the ecological literature for quite some time, in great part due to these authors themselves, but this book is the best overview yet. It will soon become the foundation for many courses and a major resource sitting on ecologists' bookshelves."--Will Wilson, Duke University

"This book is an outstandingly good summary of where we currently stand in the field of ecology. It draws together, in a clear and synoptic way, a large variety of new ideas and supporting them where possible and appropriate by data."--Robert M. May, University of Oxford0List of Figures and Tables xi
Acknowledgments xv

Chapter 1: Complexity in Ecological Systems 1
The Newtonian Paradigm in Physics 2
Dynamics and Thermodynamics 6
Emergent Properties 10
Ecosystems as Complex Adaptive Systems 13

Chapter 2: Nonlinear Dynamics 17
The Balance of Nature?17
Population Cycles 19
Catastrophes and Breakpoints 27
Deterministic Chaos 31
Evidence of Bifurcations in Nature 34
Unpredictability and Forecasting 42
The Ecology of Universality 48
Evidence of Chaos in Nature 50
Criticisms of Chaos 58
Complex Dynamics:The Interplay between Noise and Nonlinearities 61

Chapter 3: Spatial Self-Organization:From Pattern to Process 65
Space:The Missing Ingredient 65
Turing Instabilities 68
Coupled Map Lattice Models 84
Looking for Self-Organizing Spatial Patterns in Nature 95
Dispersal and Complex Dynamics 98
Spatial Synchrony in Population Cycles 108
When Is Space Relevant?A Trade-Off between Simplicity and Realism 117
Coevolution and Diffusion in Phenotype Space 123

Chapter 4: Scaling and Fractals in Ecology 127
Scaling and Fractals 127
Fractal Time Series 137
Percolation 139
Nonequilibrium Phase Transitions 144
The Branching Process 146
The Contact Process:Complexity Made Simple 149
Random Walks and Levy Flights in Population Dynamics 151
Percolation and Scaling in Random Graphs 156
Ecological Multifractals 162
Self-Organized Critical Phenomena 165
Complexity from Simplicity 168

Chapter 5: Habitat Loss and Extinction Thresholds 171
Habitat Loss and Fragmentation 171
Extinction Thresholds in Metapopulation Models 173
Extinction Thresholds in Metacommunity Models 178
Food Web Structure and Habitat Loss 186
Percolation in Spatially Explicit Landscapes 191
Extinction Thresholds in Spatially Explicit Models 195
Analytical Models of Correlated Landscapes 199
More Realistic Models of Extinction Thresholds 206

Chapter 6: Complex Ecosystems:From Species to Networks 215
Stability and Complexity 215
N-Species Lotka-Volterra Models 218
Topological and Dynamic Constraints 223
Indirect Effects 226
Keystone Species and Evolutionary Dynamics 231
Complexity and Fragility in Food Webs 237
Community Assembly:The Importance of History 251
Scaling in Ecosystems:A Stochastic Quasi-Neutral Model 254

Chapter 7: Complexity in Macroevolution 263
Extinction and Diversification 263
Internal and External Factors 264
Scaling in the Fossil Recor 270
Competition and the Fossil Recor 276
Red Queen Dynamics 279
Evolution on Fitness Landscapes 282
Extinctions and Coherent Noise 292
NetworkModels of Macroevolution 295
Ecology as It Would Be: Artificial Life 304
Recovery after Mass Extinction 308
Implications for Current Ecologies 313

Appendix 1.Lyapunov Exponents for ID Maps 317
Appendix 2.Renormalization Group Analysis 319
Appendix 3.Stochastic Multispecies Model 321

References 325
Index 359