Self-organization in complex ecosystems

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.

Author Notes

Ricard V. Sole is Professor of Research at the Catalan Institute for Research and Advanced Studies in Spain, head of the Complex Systems Lab at Universitat Pompeu Fabra in Barcelona, external professor at the Santa Fe Institute, and Senior Member of the NASA-Associate Center of Astrobiology
Jordi Bascompte is Associate Professor of Research at the Spanish Research Council, and a Visiting Scientist at the National Center for Ecological Analysis and Synthesis at the University of California, Santa Barbara

List of Figures and Tables	p. xi
Acknowledgments	p. xv
1 Complexity in Ecological Systems	p. 1
The Newtonian Paradigm in Physics	p. 2
Dynamics and Thermodynamics	p. 6
Emergent Properties	p. 10
Ecosystems as Complex Adaptive Systems	p. 13
2 Nonlinear Dynamics	p. 17
The Balance of Nature?	p. 17
Population Cycles	p. 19
Catastrophes and Breakpoints	p. 27
Deterministic Chaos	p. 31
Evidence of Bifurcations in Nature	p. 34
Unpredictability and Forecasting	p. 42
The Ecology of Universality	p. 48
Evidence of Chaos in Nature	p. 50
Criticisms of Chaos	p. 58
Complex Dynamics: The Interplay between Noise and Nonlinearities	p. 61
3 Spatial Self-Organization: From Pattern to Process	p. 65
Space: The Missing Ingredient	p. 65
Turing Instabilities	p. 68
Coupled Map Lattice Models	p. 84
Looking for Self-Organizing Spatial Patterns in Nature	p. 95
Dispersal and Complex Dynamics	p. 98
Spatial Synchrony in Population Cycles	p. 108
When Is Space Relevant? A Trade-Off between Simplicity and Realism	p. 117
Coevolution and Diffusion in Phenotype Space	p. 123
4 Scaling and Fractals in Ecology	p. 127
Scaling and Fractals	p. 127
Fractal Time Series	p. 137
Percolation	p. 139
Nonequilibrium Phase Transitions	p. 144
The Branching Process	p. 146
The Contact Process: Complexity Made Simple	p. 149
Random Walks and Levy Flights in Population Dynamics	p. 151
Percolation and Scaling in Random Graphs	p. 156
Ecological Multifractals	p. 162
Self-Organized Critical Phenomena	p. 165
Complexity from Simplicity	p. 168
5 Habitat Loss and Extinction Thresholds	p. 171
Habitat Loss and Fragmentation	p. 171
Extinction Thresholds in Metapopulation Models	p. 173
Extinction Thresholds in Metacommunity Models	p. 178
Food Web Structure and Habitat Loss	p. 186
Percolation in Spatially Explicit Landscapes	p. 191
Extinction Thresholds in Spatially Explicit Models	p. 195
Analytical Models of Correlated Landscapes	p. 199
More Realistic Models of Extinction Thresholds	p. 206
6 Complex Ecosystems: From Species to Networks	p. 215
Stability and Complexity	p. 215
N-Species Lotka-Volterra Models	p. 218
Topological and Dynamic Constraints	p. 223
Indirect Effects	p. 226
Keystone Species and Evolutionary Dynamics	p. 231
Complexity and Fragility in Food Webs	p. 237
Community Assembly: The Importance of History	p. 251
Scaling in Ecosystems: A Stochastic Quasi-Neutral Model	p. 254
7 Complexity in Macroevolution	p. 263
Extinction and Diversification	p. 263
Internal and External Factors	p. 264
Scaling in the Fossil Record	p. 270
Competition and the Fossil Record	p. 276
Red Queen Dynamics	p. 279
Evolution on Fitness Landscapes	p. 282
Extinctions and Coherent Noise	p. 292
Network Models of Macroevolution	p. 295
Ecology as It Would Be: Artificial Life	p. 304
Recovery after Mass Extinction	p. 308
Implications for Current Ecologies	p. 313
Appendix 1 Lyapunov Exponents for ID Maps	p. 317
Appendix 2 Renormalization Group Analysis	p. 319
Appendix 3 Stochastic Multispecies Model	p. 321
References	p. 325
Index	p. 359

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Table of Contents