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Self-Organization in Complex Ecosystems. (MPB-42)

โœ Scribed by Ricard Solรฉ; Jordi Bascompte


Publisher
Princeton University Press
Year
2012
Tongue
English
Leaves
391
Series
Monographs in Population Biology; 42
Edition
Course Book
Category
Library

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โœฆ Synopsis


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 Solรฉ 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.

โœฆ Table of Contents


Contents
List of Figures and Tables
Acknowledgments
CHAPTER ONE. Complexity in Ecological Systems
CHAPTER TWO. Nonlinear Dynamics
CHAPTER THREE. Spatial Self-Organization. From Pattern to Process
CHAPTER FOUR. Scaling and Fractals in Ecology
CHAPTER FIVE. Habitat Loss and Extinction Thresholds
CHAPTER SIX. Complex Ecosystems From Species to Networks
CHAPTER SEVEN. Complexity in Macroevolution
Appendix 1. Lyapunov Exponents for ID Maps
Appendix 2. Renormalization Group Analysis
Appendix 3. Stochastic Multispecies Model
References
Index


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Resolving Ecosystem Complexity (MPB-47)
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