Understanding Complex Ecosystem Dynamics - 1st Edition - ISBN: 9780128020319, 9780128020630

Understanding Complex Ecosystem Dynamics

1st Edition

A Systems and Engineering Perspective

Authors: William S. Yackinous
eBook ISBN: 9780128020630
Paperback ISBN: 9780128020319
Imprint: Academic Press
Published Date: 17th June 2015
Page Count: 436
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Understanding Complex Ecosystem Dynamics: A Systems and Engineering Perspective takes a fresh, interdisciplinary perspective on complex system dynamics, beginning with a discussion of relevant systems and engineering skills and practices, including an explanation of the systems approach and its major elements. From this perspective, the author formulates an ecosystem dynamics functionality-based framework to guide ecological investigations.

Next, because complex system theory (across many subject matter areas) is crucial to the work of this book, relevant network theory, nonlinear dynamics theory, cellular automata theory, and roughness (fractal) theory is covered in some detail. This material serves as an important resource as the book proceeds. In the context of all of the foregoing discussion and investigation, a view of the characteristics of ecological network dynamics is constructed. This view, in turn, is the basis for the central hypothesis of the book, i.e., ecological networks are ever-changing networks with propagation dynamics that are punctuated, local-to-global, and perhaps most importantly fractal. To analyze and fully test this hypothesis, an innovative ecological network dynamics model is defined, designed, and developed. The modeling approach, which seeks to emulate features of real-world ecological networks, does not make a priori assumptions about ecological network dynamics, but rather lets the dynamics develop as the model simulation runs. Model analysis results corroborate the central hypothesis. Additional important insights and principles are suggested by the model analysis results and by the other supporting investigations of this book – and can serve as a basis for going-forward complex system dynamics research, not only for ecological systems but for complex systems in general.

Key Features

  • Provides a fresh interdisciplinary perspective, offers a broad integrated development, and contains many new ideas
  • Clearly explains the elements of the systems approach and applies them throughout the book
  • Takes on the challenging and open issues of complex system network dynamics
  • Develops and utilizes a new, innovative ecosystem dynamics modeling approach
  • Contains over 135 graphic illustrations to help the reader visualize and understand important concepts


systems ecologists, systems biologists, network analysts, ecological modelers, systems engineers, and ecological engineers

Table of Contents

  • Preface
  • Introduction
    • “Map” of the Book
    • A “Fresh” Look at Complex System Dynamics
  • Part I: The Systems and Engineering Perspective
    • Introduction
    • Chapter 1: A Systems Engineer’s Perspective
      • Abstract
      • 1.1 Introduction
      • 1.2 Definitions
      • 1.3 Systems Engineering Skills Framework
      • 1.4 Technical Rationality and Reflective Rationality
    • Chapter 2: More Views on Systems Thinking
      • Abstract
      • 2.1 Origin and Evolution of Systems Thinking Movements
      • 2.2 Weaver’s Ranges of System Complexity
      • 2.3 The Many Ways of Knowing
      • 2.4 A Debate on the Integration of the Sciences and the Humanities
    • Chapter 3: The Major Elements of the Systems Approach
      • Abstract
      • 3.1 A Blend of Synthesis and Analysis
      • 3.2 Network Thinking
      • 3.3 The Systems Triad
    • Chapter 4: Reductionism and Information Loss
      • Abstract
      • 4.1 Introduction
      • 4.2 Networks and Connections
      • 4.3 Short Paths and Power-Law Distributions
      • 4.4 Information Theory
      • 4.5 Information Loss from Broken Connections
  • Part II: A Function-Structure-Process Framework for Ecological System Dynamics
    • Introduction
    • Chapter 5: Overview of an Ecological System Dynamics Framework
      • Abstract
      • 5.1 Two Essential Questions
      • 5.2 Developing the Framework
      • 5.3 The Three Core Functions of the Framework
      • 5.4 Self-organization and Thermodynamic Entropy in Ecological Systems
    • Chapter 6: Regulation/Adaptation: Control Aspects of Ecological Systems
      • Abstract
      • 6.1 Introduction
      • 6.2 General Principles and Control of Human-Made Systems
      • 6.3 Control of Biological/Ecological Systems
      • 6.4 Core Function Relationships and the Nature of the Resulting Dynamics
    • Chapter 7: Evolution and Universal Development Concepts
      • Abstract
      • 7.1 Evolution: Spatial and Temporal Perspectives
      • 7.2 Formulating an Evolution Process Model
      • 7.3 The Evolution Model as a Universal Development Model
      • 7.4 Summary Observations and the Path Forward
  • Part III: Complex Systems Theory: Networks, Nonlinear Dynamics, Cellular Automata, and Fractals (Roughness)
    • Introduction
    • Chapter 8: Network Theory: The Structure of Complex Networks
      • Abstract
      • 8.1 Network Structure Concepts, Properties, and Characteristics
      • 8.2 Empirical View of Real-World Networks
      • 8.3 Theoretical View of Model Networks
    • Chapter 9: Network Theory: The Dynamics of Complex Networks
      • Abstract
      • 9.1 Introduction
      • 9.2 Scaling, Power Laws, and Fractals
      • 9.3 The Dynamics of Network Phase Transitions
      • 9.4 Network Dynamics: Processes Taking Place on Networks
      • 9.5 Concluding Remarks
    • Chapter 10: Fundamentals of Nonlinear Dynamics
      • Abstract
      • 10.1 Introduction
      • 10.2 Fundamental Concepts
      • 10.3 Starting Simple
      • 10.4 Types of Attractors
      • 10.5 Bifurcation and Complex Nonlinear Behavior
      • 10.6 Unpredictability
      • 10.7 Universality
    • Chapter 11: Cellular Automata Investigations and Emerging Complex System Principles
      • Abstract
      • 11.1 Introduction
      • 11.2 Some Cellular Automata History
      • 11.3 Explicit Experimentation via Cellular Automata
      • 11.4 Simple Programs/Simple Rules and Highly Complex Behavior
      • 11.5 Cellular Automata Classes
      • 11.6 All Kinds of Systems
      • 11.7 A Computational View of Systems
      • 11.8 The Principle of Computational Equivalence
      • 11.9 Summary of My Perspectives on these Complex System Principles
    • Chapter 12: Fractals: The Theory of Roughness
      • Abstract
      • 12.1 Introduction
      • 12.2 Fractals and Roughness
      • 12.3 Fractal Geometry
      • 12.4 The Mandelbrot Set
      • 12.5 My Perspectives
  • Part IV: A View of the Characteristics of Ecological Network Dynamics
    • Introduction
    • Chapter 13: Issues of Human Perception
      • Abstract
      • 13.1 Introduction
      • 13.2 Is Reality Knowable?
      • 13.3 Limitations of Human Perception
      • 13.4 Roughness versus Smoothness
      • 13.5 Modeling and Human Perception
    • Chapter 14: The Nature of Order and Complexity in Ecological Systems
      • Abstract
      • 14.1 Introduction
      • 14.2 Thinking about Order, Complexity, and Systems
      • 14.3 The Myth of Persistence
      • 14.4 Chance and Change: Probabilistic Aspects of Natural Systems
      • 14.5 Optimal or Good Enough?
    • Chapter 15: Characteristics of Ecological Network Dynamics
      • Abstract
      • 15.1 Introduction
      • 15.2 Flickering Networks
      • 15.3 Punctuated Dynamics
      • 15.4 Fractal Behavior
      • 15.5 Local-to-Global Interaction
      • 15.6 Indirect Effects
      • 15.7 The Characteristics Hypothesis
  • Part V: Modeling Ecological Network Dynamics and the Generation and Analysis of Results
    • Introduction
    • Chapter 16: A New Approach to Modeling Ecological Network Dynamics
      • Abstract
      • 16.1 Introduction
      • 16.2 Overview of Model Features
      • 16.3 Cellular Automata Based Model
      • 16.4 Propagation Neighborhoods and Preferences
      • 16.5 Underlying Ecological Network Compartment Model
      • 16.6 Simple Rules
      • 16.7 Summary of Analysis Requirements
      • 16.8 Comment on Intention
    • Chapter 17: Model Software Design and Development
      • Abstract
      • 17.1 Introduction
      • 17.2 Model Network Structure, Parameters, and Relationships
      • 17.3 Ecological Network Propagation Process
      • 17.4 Analysis Activities
      • 17.5 Graphics Generation
      • 17.6 A Note about Results
    • Chapter 18: Ecological Network Dynamics Results
      • Abstract
      • 18.1 Introduction
      • 18.2 Operational Propagation Flow Results
      • 18.3 Network Propagation Event Results
      • 18.4 Path Length Results
      • 18.5 Indirect Effects Results
      • 18.6 Network Connectivity Results
  • Part VI: Pulling It All Together
    • Introduction
    • Chapter 19: An Increased Understanding of Complex System Dynamics
      • Abstract
      • 19.1 Summary of the Work
      • 19.2 An Advantageous Perspective
      • 19.3 The Mechanism of Complexity
      • 19.4 The Characteristics of Complex Ecosystem Dynamics
      • 19.5 Complex System Universal Behavior
      • 19.6 A Going-Forward Integrated View of Complex System Dynamics
  • Appendix: Selections from the Dynamics Model Programming Code
    • Code Example 1
    • Code Example 2
    • Code Example 3
    • Code Example 4
    • Code Example 5
    • Code Example 6
    • Code Example 7
    • Code Example 8
    • Code Example 9
  • References
  • Index


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© Academic Press 2015
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About the Author

William S. Yackinous

Bill Yackinous has had a distinguished 34-year career as a systems engineer at Bell Laboratories. Throughout his career he worked to solve systems problems for Bell Labs and for its clients - both domestically and internationally. Bill has earned the highest technical honors at Bell Labs. He was named a Distinguished Member of Technical Staff in 1986, a Bell Labs Fellow in 1992, and a Consulting Member of Technical Staff in 2000. Bell Labs Fellow is the most prestigious technical honor at Bell Labs - and among the most prestigious across research and development institutions throughout the world.

At Bell Labs, Bill acquired a very significant breadth and depth of systems and engineering knowledge. He made important and innovative contributions to systems thinking and engineering system development. Bill’s global perspective has taken him around the world - supporting the local Bell Labs teams and their clients. He has served as a systems engineering consultant for both executive-level and working-level groups in Japan, England, Malaysia, France, and Canada.

After earning a PhD in Ecology at the University of Georgia’s Eugene P. Odum School of Ecology, Bill is now pursuing his goal of beneficially applying the skills, perspectives, methods, and techniques of the systems approach and systems engineering to increase understanding of complex ecological systems.

Affiliations and Expertise

Retired Systems Engineer, Bell Labs, US

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