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Individual based Modeling and Ecology 1st Edition by Volker Grimm, Steven F Railsback ISBN 1400850622 9781400850624

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Author(s): Volker Grimm; Steven F. Railsback
ISBN(s): 9781400850624, 1400850622
Edition: Course Book
File Details: PDF, 2.36 MB
Year: 2013
Language: english
SKU: EB-51950116 Category: Tags: ,

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ISBN 10: 1400850622
ISBN 13: 9781400850624
Author: Volker Grimm, Steven F Railsback

Individual-based models are an exciting and widely used new tool for ecology. These computational models allow scientists to explore the mechanisms through which population and ecosystem ecology arises from how individuals interact with each other and their environment. This book provides the first in-depth treatment of individual-based modeling and its use to develop theoretical understanding of how ecological systems work, an approach the authors call “individual-based ecology.? Grimm and Railsback start with a general primer on modeling: how to design models that are as simple as possible while still allowing specific problems to be solved, and how to move efficiently through a cycle of pattern-oriented model design, implementation, and analysis. Next, they address the problems of theory and conceptual framework for individual-based ecology: What is “theory”? That is, how do we develop reusable models of how system dynamics arise from characteristics of individuals? What conceptual framework do we use when the classical differential equation framework no longer applies? An extensive review illustrates the ecological problems that have been addressed with individual-based models. The authors then identify how the mechanics of building and using individual-based models differ from those of traditional science, and provide guidance on formulating, programming, and analyzing models. This book will be helpful to ecologists interested in modeling, and to other scientists interested in agent-based modeling.

Individual based Modeling and Ecology 1st Table of contents:

PART 1: MODELING

Chapter 1: Introduction

  • 1.1 Why Individual-based Modeling and Ecology?

  • 1.2 Linking Individual Traits and System Complexity: Three Examples

  • 1.3 Individual-based Ecology

  • 1.4 Early IBMs and Their Research Programs

  • 1.5 What Makes a Model an IBM?

  • 1.6 Status and Challenges of the Individual-based Approach

  • 1.7 Conclusions and Outlook

Chapter 2: A Primer to Modeling

  • 2.1 Introduction

  • 2.2 Heuristics for Modeling

  • 2.3 The Modeling Cycle

  • 2.4 Summary and Discussion

Chapter 3: Pattern-oriented Modeling

  • 3.1 Introduction

  • 3.2 Why Patterns, and What Are Patterns?

  • 3.3 The Tasks of Pattern-oriented Modeling

  • 3.4 Discussion

PART 2: INDIVIDUAL-BASED ECOLOGY

Chapter 4: Theory in Individual-based Ecology

  • 4.1 Introduction

  • 4.2 Basis for Theory in IBE

  • 4.3 Goals of IBE Theory

  • 4.4 Theory Structure

  • 4.5 Theory Development Cycle

  • 4.6 Example: Development of Habitat Selection Theory for Trout

  • 4.7 Summary and Discussion

Chapter 5: A Conceptual Framework for Designing Individual-based Models

  • 5.1 Introduction

  • 5.2 Emergence

  • 5.3 Adaptive Traits and Behavior

  • 5.4 Fitness

  • 5.5 Prediction

  • 5.6 Interaction

  • 5.7 Sensing

  • 5.8 Stochasticity

  • 5.9 Collectives

  • 5.10 Scheduling

  • 5.11 Observation

  • 5.12 Summary and Conclusions

  • 5.13 Conceptual Design Checklist

Chapter 6: Examples

  • 6.1 Introduction

  • 6.2 Group and Social Behavior

  • 6.3 Population Dynamics of Social Animals

  • 6.4 Movement: Dispersal and Habitat Selection

  • 6.5 Regulation of Hypothetical Populations

  • 6.6 Comparison with Classical Models

  • 6.7 Dynamics of Plant Populations and Communities

  • 6.8 Structure of Communities and Ecosystems

  • 6.9 Artificially Evolved Traits

  • 6.10 Summary and Conclusions

PART 3: THE ENGINE ROOM

Chapter 7: Formulating Individual-based Models

  • 7.1 Introduction

  • 7.2 Contents of an IBM Formulation

  • 7.3 Formulating an IBM’s Spatial Elements

  • 7.4 Formulating Logical and Probabilistic Rules

  • 7.5 Formulating Adaptive Traits

  • 7.6 Controlling Uncertainty

  • 7.7 Using Object-oriented Design and Description

  • 7.8 Using Mechanistic and Discrete Mathematics

  • 7.9 Designing Superindividuals

  • 7.10 Summary and Conclusions

Chapter 8: Software for Individual-based Models

  • 8.1 Introduction

  • 8.2 The Importance of Software Design for IBMs

  • 8.3 Software Terminology and Concepts

  • 8.4 Software Platforms

  • 8.5 Software Testing

  • 8.6 Moving Software Development Forward

  • 8.7 Important Implementation Techniques

  • 8.8 Some Favorite Software Myths

  • 8.9 Summary and Conclusions

Chapter 9: Analyzing Individual-based Models

  • 9.1 Introduction

  • 9.2 Steps in Analyzing an IBM

  • 9.3 General Strategies for Analyzing IBMs

  • 9.4 Techniques for Analyzing IBMs

  • 9.5 Statistical Analysis

  • 9.6 Sensitivity and Uncertainty Analysis

  • 9.7 Robustness Analysis

  • 9.8 Parameterization

  • 9.9 Independent Predictions

  • 9.10 Summary and Conclusions

Chapter 10: Communicating Individual-based Models and Research

  • 10.1 Introduction

  • 10.2 Types of IBE Work to Communicate

  • 10.3 Complete and Efficient Model Description

  • 10.4 Common Review Comments

  • 10.5 Visual Communication of Executable Models

  • 10.6 Communicating Software

  • 10.7 Summary and Conclusions

PART 4: CONCLUSIONS AND OUTLOOK

Chapter 11: Using Analytical Models in Individual-based Ecology

  • 11.1 Introduction

  • 11.2 Classifications of Ecological Models

  • 11.3 Benefits of Analytical Models

  • 11.4 Analytical Approximation of IBMs

  • 11.5 Using Analytical Models to Understand and Analyze IBMs

  • 11.6 Summary and Discussion

Chapter 12: Conclusions and Outlook for Individual-based Ecology

  • 12.1 Introduction

  • 12.2 Why Do We Need IBE?

  • 12.3 How Is IBE Different From Traditional Ecology?

  • 12.4 What Can Ecology Contribute to the Science of Complex Systems?

  • 12.5 A Visit to the Individual-based Ecology Laboratory

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Tags: Volker Grimm, Steven F Railsback, Individual, Modeling