Individual-based Modeling and Ecology
1st Edition
Published on 16. June 2015
448 pages
978-1-4008-5062-4 (ISBN)
Description
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.
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.
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More details
Edition
Course Book
Language
English
Place of publication
Princeton, NJ
United States
Publishing group
De Gruyter
Target group
Professional and scholarly
Edition type
Digital original
Product notice
Reflowable
Illustrations
12 halftones. 34 line illus. 3 tables.
File size
2,41 MB
ISBN-13
978-1-4008-5062-4 (9781400850624)
Schweitzer Classification
Other editions
Additional editions
Volker Grimm | Steven F. Railsback
Individual-based Modeling and Ecology
Book
08/2005
Princeton University Press
€117.80
Article exhausted; check different version
Volker Grimm | Steven F. Railsback
Individual-based Modeling and Ecology
Book
07/2005
Princeton University Press
€82.70
Shipment within 10-20 days
Persons
Volker Grimm is a Senior Researcher at the UFZ Centre for Environmental Research Leipzig-Halle and Lecturer at the University of Potsdam. Steven F. Railsback is a consulting scientist and Adjunct Professor of Mathematics at Humboldt State University.
Content
Preface xi
Acknowledgments xv
PART 1.MODELING 1
Chapter 1. Introduction 3
1.1 Why Individual-based Modeling and Ecology? 3
1.2 Linking Individual Traits and System Complexity: Three Examples 5
1.3 Individual-based Ecology 9
1.4 Early IBMs and Their Research Programs 11
1.5 What Makes a Model an IBM? 13
1.6 Status and Challenges of the Individual-based Approach 15
1.7 Conclusions and Outlook 19
Chapter 2. A Primer to Modeling 22
2.1 Introduction 22
2.2 Heuristics for Modeling 24
2.3 The Modeling Cycle 27
2.4 Summary and Discussion 36
Chapter 3. Pattern-oriented Modeling 38
3.1 Introduction 38
3.2 Why Patterns, and What Are Patterns? 40
3.3 The Tasks of Pattern-oriented Modeling 41
3.4 Discussion 48
PART 2.INDIVIDUAL-BASED ECOLOGY 51
Chapter 4. Theory in Individual-based Ecology 53
4.1 Introduction 53
4.2 Basis for Theory in IBE 55
4.3 Goals of IBE Theory 56
4.4 Theory Structure 58
4.5 Theory Development Cycle 60
4.6 Example: Development of Habitat Selection Theory for Trout 63
4.7 Summary and Discussion 68
Chapter 5. A Conceptual Framework for Designing Individual-based Models 71
5.1 Introduction 71
5.2 Emergence 73
5.3 Adaptive Traits and Behavior 79
5.4 Fitness 84
5.5 Prediction 91
5.6 Interaction 95
5.7 Sensing 98
5.8 Stochasticity 101
5.9 Collectives 105
5.10 Scheduling 109
5.11 Observation 116
5.12 Summary and Conclusions 117
5.13 Conceptual Design Checklist 119
Chapter 6. Examples 122
6.1 Introduction 122
6.2 Group and Social Behavior 125
6.3 Population Dynamics of Social Animals 145
6.4 Movement: Dispersal and Habitat Selection 163
6.5 Regulation of Hypothetical Populations 178
6.6 Comparison with Classical Models 187
6.7 Dynamics of Plant Populations and Communities 199
6.8 Structure of Communities and Ecosystems 218
6.9 Artificially Evolved Traits 234
6.10 Summary and Conclusions 242
PART 3.THE ENGINE ROOM 245
Chapter 7. Formulating Individual-based Models 247
7.1 Introduction 247
7.2 Contents of an IBM Formulation 248
7.3 Formulating an IBM's Spatial Elements 249
7.4 Formulating Logical and Probabilistic Rules 253
7.5 Formulating Adaptive Traits 255
7.6 Controlling Uncertainty 260
7.7 Using Object-oriented Design and Description 262
7.8 Using Mechanistic and Discrete Mathematics 264
7.9 Designing Superindividuals 266
7.10 Summary and Conclusions 269
Chapter 8. Software for Individual-based Models 270
8.1 Introduction 270
8.2 The Importance of Software Design for IBMs 273
8.3 Software Terminology and Concepts 274
8.4 Software Platforms 279
8.5 Software Testing 288
8.6 Moving Software Development Forward 294
8.7 Important Implementation Techniques 301
8.8 Some Favorite Software Myths 306
8.9 Summary and Conclusions 308
Chapter 9. Analyzing Individual-based Models 312
9.1 Introduction 312
9.2 Steps in Analyzing an IBM 313
9.3 General Strategies for Analyzing IBMs 315
9.4 Techniques for Analyzing IBMs 319
9.5 Statistical Analysis 327
9.6 Sensitivity and Uncertainty Analysis 335
9.7 Robustness Analysis 336
9.8 Parameterization 341
9.9 Independent Predictions 345
9.10 Summary and Conclusions 346
Chapter 10. Communicating Individual-based Models and Research 349
10.1 Introduction 349
10.2 Types of IBE Work to Communicate 350
10.3 Complete and Efficient Model Description 351
10.4 Common Review Comments 354
10.5 Visual Communication of Executable Models 356
10.6 Communicating Software 358
10.7 Summary and Conclusions 359
PART 4.CONCLUSIONS AND OUTLOOK 363
Chapter 11. Using Analytical Models in Individual-based Ecology 365
11.1 Introduction 365
11.2 Classifications of Ecological Models 366
11.3 Benefits of Analytical Models 368
11.4 Analytical Approximation of IBMs 369
11.5 Using Analytical Models to Understand and Analyze IBMs 372
11.6 Summary and Discussion 379
Chapter 12. Conclusions and Outlook for Individual-based Ecology 380
12.1 Introduction 380
12.2 Why Do We Need IBE? 381
12.3 How Is IBE Different From Traditional Ecology? 382
12.4 What Can Ecology Contribute to the Science of Complex Systems? 387
12.5 A Visit to the Individual-based Ecology Laboratory 388
Glossary 391
References 395
Index 421
Acknowledgments xv
PART 1.MODELING 1
Chapter 1. Introduction 3
1.1 Why Individual-based Modeling and Ecology? 3
1.2 Linking Individual Traits and System Complexity: Three Examples 5
1.3 Individual-based Ecology 9
1.4 Early IBMs and Their Research Programs 11
1.5 What Makes a Model an IBM? 13
1.6 Status and Challenges of the Individual-based Approach 15
1.7 Conclusions and Outlook 19
Chapter 2. A Primer to Modeling 22
2.1 Introduction 22
2.2 Heuristics for Modeling 24
2.3 The Modeling Cycle 27
2.4 Summary and Discussion 36
Chapter 3. Pattern-oriented Modeling 38
3.1 Introduction 38
3.2 Why Patterns, and What Are Patterns? 40
3.3 The Tasks of Pattern-oriented Modeling 41
3.4 Discussion 48
PART 2.INDIVIDUAL-BASED ECOLOGY 51
Chapter 4. Theory in Individual-based Ecology 53
4.1 Introduction 53
4.2 Basis for Theory in IBE 55
4.3 Goals of IBE Theory 56
4.4 Theory Structure 58
4.5 Theory Development Cycle 60
4.6 Example: Development of Habitat Selection Theory for Trout 63
4.7 Summary and Discussion 68
Chapter 5. A Conceptual Framework for Designing Individual-based Models 71
5.1 Introduction 71
5.2 Emergence 73
5.3 Adaptive Traits and Behavior 79
5.4 Fitness 84
5.5 Prediction 91
5.6 Interaction 95
5.7 Sensing 98
5.8 Stochasticity 101
5.9 Collectives 105
5.10 Scheduling 109
5.11 Observation 116
5.12 Summary and Conclusions 117
5.13 Conceptual Design Checklist 119
Chapter 6. Examples 122
6.1 Introduction 122
6.2 Group and Social Behavior 125
6.3 Population Dynamics of Social Animals 145
6.4 Movement: Dispersal and Habitat Selection 163
6.5 Regulation of Hypothetical Populations 178
6.6 Comparison with Classical Models 187
6.7 Dynamics of Plant Populations and Communities 199
6.8 Structure of Communities and Ecosystems 218
6.9 Artificially Evolved Traits 234
6.10 Summary and Conclusions 242
PART 3.THE ENGINE ROOM 245
Chapter 7. Formulating Individual-based Models 247
7.1 Introduction 247
7.2 Contents of an IBM Formulation 248
7.3 Formulating an IBM's Spatial Elements 249
7.4 Formulating Logical and Probabilistic Rules 253
7.5 Formulating Adaptive Traits 255
7.6 Controlling Uncertainty 260
7.7 Using Object-oriented Design and Description 262
7.8 Using Mechanistic and Discrete Mathematics 264
7.9 Designing Superindividuals 266
7.10 Summary and Conclusions 269
Chapter 8. Software for Individual-based Models 270
8.1 Introduction 270
8.2 The Importance of Software Design for IBMs 273
8.3 Software Terminology and Concepts 274
8.4 Software Platforms 279
8.5 Software Testing 288
8.6 Moving Software Development Forward 294
8.7 Important Implementation Techniques 301
8.8 Some Favorite Software Myths 306
8.9 Summary and Conclusions 308
Chapter 9. Analyzing Individual-based Models 312
9.1 Introduction 312
9.2 Steps in Analyzing an IBM 313
9.3 General Strategies for Analyzing IBMs 315
9.4 Techniques for Analyzing IBMs 319
9.5 Statistical Analysis 327
9.6 Sensitivity and Uncertainty Analysis 335
9.7 Robustness Analysis 336
9.8 Parameterization 341
9.9 Independent Predictions 345
9.10 Summary and Conclusions 346
Chapter 10. Communicating Individual-based Models and Research 349
10.1 Introduction 349
10.2 Types of IBE Work to Communicate 350
10.3 Complete and Efficient Model Description 351
10.4 Common Review Comments 354
10.5 Visual Communication of Executable Models 356
10.6 Communicating Software 358
10.7 Summary and Conclusions 359
PART 4.CONCLUSIONS AND OUTLOOK 363
Chapter 11. Using Analytical Models in Individual-based Ecology 365
11.1 Introduction 365
11.2 Classifications of Ecological Models 366
11.3 Benefits of Analytical Models 368
11.4 Analytical Approximation of IBMs 369
11.5 Using Analytical Models to Understand and Analyze IBMs 372
11.6 Summary and Discussion 379
Chapter 12. Conclusions and Outlook for Individual-based Ecology 380
12.1 Introduction 380
12.2 Why Do We Need IBE? 381
12.3 How Is IBE Different From Traditional Ecology? 382
12.4 What Can Ecology Contribute to the Science of Complex Systems? 387
12.5 A Visit to the Individual-based Ecology Laboratory 388
Glossary 391
References 395
Index 421
