
Modeling Populations of Adaptive Individuals
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Modeling Populations of Adaptive Individuals features a wealth of examples that range from highly simplified behavior models to complex population models in which individuals make adaptive trade-off decisions about habitat and activity selection in highly heterogeneous environments. Steven Railsback and Bret Harvey explain how SPT builds on key concepts from the state-based dynamic modeling theory of behavioral ecology, and how it combines explicit predictions of future conditions with approximations of a fitness measure to represent how individuals make good-not optimal-decisions that they revise as conditions change. The resulting models are realistic, testable, adaptable, and invaluable for answering fundamental questions in ecology and forecasting ecological outcomes of real-world scenarios.
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Content
- Cover
- Title
- Copyright
- Dedication
- Contents
- Preface
- Acknowledgments
- 1. Adaptive Individuals and Population Ecology
- 1.1 Adaptive Trade-Off Behavior and Ecology
- 1.2 Modeling Systems of Adaptive Individuals
- 1.3 Adaptive Behavior in Individual-Based Models
- 1.4 Adaptive Behavior, Physiology, and Neurobiology
- 1.5 What We Need to Link Behavioral and Population Ecology: Across-Level Theory
- 1.6 State-and Prediction-Based Theory (SPT)
- 1.7 Monograph Objectives and Overview
- 2. Case Study: Modeling Trout Population Response to River Management
- 2.1 Introduction and Model Purpose
- 2.2 Adaptive Behavior in the Trout Model: Habitat Selection
- 2.3 A Second Adaptive Behavior: Activity Selection
- 2.4 Conclusions
- 3. Introduction to State- and Prediction-Based Theory
- 3.1 What Is SPT?
- 3.2 Five Steps for Implementing SPT
- 3.3 A Look Ahead
- 4. A First Example: Forager Patch Selection
- 4.1 Objectives
- 4.2 The Model
- 4.3 Results and Comparison of SPT to Dynamic State Variable Modeling
- 4.4 Version 2: Foraging with Competition
- 4.5 Version 3: Continuous Starvation Risk
- 4.6 Conclusions
- 5. A Second Example: Vertical Migration and Reproductive Effort in Daphnia
- 5.1 Objectives
- 5.2 The Model
- 5.3 SPT Version 1: Expected Future Reproduction with Current Growth and Survival
- 5.4 SPT Version 2: Predicted Offspring
- 5.5 SPT Version 3: Diurnal Prediction
- 5.6 Prediction Complexity and Fitness: Population Simulations
- 5.7 Conclusions
- 6. Example Three: Temporal Patterns in Limpet Foraging
- 6.1 Background and Objectives
- 6.2 The DSVM Model of Limpet Foraging
- 6.3 The Model
- 6.4 SPT Version 1: Maximizing Short-Term Expected Energy Reserves
- 6.5 SPT Version 2: Maximizing Mean Expected Energy Reserves until Day's End
- 6.6 Conclusions
- 7. Example Four: Facultative Anadromy in Salmonid Fishes
- 7.1 Introduction and Objectives
- 7.2 The DSVM Model
- 7.3 The IBM Using SPT
- 7.4 SPT Model Results and Applications
- 8. Guidance for Using State- and Prediction-Based Theory
- 8.1 Introduction and Objectives
- 8.2 Step 1: Defining the Decision That SPT Models
- 8.3 Step 2: Selecting Fitness Measures and Time Horizons
- 8.4 Step 3: Modeling Prediction of Environmental Conditions and Fitness Elements
- 8.4.1 General Guidance on Modeling Prediction
- 8.4.2 Predicting Growth and Size
- 8.4.3 Predicting Starvation Risk
- 8.4.4 Predicting Predation and Other Risks
- 8.4.5 Predicting Reproductive Success
- 8.5 Step 4: Selecting a Decision Algorithm
- 8.6 Step 5: Implementing and Testing the Theory
- 8.7 Conclusions
- 9. Testing and Refining State- and Prediction-Based Theory
- 9.1 Introduction and Objectives
- 9.2 The Pattern-Oriented Theory Development Cycle
- 9.3 Examples of Theory Development and Testing
- 9.3.1 Literature Examples
- 9.3.2 Trout Habitat Selection
- 9.3.3 Activity Selection in Trout
- 9.3.4 Foraging Habitat Selection in Songbirds
- 9.4 Conclusions
- 10. Building Model Credibility
- 10.1 Introduction and Objectives
- 10.2 Issues in "Validation" of Individual-Based Population Models
- 10.3 Strategies for Building Credibility
- 10.4 Lessons Learned in Field, Laboratory, and Simulation Experiments
- 10.5 Conclusions
- 11. Empirical Research on Populations of Adaptive Individuals
- 11.1 Introduction and Objectives
- 11.2 Benefits of Models for Field Studies
- 11.3 Modeling Phase 1: Formulate the Question
- 11.4 Modeling Phase 2: Assemble Hypotheses
- 11.5 Modeling Phase 3: Choose Model Structure
- 11.6 Modeling Phase 5: Analyze the Model
- 11.7 Conclusions
- 12. Conclusions and Outlook
- 12.1 Modeling Populations of Adaptive Individuals
- 12.2 Key Characteristics of the Approach
- 12.3 Conclusions from Example Models
- 12.4 Outlook
- References
- Index
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