Ecological Modeling A Commonsense Approach to Theory and Practice

About this book

In addition to providing a common-sense introduction to the basic principles of systems modeling, the authors suggest a practical strategy for dealing with pitfalls commonly encountered during model development. The ties between theory and practice, which beginning modelers often find so elusive, are demystified via the step-by-step development of three models representing ecological systems of increasing complexity.

Contents

PrefaceAcknowledgments1 Introduction1.1 Common-Sense Solutions: Three Exercises1.2 Modeling Theory1.3 Modeling Practice1.4 Theory, Practice, and Common Sense1.5 Intended Use of this BookPart 1 Common-Sense Solutions: Three Exercises2 Common-Sense Solutions2.1 Three Problems2.1.1 Harvesting Food for the Winter2.1.2 Estimating the Probability of Population Extinction2.1.3 Managing the Commons2.2 The Systems Approach to Problem Solving2.2.1 The Conceptual Model (Phase I)2.2.2 The Quantitative Model (Phase II)2.2.3 Model Evaluation (Phase IIII)2.2.4 Model Application (Phase IV)2.3 The Three Problems Revisited: The Systems Approach in Theory and PracticePart 2 Modeling Theory3 Theory I: The Conceptual Model3.1 State the Model Objectives (Ia)3.2 Bound the System-of-Interest (Ib)3.3 Categorize the Components within the System-of-Interest (Ic)3.3.1 State Variables3.3.2 Material Transfers3.3.3 Sources and Sinks3.3.4 Information Transfers3.3.5 Driving Variables3.3.6 Constants3.3.7 Auxiliary Variables3.4 Identify the Relationships among the Components That Are of Interest (Id)3.4.1 Submodels3.5 Represent the Conceptual Model (Ie)3.5.1 Conceptual-Model Diagrams3.6 Describe the Expected Patterns of Model Behavior (If)4 Theory II: The Quantitative Model4.1 Select the General Quantitative Structure for the Model (IIa)4.2 Choose the Basic Time Unit for the Simulations (IIb) 4.3 Identify the Functional Forms of the Model Equations (IIc)4.3.1 Information on Which to Base the Choice of Functional Forms4.3.2 Selecting Types of Equations to Represent the Chosen Functional Forms4.4 Estimate the Parameters of the Model Equations (IId)4.4.1 Statistical Analyses within the Context of Simulation Model Parameterization4.4.2 Quantifying Qualitative Information 4.4.3 Deterministic- versus Stochastic-Model Parameterization4.5 Execute the Baseline Simulation (IIe)4.5.1 Baseline Simulations for Stochastic Models5 Theory III: Model Evaluation5.1 Assess the Reasonableness of the Model Structure and the Interpretability of Functional Relationships within the Model (IIIa)5.2 Evaluate the Correspondence between Model Behavior and the Expected Patterns of Model Behavior (IIIb)5.3 Examine the Correspondence between Model Projections and the Data from the Real System (IIIc)5.3.1 Quantitative versus Qualitative Model Evaluation5.4 Determine the Sensitivity of Model Projections to Changes in the Values of Important Parameters (IIId)5.4.1 Interpreting Sensitivity Analysis within a Model Evaluation Framework6 Theory IV: Model Application6.1 Develop and Execute the Experimental Design for the Simulations (IVa)6.2 Analyze and Interpret the Simulation Results (IVb)6.3 Communicate the Simulation Results (IVc)Part 3 Modeling Practice7 Some Common Pitfalls7.1 Phase I: Pitfalls: The Conceptual Model7.2 Phase II Pitfalls: The Quantitative Model7.3 Phase III Pitfalls: Model Evaluation7.4 Phase IV Pitfalls: Model Application8 The Modeling Process In Practice8.1 Preliminary Conceptual Model (CM)8.1.1 How to Begin8.1.2 Adding New Components to the Model8.1.3 Describing Expected Patterns8.1.4 Describing the Plan of Attack8.2 Intermediate Developmental Models (IDMi)8.2.1 Evaluate-Adjust Cycle for each Developmental Model8.2.2 Sensitivity Analysis of the Last Developmental Model8.3 Final Model (FM)Part 4 Theory, Practice, and Common Sense9 The Common-Sense Problems Revisited9.1 Harvesting Food for the Winter9.1.1 The Preliminary Conceptual Model (CM)9.1.2 The Last (only) Intermediate Developmental Model (IDMlast)9.1.3 The Final Model (FM)9.2 Estimating the Probability of Population Extinction9.2.1 The Preliminary Conceptual Model (CM)9.2.2 The Intermediate Developmental Models (IDMi)9.2.3 The Final Model (FM)10 Reflections10.1 The Systems Approach as a Complement to Other Methods of Problem Solving10.2 Ecological Modeling as a Problem-Solving Process10.3 Expectations for Ecological Models10.4 A Final ThoughtReferencesAppendix A: Introduction To The Ecological Modeling LiteratureAppendix B: Scientific Reports For The Examples in Chapter 2B.1: Effect of Deforestation on Rate of Food HarvestB.2: Effect of Hurricane Frequency on Probability of Population ExtinctionB.3: Effect of Stocking Rate on Forage and Animal Production Index

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Biography

Bill Grant has taught ecological modeling in the Department of Wildlife and Fisheries Sciences (WFSC) at Texas A&M University since 1976, has served on the Board of Governors and as President of the International Society for Ecological Modeling, and has been Associate Editor of the international journal Ecological Modelling since 1997. Todd Swannack also has taught ecological modeling in WFSC at Texas A&M University, and has been modeling the population dynamics of endangered species since 2002.