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Ecological Modeling

De
176 pages
Ecological Modeling:A Commonsense Approach to Theory and Practice explores how simulation modeling and its new ecological applications can offer solutions to complex natural resource management problems. This is a practical guide for students, teachers, and professional ecologists.
  • Examines four phases of the modeling process: conceptual model formulation, quantitative model specification, model evaluation, and model use
  • Provides useful building blocks for constructing systems simulation models
  • Includes a format for reporting the development and use of simulation models
  • Offers an integrated systems perspective for students, faculty, and professionals
  • Features helpful insights from the author, gained over 30 years of university teaching

"I can strongly recommend the book as textbook for all courses in population dynamic modeling particularly when the course is planned for the second or third year of a bachelor study in ecology, environmental science or ecological engineering. It uncovers very clearly for the readers the scientific idea and thinking behind modeling and all the necessary steps in the development of models."
Ecological Modeling Journal, 2009

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Contents
Preface Acknowledgments
 1 Introduction
1.1 Commonsense solutions: three exercises 1.2 Modeling theory 1.3 Modeling practice 1.4 Theory, practice, and common sense 1.5 Intended use of this book
Part 1
Commonsense solutions: three exercises
 2 Commonsense solutions
2.1 Three problems food for the winter2.1.1 Harvesting  2.1.2 Estimating the probability of population extinction  2.1.3 Managing the Commons 2.2 The systems approach to problem solving
 2.2.1 The conceptual model (Phase I)  2.2.2 The quantitative model (Phase II)  2.2.3 Model evaluation (Phase III)  2.2.4 Model application (Phase IV) 2.3 The three problems revisited: the systems approach in theory and practice
xi xiii
1
1 2 2 3 3
5
6
6 12 20 49
50 51 51 51
51
73
3.1 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 variables  3.3.2 Material transfers  3.3.3 Sources and sinks  3.3.4 Information transfers  3.3.5 Driving variables  3.3.6 Constants  3.3.7 Auxiliary variables
3.4 Identify the relationships among the components that are of interest (Id)
 4 Theory II: the quantitative model
3.6 Describe the expected patterns of model behavior (If)
4.1 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)
4.4 Estimate the parameters of the model equations (IId)
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75 76 76
4.4.1 Statistical analyses within the context of simulation model parameterization 4.4.2 Quantifying qualitative information 4.4.3 Deterministic versus stochasticmodel parameterization
3.5 Represent the conceptual model (Ie)
68 72
CONTENTS
vi
7
6
66
54 55
63
65
65
5
3
63
72
3.5.1 Conceptualmodel diagrams
Part 2
73
57 57 59 61 61 62 62 62
Modeling theory
 3 Theory I: the conceptual model
3.4.1 Submodels
4.3.1 Information on which to base the choice of functional forms 4.3.2 Selecting types of equations to represent the chosen functional forms
4.5 Execute the baseline simulation (IIe)
4.5.1 Baseline simulations for stochastic models
 5 Theory III: model evaluation
5.1 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 evaluation 5.4 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 framework
 6 Theory IV: model application
6.1 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 practice
 7 Some common pitfalls
7.1 Phase I pitfalls: the conceptual model 7.2 Phase II pitfalls: the quantitative model 7.3 Phase III pitfalls: model evaluation 7.4 Phase IV pitfalls: model application
77
78
7
9
81
82
84
86
86
87
8
9
89 91 91
9
3
93 97 100 102
CONTENTS
vii
123 126 127 129
 9 The commonsense problems revisted
viii
123
105
9.2.1 The preliminary conceptual model (CM) 9.2.2 The intermediate development models (IDMi) 9.2.3 The final model (FM)
118 120 121
115
112
118
117 118 118
117
106
109
110 112
9.2 Estimating the probability of population extinction
10 Reflections
8.2 Intermediate developmental models (IDMi)
 8 The modeling process in practice
8.1 Preliminary conceptual model (CM)
8.3 Final model (FM)
9.1 Harvesting food for the winter
9.3 Managing the Commons
10.1 The systems approach as a complement to other methods of problem solving 10.2 Ecological modeling as a problemsolving process 10.3 Expectations for ecological models 10.4 A final thought
CONTENTS
Part 4 Theory, practice, and common sense
115
115 116 117
106 108 108 108
8.2.1 Evaluate–adjust cycle for each developmental model 8.2.2 Sensitivity analysis of the last developmental model
8.1.1 How to begin 8.1.2 Adding new components to the model 8.1.3 Describing expected patterns 8.1.4 Describing the plan of attack
9.1.1 The preliminary conceptual model (CM) 9.1.2 The last (only) intermediate development model (IDMlast) 9.1.3 The final model (FM)
9.3.1 The preliminary conceptual model (CM) 9.3.2 The intermediate development models (IDMi) 9.3.3 The final model (FM)
References
Appendix A: Introduction to the ecological modeling literature
Appendix B: Scientific reports for the examples in Chapter 2 of deforestation on rate of food harvestB.1 Effect  B.2 Effect of hurricane frequency on probability of population extinction  B.3 Effect of stocking rate on forage and animal production
Index
131
133
139 139
141
143
149
CONTENTS
ix