Ecological Modeling A Common-Sense Approach to Theory and Practice

, by Grant, William E.; Swannack, Todd M.

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ISBN: 9781405161688 | 140516168X
Cover: Paperback
Copyright: 12/26/2007

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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

Preface	p. xi
Acknowledgments	p. xiii
Introduction	p. 1
Common-sense solutions: three exercises	p. 1
Modeling theory	p. 2
Modeling practice	p. 2
Theory, practice, and common sense	p. 3
Intended use of this book	p. 3
Common-sense solutions: three exercises
Common-sense solutions	p. 5
Three problems	p. 6
Harvesting food for the winter	p. 6
Estimating the probability of population extinction	p. 12
Managing the Commons	p. 20
The systems approach to problem solving	p. 49
The conceptual model (Phase I)	p. 50
The quantitative model (Phase II)	p. 51
Model evaluation (Phase III)	p. 51
Model application (Phase IV)	p. 51
The three problems revisited: the systems approach in theory and practice	p. 51
Modeling theory
Theory I: the conceptual model	p. 53
State the model objectives (I[subscript a])	p. 54
Bound the system-of-interest (I[subscript b])	p. 55
Categorize the components within the system-of-interest (I[subscript c])	p. 57
State variables	p. 57
Material transfers	p. 59
Sources and sinks	p. 61
Information transfers	p. 61
Driving variables	p. 62
Constants	p. 62
Auxiliary variables	p. 62
Identify the relationships among the components that are of interest (I[subscript d])	p. 63
Submodels	p. 63
Represent the conceptual model (I[subscript e])	p. 65
Conceptual-model diagrams	p. 65
Describe the expected patterns of model behavior (I[subscript f])	p. 66
Theory II: the quantitative model	p. 67
Select the general quantitative structure for the model (II[subscript a])	p. 68
Choose the basic time unit for the simulations (II[subscript b])	p. 72
Identify the functional forms of the model equations (II[subscript c])	p. 72
Information on which to base the choice of functional forms	p. 73
Selecting types of equations to represent the chosen functional forms	p. 73
Estimate the parameters of the model equations (II[subscript d])	p. 75
Statistical analyses within the context of simulation model parameterization	p. 75
Quantifying qualitative information	p. 76
Deterministic- versus stochastic-model parameterization	p. 76
Execute the baseline simulation (II[subscript e])	p. 77
Baseline simulations for stochastic models	p. 78
Theory III: model evaluation	p. 79
Assess the reasonableness of the model structure and the interpretability of functional relationships within the model (III[subscript a])	p. 81
Evaluate the correspondence between model behavior and the expected patterns of model behavior (III[subscript b])	p. 82
Examine the correspondence between model projections and the data from the real system (III[subscript c])	p. 84
Quantitative versus qualitative model evaluation	p. 86
Determine the sensitivity of model projections to changes in the values of important parameters (III[subscript d])	p. 86
Interpreting sensitivity analysis within a model evaluation framework	p. 87
Theory IV: model application	p. 89
Develop and execute the experimental design for the simulations (IV[subscript a])	p. 89
Analyze and interpret the simulation results (IV[subscript b])	p. 91
Communicate the simulation results (IV[subscript c])	p. 91
Modeling practice
Some common pitfalls	p. 93
Phase I pitfalls: the conceptual model	p. 93
Phase II pitfalls: the quantitative model	p. 97
Phase III pitfalls: model evaluation	p. 100
Phase IV pitfalls: model application	p. 102
The modeling process in practice	p. 105
Preliminary conceptual model (CM)	p. 106
How to begin	p. 106
Adding new components to the model	p. 108
Describing expected patterns	p. 108
Describing the plan of attack	p. 108
Intermediate developmental models (IDM[subscript i])	p. 109
Evaluate-adjust cycle for each developmental model	p. 110
Sensitivity analysis of the last developmental model	p. 112
Final model (FM)	p. 112
Theory, practice, and common sense
The common-sense problems revisted	p. 115
Harvesting food for the winter	p. 115
The preliminary conceptual model (CM)	p. 115
The last (only) intermediate development model (IDM[subscript last])	p. 116
The final model (FM)	p. 117
Estimating the probability of population extinction	p. 117
The preliminary conceptual model (CM)	p. 117
The intermediate development models (IDM[subscript i])	p. 118
The final model (FM)	p. 118
Managing the Commons	p. 118
The preliminary conceptual model (CM)	p. 118
The intermediate development models (IDM[subscript i])	p. 120
The final model (FM)	p. 121
Reflections	p. 123
The systems approach as a complement to other methods of problem solving	p. 123
Ecological modeling as a problem-solving process	p. 126
Expectations for ecological models	p. 127
A final thought	p. 129
References	p. 131
Introduction to the ecological modeling literature	p. 133
Scientific reports for the examples in Chapter 2	p. 139
Effect of deforestation on rate of food harvest	p. 139
Effect of hurricane frequency on probability of population extinction	p. 141
Effect of stocking rate on forage and animal production	p. 143
Index	p. 149
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Ecological Modeling A Common-Sense Approach to Theory and Practice

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Ecological Modeling A Common-Sense Approach to Theory and Practice

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