The decision to implement environmental protection options is a political one. These, and other political and social decisions affect the balance of the ecosystem and how the point of equilibrium desired is to be reached. This book develops a stochastic, temporal model of how political processes influence and are influenced by ecosystem processes and looks at how to find the most politically feasible plan for managing an at-risk ecosystem. Finding such a plan is accomplished by first fitting a mechanistic political and ecological model to a data set composed of observations on both political actions that impact an ecosystem and variables that describe the ecosystem.
The parameters of this fitted model are perturbed just enough to cause human behaviour to change so that desired ecosystem states occur. This perturbed model gives the ecosystem management plan needed to reach desired ecosystem states. To construct such a set of interacting models, topics from political science, ecology, probability, and statistics are developed and explored.
Preface List of Figures List of Tables Nomenclature Part I Managing a Political-Ecological System 1 Introduction 2 Simulator Architecture, Operation, and Example Output 3 Blue Whale Population Management 4 Finding the Most Practical Ecosystem Management Plan 5 An Open, Web-Based Ecosystem Management Tool Part II Model Formulation, Estimation, and Reliability 6 Influence Diagrams of Political Decision Making 7 Group IDs for the East African Cheetah EMT 8 Modeling Wildlife Population Dynamics with an Influence Diagram 9 Political Action Taxonomies, Collection Protocols, and an Actions History Example 10 Ecosystem Data 11 Statistical Fitting of the Political-Ecological System Simulator 12 Assessing the Simulator's Reliability and Improving Its Construct Validity Part III Assessment 13 Current Capabilities and Limitations of the Politically Realistic EMT Appendices Appendix A Heuristics Used to Assign Hypothesis Values to Parameters Appendix B Cluster Computing Version of Hooke and Jeeves Search References Index
Timothy Haas is involved in teaching undergraduate and graduate courses in statistical methods, pursuing decision making and environmental statistics research, and collaborating with faculty on application of statistics to Marketing and Economics.