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Environmental Modeling with Stakeholders : Theory, Methods, and Applications.

By: Gray, Steven.
Contributor(s): Paolisso, Michael | Jordan, Rebecca | Gray, Stefan.
Material type: TextTextSeries: eBooks on Demand.Publisher: Cham : Springer International Publishing, 2016Copyright date: ©2017Description: 1 online resource (377 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9783319250533.Subject(s): Environmental managementGenre/Form: Electronic books.Additional physical formats: Print version:: Environmental Modeling with Stakeholders : Theory, Methods, and ApplicationsDDC classification: 363.70068 Online resources: Click here to view this ebook.
Contents:
Dedication -- Foreword -- Preface -- Structure of the Book -- Book Chapters -- Concluding Remarks -- Contents -- Contributors -- Part I: The Process of Environmental Modeling with Stakeholders -- Chapter 1: Cognitive, Material and Technological Considerations in Participatory Environmental Modeling -- 1.1 Introduction -- 1.2 Cognitive Environmental Knowledge and Values -- 1.3 Material and Technological Dynamics -- 1.3.1 The Conceptual Limitations of Models -- 1.3.2 The Materiality of Computational Modeling -- 1.3.3 Code Structures -- 1.3.4 Broader Socio-Ecological Systems -- 1.4 Conclusion: Insights from the Chesapeake Bay -- References -- Chapter 2: Learning Through Participatory Modeling: Reflections on What It Means and How It Is Measured -- 2.1 Introduction -- 2.2 Our Approach to Participatory Modeling and Efforts to Assess Participant Learning -- 2.2.1 The VCAPS Process -- 2.2.2 Challenges to Assessing Participant Learning in VCAPS -- 2.3 Characterizing Learning in Participatory Modeling Activities -- 2.3.1 A Socio-Cultural Approach to Learning -- 2.3.2 A Developmental Approach to Assessing Learning -- 2.4 Designing Participatory Modeling Processes to Promote Learning -- 2.4.1 Cultural Tools That Participants Can Learn by Engagement in Participatory Modeling -- 2.4.2 Process Designers Can Promote Interactions and Activities to Promote Learning of Cultural Tools -- 2.4.3 Process Designers Can Select Participants and Define Roles to Promote Learning of Cultural Tools -- 2.4.4 Process Designers Can Selectively Use Cultural Tools to Promote Learning -- 2.5 Conclusion -- References -- Chapter 3: Values in Participatory Modeling: Theory and Practice -- 3.1 Introduction -- 3.2 Philosophy of Participatory Modeling: Integrating Values, Not Just Knowledge -- 3.3 Revisiting Best Practices of Participatory Modeling.
3.4 An Example: Can Optimization Help with Value-Setting? -- 3.5 Conclusions -- References -- Chapter 4: Eliciting Judgments, Priorities, and Values Using Structured Survey Methods -- 4.1 Introduction -- 4.2 Survey Respondents -- 4.3 Survey Design and Deployment -- 4.4 Elicitation Approaches -- 4.5 Applications in Environmental Science and Decision Making -- 4.5.1 Characterizing the Significance of Adverse Events Across a Large-Scale Hydropower System in British Columbia, Canada -- 4.5.2 Selecting Regulatory Options for Managing Incidental Take of Migratory Birds from Human Development Across Canada -- 4.5.3 Understanding Boater Perceptions of Environmental Issues Affecting Lakes in Northern Wisconsin, USA -- 4.6 Final Thoughts -- References -- Chapter 5: Participatory Modeling and Structured Decision Making -- 5.1 Introduction -- 5.1.1 Collaborative Decision Making: A Participatory Process -- 5.2 The Structured Decision Making Framework -- 5.2.1 Problem -- 5.2.2 Objectives -- 5.2.3 Alternatives -- 5.2.4 Consequences -- 5.2.4.1 Influence Diagrams -- 5.2.4.2 Decision Trees -- 5.2.4.3 Bayesian Belief Networks -- 5.2.4.4 Empirical Models -- 5.2.4.5 Expert Elicitation -- 5.2.4.6 Consequence Tables -- 5.2.5 Tradeoffs -- 5.2.6 Implementing the Decision -- 5.3 Conclusions -- References -- Chapter 6: Ensuring that Ecological Science Contributes to Natural Resource Management Using a Delphi-Derived Approach -- 6.1 Introduction -- 6.2 Resource Management and Environmental Research at Fort Benning -- 6.3 Participatory Methods for Addressing Integration Goals -- 6.4 Participatory Approaches and Their Outcomes -- 6.4.1 Preliminary Consultation with Land Managers: Developing an Initial Land-Use Framework -- 6.4.2 Round 1 with SEMP Researchers: Raising Challenging Issues -- 6.4.3 Round 2: Refining the Integration Matrix.
6.4.4 Round 3 and the Face-to-Face Elicitation: The "Final" Integration Matrix Emerges -- 6.4.5 Mapping the Land Management Goals Based on the Integration Matrix -- 6.5 Discussion -- References -- Part II: The Application and Products of Environmental Modeling with Stakeholders -- Chapter 7: Fuzzy-Logic Cognitive Mapping: Introduction and Overview of the Method -- 7.1 Introduction -- 7.2 Description -- 7.3 Evolution of FCM -- 7.4 Fuzzy-Logic Cognitive Mapping in the Environmental-­Modeling Context -- 7.4.1 Facilitating Public Participation -- 7.4.2 Expert Knowledge to Deal with Data and Knowledge Limitations -- 7.4.3 Simulating Changes to the System and Decision Outcomes -- 7.4.4 Examples of FCM in Environmental Research -- 7.5 Limitations of Fuzzy-Logic Cognitive Mapping -- 7.6 Conclusion -- References -- Chapter 8: FCMs as a Common Base for Linking Participatory Products and Models -- 8.1 Introduction -- 8.1.1 Objectives -- 8.2 Background -- 8.2.1 SCENES -- 8.2.2 Fuzzy Cognitive Maps -- 8.2.3 WaterGAP Model -- 8.3 Methods -- 8.3.1 Development of Stakeholder-Based FCM -- 8.3.2 Development of a Model-Based FCM -- 8.3.3 Comparison of Both FCMs -- 8.3.3.1 System Configuration -- 8.3.3.2 Quasi-Dynamic System Behavior -- 8.4 Results -- 8.4.1 System Configuration -- 8.4.2 Quasi-Dynamic System Behavior -- 8.5 Discussion and Outlook -- 8.5.1 Development of FCM-SH, Based on Information from Three Case Studies -- 8.5.2 Development of FCM-WG, Based on a Mathematical Model -- 8.5.3 Comparing Both FCMs to Identify Crucial Differences and Similarities -- 8.5.4 Comparing FCMs and Mathematical Models -- 8.5.5 Recommendations to Better Match FCMs and Models to Bridge Between Qualitative and Quantitative Scenarios -- 8.6 Conclusions -- References.
Chapter 9: Extending Participatory Fuzzy Cognitive Mapping with a Control Nodes Methodology: A Case Study of the Development of a Bio-based Economy in the Humber Region, UK -- 9.1 Introduction -- 9.1.1 Tools for Steering Complex Systems -- 9.1.2 The Humber Region Case Study -- 9.1.3 Participatory Modeling in Our Methodology -- 9.2 Methodology: Expanding Fuzzy Cognitive Mapping with Network Controllability Analysis -- 9.2.1 Fuzzy Cognitive Mapping -- 9.2.2 Interpretation of Fuzzy Cognitive Maps -- 9.2.3 Control Nodes Methodology -- 9.2.4 Incorporating Control Nodes into a Participatory FCM Workshop -- 9.3 Case Study: Applying Control Nodes Methodology to Stakeholder-Produced Fuzzy Cognitive Maps -- 9.3.1 Producing a Cognitive Map of the Humber Bio-Based Energy System -- 9.3.2 Humber Bio-Based Economy Control Nodes Workshop -- 9.3.3 Controllability Results -- 9.3.3.1 Factor Controllability as Perceived by Stakeholders -- 9.3.3.2 Control Configurations -- 9.3.3.3 Stakeholder Ranking of Control Configurations -- 9.4 Discussion -- 9.4.1 Stakeholder Response to the Process -- 9.4.2 Who Is the Appropriate Audience? -- 9.4.3 Methodological Limitations and Further Work -- 9.5 Conclusions -- References -- Chapter 10: Effects of Livelihood-Diversification on Sustainability of Natural Resources in the Rangelands of East Africa: Participatory Field Studies and Results of an Agent-Based Model Using the Knowledge of Indigenous Maasai Pastoralists of Kenya -- 10.1 Introduction -- 10.2 Research Approach and Methods -- 10.3 Structure and Operation of Maasai-Pastoralism and Resources Management -- 10.4 Maasai Knowledge, Values, and Preferences in Natural Resource Management -- 10.5 Livelihood-Diversification and Sustainability of Natural Resources in Indigenous Maasai-Pastoralism.
10.6 Scenarios for Change: Livelihood-Diversification and Scalar Environmental, Socioeconomic, and Climatic Changes -- 10.7 Conclusions and Emerging Themes -- References -- Chapter 11: Level of Sustainable Activity: A Framework for Integrating Stakeholders into the Simulation Modeling and Management of Mixed-Use Waterways -- 11.1 Introduction -- 11.2 Background: Carrying Capacity for Water-Based Recreation -- 11.2.1 WROS: Water Recreational Opportunity Spectrum -- 11.2.2 Level of Service: Capacity for Roadways -- 11.3 Level of Sustainable Activity (LSA) Framework for Waterways -- 11.4 The LSA Approach -- 11.4.1 Waterway Classification -- 11.4.2 Waterway Inventory -- 11.4.3 Selection of Stakeholder Groups -- 11.4.4 Define Issues -- 11.4.5 Pattern of Use Analysis -- 11.4.6 Forecast Use Trends -- 11.4.7 Establish LSA Classes -- 11.4.8 Define Level of Sustainable Activity for Each Stakeholder Group and Each Management Zone -- 11.4.9 Define Management Options -- 11.4.10 Develop a Vessel Traffic Management Plan -- 11.5 Case Study A: Vessel Traffic Management in an Urban Waterway -- 11.5.1 Waterway Classification -- 11.5.2 Marina/Transit Zone Inventory -- 11.5.3 Selection of Stakeholder Groups -- 11.5.4 Define Issues -- 11.5.5 Pattern of Use Analysis -- 11.5.6 Forecast Use Trends -- 11.5.7 Establish LSA Classes -- 11.5.8 Marina/Transit Zone Level of Sustainable Activity -- 11.5.9 Results of LSA Workshop -- 11.5.9.1 Quality of Experience -- 11.5.10 Implications of LSA Results in Relation to Simulation Outputs -- 11.5.11 Summary and Conclusions -- 11.6 Prince William Sound: LSA in a Wilderness Waterway -- 11.6.1 Waterway Classification and Inventory: Selecting Representative Bays -- 11.6.2 Selection of Stakeholder Groups -- 11.6.3 Define Issues -- 11.6.3.1 Results of the Survey -- 11.6.4 Establish LSA Classes.
11.6.5 Define Level of Sustainable Activity for Each Stakeholder Group for Each of Three Bays.
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Dedication -- Foreword -- Preface -- Structure of the Book -- Book Chapters -- Concluding Remarks -- Contents -- Contributors -- Part I: The Process of Environmental Modeling with Stakeholders -- Chapter 1: Cognitive, Material and Technological Considerations in Participatory Environmental Modeling -- 1.1 Introduction -- 1.2 Cognitive Environmental Knowledge and Values -- 1.3 Material and Technological Dynamics -- 1.3.1 The Conceptual Limitations of Models -- 1.3.2 The Materiality of Computational Modeling -- 1.3.3 Code Structures -- 1.3.4 Broader Socio-Ecological Systems -- 1.4 Conclusion: Insights from the Chesapeake Bay -- References -- Chapter 2: Learning Through Participatory Modeling: Reflections on What It Means and How It Is Measured -- 2.1 Introduction -- 2.2 Our Approach to Participatory Modeling and Efforts to Assess Participant Learning -- 2.2.1 The VCAPS Process -- 2.2.2 Challenges to Assessing Participant Learning in VCAPS -- 2.3 Characterizing Learning in Participatory Modeling Activities -- 2.3.1 A Socio-Cultural Approach to Learning -- 2.3.2 A Developmental Approach to Assessing Learning -- 2.4 Designing Participatory Modeling Processes to Promote Learning -- 2.4.1 Cultural Tools That Participants Can Learn by Engagement in Participatory Modeling -- 2.4.2 Process Designers Can Promote Interactions and Activities to Promote Learning of Cultural Tools -- 2.4.3 Process Designers Can Select Participants and Define Roles to Promote Learning of Cultural Tools -- 2.4.4 Process Designers Can Selectively Use Cultural Tools to Promote Learning -- 2.5 Conclusion -- References -- Chapter 3: Values in Participatory Modeling: Theory and Practice -- 3.1 Introduction -- 3.2 Philosophy of Participatory Modeling: Integrating Values, Not Just Knowledge -- 3.3 Revisiting Best Practices of Participatory Modeling.

3.4 An Example: Can Optimization Help with Value-Setting? -- 3.5 Conclusions -- References -- Chapter 4: Eliciting Judgments, Priorities, and Values Using Structured Survey Methods -- 4.1 Introduction -- 4.2 Survey Respondents -- 4.3 Survey Design and Deployment -- 4.4 Elicitation Approaches -- 4.5 Applications in Environmental Science and Decision Making -- 4.5.1 Characterizing the Significance of Adverse Events Across a Large-Scale Hydropower System in British Columbia, Canada -- 4.5.2 Selecting Regulatory Options for Managing Incidental Take of Migratory Birds from Human Development Across Canada -- 4.5.3 Understanding Boater Perceptions of Environmental Issues Affecting Lakes in Northern Wisconsin, USA -- 4.6 Final Thoughts -- References -- Chapter 5: Participatory Modeling and Structured Decision Making -- 5.1 Introduction -- 5.1.1 Collaborative Decision Making: A Participatory Process -- 5.2 The Structured Decision Making Framework -- 5.2.1 Problem -- 5.2.2 Objectives -- 5.2.3 Alternatives -- 5.2.4 Consequences -- 5.2.4.1 Influence Diagrams -- 5.2.4.2 Decision Trees -- 5.2.4.3 Bayesian Belief Networks -- 5.2.4.4 Empirical Models -- 5.2.4.5 Expert Elicitation -- 5.2.4.6 Consequence Tables -- 5.2.5 Tradeoffs -- 5.2.6 Implementing the Decision -- 5.3 Conclusions -- References -- Chapter 6: Ensuring that Ecological Science Contributes to Natural Resource Management Using a Delphi-Derived Approach -- 6.1 Introduction -- 6.2 Resource Management and Environmental Research at Fort Benning -- 6.3 Participatory Methods for Addressing Integration Goals -- 6.4 Participatory Approaches and Their Outcomes -- 6.4.1 Preliminary Consultation with Land Managers: Developing an Initial Land-Use Framework -- 6.4.2 Round 1 with SEMP Researchers: Raising Challenging Issues -- 6.4.3 Round 2: Refining the Integration Matrix.

6.4.4 Round 3 and the Face-to-Face Elicitation: The "Final" Integration Matrix Emerges -- 6.4.5 Mapping the Land Management Goals Based on the Integration Matrix -- 6.5 Discussion -- References -- Part II: The Application and Products of Environmental Modeling with Stakeholders -- Chapter 7: Fuzzy-Logic Cognitive Mapping: Introduction and Overview of the Method -- 7.1 Introduction -- 7.2 Description -- 7.3 Evolution of FCM -- 7.4 Fuzzy-Logic Cognitive Mapping in the Environmental-­Modeling Context -- 7.4.1 Facilitating Public Participation -- 7.4.2 Expert Knowledge to Deal with Data and Knowledge Limitations -- 7.4.3 Simulating Changes to the System and Decision Outcomes -- 7.4.4 Examples of FCM in Environmental Research -- 7.5 Limitations of Fuzzy-Logic Cognitive Mapping -- 7.6 Conclusion -- References -- Chapter 8: FCMs as a Common Base for Linking Participatory Products and Models -- 8.1 Introduction -- 8.1.1 Objectives -- 8.2 Background -- 8.2.1 SCENES -- 8.2.2 Fuzzy Cognitive Maps -- 8.2.3 WaterGAP Model -- 8.3 Methods -- 8.3.1 Development of Stakeholder-Based FCM -- 8.3.2 Development of a Model-Based FCM -- 8.3.3 Comparison of Both FCMs -- 8.3.3.1 System Configuration -- 8.3.3.2 Quasi-Dynamic System Behavior -- 8.4 Results -- 8.4.1 System Configuration -- 8.4.2 Quasi-Dynamic System Behavior -- 8.5 Discussion and Outlook -- 8.5.1 Development of FCM-SH, Based on Information from Three Case Studies -- 8.5.2 Development of FCM-WG, Based on a Mathematical Model -- 8.5.3 Comparing Both FCMs to Identify Crucial Differences and Similarities -- 8.5.4 Comparing FCMs and Mathematical Models -- 8.5.5 Recommendations to Better Match FCMs and Models to Bridge Between Qualitative and Quantitative Scenarios -- 8.6 Conclusions -- References.

Chapter 9: Extending Participatory Fuzzy Cognitive Mapping with a Control Nodes Methodology: A Case Study of the Development of a Bio-based Economy in the Humber Region, UK -- 9.1 Introduction -- 9.1.1 Tools for Steering Complex Systems -- 9.1.2 The Humber Region Case Study -- 9.1.3 Participatory Modeling in Our Methodology -- 9.2 Methodology: Expanding Fuzzy Cognitive Mapping with Network Controllability Analysis -- 9.2.1 Fuzzy Cognitive Mapping -- 9.2.2 Interpretation of Fuzzy Cognitive Maps -- 9.2.3 Control Nodes Methodology -- 9.2.4 Incorporating Control Nodes into a Participatory FCM Workshop -- 9.3 Case Study: Applying Control Nodes Methodology to Stakeholder-Produced Fuzzy Cognitive Maps -- 9.3.1 Producing a Cognitive Map of the Humber Bio-Based Energy System -- 9.3.2 Humber Bio-Based Economy Control Nodes Workshop -- 9.3.3 Controllability Results -- 9.3.3.1 Factor Controllability as Perceived by Stakeholders -- 9.3.3.2 Control Configurations -- 9.3.3.3 Stakeholder Ranking of Control Configurations -- 9.4 Discussion -- 9.4.1 Stakeholder Response to the Process -- 9.4.2 Who Is the Appropriate Audience? -- 9.4.3 Methodological Limitations and Further Work -- 9.5 Conclusions -- References -- Chapter 10: Effects of Livelihood-Diversification on Sustainability of Natural Resources in the Rangelands of East Africa: Participatory Field Studies and Results of an Agent-Based Model Using the Knowledge of Indigenous Maasai Pastoralists of Kenya -- 10.1 Introduction -- 10.2 Research Approach and Methods -- 10.3 Structure and Operation of Maasai-Pastoralism and Resources Management -- 10.4 Maasai Knowledge, Values, and Preferences in Natural Resource Management -- 10.5 Livelihood-Diversification and Sustainability of Natural Resources in Indigenous Maasai-Pastoralism.

10.6 Scenarios for Change: Livelihood-Diversification and Scalar Environmental, Socioeconomic, and Climatic Changes -- 10.7 Conclusions and Emerging Themes -- References -- Chapter 11: Level of Sustainable Activity: A Framework for Integrating Stakeholders into the Simulation Modeling and Management of Mixed-Use Waterways -- 11.1 Introduction -- 11.2 Background: Carrying Capacity for Water-Based Recreation -- 11.2.1 WROS: Water Recreational Opportunity Spectrum -- 11.2.2 Level of Service: Capacity for Roadways -- 11.3 Level of Sustainable Activity (LSA) Framework for Waterways -- 11.4 The LSA Approach -- 11.4.1 Waterway Classification -- 11.4.2 Waterway Inventory -- 11.4.3 Selection of Stakeholder Groups -- 11.4.4 Define Issues -- 11.4.5 Pattern of Use Analysis -- 11.4.6 Forecast Use Trends -- 11.4.7 Establish LSA Classes -- 11.4.8 Define Level of Sustainable Activity for Each Stakeholder Group and Each Management Zone -- 11.4.9 Define Management Options -- 11.4.10 Develop a Vessel Traffic Management Plan -- 11.5 Case Study A: Vessel Traffic Management in an Urban Waterway -- 11.5.1 Waterway Classification -- 11.5.2 Marina/Transit Zone Inventory -- 11.5.3 Selection of Stakeholder Groups -- 11.5.4 Define Issues -- 11.5.5 Pattern of Use Analysis -- 11.5.6 Forecast Use Trends -- 11.5.7 Establish LSA Classes -- 11.5.8 Marina/Transit Zone Level of Sustainable Activity -- 11.5.9 Results of LSA Workshop -- 11.5.9.1 Quality of Experience -- 11.5.10 Implications of LSA Results in Relation to Simulation Outputs -- 11.5.11 Summary and Conclusions -- 11.6 Prince William Sound: LSA in a Wilderness Waterway -- 11.6.1 Waterway Classification and Inventory: Selecting Representative Bays -- 11.6.2 Selection of Stakeholder Groups -- 11.6.3 Define Issues -- 11.6.3.1 Results of the Survey -- 11.6.4 Establish LSA Classes.

11.6.5 Define Level of Sustainable Activity for Each Stakeholder Group for Each of Three Bays.

Description based on publisher supplied metadata and other sources.

Author notes provided by Syndetics

Steven Gray is an Assistant Professor in the Department of Community Sustainability at Michigan State University. His research focuses on the theory and practice of participatory modeling and developing decision-support software to help communities, resource managers, and other decision-makers to understand the social impacts of environmental change through modeling. <br> Michael Paolisso is a Professor in the Department of Anthropology at the University of Maryland whose research seeks to demonstrate how cultural models of the environment have a direct bearing on the use and management of natural resources, and how cognitive-cultural approaches and collaborative learning improve scientist and public understanding, dialogue, and collaboration in addressing environmental issues. <br> Rebecca Jordan is a Professor in the Department of Human Ecology at Rutgers University. Trained as a behavioral ecologist her scholarly work focusses on public participation in scientific research and the contribution of learning to the sustainability of coupled social-ecological systems. <br> Stefan Gray currently works as an adviser to the Parliamentary Commissioner for the Environment in Wellington, New Zealand. At the time of the production of this book, Stefan held a Research Fellowship funded by the Irish Environmental Protection Agency, supporting climate change adaptation at central and local government levels in Ireland. His research in Europe focused on issues related to expanding decision-making in environmental management to incorporate complex adaptive systems theory.

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