Food Systems Modelling: Tools for Assessing Sustainability in Food and Agriculture

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Title
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Contents
Contributors
Acknowledgements
Chapter1 Using models to study food systems
1.1 Introduction
1.2 Models and why we use them
1.3 Models in food systems
1.4 Types of models used to study food systems
1.5 Stage of food production
1.5.1 Single stages of the food system
1.5.2 Supply chains
1.5.3 Broader food systems
1.6 Three major types of models
1.6.1 Biophysical models
1.6.2 Socio-Economic models
1.6.3 Participatory modeling
1.7 Common issues with models
1.8 Organization of this book
Acknowledgements
References
Chapter2 The origins, definitions and differences among concepts that underlie food systems modeling
2.1 Introduction
2.2 Origins and definitions of terms
2.2.1 Sustainability and related concepts
2.2.2 Sustainable development
2.2.3 Sustainable agriculture
2.3 Systems concepts
2.3.1 Food systems
2.3.2 Sustainable food systems
2.3.3 Systems thinking and modeling
2.3.4 Multi-, inter- and transdisciplinary research
2.4 Differences between sustainability and resilience and food systems and systems thinking
2.4.1 The difference between sustainability and resilience
2.4.2 The difference between food systems and systems thinking
2.4.3 Systems properties of food systems and their use in modeling
2.5 Conclusions
References
Chapter3 Life cycle assessment of food systems and diets
3.1 Introduction
3.2 A brief history of life cycle assessment
3.3 The four phases of LCA
3.3.1 Phase 1: goal and scope
3.3.2 Phase 2: life cycle inventory(LCI)
3.3.3 The problem of multi-functionality
3.3.4 Phase 3: life cycle impact assessment(LCIA)
3.3.5 Phase 4: interpretation of the assessment
3.4 Yogurt case study: LCIA result and interpretation example at midpoint
3.5 Yogurt case study: LCIA results and interpretation at endpoint
3.6 Including nutritional benefits and impacts in LCA
3.6.1 Which yogurt is better?
3.7 Uncertainty in LCA
3.8 Sensitivity analysis
3.8.1 Monte carlo analysis
3.9 Gaps and further research needs
3.10 Conclusions
Acknowledgements
References
Chapter4 Water Footprint Assessment: towards water-wise food systems
4.1 Introduction
4.1.1 The water footprint concept
4.1.2 The position of this chapter in WFA literature
4.2 Accounting the consumptive water footprint of growing a crop
4.2.1 The use of soil water balance models for crop water footprint accounting
4.2.2 The use of crop models for crop water footprint accounting
4.2.3 Distinguishing between green and blue crop water use
4.3 Environmental sustainability, efficiency and equitability of the water footprint of food systems
4.3.1 Environmental sustainability
4.3.2 Efficiency
4.3.3 Equitability
4.4 Towards water-wise food systems
4.4.1 What can governments do?
4.4.2 What can citizens do?
4.4.3 What can companies do?
4.4.4 What can investors do?
4.4.5 What can international organizations do?
4.4.6 What can civil society, media, and academia do?
References
Chapter5 Land use modeling: from farm to food systems
5.1 Introduction
5.2 Life cycle assessment
5.2.1 Methodology and relevance
5.2.2 Example results
5.3 Land use ratio
5.3.1 The methodology and relevance
5.3.2 Example results
5.3.3 Allocation
5.4 Food systems approach - accounting for food system level interlinkages and circularity
5.5 Pros and cons and recommendations for land use modeling
Acknowledgement
References
Chapter6 Foodshed analysis and carrying capacity estimation
6.1 Introduction
6.2 History and conceptual foundations
6.2.1 Carrying capacity of human populations
6.2.2The concept of a “foodshed”
6.2.3 Relationship between the two ideas
6.3 Methodology
6.3.1 Net balance approaches
6.3.2 Carrying capacity modeling
6.3.3 Spatial optimization of foodsheds
6.4 Results and implications
6.4.1 What does a regional self-reliance study teach you?
6.4.2 The meaning of carrying capacity estimates
6.4.3 The allure and limits of foodshed analysis
6.4.4 Key lessons
Acknowledgements
References
Chapter7 Market and supply chain models for analysis of food systems
7.1 Introduction
7.2 Spatial optimization models(Transportation and transshipment models)
7.2.1 The transportation model
7.2.2 The transshipment model
7.2.3 Examples and extensions
7.3 Partial equilibrium models
7.3.1 Partial equilibrium model characteristics and metrics
7.3.2 Example of analysis with a PE model: a tax on sugary soft drinks
7.3.3 PE model optimization formulation
7.3.4 Empirical examples of PE models
7.3.5 Data needs and model calibration
7.3.6 Examples and extensions for food systems
7.4 Dynamic supply chain models
7.4.1 Model structures
7.4.2 Empirical example: vegetable supply chains in Kenya
7.4.3 Simulation results for three interventions
7.4.4 Data needs, sensitivity analysis and participatory stakeholder modeling
7.4.5 Examples of SD modeling of food supply chains
7.5 Concluding comments
References
Chapter8 Using input-output analysis to estimate the economic impacts of food system initiatives
8.1 Introduction
8.1.1 An overview of economic impact methods
8.1.2 Case study: nutrition incentive programs(including gusnip, formerly called FINI)
8.1.3 Data
8.1.4 Integrating economic impact assessment methods with other food system modeling efforts
8.2 Conclusion
Acknowledgements
Disclaimer
References
Chapter 9Environmental Input-Output (EIO) Models for Food Systems Research: Application and Extensions
9.1 Introduction
9.2 Background
9.3 Adapting the EIO framework for modeling food systems
9.3.1 Supply and use tables
9.3.2 Environmental multipliers and food system scenarios
9.3.3 Supply chain modeling
9.3.4 Special topics for food system modeling
9.4 Application: a U.S. food economy EIO model
9.5 Extensions: linear programming and comparative diets analysis
9.6 Conclusion
Supplementary materials
References
Chapter10 Modeling biophysical and socioeconomic interactions in food systems with the International Model for Policy Analysis of Agricultural Commodities and Trade \(IMPACT\)
10.1 Food system challenges
10.2 How do we think about the future?
10.3 The IMPACT model
10.3.1 Development and evolution of the model
10.3.2 The IMPACT model today
10.4 Scenario analysis using IMPACT
10.5 Examples of IMPACT-based applications
10.5.1 On the impacts of specific technologies
10.5.2 On the importance of incorporating both biophysical and socioeconomic drivers and interactions
10.5.3 On impacts of different investment strategies and tradeoffs across outcomes
10.5.4 On comparing impacts of multiple drivers on desired outcomes
10.5.5 On examining impacts of future trends on multiple outcomes
10.6 Use of modeling to inform decision making
10.7 Lessons learned and conclusions
Acknowledgments
References
Chapter11 Using social network analysis to understand and enhance local and regional food systems
11.1 Introduction
11.2 A brief history and overview of social network analysis
11.3 Emerging applications of SNA in food systems research and practice
11.4 Designing a food systems network study
11.4.1 Identifying a research question, theoretical concept and study context
11.4.2 Determining network research level of analysis
11.4.3 Selecting data collection methods
11.4.4 Collecting attribute data
11.4.5 Selecting SNA measures for analysis
11.4.6 Interpretation: putting it all together
11.5 Future opportunities for SNA in food systems research
11.5.1 Scenario 1 - Whole Network study: business exchange among local/regional food producers and buyers
11.5.2 Scenario 2 - Connected Ego-Network study: information networks of community food leaders with a focus on inclusion and access
11.6 Implementing social network analysis going forward
11.6.1 Ethical considerations
11.6.2 Analysis and visualization tools
11.6.3 Integration of SNA with other methods
11.7 Conclusion
11.8 Acknowledgement
References
Chapter12 Participatory modeling of the food system: The case of community-based systems dynamics
12.1 Introduction
12.2 Community-based systems dynamics
12.2.1 Project planning: problem identification and the importance of reflexivity
12.2.2 Core modeling team recruitment
12.2.3 Group model building: activities and outputs
12.2.4 Next steps: implementation and evaluation
12.2.5 Potential extensions of CBSD
12.2.6 Useful resources
12.3 Case study: foodNEST 2.0, modeling the future of food in your neighborhood
12.3.1 Planning
12.3.2 Core modeling team (CMTrecruitment
12.3.3 Group model building activities
12.3.4 Causal loop diagrams
12.3.5 Community convenings
12.3.6 The Menu of Actions
12.3.7 Stock-and-Flow models and simulations
12.3.8 Moving forward
12.4 Conclusion
References
Chapter13 Using models to understand community interventions for improving public health and food systems
13.1 Introduction
13.2 Food systems change at the local level: Shape up Somerville intervention
13.3 Understanding how coalitions achieve change: the stakeholder-driven community diffusion theory
13.4 The SDCD theory in action
13.4.1 Shape up under 5 case study
13.5The SDCD theory in action – community expansion
13.5.1 Case study: Tucson, AZ
13.5.2 Case study: Milwaukee, WI
13.5.3 Case study: Greenville, SC
13.6 Implications for food systems modeling
13.7 Conclusion
Acknowledgement
References
Chapter14 Applying environmental models in the food business context
14.1 Motivations for food companies to leverage environmental models
14.1.1 Pursuing a triple bottom line business model
14.1.2 Communicating environmental impact to diverse stakeholders
14.2 Applications of environmental models within food companies
14.2.1 Using LCA to track corporate greenhouse gas reduction targets
14.2.2 Using LCA to substantiate product-level green marketing
14.2.3 Using farm-level surveys to account for agricultural activities in a company's supply chain
14.3 Limitations in the application of environmental models in the food industry
14.4 Conclusion
References
Chapter15 Inquiry within, between, and beyond disciplines
15.1 Introduction
15.2 Food systems research and participatory team science
15.2.1 Individual competencies for participatory team science
15.2.2 Team capacities for participatory team science
15.2.3 Developmental evaluation
15.3 Case study team: meeting the challenges of team science
15.3.1 Phase 1. building a transdisciplinary team
15.3.2 Phase 2. team coalescence
15.4 Team management and leadership
15.4.1 Shared authentic leadership
15.4.2 Roles, responsibilities and network structures
15.4.3 Project management
15.5 Navigating collaborative science tensions
15.5.1 Discussion
Acknowledgements
References
Chapter16 Towards a holistic understanding of food systems
16.1 Introduction
16.2 Epistemology and modeling
16.3 Considering results from multiple models
16.3.1 Scope and disciplinary perspective
16.3.2 Spatial and temporal scale
16.3.3Thinking across scope and scale – an example
16.4Application of models – from knowing to doing
16.5 Future directions for the field
16.5.1 Integrated modeling approaches
16.5.2 Interdisciplinary and transdisciplinary inquiry
16.6 Closing points
Acknowledgements
References
Glossary of terms
Index
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