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

Description

Food Systems Modelling emphasizes sustainability, including the impact of agriculture and food production on profits, people and environment, with a particular focus on the ability of humanity to continue producing food in the midst of global environmental change. Sections introduce the purpose of models, the definition of a food system, the importance of disciplinary, interdisciplinary, and transdisciplinary inquiry, cover specific branches of modeling in the sustainability of food systems, and wrestle with the challenge of communicating modeling research and appropriately integrating multiple dimensions of sustainability. This book will be a welcomed reference for food scientists, agricultural scientists, nutritionists, environmental scientists, ecologists, economists, those working in agribusiness and food supply chain management, community and public health, and urban and regional planning, as well as academicians and graduate students interested in the sustainability of food systems. front cover Half title Title Copyright 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 Back cover