Performing Department
Crop & Soil Sciences
Non Technical Summary
Our food and agricultural system faces a three-fold challenge in the 21st Century: improve the health and food security of a growing world population (1) with finite and increasingly constrained natural resources (2) while mitigating and adapting to climate change (3). The enormity of this imperative is only intensified by its urgency. Humanity lacks the luxury of unlimited time to act and faces conflicting answers to the question of how best to act. For this reason, tools are needed that can swiftly and accurately help to determine how changes at both the consumption and production ends of the food and agricultural system will influence the environment and food security. We will build on previous work conducted in the Department of Crop and Soil Science at Cornell University which developed two such tools for New York State (NYS). The first tool is a spreadsheet model that calculates the size of an individual's "foodprint", the area of agricultural land required to produce a year's worth of food for the average person. The second tool is a spatial model that maps potential, local foodsheds, in other words, the areas of agricultural land that could be used to meet the food needs of each of the state's population centers. These tools will be adapted for states in different regions and ultimately for the 48 conterminous U.S. states. Collaborations with other research teams will explore the possibilities for adapting the models to estimate system requirements for other resources (e.g. water and energy) and greenhouse gas emissions. Such research should help society to craft strategies for addressing the 21st century challenges to the food system. To ensure that the research actually aids decision-making processes, we propose to engage key food system stakeholders in the research and extension aspects of our project. In addition, we will develop a comprehensive communication plan to enable us to share information with and receive input from a broader audience. This will include development of a web site and interactive web-based tools for teaching and outreach. It is difficult to overstate the importance of this proposed work. While the concept of sustainability has helped people appreciate the interconnectedness of problems and the importance of non-economic indicators of well-being, society has been slow to make changes. Part of the reason for this inertia is that we lack tools for understanding the likely affect of our actions. Computer models provide a means of testing the likely affects of many possible solutions without having to live with the consequences. If humanity is to meet the daunting challenge of feeding a growing population from a finite land base while addressing climate change and energy and water scarcity, tools like the foodprint and foodshed models will be necessary to guide our choice of solutions.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
50%
Developmental
50%
Goals / Objectives
This project has three major goals. First, we seek to improve scientific understanding of how food consumption patterns influence the resource requirements (land, water, and energy) of food production, human carrying capacity, and the capacity of states or regions to create a more localized food system. Second, we plan to adapt the foodprint and foodshed computer models, initially developed for New York State, for other geographic areas to aid decision makers at multiple scales and across diverse jurisdictions to consider how fundamental food system resources, particularly land, are used. Third, we hope to provide analysis that helps food system stakeholders craft policy that increases the sustainability of the food system at a pace commensurate with the magnitude of the challenges and the time available for action. To achieve these goals, the project has six major objectives. The first objective is to replicate the existing foodprint and foodshed models developed for New York State to the three priority states identified by the WK Kellogg Foundation: Michigan, Mississippi, and New Mexico. The second objective is to adapt the models to accommodate the diversity of climates and land resources found in the U.S. and perform foodprint and foodshed analyses of the lower 48 states. The third objective is to use life cycle analysis to compare the greenhouse gas emissions and the land, energy, and water requirements of food from conventional versus local supply chains. The fourth objective is to engage a diverse group of food system stakeholders to both share the findings of existing research and solicit feedback on how the work can be adapted to better aid their decision-making. The fifth objective is to revise the foodshed models based this feedback. The sixth, and final, objective is to develop a communication plan to share information on the tools developed and analyses performed in this project. Through pursuit of these objectives, the project will produce several key outputs. Methods developed and analyses performed will be published in peer-reviewed journals. Key findings will be communicated through lay publications and a project website developed to serve as the central location for information about the project. Finally, the existing internet map server will be enhanced to make some of the geographic data accessible to a non-technical audience.
Project Methods
The Foodprint and Foodsheds Project use both new and established methodologies. A summary of the methods follows. The foodprint analysis of New York State (NYS) used a spreadsheet model to calculate annual per capita land requirements for a range of dietary patterns. This model used a series of conversion factors to estimate the quantity of agricultural commodities needed to provide the foods in each diet, then used crop yield data along with information on livestock feeding practices to estimate the area of land required to produce these commodities. Per capita land requirements were then used to calculate the number of people which could be fed from agricultural land in NYS, based on the quality and quantity of land available. These methods will be adapted and applied to states in other regions and ultimately to the 48 conterminous United States. The foodshed analysis of NYS used a combination of spatial modeling and optimization techniques to estimate the capacity for NYS population centers to supply their food needs from within the state. Two versions of the foodshed model have been developed. One optimizes for minimum food miles, and the other optimizes for maximum land use value that can be obtained from meeting in-state food needs. These models will be adapted for states in other regions and ultimately to the conterminous U.S. To complement the foodprint and foodshed analyses, collaboration with UC Davis will investigate the greenhouse gas emissions associated with the production, post-harvest handling, processing, and retail distribution of 3-5 food commodities. The selected commodities will serve as proxies for a range of food groups in the diet. This research will use a life cycle approach to modeling greenhouse gas emissions. Where applicable, the life cycle assessment methodology put forth by the International Organization for Standardization will be used to guide life cycle energy model development and calculations. An Internet Map Server (IMS) will be developed in collaboration with Salisbury University to serve as both a teaching and an outreach tool for the project. The IMS will enable a non-technical audience to view and process geographic data through a web browser. The practical value of the tools and analyses will be assessed through engagement with food system stakeholder groups. Several workshops will be held over the life of the project to share research findings and solicit feedback on the strengths and weaknesses of the work for informing decision-making. In addition, a formal communication plan will be developed to both share information about the project and to receive input from a wider audience. Ideas received through both channels will be thoughtfully considered, and selected ideas will be incorporated into the design of the models, the life cycle analysis, and the IMS tool.