This paper describes on-going research also involving Nancy Brodsky, Sharon Deland, Vanessa Vargas and Jackson Thies We thank Andy Ford and four anonymous reviewers for their constructive critiques and helpful comments A special thank you to Louise Maffitt for helping us create this poster Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL Example Subheading… Example Text Box…….. Example Heading…… Sandia National Laboratories, Systems Engineering & Analysis, Critical Infrastructure Protection Decision Support Systems (CIP/DSS) 23rd International Conference of the System Dynamics Society – Boston (July 17-21, 2005) Paul G. Kaplan Stephen H. Conrad Aldo A. Zagonel Modeling the Impact of Loss in U.S. Soybean Production Resulting from Soy Rust Disease Synopsis Client Department of Homeland Security Problem Presence of soybean rust in the continental United StatesPresence of soybean rust in the continental United States Potential consequence Significant impact to U.S. agriculture and economy (e.g., 1970 corn blight)Significant impact to U.S. agriculture and economy (e.g., 1970 corn blight) Significance and inter- dependencies 2 nd largest U.S. crop2 nd largest U.S. crop $12B in cash receipts, half from exports$12B in cash receipts, half from exports Affects other grains (e.g., corn) and animals (e.g., beef)Affects other grains (e.g., corn) and animals (e.g., beef) This economy works on a global scaleThis economy works on a global scale Interactions with the chemical, water and energy infrastructuresInteractions with the chemical, water and energy infrastructures Goals/ objectives Immediate: Examine the magnitude of the soy rust threat Future: Understand the dynamic complexity involved in this systemUnderstand the dynamic complexity involved in this system Understand the long term implications of soy rust to the agricultural economyUnderstand the long term implications of soy rust to the agricultural economy Assess vulnerabilities resulting from interdependenciesAssess vulnerabilities resulting from interdependencies Evaluate adequacy of agricultural policiesEvaluate adequacy of agricultural policies Modeling foundation Meadow’s (1970) “Dynamics of Commodity Production Cycles” Disease treated as “scenario” Expert-based analysis of risk used to estimate the “net fraction of crop loss” Disease scenario versus natural noise (e.g., corn) Stock-and-flow dynamics Stock-and-flow dynamics Willingness to supply Conceptual mechanisms Prices (spot, forecasted, futures) shape willingness to supply Price subsidies constitute a production floor Land availability constitutes a production ceiling Desired production will depend upon: … Price elasticity of supply … Analysis of risk and alternatives … Farm insurance and other farm support policies … Increased costs of production, break-even prices, and profit margins Interdependency with Chemical Industry Dynamic hypothesis Soy rust could add instability in the agricultural economy due to the newly created interdependency with the chemical industry for fungicide (~ flu vaccine phenomenon) Structure Behaviors Feedback-rich dynamics Feedback-rich dynamics Sources: Spot – USDA NASS Soybean Monthly Price Reports; Forecasted – USDA World Agricultural Supply & Demand Estimates (WASDE); Futures – USDA Economic Research Service (ERS) Meadow’s (1970) vs. Plato & Chambers (2004) Sources: USDA NASS historical data site: Stochastic climate conditions could even cause expanding oscillations Willingness to demand Conceptual mechanisms Prices (spot, forecasted, futures) also shape willingness to demand Different price elasticities of demand: … Foreign demand … Domestic demand - Animal feed - Other uses Substitution effects Infrastructure intra- and interdependencies Other grains (e.g., corn) Other commodities (e.g., beef) Chemical industry Irrigation (energy & water) Globalization Globalization revolutionized the soybean industry Highly adaptive global market for soybean production Aggressive competitors Rising world production and inventories Dependency on inputs from other countries (e.g., core chemicals produced in China) Conceptual Crop Model (soybean/corn) 1970 corn blight Without forecasts and the futures market, crop loss due to disease at the time “t” would constrain sales one year later. When working properly, forecasts and the futures market should anticipate and help correct for “future” surpluses or deficits. Price Coverage P&C M