# Presentation: 918836

## Modeling the Impact of Loss in U.S. Soybean Production Resulting from Soy Rust Disease

***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-AC04-94AL85000.***

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**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**
- pgkapla@sandia.gov

**Stephen H. Conrad**
- shconra@sandia.gov

**Aldo A. Zagonel**
- aazagon@sandia.gov

**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 States

 |
| Potential consequence | Significant impact to U.S. agriculture and economy (e.g., 1970 corn blight)

 |
| Significance and inter-
dependencies | 2nd largest U.S. crop 
$12B in cash receipts, half from exports
Affects other grains (e.g., corn) and animals (e.g., beef)
This economy works on a global scale
Interactions 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 system
Understand the long term implications of soy rust to the agricultural economy
Assess vulnerabilities resulting from interdependencies
Evaluate 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 |
| --- |
|  |

| 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 |
| --- |
|  |

- 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: http://www.usda.gov/nass/pubs/trackrec/croptr05.pdf

- 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**

**1**

**6**

**3**

**2**

**1**

**9**

**5**

**8**

**7**

**10**