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System Dynamics Modeling of Community Sustainability in NetLogo Thomas Bettge TJHSST Computer Systems Lab Senior Research Project 2008-2009.

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Presentation on theme: "System Dynamics Modeling of Community Sustainability in NetLogo Thomas Bettge TJHSST Computer Systems Lab Senior Research Project 2008-2009."— Presentation transcript:

1 System Dynamics Modeling of Community Sustainability in NetLogo Thomas Bettge TJHSST Computer Systems Lab Senior Research Project 2008-2009

2 Abstract Apply system dynamics to issue of sustainability Stocks and flows inherent to system dynamics well-suited to this topic Arbitrary system based on real-life systems and data

3 Expected Results Display data graphically Goal: to create a system that is sustainable over long periods of time Potentially harmonious relationship without extinction or overshoot Provided the user-defined parameters for famine and other variables are reasonable

4 Background Sustainability is a large and important issue Prior research applying system dynamics to sustainability: Tragedy of the Sahel Applications to other issues: Similar models with supply chains, etc. System dynamics as opposed to agent-based or Lotka-Volterra

5 Development Used NetLogo with System Dynamics Modeler Basic process: start simple, build up Foundation of model: Stock: population Flow: births (constant) Flow: deaths (constant) Obviously not at all accurate More complexity needed

6 Model Stocks: Population→Infected Population Workforce Food Land Flows: Population: births, deaths, infections Food: harvested, consumed, spoiled, (famines) Variables: Birth rate, death rate, reproduction rate, fraction live births, starvation rate, food per capita, workforce percentage, famine intensity, famine frequency, population density, optimal population density, AIDS rate, AIDS death rate, spoilation rate, consumption rate, worker productivity, farmable land, uninfected population, total population

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8 Analysis of Model Now relatively complex Famines: Occur at regular intervals with regular intensity Intensity and interval are user-determined Coded outside of system dynamics interface, rely on calculations with dt AIDS : – Outflow from population into infected-population as the virus spreads – Connected to reproduction rate – Higher death rate for the infected population

9 Testing Examine outcomes in the context of time frame to determine feasibility Alter and experiment with parameters to ensure that results and trends are consistent Compare graphs to expected mathematical relationships Test after each major addition

10 Problems and Errors NetLogo cannot perform calculations on especially large values Thus, starting parameters must be scaled down AIDS still relatively basic Problems with famines: Originally did not occur at the expected intervals or with the expected magnitude Extensive testing and code experimentation has now fixed these issues

11 Results Two outcomes for model: Ultimate overshoot: Ultimate decay:

12 Results with Population Density Limited amount of land creates a ceiling If people are living too packed together, the death rate increases Greater sustainability

13 Results: AIDS included Due to the nature of the infection, the isolated nature of the population, and the absence of immunity, the only outcome is ultimate decay:

14 Analysis of Results Given the large time scales, it is not unreasonable that the model should ultimately choose one extreme Population density corrects this, providing a basic model of infinite sustainability. Famine threshold- if 92% of food is destroyed every 10 years, the population still flourishes eventually. If 93%, it dies out. Reasonable that AIDS necessitates extinction

15 Conclusions Adding complexity has helped to make the model realistic; it is now truly sustainable with regards to this project AIDS is a natural and expected exception to this, by its very nature it is not sustainable, but is included to provide insight into the model’s behavior. Things to add- weather events User-defined variables increase interactivity and understanding of system dynamics and sustainability.


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