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System Dynamics Modeling of Community Sustainability in NetLogo

Thomas Bettge TJHSST Computer Systems Lab Senior Research Project 2008-2009. System Dynamics Modeling of Community Sustainability in NetLogo. Abstract. Apply system dynamics to issue of sustainability Stocks and flows inherent to system dynamics well-suited to this topic

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System Dynamics Modeling of Community Sustainability in NetLogo

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

  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 • Harmonious relationship without extinction or overshoot

  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 → Workforce • Food • Flows: • Population: births, deaths • Food: harvested, consumed, spoiled • Variables: • Birth rate, death rate, starvation rate, food per capita, workforce percentage, famine intensity, famine frequency

  7. Analysis of Model • Still relatively basic • 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

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

  9. Problems and Errors • NetLogo cannot perform calculations on especially large values • Thus, starting parameters must be scaled down • 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

  10. Results • Two outcomes for model: • Ultimate overshoot: • Ultimate decay:

  11. Analysis of Results • Given the large time scales, it is not unreasonable that the model should ultimately choose one extreme • However, a middle course “infinitely sustainable” outcome should be pursued • Famine threshold- if 92% of food is destroyed every 10 years, the population still flourishes eventually. If 93%, it dies out.

  12. Conclusions • Adding complexity has helped to make the model realistic, but it is not yet truly sustainable • Things to add- population density, potentially weather events • User-defined variables increase interactivity and understanding of system dynamics and sustainability.

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