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

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

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

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

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

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

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

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

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

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

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

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:

Weather Events Random interval Random Magnitude Same random variables applied to Food, Population, and Infected-Population Update each turn

Weather Events

Analysis of Results Given the large time scales, it is not unreasonable that the model should ultimately Population density corrects this, providing a basic model of infinite sustainability. Now, extinction is the ultimate outcome, yet without AIDS and weather events the model is infinitely sustainable. Reasonable that AIDS and weather events necessitates extinction

Conclusions Adding complexity has helped to make the model realistic; it is now truly sustainable with regards to this project AIDS and weather events are natural and expected exceptions to this, by their very nature they are not sustainable, but are included to provide insight into the model’s behavior. Randomness increases realism, offers insight User-defined variables increase interactivity and understanding of system dynamics and sustainability.