System Dynamics Modeling of Community Sustainability in NetLogo Thomas Bettge TJHSST Computer...

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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

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System Dynamics Modeling of Community Sustainability in

NetLogo

Thomas BettgeTJHSST Computer Systems Lab Senior Research

Project2008-2009

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:

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

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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