The Great Barrier Reef Sustainability Model:        Credit and Resources (not including non-graph images):         1. Chapter Two- Basic System Dynamics:  Harris,S.E., Burch, S.L (2014).  Understanding climate change: Science, policy, and practice         2. The Scripps Institute of Oceanography
The Great Barrier Reef Sustainability Model:

Credit and Resources (not including non-graph images):

1. Chapter Two- Basic System Dynamics:
Harris,S.E., Burch, S.L (2014). Understanding climate change: Science, policy, and practice

2. The Scripps Institute of Oceanography
Graphs and data for levels of CO2  provided via the published material from the Mauna Loa Observatory in Hawaii

3. How many Gigatons of CO2 ...?
http://www.informationisbeautiful.net/visualizations/how-many-gigatons-of-co2/
This is the compiled results of levels of CO2 used in this model. The website itself has a list of resources used to compile the summarized mean data.

4.Week Two and Three ISCI 360 Lectures:
Emily Scribner and Stuart Sutherland 

5. Dr. Harvey's Proposition 
Harvey,D.D.L (2007). Mitigating the atmospheric CO2 increase and ocean acidification  by adding limestone powder to upwelling regions 
Website: http://faculty.geog.utoronto.ca/Harvey/Harvey/
Article:http://www.treehugger.com/clean-technology/giving-geo-engineering-another-go-dumping-limestone-into-the-oceans-to-fight-acidification.html

6. 5. Limestone Quarry and Processing
University of Tennessee and published by the National Stone Council 
http://www.naturalstonecouncil.org/content/file/LCI%20Reports/Limestone_LCIv1_October2008.pdf
6.
l


E
From Jay Forrester 1988 killian lectures youtube  video  describing system dynamics at MIT. For more detailed biography See Jay Forrester memorial  webpage  For MIT HIstory see  IM-184930  For Applications se  IM-185462
From Jay Forrester 1988 killian lectures youtube video describing system dynamics at MIT. For more detailed biography See Jay Forrester memorial webpage For MIT HIstory see IM-184930 For Applications se IM-185462
4 9 months ago
This model simulates the economics of buying a home. It was created to compare buying a home against using investment returns to pay for rent.    Try cloning this insight, setting the parameter values for real-world scenarios, and then running sensitivity analysis (see tools) to determine the likely
This model simulates the economics of buying a home. It was created to compare buying a home against using investment returns to pay for rent.

Try cloning this insight, setting the parameter values for real-world scenarios, and then running sensitivity analysis (see tools) to determine the likely wealth outcomes. Compare buying a home to renting. Note that each run will keep the parameters the same while simulating market volatility.

version 1.8
 Nobody seems to notice bubbles until they burst. One possible reason is that those caught up in a bubble are completely blinded by the grip, the overpowering logic and force  excerted by the positive feedback loop that drives it. Financial bubbles occur time and time again - and nobody seems to lea

Nobody seems to notice bubbles until they burst. One possible reason is that those caught up in a bubble are completely blinded by the grip, the overpowering logic and force excerted by the positive feedback loop that drives it. Financial bubbles occur time and time again - and nobody seems to learn. Another example on a different time scale is an argument that spins out of control and ends in violence. The participants seem to be blind to the consequences; the immediate and imperative logic of the feedback loop imposes itself. The vortex created by the feedback loop even seems to draw in outsiders, such as new investors. Is this the reason why we don't notice bubbles? This explanation is meant to stimulate discussion!

 This model is based on the article Dynamic modeling of Infectious Diseases, An application to Economic Evaluation of Influenza Vaccination Farmacoeconomics 2008, 26(1): 45-56 .  And EBOLA

This model is based on the article Dynamic modeling of Infectious Diseases, An application to Economic Evaluation of Influenza Vaccination Farmacoeconomics 2008, 26(1): 45-56 .

And EBOLA


Clone of Pesticide Use in Central America for Lab work        This model is an attempt to simulate what is commonly referred to as the “pesticide treadmill” in agriculture and how it played out in the cotton industry in Central America after the Second World War until around the 1990s.     The cotto
Clone of Pesticide Use in Central America for Lab work


This model is an attempt to simulate what is commonly referred to as the “pesticide treadmill” in agriculture and how it played out in the cotton industry in Central America after the Second World War until around the 1990s.

The cotton industry expanded dramatically in Central America after WW2, increasing from 20,000 hectares to 463,000 in the late 1970s. This expansion was accompanied by a huge increase in industrial pesticide application which would eventually become the downfall of the industry.

The primary pest for cotton production, bol weevil, became increasingly resistant to chemical pesticides as they were applied each year. The application of pesticides also caused new pests to appear, such as leafworms, cotton aphids and whitefly, which in turn further fuelled increased application of pesticides. 

The treadmill resulted in massive increases in pesticide applications: in the early years they were only applied a few times per season, but this application rose to up to 40 applications per season by the 1970s; accounting for over 50% of the costs of production in some regions. 

The skyrocketing costs associated with increasing pesticide use were one of the key factors that led to the dramatic decline of the cotton industry in Central America: decreasing from its peak in the 1970s to less than 100,000 hectares in the 1990s. “In its wake, economic ruin and environmental devastation were left” as once thriving towns became ghost towns, and once fertile soils were wasted, eroded and abandoned (Lappe, 1998). 

Sources: Douglas L. Murray (1994), Cultivating Crisis: The Human Cost of Pesticides in Latin America, pp35-41; Francis Moore Lappe et al (1998), World Hunger: 12 Myths, 2nd Edition, pp54-55.

Based on Nate Osgood's April 2014 Singapore Presentation  Youtube video  and Lyle Wallis material Gojii at  DecisioTech  See also  Complex Decison Technologies IM  as a more polished version
Based on Nate Osgood's April 2014 Singapore Presentation Youtube video and Lyle Wallis material Gojii at DecisioTech See also Complex Decison Technologies IM as a more polished version
Circular equations WIP for Runy.    Added several versions of the model. Added a flow to make C increase. Added a factor to be able to change the value 0.5. Older version cloned at  IM-46280
Circular equations WIP for Runy.

Added several versions of the model. Added a flow to make C increase. Added a factor to be able to change the value 0.5. Older version cloned at IM-46280
 Regulation of resource allocation to production in response to inventory adequacy and delivery delay. A non-price-mediated resource allocation system. From Sterman JD Business Dynamics p172 Fig 5-27

Regulation of resource allocation to production in response to inventory adequacy and delivery delay. A non-price-mediated resource allocation system. From Sterman JD Business Dynamics p172 Fig 5-27

Starts from the bathtub model of economics developed by TSSEF.se ( see the explanation here ). It adds rich and poor and you can change the constraints on the system by moving the sliders (taxes, wages, rates, dividends etc) to see how the economic system functions at national level.    I have tried
Starts from the bathtub model of economics developed by TSSEF.se (see the explanation here). It adds rich and poor and you can change the constraints on the system by moving the sliders (taxes, wages, rates, dividends etc) to see how the economic system functions at national level.

I have tried every combination I can but I think you will agree with me that the system is unstable. OR maybe I forgot something.