From Jay Forrester 1971 Book  World Dynamics , the earlier, simpler version of the  World 3   Limits to Growth  Model. adapted from Mark Heffernan's ithink version at  Systemswiki .  An element of Perspectives: The Foundation of Understanding and Insights for Effective Action. Register at  http://w

From Jay Forrester 1971 Book World Dynamics, the earlier, simpler version of the World 3 Limits to Growth Model. adapted from Mark Heffernan's ithink version at Systemswiki.

An element of Perspectives: The Foundation of Understanding and Insights for Effective Action. Register at http://www.systemswiki.org/

Westley, F. R., O. Tjornbo, L. Schultz, P. Olsson, C. Folke, B. Crona and Ö. Bodin. 2013. A theory of transformative agency in linked social-ecological systems.  Ecology and Society   18 (3): 27.  link
Westley, F. R., O. Tjornbo, L. Schultz, P. Olsson, C. Folke, B. Crona and Ö. Bodin. 2013. A theory of transformative agency in linked social-ecological systems. Ecology and Society 18(3): 27. link

 Work Cited   E., Kaplan. "Biomes of the World: Tundra." Alpine Biome. Hong Kong: Marshall Cavendish Corporation., n.d. Web. 23 May 2017.      http://www.blueplanetbiomes.org/tundra.htm
Work Cited


E., Kaplan. "Biomes of the World: Tundra." Alpine Biome. Hong Kong: Marshall Cavendish Corporation., n.d. Web. 23 May 2017.     http://www.blueplanetbiomes.org/tundra.htm
Simple mass balance model for lakes, based on the Vollenweider equation:  dMw/dt = Min - sMw - Mout  The model was first used in the 1960s to determine the phosphorus concentration in lakes and reservoirs for eutrophication assessment.  This version adds diagenesis, using an extra state variable (ph
Simple mass balance model for lakes, based on the Vollenweider equation:

dMw/dt = Min - sMw - Mout

The model was first used in the 1960s to determine the phosphorus concentration in lakes and reservoirs for eutrophication assessment.

This version adds diagenesis, using an extra state variable (phosphorus in the sediment) and incorporates desorption processes that release phosphorus trapped in the sediment back to the water column.

The temporal dynamics of the model simulate the typical development of pollution in time.

1. Low loading, low P concentration in lake
2. High loading, increasing P concentration in lake
3. Desorption rate is low, P in sediment increases
4. Measures implemented for source control, loading reduces
5. P in lake gradually decreases, but below a certain point, desorption increases, and lake P concentration does not improve
6. Recovery only occurs when the secondary load in the sediment is strongly reduced.
Simple model to illustrate   algal  ,   growth based on primary production of Phytoplankton as a state variable, forced by light and nutrients, running for a yearly period.  Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:   Primary Production=(([Pmax]*[I]/[Iopt]*exp
Simple model to illustrate   algal  ,   growth based on primary production of Phytoplankton as a state variable, forced by light and nutrients, running for a yearly period.

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where: 

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)
I: Light energy at depth of interest (uE m-2 s-1)
Iopt: Light energy at which Pmax occurs (uE m-2 s-1)
S: Nutrient concentration (umol N L-1)
Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:
- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.
- Light limited by the concentration of phytoplankton.
- Temperature effect on phytoplankton and Oyster growth.

  Biogas, model  as well birefineray option to seperate c02 , chp from bogas model are proposed
This model is a classic simulation of the production cycle in the ocean, including the effects of the thermocline in switching off advection of dissolved nutrients and detritus to the surface layer.  It illustrates a number of interesting features including the coupling of three state variables in a
This model is a classic simulation of the production cycle in the ocean, including the effects of the thermocline in switching off advection of dissolved nutrients and detritus to the surface layer.

It illustrates a number of interesting features including the coupling of three state variables in a closed cycle, the use of time to control the duration of advection, and the modulus function for cycling annual temperature data over multiple years.

The model state variables are expressed in nitrogen units (mg N m-3), and the calibration is based on:

Baliño, B.M. 1996. Eutrophication of the North Sea, 1980-1990: An evaluation of anthropogenic nutrient inputs using a 2D phytoplankton production model. Dr. scient. thesis, University of Bergen.
 
Fransz, H.G. & Verhagen, J.H.G. 1985. Modelling Research on the Production Cycle of Phytoplankton in the Southern Bight of the Northn Sea in Relation to Riverborne Nutrient Loads. Netherlands Journal of Sea Research 19 (3/4): 241-250.

This model was first implemented in PowerSim some years ago by one of my M.Sc. students, who then went on to become a Buddhist monk. Although this is a very Zen model, as far as I'm aware, the two facts are unrelated.
Daisyworld is a classic model of planetary feedbacks, due to Andrew Watson and James Lovelock (1983). See http://en.wikipedia.org/wiki/Daisyworld.
Daisyworld is a classic model of planetary feedbacks, due to Andrew Watson and James Lovelock (1983). See http://en.wikipedia.org/wiki/Daisyworld.
 Clone of IM-1954 to tidy up layout. The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors. 
   
 Use the sliders to experiment with the initial amount of non-renewable resources to see how these affec

Clone of IM-1954 to tidy up layout. The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

 

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a low birth-rate, environmentally focused policy.

Simple energy balance model of a planet with albedo, ocean, and atmosphere.  This simulation models the stock and flow of energy between a
star, a planet’s surface (primarily its oceans, which are the largest reservoir
of heat), and space.The assumptions governing this model are:  1. The planet abso
Simple energy balance model of a planet with albedo, ocean, and atmosphere.

This simulation models the stock and flow of energy between a star, a planet’s surface (primarily its oceans, which are the largest reservoir of heat), and space.The assumptions governing this model are:

1. The planet absorbs a fraction of the shortwave radiation arriving from its star, with that fraction given by (1-A), where A is albedo. 

2. The planet radiates longwave infrared radiation into space, with the amount of radiation into space given by σΤe4, where σ is the Stefan-Boltzmann constant and Te is the temperature of the effective radiating level.

3. The atmospheric lapse rate is 6 K/km.

4. If there is an imbalance between shortwave radiation absorbed and longwave radiation emitted, the imbalance affects the temperature of the planet. However, it does not do so instantaneously – the imbalance must heat or cool the mixed layer of the ocean.

5. At the start of the simulation, the planet is extremely close to equilibrium given its default parameters. If any of these parameters are changed, the planet will be out of equilibrium, and will have to adjust.

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.

This model shows how a persistent pollutant such as mercury or DDT can be bioamplified along a trophic chain to levels that result in reduction of top predator populations.
This model shows how a persistent pollutant such as mercury or DDT can be bioamplified along a trophic chain to levels that result in reduction of top predator populations.
This model describes the flow of energy from generation to consumption for neighborhoods in the metro Atlanta area. It also calculates the cost of energy production and the number of years it will take to recover that cost.
This model describes the flow of energy from generation to consumption for neighborhoods in the metro Atlanta area. It also calculates the cost of energy production and the number of years it will take to recover that cost.
This is a simulation that represents the populations of lions in the world over the last 200 years.
This is a simulation that represents the populations of lions in the world over the last 200 years.
 Similar layout to  CEU insight  based on 2016 Land Use Science  article  on Causal Analysis by Patrick Meyfroidt This is focussed on causal chains

Similar layout to CEU insight based on 2016 Land Use Science article on Causal Analysis by Patrick Meyfroidt This is focussed on causal chains

11 months ago