Insight diagram
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.
Clone of NPD model (Nutrients, Phytoplankton, Detritus)
Insight diagram
This model explains the mussel growth (Mytillus Edulis) based on primary production of phytoplankton biomass.

Light, nutrients and temperature were used as forcing functions over a two year period.



Mussel Growth based on Phytoplankton Biomass
Insight diagram
Simple mass balance model for lakes based on the Vollenweider equation:

dMw/dt = Min - sMw + pMs - Mout

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

This version considers mercury, and adds diagenesis, using an extra state variable (mercury in the sediment), and incorporates desorption processes that release mercury 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 Hg concentration in lake
2. High loading, increasing Hg concentration in lake
3. Desorption rate is low, Hg in sediment increases
4. Measures implemented for source control, loading reduces
5. Hg in lake gradually decreases, but below a certain point, desorption increases, and lake Hg concentration does not improve
6. Recovery only occurs when the secondary load in the sediment is strongly reduced.
Clone of Mercury pollution model with diagenesis
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Hudson River Estuary Food Web
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In Chile, 60% of its population are exposed to levels of Particulate Matter (PM) above international standards. Air Pollution is causing 4,000 premature deaths per year, including health costs over US$8 billion.

The System Dynamics Causal Loop Diagram developed herein shows an initial study of the dynamics among the variables that influences the accumulation of PM in the air, in particular the case of Temuco, in the South of Chile. In Temuco, 97% of the PM inventories comes from the combustion of low quality firewood, which in turns is being burned due to its low price and cultural habits/tradition.
Clone of Air Pollution Dynamics - Firewood Combustion
Insight diagram
Food Security and Climate Change in East Africa
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Killed People by Made-up virus
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Fluxograma da produção de biodiesel a partir de microalgas
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Interplay between wolves eating sheep and farmers killing wolves who kill deer that eat crops that feed sheep.

Complex Sheep, Wolves, Deer, Crops
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Global Warming
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This model shows the cycling of Mercury within a coastal wetland system. This cycling shows Elemental Mercury, Hg 2+, and Methylmercury within the soil, water, and air, and also interaction with the plants in the system.

Total wetland transpiration: 1.95x10^-5 m^3 m^-2 s^-1
Settling rate and resuspension units (%of settling): g m^-2 day^-1
Project 2 Wetland Mercury
Insight diagram
Polyrhachis identification chart
Not aware of your Polyrhachis identification type, use this to help identify it.

(Not all species listed) (all located on Australia)
Polyrhachis identification chart
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Simple box-model of the global carbon cycle
Clone of Global Carbon Cycle
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Verkoppelung der drei Teilmodelle zu einem Gesamtmodell, der "Miniwelt" im Umfang von Bossel.
Eine Modifikation besteht darin, dass ein hohes Konsumniveau wieder zu einer Absenkung der Geburten führt.
Miniwelt nach Bossel, Reiche kriegen weniger Kinder
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Interplay between wolves eating sheep and farmers killing wolves.

Sheep and Wolves
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Collapse of the economy, not just recession, is now very likely. To give just one possible cause, in the U.S. the fracking industry is in deep trouble. It is not only that most fracking companies have never achieved a free cash flow (made a profit) since the fracking boom started in 2008, but that  an already very weak  and unprofitable oil industry cannot cope with extremely low oil prices. The result will be the imminent collapse of the industry. However, when the fracking industry collapses in the US, so will the American economy – and by extension, probably, the rest of the world economy. To grasp a second and far more serious threat it is vital to understand the phenomenon of ‘Global Dimming’. Industrial activity not only produces greenhouse gases, but emits also sulphur dioxide which converts to reflective sulphate aerosols in the atmosphere. Sulphate aerosols act like little mirrors that reflect sunlight back into space, cooling the atmosphere. But when economic activity stops, these aerosols (unlike carbon dioxide) drop out of the atmosphere, adding perhaps as much as 1° C to global average temperatures. This can happen in a very short period time, and when it does mankind will be bereft of any means to mitigate the furious onslaught of an out-of-control and merciless climate. The data and the unrelenting dynamic of the viral pandemic paint bleak picture.  As events unfold in the next few months,  we may discover that it is too late to act,  that our reign on this planet has, indeed,  come to an abrupt end?  
Covid 19 - irreversible and catastrophic consequences
Insight diagram
Simple model to illustrate oyster 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.


Oyster Growth based on Phytoplankton Biomass
Insight diagram
Simple (Kind of) food web of the Cane Toad Species. Includes different levels of consumers including predators.
Clone of Cane Toad Food Web
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Interplay between wolves eating sheep and farmers killing wolves.

Simple Sheep and Wolves
Insight diagram
School assessment
Australian King parrot food web
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Combining electromobility and renewable energies since 2014.

http://www.amsterdamvehicle2grid.nl/

Clone of Amsterdam V2G simulation 2.0
Insight diagram
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

Clone of Transformative Agency in Social-Ecological System
Insight diagram
Factors Affecting the Koala Mortality Incline