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]
Growth Environment Phytoplankton Primary Production Bivalves
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.


Clone of Clone of Clone of micro algae , biogas , bioelectrcidades
Pagandai V Pannir Selvam
Simple model to illustrate Michaelis-Menten equation for nutrient uptake by phytoplankton. The equation is: P = Ppot S / (Ks + S) Where: P: Nutrient-limited production (e.g. d-1, or mg C m-2 d-1) Ppot: Potential production (same units as P) S: Nutrient concentation (e.g. umol N L-1) Ks: Half sat
Environment Primary Production Nutrients
Simple model to illustrate Michaelis-Menten equation for nutrient uptake by phytoplankton.

The equation is:

P = Ppot S / (Ks + S)

Where:

P: Nutrient-limited production (e.g. d-1, or mg C m-2 d-1)
Ppot: Potential production (same units as P)
S: Nutrient concentation (e.g. umol N L-1)
Ks: Half saturation constant for nutrient (same units as S)

The model contains no state variables, just illustrates the rate of production, by making the value of S equal to the timestep (in days). Move the slider to the left for more pronounced hyperbolic response, to the right for linear response.
Clone of Phyto 2 - Michaelis-Menten curve for phytoplankton
Joana Ferreira Cardoso
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
Ocean Environment Primary Production Phytoplankton Biogeochemistry
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)
yordan arango
This diagram provides a stylised description of important feedbacks within a shallow-lake system. Mahinga Kai
Eutrophication Turbidity Environment Lakes
This diagram provides a stylised description of important feedbacks within a shallow-lake system.
Mahinga Kai
Clone of Clone of Key feedbacks in a shallow lake relating to Koura
Graeme Doole
Z212 from System Zoo 1 p142-148
Environment Health Care Physics

Z212 from System Zoo 1 p142-148

Clone of House Heating Dynamics
Igor Krejčí
Insight diagram
Environment Books
Clone of HarperCollins updated!
team123
6
STEM-SM combines a simple ecosystem model (modified version of VSEM; Hartig et al. 2019) with a soil moisture model (Guswa et al. (2002) leaky bucket model). Outputs from the soil moisture model influence ecosystem dynamics in three ways.  (1) The ratio of actual transpiration to maximum evapotran
GEG5224 Ecosystem Ecology Environment Carbon Productivity Decomposition Evapotranspiration Water Soil moisture
STEM-SM combines a simple ecosystem model (modified version of VSEM; Hartig et al. 2019) with a soil moisture model (Guswa et al. (2002) leaky bucket model). Outputs from the soil moisture model influence ecosystem dynamics in three ways. 
(1) The ratio of actual transpiration to maximum evapotranspiration (T/ETmax) modifies gross primary productivity (GPP).
(2) Degree of saturation of the soil (Sd) modifies the rate of soil heterotrophic respiration.
(3) Water limitation of GPP (by T/ETmax) and of soil nutrient availability (approximated by Sd) combine with leaf area limitation (approximated by fraction of incident photosynthetically-active radiation that is absorbed) to modify the allocation of net primary productivity to aboveground and belowground parts of the vegetation.

Ecosystem dynamics in turn influence flows of water in to and out of the soil moisture stock. The size of the aboveground biomass stock determines fractional vegetation cover, which modifies interception, soil evaporation and transpiration by plants.

References:
Guswa, A.J., Celia, M.A., Rodriguez-Iturbe, I. (2002) Models of soil moisture dynamics in ecohydrology: a comparative study. Water Resources Research 38, 5-1 - 5-15.

Hartig, F., Minunno, F., and Paul, S. (2019). BayesianTools: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics. R package version 0.1.7. https://CRAN.R-project.org/package=BayesianTools

Clone of Simple Terrestrial Ecosystem Model - Soil Moisture (STEM-SM)
MAC
Find the steady state completely mixed model with reaction decay and the three-compartment steady state model with reaction decay of a non-conservative tracer.
Environment Chemistry Engineering
Find the steady state completely mixed model with reaction decay and the three-compartment steady state model with reaction decay of a non-conservative tracer.
Clone of ENVE 431 - HW 5 - Problem #4
Bridgette M Medeghini
THE 2020 MODEL (BY GUY LAKEMAN) EMPHASIZES THE PEAK IN POLLUTION BEING CREATED BY OVERPOPULATION. WITH THE CARRYING CAPACITY OF ARABLE LAND NOW BEING 1.5 TIMES OVER A SUSTAINABLE FUTURE (PASSED IN 1990) AND NOW INCREASING IN LOSS OF HUMAN SUSTAINABILITY DUE TO SEA RISE AND EXTREME GLOBAL WATER R
Yield Transport Silicene Graphene Resource Solar Nuclear Energy Food Agriculture Cyclone Tornado Typhoon Hurricane Loss Drought Flood Animals Plants Fish Sea Ocean Regeneration Pollution Lifetime Rural Industrial Urban Labor Jobs Land Resources Services Health Fertility Politics Economics Strategy Engineering Technology Science Mortality Death Failure Climate Weather Population Population Growth Demographics Environment

THE 2020 MODEL (BY GUY LAKEMAN) EMPHASIZES THE PEAK IN POLLUTION BEING CREATED BY OVERPOPULATION.
WITH THE CARRYING CAPACITY OF ARABLE LAND NOW BEING 1.5 TIMES OVER A SUSTAINABLE FUTURE (PASSED IN 1990) AND NOW INCREASING IN LOSS OF HUMAN SUSTAINABILITY DUE TO SEA RISE AND EXTREME GLOBAL WATER RELOCATION IN WEATHER CHANGES IN FLOODS AND DROUGHTS AND EXTENDED TROPICAL AND HORSE LATTITUDE CYCLONE ACTIVITY AROUND HADLEY CELLS

The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

THIS MODEL BY GUY LAKEMAN, FROM METRICS OBTAINED USING A MORE COMPREHENSIVE VENSIM SOFTWARE MODEL, SHOWS CURRENT CONDITIONS CREATED BY THE LATEST WEATHER EXTREMES AND LOSS OF ARABLE LAND BY THE  ALBEDO EFECT MELTING THE POLAR CAPS TOGETHER WITH NORTHERN JETSTREAM SHIFT NORTHWARDS, AND A NECESSITY TO ACT BEFORE THERE IS HUGE SUFFERING.
BY SETTING THE NEW ECOLOGICAL POLICIES TO 2015 WE CAN SEE THAT SOME POPULATIONS CAN BE SAVED BUT CITIES WILL SUFFER MOST. 
CURRENT MARKET SATURATION PLATEAU OF SOLID PRODUCTS AND BEHAVIORAL SINK FACTORS ARE ALSO ADDED

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.

WORLD2020 to PLANET2020
Guy Lakeman
12
It seems that I've made a mess of mine! But it's a mess with a purpose.... This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale. Experiment with adjusting the initial number of moose and wolves on the island.
Populations Environment Ecology
It seems that I've made a mess of mine! But it's a mess with a purpose....

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

Experiment with adjusting the initial number of moose and wolves on the island.
Mat375: Isle Royale: Predator Prey Interactions
Andrew E Long
15
Find the steady state completely mixed model with reaction decay and the three-compartment steady state model with reaction decay of a non-conservative tracer.
Engineering Chemistry Environment
Find the steady state completely mixed model with reaction decay and the three-compartment steady state model with reaction decay of a non-conservative tracer.
ENVE 431 - HW 5 - Problem #4
Logan Adams
Insight diagram
Environment Books
Clone of Clone of Clone of HarperCollins updated!
Daniel Verweij
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
Ocean Environment Primary Production Phytoplankton Biogeochemistry
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)
Luisa Lopera
Simple model to illustrate a simple simulation of the microalgae biomass production, focusing on the dependent variables such as light, nutrients and other factor that is running for a yearly period. The biomass model uses an example, Phytoplankton growth based on Steele's and Michaelis-Menten equa
Environment Primary Production Phytoplankton Bivalves Growth
Simple model to illustrate a simple simulation of the microalgae biomass production, focusing on the dependent variables such as light, nutrients and other factor that is running for a yearly period.

The biomass model uses an example, Phytoplankton growth based 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).

Once this is understood, it looks upon the viability of biogas production from the microalgae biomass.


Clone of Clone of Clone3f micro algae , biogas and bioelectricity
Mark Nickelo Blanco
European Masters in System Dynamics 2016 New University of Lisbon, Portugal Simple model to represent oyster individual growth by simulating feeding and metabolism.
Environment Aquaculture
European Masters in System Dynamics 2016
New University of Lisbon, Portugal

Simple model to represent oyster individual growth by simulating feeding and metabolism.
EMSD 2016
Joao G. Ferreira
10
Simple model to illustrate an annual cycle for phytoplankton biomass in temperate waters. Potential primary production uses Steele's equation and a Michaelis-Menten (or Monod) function for nutrient limitation. Respiratory losses are only a function of biomass.
Environment Primary Production Light
Simple model to illustrate an annual cycle for phytoplankton biomass in temperate waters.
Potential primary production uses Steele's equation and a Michaelis-Menten (or Monod) function for nutrient limitation. Respiratory losses are only a function of biomass.
Clone of Phytoplankton model URI
Pedro Pato
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
Ocean Environment Biogeochemistry Phytoplankton Primary Production
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)
Laura Catalina Cantor Acosta
Sandusky Treatment Plant for Arsenic and Water purification
Michigan Environment Water Sandusky
Sandusky Treatment Plant for Arsenic and Water purification

Clone of Sandusky Water Treatement Plant
Pagandai V Pannir Selvam
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.
Eutrophication Lakes And Reservoirs Environment
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.
Clone of Vollenweider model
Mason Stahl
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]
Bivalves Primary Production Environment Phytoplankton Growth
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.


Clone of Clone of Clone of micro algae , biogas , bioelectrcidades
Pagandai V Pannir Selvam
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
Ocean Biogeochemistry Environment Primary Production Phytoplankton
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)
Soraya Castillo Giraldo
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
Primary Production Ocean Biogeochemistry Environment Phytoplankton
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)
Carlos Bonilla
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
Environment Primary Production Phytoplankton Ocean Biogeochemistry
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)
Juan Antonio Jaramillo Zapata
This non-dimensionalized, sleekest most neatest model illustrates predator prey interactions using logistic growth for the moose population, for the wolf and moose populations on Isle Royale. Thanks Scott Fortmann-Roe for the original model. I've added in an adjustment to handle population sizes,
Math Modeling Populations Ecology Environment
This non-dimensionalized, sleekest most neatest model illustrates predator prey interactions using logistic growth for the moose population, for the wolf and moose populations on Isle Royale.

Thanks Scott Fortmann-Roe for the original model.

I've added in an adjustment to handle population sizes, by dividing by moose carrying capacity.

Time is scaled by the moose birth parameter:
tau=bm*t

There are therefore only three parameters left to account for any dynamics:

beta = bw/bm (relative wolf to moose births)
delta = dm/bm (relative death to birth ratio for moose)
gamma = dw/bm (wolf deaths to moose births)

The equations are thus

dM/dtau = M [ (1-M) - delta W ]
dW/dtau = W [beta M - gamma ]

There is a stable equilibrium pair of population values, relative to the carrying capacity:

M^* = gamma / beta
W^* = (1-gamma / beta) / delta

I have a sleek version with a logistical growth term for the moose, at

http://www.nku.edu/~longa/classes/2018spring/mat375/mathematica/Moose-n-Wolf-InsightMaker-sleek.nb
Sleek, non-dimensionalized Isle Royale: Predator/Prey Model for Moose and Wolves
Andrew E Long