This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION  The existing global capitalistic growth paradigm is totally flawed  Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a compon
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a component the creation of unpredictable chaotic turbulence puts the controls ito a situation that will never return the system to its initial conditions as it is STIC system (Lorenz)

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite working containers (villages communities)

    Dynamic simulation modelers are particularly interested in understanding and being able to distinguish between the behavior of stocks and flows that result from internal interactions and those that result from external forces acting on a system.  For some time modelers have been particularly int

Dynamic simulation modelers are particularly interested in understanding and being able to distinguish between the behavior of stocks and flows that result from internal interactions and those that result from external forces acting on a system.  For some time modelers have been particularly interested in internal interactions that result in stable oscillations in the absence of any external forces acting on a system.  The model in this last scenario was independently developed by Alfred Lotka (1924) and Vito Volterra (1926).  Lotka was interested in understanding internal dynamics that might explain oscillations in moth and butterfly populations and the parasitoids that attack them.  Volterra was interested in explaining an increase in coastal populations of predatory fish and a decrease in their prey that was observed during World War I when human fishing pressures on the predator species declined.  Both discovered that a relatively simple model is capable of producing the cyclical behaviors they observed.  Since that time, several researchers have been able to reproduce the modeling dynamics in simple experimental systems consisting of only predators and prey.  It is now generally recognized that the model world that Lotka and Volterra produced is too simple to explain the complexity of most and predator-prey dynamics in nature.  And yet, the model significantly advanced our understanding of the critical role of feedback in predator-prey interactions and in feeding relationships that result in community dynamics.The Lotka–Volterra model makes a number of assumptions about the environment and evolution of the predator and prey populations:

1. The prey population finds ample food at all times.
2. The food supply of the predator population depends entirely on the size of the prey population.
3. The rate of change of population is proportional to its size.
4. During the process, the environment does not change in favour of one species and genetic adaptation is inconsequential.
5. Predators have limitless appetite.
As differential equations are used, the solution is deterministic and continuous. This, in turn, implies that the generations of both the predator and prey are continually overlapping.[23]

Prey
When multiplied out, the prey equation becomes
dx/dtαx - βxy
 The prey are assumed to have an unlimited food supply, and to reproduce exponentially unless subject to predation; this exponential growth is represented in the equation above by the term αx. The rate of predation upon the prey is assumed to be proportional to the rate at which the predators and the prey meet; this is represented above by βxy. If either x or y is zero then there can be no predation.

With these two terms the equation above can be interpreted as: the change in the prey's numbers is given by its own growth minus the rate at which it is preyed upon.

Predators

The predator equation becomes

dy/dt =  - 

In this equation, {\displaystyle \displaystyle \delta xy} represents the growth of the predator population. (Note the similarity to the predation rate; however, a different constant is used as the rate at which the predator population grows is not necessarily equal to the rate at which it consumes the prey). {\displaystyle \displaystyle \gamma y} represents the loss rate of the predators due to either natural death or emigration; it leads to an exponential decay in the absence of prey.

Hence the equation expresses the change in the predator population as growth fueled by the food supply, minus natural death.


 ​Physical meaning of the equations  The Lotka–Volterra model makes a number of assumptions about the environment and evolution of the predator and prey populations:        1. The prey population finds ample food at all times.    2. The food supply of the predator population depends entirely on the
​Physical meaning of the equations
The Lotka–Volterra model makes a number of assumptions about the environment and evolution of the predator and prey populations:

1. The prey population finds ample food at all times.
2. The food supply of the predator population depends entirely on the size of the prey population.
3. The rate of change of population is proportional to its size.
4. During the process, the environment does not change in favour of one species and genetic adaptation is inconsequential.
5. Predators have limitless appetite.
As differential equations are used, the solution is deterministic and continuous. This, in turn, implies that the generations of both the predator and prey are continually overlapping.[23]

Prey
When multiplied out, the prey equation becomes
dx/dtαx - βxy
 The prey are assumed to have an unlimited food supply, and to reproduce exponentially unless subject to predation; this exponential growth is represented in the equation above by the term αx. The rate of predation upon the prey is assumed to be proportional to the rate at which the predators and the prey meet; this is represented above by βxy. If either x or y is zero then there can be no predation.

With these two terms the equation above can be interpreted as: the change in the prey's numbers is given by its own growth minus the rate at which it is preyed upon.

Predators

The predator equation becomes

dy/dt =  - 

In this equation, {\displaystyle \displaystyle \delta xy} represents the growth of the predator population. (Note the similarity to the predation rate; however, a different constant is used as the rate at which the predator population grows is not necessarily equal to the rate at which it consumes the prey). {\displaystyle \displaystyle \gamma y} represents the loss rate of the predators due to either natural death or emigration; it leads to an exponential decay in the absence of prey.

Hence the equation expresses the change in the predator population as growth fueled by the food supply, minus natural death.


Un modello minimo per la crescita esponenziale di una popolazione microbica
Un modello minimo per la crescita esponenziale di una popolazione microbica
55 2 months ago
A stock-flow diagram of the water cycle, humans not included.
A stock-flow diagram of the water cycle, humans not included.
A model of the exponential growth phase of  E. coli  growth.
A model of the exponential growth phase of E. coli growth.
Evolutionary Accretion Model of Human Memory mostly from Murray 2016/7  Book  and 2019 Ferbinteanu Memory Theory  article  See also Brain systems modelling 2021  article
Evolutionary Accretion Model of Human Memory mostly from Murray 2016/7 Book and 2019 Ferbinteanu Memory Theory article See also Brain systems modelling 2021 article
Il modello dinamico di Baranyi e Roberts per la curva di crescita di microrganismi (Baranyi, J., Roberts, T. (1994). A dynamic approach to predicting bacterial growth in food International journal of food microbiology  23(), 1 - 18).    __  E' simile al D model (https://insightmaker.com/insight/2060
Il modello dinamico di Baranyi e Roberts per la curva di crescita di microrganismi (Baranyi, J., Roberts, T. (1994). A dynamic approach to predicting bacterial growth in food International journal of food microbiology  23(), 1 - 18).

__
E' simile al D model (https://insightmaker.com/insight/206054/D-model-curve-di-Richards) ma qui la fase lag è esplicitamente inversamente proporzionale a mu. Questo semplifica alcuni calcoli quando mumax non è costante ma dipendente dalla temperatura. 
80 last month
Un modello minimo per la crescita esponenziale di una popolazione microbica, con popolazione massima limitata
Un modello minimo per la crescita esponenziale di una popolazione microbica, con popolazione massima limitata
stock flow diagram illustrating the lac operon
stock flow diagram illustrating the lac operon
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
This simulation shows how plant, deer and wolf populations impact each other in a deciduous forest ecosystem.
Un modello minimo per la crescita esponenziale di una popolazione microbica, con popolazione massima limitata
Un modello minimo per la crescita esponenziale di una popolazione microbica, con popolazione massima limitata
128 last month
Il modello dinamico di Baranyi e Roberts per la curva di crescita di microrganismi (Baranyi, J., Roberts, T. (1994). A dynamic approach to predicting bacterial growth in food International journal of food microbiology  23(), 1 - 18).    __  E' un modello dinamico che assume che la fase lag sia dovut
Il modello dinamico di Baranyi e Roberts per la curva di crescita di microrganismi (Baranyi, J., Roberts, T. (1994). A dynamic approach to predicting bacterial growth in food International journal of food microbiology  23(), 1 - 18).

__
E' un modello dinamico che assume che la fase lag sia dovuto all'accumulo di un composto essenziale (la cui quantità iniziale riflette lo stato iniziale delle cellule nell'ambiente E1, da cui provengono), secondo una cinetica di primo ordine, ad una velocità che dipende dall'ambiente E2. Il modello è lievemente modificato rispetto all'originale, per evitare che la quantità del prodotto essenziale tenda all'infinito. 
113 last month
OVERSHOOT GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION  The existing global capitalistic growth paradigm is totally flawed  The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunb
OVERSHOOT GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

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.
 for more information, contact Dr. Ann Stapleton at: stapletona@uncw.edu     Description:    A simple model for breeding plants from generation to generation, with one "yield" variable (e.g. height) and 4 combinations of plants from the parents. Simulation tracks the frequencies of each combination
for more information, contact Dr. Ann Stapleton at: stapletona@uncw.edu

Description:

A simple model for breeding plants from generation to generation, with one "yield" variable (e.g. height) and 4 combinations of plants from the parents. Simulation tracks the frequencies of each combination in each generation as well as the overall average height by generation.

Adjust all sliders before beginning simulation. Make sure the A1A2 parameters are equal to the A2A1 parameters.
Un modello per l'effetto della temperatura (costante) sulla crescita di un pericoloso patogeno, agente di tossinfezioni alimentari (Listeria monocytogenes)    __  Il modello è basato su questo Insight https://insightmaker.com/insight/206861/D-model-curve-di-Richards-con-ln-alpha-lag-mu
Un modello per l'effetto della temperatura (costante) sulla crescita di un pericoloso patogeno, agente di tossinfezioni alimentari (Listeria monocytogenes)

__
Il modello è basato su questo Insight https://insightmaker.com/insight/206861/D-model-curve-di-Richards-con-ln-alpha-lag-mu
77 last month