#### Clone of honeybee hive population model

##### jw drijver

- 5 years 4 months ago

#### Clone of OVERSHOOT GROWTH INTO TURBULENCE

##### Brian Lee

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)

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth Strategy Weather

- 4 years 9 months ago

#### JellyFish

##### Sarah Howell

- 3 years 8 months ago

#### Clone of E coli life cycle model

##### Frankie LAU

Exponential Growth Collapse Bacteria Biology Microbiology Science

- 4 years 10 months ago

#### Moose-Wolf

##### Wendy Jurmu

- 3 years 2 months ago

#### substrate-depletion model with synchronizer

##### Guy Katriel

- 4 years 1 month ago

#### Moose-Wolf

##### Novelyn Verran

- 3 years 2 months ago

#### Moose-Wolf

##### Jetaime Lampinen

- 3 years 2 months ago

#### Wolf-Moose

##### Aiva Sweeney

- 3 years 2 months ago

#### D-model (curve di Richards) con -ln(alpha)=lag*mu

##### Eugenio Parente

__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.

Biology Microbiology Bacterial Growth Richards Curves Predictive Microbiology

- 2 months 4 weeks ago

#### Wolf Moose Population: Version 1

##### Brenna Hill

- 2 years 12 months ago

#### Clone of Food Chain

##### steve

- 1 year 7 months ago

#### Clone of THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES CHAOTIC TURBULENCE (+controls)

##### Marco

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)

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Supply Demand Strategy

- 4 years 4 months ago

#### Wolf-Moose

##### Adelaide S

- 3 years 2 months ago

#### Seagrass habitat food web

##### Tapanga Jansen

- 2 years 11 months ago

#### Moose and Wolf Birth and Deaths rates

##### james bates

- 3 years 2 months ago

#### Moose-Wolf

##### Jetaime Lampinen

- 3 years 2 months ago

#### Trey's Food Chain

##### Kelsey Lowe

- 1 year 2 months ago

#### Wolf-Moose predator Prey Model

##### Heidi Erickson

- 3 years 2 months ago

#### Clone of Bio103 Predator-Prey Model ("Lotka'Volterra")

##### Celil Ekici

**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 becomesdx/dt = αx - 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.

PredatorsThe 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.

- 3 years 2 months ago

#### Moose-Wolf

##### Irene

- 3 years 2 months ago

#### Mammoth Cave Relationship

##### Zane Smith

- 3 years 7 months ago

#### Clone of Biology levels and genetics

##### David Fan

- 6 years 7 months ago

#### Clone of Food Chain

##### Krirushan

- 3 years 2 months ago