This is a basic model for use with our lab section.  The full BIDE options.

This is a basic model for use with our lab section.  The full BIDE options.

    Clone of Bio103 Predator-Prey Model ("Lotka'Volterra")  Tags:  Education ,  Chaos ,  Ecology ,  Biology ,  Population   Thanks to Insight Author:  John Petersen       Edits by Andy Long     Everything that follows the dashes was created by John Petersen (or at least came from his Insight model).

Clone of Bio103 Predator-Prey Model ("Lotka'Volterra")
Thanks to Insight Author: John Petersen

Edits by Andy Long

Everything that follows the dashes was created by John Petersen (or at least came from his Insight model). I just wanted to make a few comments.

We are looking at Hare and Lynx, of course. Clone this insight, and change the names.

Then read the text below, to get acquainted with one of the most important and well-known examples of a simple system of differential equations in all of mathematics.

http://www.nku.edu/~longa/classes/mat375/mathematica/Lotka-Volterra.nb
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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 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.


In this insight, we model the growth of a population based on age. Children are produced by the number of adults with a random birth rate centered around a mean birth rate.
In this insight, we model the growth of a population based on age. Children are produced by the number of adults with a random birth rate centered around a mean birth rate.
The SEQ Koala Population over recent years has suffered due to a number of factors; habitat loss, predators, natural disasters, health issues and road fatalities to name a few.  All the while conservation efforts are being made to aid the population growth of  the national icon.  This insight draws
The SEQ Koala Population over recent years has suffered due to a number of factors; habitat loss, predators, natural disasters, health issues and road fatalities to name a few.  All the while conservation efforts are being made to aid the population growth of  the national icon.

This insight draws together these contributing factors into a single population model (simulation).  This model begins with the known 2006 population and it projected based on current decline rates.  Accuracy is limited, however the downward trend is clearly evident.

Developed by Patrick O'Shaughnessy
  Between 1999 and 2006 Koala population had dropped 26% in Queensland.   By 2008 it was estimated there were around 2300 Koalas with more than a 50% population loss in less than 3 years.   Main threats for Koala survival are a loss of habitat, vehicular trauma, dog attacks, urbanisation, disease an
Show relation of birth and death rate over time, creating the elements of the demographic transition. This one is for Sweden. You can clone this insight for other nations, just plug in the new crude birth and death rates and find the starting population in 1960.
Show relation of birth and death rate over time, creating the elements of the demographic transition. This one is for Sweden. You can clone this insight for other nations, just plug in the new crude birth and death rates and find the starting population in 1960.
Show relation of birth and death rate over time, creating the elements of the demographic transition. This one is for Tanzania. You can clone this insight for other nations, just plug in the new crude birth and death rates and find the starting population in 1960.
Show relation of birth and death rate over time, creating the elements of the demographic transition. This one is for Tanzania. You can clone this insight for other nations, just plug in the new crude birth and death rates and find the starting population in 1960.
 This model has two main components. First is modelling the change in population composition as non-First Nations immigration increases with the opening of new mines in the region. The second is modelling the increasing income disparity between First Nations and non-First Nations as mining jobs are

This model has two main components. First is modelling the change in population composition as non-First Nations immigration increases with the opening of new mines in the region. The second is modelling the increasing income disparity between First Nations and non-First Nations as mining jobs are disproportionately gained by non-First Nations workers.

Show relation of birth and death rate over time, creating the elements of the demographic transition. This one is for Italy. You can clone this insight for other nations, just plug in the new crude birth and death rates and find the starting population in 1960.
Show relation of birth and death rate over time, creating the elements of the demographic transition. This one is for Italy. You can clone this insight for other nations, just plug in the new crude birth and death rates and find the starting population in 1960.
 This is a basic BIDE (birth, immigration, death, emigration) model.  Not all parts are implemented, however Birth and Death are.

This is a basic BIDE (birth, immigration, death, emigration) model.  Not all parts are implemented, however Birth and Death are.

  ​Predator-prey
models are the building masses of the bio-and environments as bio
masses are become out of their asset masses. Species contend, advance and
scatter essentially to look for assets to support their battle for their very
presence. Contingent upon their particular settings of uses, they

​Predator-prey models are the building masses of the bio-and environments as bio masses are become out of their asset masses. Species contend, advance and scatter essentially to look for assets to support their battle for their very presence. Contingent upon their particular settings of uses, they can take the types of asset resource-consumer, plant-herbivore, parasite-have, tumor cells- immune structure, vulnerable irresistible collaborations, and so on. They manage the general misfortune win connections and thus may have applications outside of biological systems. At the point when focused connections are painstakingly inspected, they are regularly in actuality a few types of predator-prey communication in simulation. 

 Looking at Lotka-Volterra Model:

The well known Italian mathematician Vito Volterra proposed a differential condition model to clarify the watched increment in predator fish in the Adriatic Sea during World War I. Simultaneously in the United States, the conditions contemplated by Volterra were determined freely by Alfred Lotka (1925) to portray a theoretical synthetic response wherein the concoction fixations waver. The Lotka-Volterra model is the least complex model of predator-prey communications. It depends on direct per capita development rates, which are composed as f=b−py and g=rx−d. 

A detailed explanation of the parameters:

  • The parameter b is the development rate of species x (the prey) without communication with species y (the predators). Prey numbers are reduced by these collaborations: The per capita development rate diminishes (here directly) with expanding y, conceivably getting to be negative. 
  • The parameter p estimates the effect of predation on x˙/x. 
  • The parameter d is the death rate of species y without connection with species x. 
  • The term rx means the net rate of development of the predator population in light of the size of the prey population.

Reference:

http://www.scholarpedia.org/article/Predator-prey_model

 

 This is a basic BIDE (birth, immigration, death, emigration) model.  Not all parts are implemented, however Birth and Death are.

This is a basic BIDE (birth, immigration, death, emigration) model.  Not all parts are implemented, however Birth and Death are.

 This is a basic model for use with our lab section.  The full BIDE options.

This is a basic model for use with our lab section.  The full BIDE options.

This simulation examines the caloric well of the world. World population is estimated to start at about 7.7 billion. Per capita estimates are from the International Energy Agency (IEA).
This simulation examines the caloric well of the world. World population is estimated to start at about 7.7 billion. Per capita estimates are from the International Energy Agency (IEA).