Population | Insight Maker

Assessment 4.

This model highlights the interdependent relationship between:

- Police funding

- Community Development

- Youth Alienation

And the impact they have on youth engagement levels over time in the NSW town of Bourke.

Assumptions

The model assumes the youth population of bourke to be 1000 people.

Constants

-Community Group effect is delayed by 3 months, aligning the model to seasonality to account for the large impact seasonal sport has on rural community.

- 20% of youth will disengage with the community after realising the development funding doesn't align to their interests.

- 80% of disengaged youth will be at risk of committing a crime.

- 19% of youth arrested will have their charges dropped

- 81% will have a conviction recorded

- 21% of detained youth will be rehabilitated in line with the NSW average.

- 79% of detained youth will re-offend in line with the NSW average.

Variables

- Police Force Funding can be adjusted upward or downward to simulate the effect on engagement, disengagement and crime levels.

- Community Development Funding can be adjusted to simulate the positive effect developing programs and opportunity for youth in Bourke may have on their engagement in society and the overall crime rate amongst their cohort.

- Youth Alienation slider allows the rate of youth alienation (Exposure to violence, drugs, alcohol. Lack of training, education and opportunity), to be slowed and speed up to simulate the impact it has on engagement and crime levels.

MKT - 563 - Student 11376247 Brenton Nisbet

Brenton Nisbet

Simulation of how tiger population and anti poaching efforts effect the black market value of tiger organs.

Clone of Tiger Population and Black Market Value

Mikayla Kelley

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

Clone of Clone of Bio 190: BIDE Model With Carrying Capacity

Heidi Ballew

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

Clone of Bio 190: BIDE Model With Carrying Capacity

Todd Levine

Influence of migration on the number of working-age population.

Clone of Clone of Clone of Radno sposobno stanovništvo

Antun

Josie Morgan Lab 2 Geog 166

Lab 2

Josie Morgan

Modelagem do estado psicológico de uma população. Inicialmente, todos os indivíduos estão no estado "Calmo". Com o passar do tempo e com as interações mútuas, há o surgimento e progressivo aumento do total de indivíduos com raiva (estado "Raivoso"). Deste estado e, com o passar do tempo, os indivíduos podem evoluir mentalmente e atingirem o estado "Indiferente", nos quais eles se tornam indiferentes à qualquer interação. Outra possibilidade é o indivíduo se enriquecer e, assim, atingir a felicidade (estado "Feliz").

Estado psicológico de uma população (DS)

João Paulo Scoralick

age demographics using Delay function

lecture4.3

Christopher Bystroff

4

This simulation examines carbon stocks and flows as a function of population.

India: Carbon and Population

Elise North-Kirkman

Simple BIDE model

Population - BIDE

Todd Levine

3

This model incorporates several options in examining fisheries dynamics and fisheries employment. The two most important aspects are the choice between I)managing based on setting fixed quota versus setting fixed effort , and ii) using the 'scientific advice' for quota setting versus allowing 'political influence' on quota setting (the assumption here is that you have good estimates of recruitment and stock assessments that form the basis of 'scientific advice' and then 'political influnce' that desires increased quota beyond the scientific advice).

Clone of Fixed Quota versus Fixed Effort

Jacquelyn Pittman

This in-depth concept map portrays the factors influencing koala births and deaths in SEQ. It also shows that the eucalyptus tree population in SEQ is vital for the survival of the koala.

Clone of Koala Population SEQ

Kérim Assouad

Adapted from Hartmut Bossel's "System Zoo 3 Simulation Models, Economy, Society, Development."

Population model where the population is summarized in four age groups (children, parents, older people, old people). Used as a base population model for dealing with issues such as employment, care for the elderly, pensions dynamics, etc.

Clone of Clone of Z602 Population with four age groups

Jeb Eddy

Simulation of how tiger population and anti poaching efforts effect the black market value of tiger organs.

Clone of Tiger Population and Black Market Value

Sarah Miller

Simulation of how tiger population and anti poaching efforts effect the black market value of tiger organs.

Clone of Tiger Population and Black Market Value

Juan Antonio Jaramillo Zapata

A detailed insight map into the current population trends surrounding koalas and the different variables involved which will influence these trends in years to come.

UBD101- Koala Population

Mitch Perry

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/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.

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.

Bio103 Predator-Prey Model ("Lotka'Volterra")

John Petersen

252

Een dynamisch model over een prooi predator relatie tussen verschillende populaties onder invloed van abiotische factoren.

Catastrophe, Abiotischefactoren Koein en Reuzenvogels en blumentjens Dio 5V prey predator

Dionijs Burmeister

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/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.

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.

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

Sean R Westley

Climate Sector Boundary Diagram By Guy Lakeman

Climate, Weather, Ecology, Economics, Population, Welfare, Energy, Policy, CO2, Carbon Cycle, GHG (green house gasses, combined effects)

As general population is composed of 85% with an education level of a 12 grader or less (a 17 year old), a simple block of components concerning the health of the planet needs to be broken down into simple blocks.

Perhaps this picture will show the basics on which to vote for a sustained healthy future

Democracy is only as good as the ability of the voters to FULLY understand the implications of the policies on which they vote., both context and the various perspectives. National voting of unqualified voters on specific policy issues is the sign of corrupt manipulation.

Climate Sector Boundary Diagram of Guy Lakeman

Guy Lakeman

3

This is a first attempt to model I=PAT population growth. Impact on the renewables is equal to P*A*T. Footprint is limited by the amount of renewables left divided by the population. Death rate goes up if the Footprint goes down too far.

IPAT v.1.0

Christopher Bystroff