The dynamics of the human population in Oshawa are influenced by the carrying capacity.
When the population is below the carrying capacity, the birth rate exceeds the death rate, leading to population growth.
At the carrying capacity, the birth rate equals the death rate, and the population stabilizes.
If the population exceeds the carrying capacity, the death rate surpasses the birth rate, causing a population decline.
This model demonstrates how population growth is controlled by the availability of resources and space.
People (Human): Used for stocks like population and carrying capacity. It represents the number of individual humans.People per person per year (Human / Human / Year): Used for rates like birth and death rates, indicating the number of people added or subtracted per person in the population each year.People per year (Human / Year): Used for flows like population change, representing the total number of people added or subtracted from the population annually.
Logistic Human Population Dynamics - Oshawa
The dynamics of a moose population with density-dependent birth rate...the birth rate equals the death rate when the population is at carrying capacity; the birth rate is greater than the death rate when the population is below carrying capacity; the birth rate is below the death rate when the population is above carrying capacity.
Clone of Logistic Moose Population Dynamics
population of oshawa model 2
The dynamics of a moose population with density-dependent birth rate...the birth rate equals the death rate when the population is at carrying capacity; the birth rate is greater than the death rate when the population is below carrying capacity; the birth rate is below the death rate when the population is above carrying capacity.
Clone of Logistic Moose Population Dynamics
The following model shows us the fictional city in Ontario a municipality called Omnicity with fictional energy values and the relationship between all the energy types used within the city, how it affects the energy grid, with the inflows from the various types of energy the city produces. The power usage coming from Businesses and Residential, whilst the energy produced comes from Wind, Solar, Hydro, Nuclear, Natural Gas, and Micro-generated Solar Electricity from residential housing.
Omnicity Energy Flow Grid Insight
Modeling a Human Population
This is the Logistics model for the country Nigeria over 25 years. Using a density-dependent rate,
At carrying capacity: Birth rate = Death rate. This is why at this point the population at reached a constant (a plateau) because the two rates equate themselves.
Below carrying capacity:Birth rate > death rate. There are enough resources for so the population so max birth rate is reached and more people are being birthed or are migrating into the country
Above carrying capacity: The birth rate < death rate. Nigeria's ecosystem have depleted and not enough to support its population so max death rate is reached.
Using this model, we see how population replenished per person
(Population per capita) decreases as the population nears carrying
capacity.
Clone of Logistic Moose Population Dynamics
The dynamics of a moose population with constant birth and death rates.
Clone of Exponential Moose Population Dynamics
This model stimulates the growth of the human population at a large scale, ranging from global to local growth. It is modeled using logistic growth, where the carrying capacity (maximum sustainable population) limits the exponential growth due to available resources.
Human Population Growth Model
The dynamics of a moose population with constant birth and death rates.
Clone of Moose Population Exponential Growth
The dynamics of a moose population with density-dependent birth rate...the birth rate equals the death rate when the population is at carrying capacity; the birth rate is greater than the death rate when the population is below carrying capacity; the birth rate is below the death rate when the population is above carrying capacity.
Clone of Logistic Moose Population Dynamics
The dynamics of a moose population with density-dependent birth rate...the birth rate equals the death rate when the population is at carrying capacity; the birth rate is greater than the death rate when the population is below carrying capacity; the birth rate is below the death rate when the population is above carrying capacity.
Clone of Logistic Moose Population Dynamics
The dynamics of a moose population with constant birth and death rates.
Clone of Exponential Moose Population Dynamics
The dynamics of the human population in Oshawa with density-dependent birth rate...the birth rate equals the death rate when the population is at carrying capacity; the birth rate is greater than the death rate when the population is below carrying capacity; the birth rate is below the death rate when the population is above carrying capacity.
Values are in thousands
Logistic Model of Oshawa Population Dynamics
The dynamics of a constant bathtub water level with constant water inflow and water outflow rates.
Constant Bathtub Water Level Dynamics
The dynamics of a moose population with constant birth and death rates.
And the moose go into rut, and then calves are born....
Bailey, R.C. 1982. The moose that I have known. Can.J.Zool. 67:101-112.
Clone of Moose Population Exponential Growth
This system diagram represents population levels for humans ranging from the world population level down to the Oshawa population level. This diagram consists of stocks which represent World, Canada, Ontario, Durham Region, and Oshawa in terms of number of people. The flows in the diagram represent the movement of people between the population levels in terms of people per year.
Haifa Arfan's Human Population Dynamics
This model displays how the population of the Earth changes. With a larger birth rate than death rate the population increases and heads towards K (carrying capacity). If the birth rate is lower than the death rate, the population will slowly diminish and will move away from carrying capacity.
Globe Population Dynamics
The dynamics of Oshawa’s population are modeled with a carrying capacity, where population growth is influenced by density-dependent factors. At lower population sizes, the birth rate exceeds the death rate, with a maximum birth rate and a maximum death rate. As the population increases and approaches the carrying capacity, resource limitations cause the birth rate and death rate to equalize. If the population exceeds the carrying capacity, the death rate will surpass the birth rate, gradually reducing population size, stabilizing near equilibrium.
Logistic Oshawa Population Dynamics
The dynamics of a moose population with density-dependent birth rate...the birth rate equals the death rate when the population is at carrying capacity; the birth rate is greater than the death rate when the population is below carrying capacity; the birth rate is below the death rate when the population is above carrying capacity.
Clone of Logistic Moose Population Dynamics
Modeling the growth in the number of whales
The dynamics of a moose population with density-dependent birth rate...the birth rate equals the death rate when the population is at carrying capacity; the birth rate is greater than the death rate when the population is below carrying capacity; the birth rate is below the death rate when the population is above carrying capacity.
Clone of Logistic Moose Population Dynamics
This model shows the growth of the human population of Edmonton, Alberta over a 100 year period. The model starts with an estimated population of 1.3 million and uses birth/death rates to determine the population's natural growth.
As the population increases, the per-capita growth rate decreases. This causes population growth to slow down as Edmonton approaches its carrying capacity of 2 million people. A 10 year delay represents the time for population density to affect growth.
Sources:
https://regionaldashboard.alberta.ca/#/explore-an-indicator?i=births&d=CalculatedValue
Julia Pajaro: Logistic Growth Model of Edmonton's Human Population (2026–2126)
The model shows the change of Pickering's population by using birth rate, death rate and also how many people move in and out of the city. The population stock shows the number of residents and the flows are based on people per year. The model assumes that as the population grows and housing becomes more limited, the rate at which people move in decreases. Every data value that I entered aside from the population is my own assumption.
Pickering's estimated population over a century