The dynamics of a Human population with birth and death rates that are the same year in and year out, as of 2024 (the most recent I could find), in the Oshawa Region. 

The goal of this simulation is to model the population growth of Markham, Ontario, Canada. The model begins with the initial population from 2025 statistics and examines how births, deaths, immigration and emigration affect the population. Births and deaths are represented by using the annual birth and death rate applied to the current population. Immigration and emigration are represented as annual values.

This model shows how Toronto's population can change over time while considering the city's limited space and resources. As more people move into the city, resources such as housing, jobs, and food may become more limited, which can slow population growth. The model uses a carrying capacity to represent the population Toronto could reasonably support. It also includes a delay to show that the effects of a growing population may take some time to occur. Overall, I made this model to show how population growth over the span of 100 years can happen quickly, and as Toronto gets closer to its carrying capacity, it will effect many lives of the individuals living there. 

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.

A graphic model that displays the human population from a global to local scale. The model presents how the population gets smaller as you move from a global scale to a local scale which is Ajax. The city holds approximately 130,000 people and connects to the larger population of Durham Region, Canada, and globally. 

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.

The dynamics of a human 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.

The dynamics of a moose population with  birth and death rates that are the same year in and year out.

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.

This model demonstrates Ontario's population and its projected growth over 100 years. It uses variables such as the birth rate, death rate, immigration rate and emigration rate to predict how Ontario's population will change in coming years. A projected carrying capacity (K) of 25 million people is included to represent the idea that population growth decreases as the population increases. In the simulation, Ontario's population grows from approximately 16 million to approximately 19 million people over 100 years, while the per capita growth rate gradually decreases.

The dynamics of moose (prey) and wolf (predator) populations

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.

This model represents the dynamics of the human population in Ajax, Ontario, using logistic population growth. The population changes based on birth rate, death rate, carrying capacity, and density dependent effects. When the population is below carrying capacity, the population can continue to grow. As the population approaches carrying capacity, factors such as limited housing, land, infrastructure, and resources can slow population growth. The model also includes a delay to represent the time it can take for the effects of population density to influence population growth. The stock in this model is the Ajax population, which represents the total number of people, while the flow represents the change in Ajax's population over time. 

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.

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.

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.

Oshawa population dynamics: Includes the

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.

The dynamics of a human 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.

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.

This model simulates long-term human population growth in Durham Region, Ontario. It begins with an approximate population of 800,000 people and uses birth and death rates to calculate population change. Population growth is density-dependent, meaning that growth gradually slows as the population approaches an assumed carrying capacity of 1.2 million people. A five-year delay is included to represent the time required for population pressures, such as housing availability, infrastructure capacity and resource limitations, to influence population growth. The model is a simplified representation intended to demonstrate logistic human population dynamics rather than provide an exact population forecast.

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.

The dynamics of a human population. This shows how the birth rate and death rate interact to form our population, alongside factors such as density and environment.