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 constant birth and death rates.

This model graphs the general idea of the inflow and outflow of energy in a small town in Ontario's power grid. The main sources of energy come from Nuclear being one of Ontario's biggest sources of energy, Wind, and Solar. The graph shows energy generation vs energy consumption and the demand in energy in the town.

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.

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.

This is the flow of electricity in homes and business of the fictional town Wilton. The values were based on the projected power plan of the town Milton. In this stimulation, we see how much electricity is coming in from each energy source and how the total energy on the town's power grid is distributed between residents and corporate buildings in Wilton.

This model simulates human population growth on both a global scale and a local scale for Ajax, Ontario. The global population starts at 8 billion and Ajax starts at 121,780 Carrying capacities are set to 12 billion for Earth and 150,000 for Ajax. The model demonstrates the growth, showing how populations grow and stabilize as they approach their environmental limits.

The dynamics of a constant bathtub water level with constant water inflow and water outflow rates.

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. 

The power dynamics of a fictitious rural community (Bobville). The dynamics illustrate the power needs of Bobville residents and businesses throughout the day and how they change when microgeneration, residential/commercial daytime use, and nighttime use are considered.

This model simulates the financial dynamics of an organic strawberry farm, illustrating how different variables impact the cumulative net income. Key inputs include the strawberry yield, sale price, worker hours, machine costs, and organic pesticide costs, all of which influence either the farm's revenue or expenses. The model allows adjustments to these variables, showing how factors like production levels, labor costs, and initial capital affect overall profitability. By visualizing these relationships, the model helps in exploring strategies to optimize income while managing costs effectively.

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.

This complex system models the dynamics and impacts of transportation efficacy and efficiency of sustainable urban transportation in Durham Region. Within the Regional Municipality of Durham, there are eight local Municipalities consisting of Ajax, Brock, Clarington, Oshawa, Pickering, Scugog, Uxbridge, and Whitby, which account for a total population of approximately 750,000 individuals as of 2023. As Durham Region continues to expand and increase in population, road structures will be faced with an increasing traffic load that will generate a significant amount of carbon emissions. Due to the prevailing climate concerns, the need for sustainable urban transportation is evident.

Urban transportation systems are a cornerstone of city life. They connect communities and businesses, while providing access to services, supporting economic and social activities. Maintaining a vast network of transportation systems as cities grow, becomes increasingly challenging. These challenges, consisting of traffic congestion, environmental impact, and diverse transportation needs, become of paramount concern, such that political campaigns run solely on these platforms.

Within this stock and flow model are the main variables that comprise transportation emissions within Durham Region. The urban transportation model highlights different modes of transportation in the form of stocks, which consist of public transit users (bus), fossil fuel car drivers, and EV car drivers, as well as the inflows and outflows that are influenced by various variables. 

All data used within this model was obtained from the various sources on the internet. The data used within the model is based off of estimate values. Data pertaining to population values and cities/towns that comprise Durham Region, ON obtained from the following source(s): 

Regional Municipality of Durham. (n.d.). Demographics and statistics. Durham Region Economic Development and Tourism. Retrieved November 24, 2024, from https://www.durham.ca/en/economic-development/invest-and-grow/demographics-and-statistics.aspx

Regional Municipality of Durham. (n.d.). Local municipalities. Durham Region. Retrieved from https://www.durham.ca/en/regional-government/local-municipalities.aspx

Group 8 Members: Leda Alizada (100821720), Pritika Lally (100867821), Mahad Rashid (100779108), Rileigh Rodych (100515185), Sami Siddique (100460897)

This model simulates the management of water in a household. The “Water Reservoir” stock represents the total amount of water available. The “Water Supply” inflow adds water to the reservoir based on the “Supply Rate.” The “Water Usage” outflow removes water from the reservoir based on the “Usage Rate.” By adjusting the “Supply Rate” and “Usage Rate,” users can see how conservation efforts impact water availability 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 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.

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

The dynamics of a moose population with constant birth and death rates.

This model projects how the population of the Charlottetown Census Agglomeration can change over the next 100 years, starting with 96,516 people, as of January 14, 2026. Population change is based on the annual birth, death, immigration, and emigration rates from Statistics Canada. Births and immigration add people to the population, while deaths and emigration can reduce it. The model also looks at population density, which means the number of people living in each square kilometre. The Charlottetown Census Agglomeration has a land area of 1,112.43 km², which is kept the same throughout our simulation. As the population increases or decreases, the number of people living in each square kilometre also changes. A Population Density Index is included to make this change easier to understand; the density at the beginning of the model is represented by 1. An index of 2 would mean that twice as many people are living in each square kilometre compared with the beginning of the simulation.  

This model represents the population of ancient Rome in 200 BC with a density-dependent birth rate...the birth rate does not equal the death rate when the population is at carrying capacity because immigration and emigration are also factors. All values are based on historical estimates, as precise figures are not available.