The dynamics of a moose population with  birth and death rates that vary year to year depending on factors like food supply, predators, and random chance.

This model simulates the basic dynamics of a water reservoir, including the impact of rainfall, community water consumption, conservation efforts, and evaporation. The model shows how the reservoir’s water level changes over time based on natural inflows and human , nature water use.

This model represents a population with a density-dependent birth rate for the population of the town of Whitby. The birth rate and death rate for the town of Whitby will be equal if the population in this model reaches its carrying capacity (K). When the town of Whitby's population exceeds its carrying capacity, that means that the death rate has exceeded the birth rate. The opposite occurs when the population is below its carrying capacity, which in this case, the birth rate has exceeded the death rate for this population. This model aims to demonstrate what happens to the current population of Whitby when it reaches its carrying capacity (K). 

This complex system displays the dynamics of Uxbridge, ON's estimated human population in the year of 2021 by use of density-dependent birth rate. Within this population model, the birth rate equals the death rate when the population of Uxbridge, ON is at its carrying capacity (birth rate = death rate). Two other scenarios can occur: When the birth rate is greater than the death rate, the population of Uxbridge, ON is below its carrying capacity (birth rate > death rate); when the birth rate is less than the death rate, the population of Uxbridge, ON is above the carrying capacity (birth rate < death rate). 

This model simulates the tradeoff between the total costs and total benefits of using AI. The model shows the investment rate in comparison to the effectiveness and efficiency rate of the AI and we can visualize this relationship with our graph to see the cost and benefits of AI.

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

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

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 model demonstrating the differences in productivity and cost in an arbitrary workforce (this could be one company/institution or an entire area). I used AI to assist me in creating this model, by explaining to it what I would like to have as my main stocks and what I'd like to model, and then had it suggest variables, flows, and links (and thus equations for the flows and variables as well). The actual initial values were also suggested by the AI.

This model illustrates the flow of water in a reservoir, with inflows from rainfall and outflows from community water usage. It tracks how the amount of water in the reservoir changes over time, depending on the balance between inflow and outflow. In this example, the inflow from rainfall (2,000 liters/day) exceeds the outflow from water consumption (1,500 liters/day + 400 liters/day = 1,900 liters/day), leading to a gradual increase in the reservoir's water level by 100 liters per day. The model demonstrates how fluctuations in rainfall and water usage rates affect the sustainability of water resources, making it useful for understanding water management in changing environmental conditions.

Canadian population dynamics where growth rate (birth rate plus immigration rate) depends on density ...... When the population is at carrying capacity, the growth rate is equal to the mortality rate; when the population is below carrying capacity, the growth rate is greater than the mortality rate; when the population is above carrying capacity, the growth rate is lower than the mortality rate.

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.

This model represents the exponential growth of a Quokka population. Quokka's are a small creature which are native to the Australian continent. This model's inflow are the joey's that enter the initial quokka population through each quokka mother that gives birth. This would be like the faucet turning on in the bathtub model which then adds to the stock. The initial quokka population is the stock according to the bathtub model as previously mentioned in this week's reading by Donella Meadows. The stock is what is already present. So the tub contains water, just like how the initial population of quokka's is present before the addition of baby quokka's, also known as joey's. Finally, the outflow, are the quokka's leaving the population by death. Similar to the bathtub model, this would be similar to the drain, removing the stock from the model. This whole system keeps the quokka population in equilibrium and can also act as a guide to sustainability, as it allows us to view birth and death rates of a population. We can then work with the numbers of this model to decide how we want to approach this population with sustainability in mind. For example, a high birth rate means we would need to find methods to control the population to create a sustainable environment which is able to maintain this population. Overall, this model can help look at population rates, while keeping sustainability in mind. 

The population dynamics of rabbits (prey) and foxes (predator) under different birth and death rates for both 

The dynamics of population growth and decline are influenced by a balance between birth rates and death rates, which are affected by various social, economic, and environmental factors. One key concept in population dynamics is the idea of carrying capacity, which refers to the maximum population size that an environment can sustain indefinitely given the available resources like food, water, shelter, and medical care.

Plastic Pollution in the world. 

A model demonstrating the differences in productivity and cost in an arbitrary workforce (this could be one company/institution or an entire area). I used AI to assist me in creating this model, by explaining to it what I would like to have as my main stocks and what I'd like to model, and then had it suggest variables, flows, and links (and thus equations for the flows and variables as well). The actual initial values were also suggested by the AI.

The dynamics of a human population with density-dependent birth rate. When the population reaches the limit that the environment can support (carrying capacity), births and deaths happen at the same rate. If the population is below this limit, more people are born than die, so the population grows. If the population goes above the limit, more people die than are born, so the population shrinks

This model exemplifies the simple system of a bathtub. The total water volume in the bathtub (lWater) at any given time is determined by the water added from the faucet and the water removed through the drain. The volume of water added from the faucet is affected by the water inflow rate, and the volume of water draining out of the bathtub is affected by the outflow rate. In this model, the total water volume (lWater) increases over time because the inflow rate (0.5L/s) is greater than the outflow rate (0.2L/s).

Group 4:

Nami Zuha (100821467)

Zachary Wayne (100814747)

The purpose of the InsightMaker model is to model how Waste-to-Energy (WtE) technology impacts waste management efficiency, energy output and greenhouse gas emissions for the scale of ten years (assuming the WtE technology integration in an urban setting). This will determine if WtE has the capability of minimizing the reliance on waste landfills as well as assisting reaching renewable energy targets. This model will shine light on Waste-to-Energy sustainability opportunities and challenges.

Orange variables are associated with calculating waste volume, green variables are associated with calculating energy generation.

Note: The following model is purely designed by ChatGPT with very limited human intervention.

This model simulates the tradeoff between the costs of AI resource allocation and the resulting benefits in terms of increased efficiency and effectiveness. It demonstrates how resources are invested in AI, how efficiency gains accumulate, and how diminishing returns impact the overall effectiveness over time. Key variables, such as resource cost, return on investment, and diminishing returns, illustrate the dynamic balance between resource consumption and productivity improvements.

This complex system models the dynamics of energy demand and consumption within the small, rural town of Uxbridge, ON. The town of Uxbridge, ON has a total population of approximately 21,500 individuals as of 2021. Within this town, there are an estimated total of 8,310 residential dwellings and 855 businesses, all of which consume various degrees of energy from various sources on the daily.