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Assessment 2
This assessment builds off of the work you completed in Assessment #1: Modelling Ecological Homeostasis. In that assignment you built a computational model of homeostasis, where the density of daises influenced the temperature of the planet and conversely, the temperature of the planet influenced the population density of the daisies.
In this assessment, you will investigate that same model to improve your understanding of its dynamics.
Scientific investigation often involves
• an independent variable — a property that you, the investigator, vary experimentally. (This is also sometimes known as the ‘experimental variable’.)
• a dependent variable — a property that you expect to change as you vary the independent variable, i.e., this is what you, as the investigator, observe and measure.
In the model you developed, there were a number of design decisions that were made. Each one of these represents a possible independent variable—a thing that you can vary experimentally, so as to better understand its effect upon the system’s dynamics. Here are the most obvious examples.
1. The shape of the carrying capacity function. We used a ‘Witch’s Hat’ function. What happens if you replace this function with a Gaussian curve or a ‘top-hat’ function?
2. The influence of the daisies. What happens we simulate black daisies instead of white? In other words, what if the daisies increase the temperature rather than decrease it?
3. The rate at which the population density approaches the carrying capacity. What happens when you increase (or decrease) this rate?
To complete this assignment, you should
1. Conduct an experiment for each of these three independent variables. For each, you should vary the independent variable, and generate one or more plots that show how the variations have affected the system’s dynamics.
2. Write a very brief report of each experiment. Each report should be 1-2 paragraphs and should include the plots that you generated in your experiments. The text of these paragraphs should explain:
1. The independent variable you varied, how you varied it, and why you chose that particular variation.
2. The effect of the variation. This should refer to the plots that you generated.
3. A brief explanation for why you think that the effect took place. i.e., a description of why the variation caused the effect that it caused.