I will be conducting a computer simulation called “Rabbits and Wolves”. In this experiment I will be interaction with a simple forest ecosystem model that will simply take into account three organisms: rabbits, wolves, and grass.
As defined by “Environmental Science- 14th Edition”, an ecosystem is “a set of organisms within a defined area or volume that interact with one another and with their environment of nonliving matter and energy.” I will be using the computer simulation to alter the interactions of the organisms in the ecosystem to see what changes occur.
Based on mathematical formulas and probability of certain events occurring, the model predicts the changes in the populations of the three …show more content…
In every graph in which wolves were a part of the simulation, they never rose above a population of 83 dead by the end of the simulation, with their low being 67 dead at the end of the first simulation. The wolves, no matter the change in parameters concerning the rabbits, are not prolific in the ecosystem. On the other hand, rabbits are so prolific in their ecosystems that with the help of some predation performed by the wolves, they eat all of the grass and start dying off, as shown in Graphs 1,3, and 4. As shown in Graph 2 though, if the rabbits are left alone to their own devices, while 1693 die by the 200th iteration, they still have a surviving population of 220, and the only organism besides grass to make it to the 200th iteration alive.
If this simulation were to apply to the real world there would be a great deal more variables to consider. Weather patterns would have to be taken into account, mating seasons, health issues independent of predation, human interaction with the simulation, and these are just to name a few. Indeed, humans could be added to the simulation and would, frankly, ruin the simulation. Humans would hunt both the wolves and the rabbits to extinction, and would result in a number of futile simulations. This is why the computer model is an excellent tool for science, with it we can predict the ways in which the