BIOL 1134 Lab Notebook 3
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Oklahoma City Community College *
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1124
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Mathematics
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Feb 20, 2024
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docx
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7
Uploaded by ElanLimos
21 September 2020 Title:
Isle Royale
Team Members:
Research Question:
Is the length of the growing season directly correlated to the population growth of moose and wolves?
Hypothesis:
If Isle Royale goes through a short growing season, then the total population of both gray wolves and moose will decrease because the population of grasses has not had enough time to replenish to its original numbers, thus destabilizing the animals’ population and causing the carrying capacity to fall.
H
0
: A short growing season will have no impact on moose and wolf populations.
H
A
: A short growing season will decrease moose and wolf populations.
If Isle Royale goes through a long growing season, then the total population of both gray wolves and moose will increase because the grass population has had plenty of time to survive and reproduce, thus stabilizing the animals’ population and causing the carrying capacity to rise.
H
0
: A long growing season will have no impact on moose and wolf populations.
H
A
: A long growing season will increase moose and wolf populations.
Procedure: 1.
Start with 200 moose and 60 wolves with a growing season of long length. Run simulation for 500 years and record the population. a.
Randomly select ten moose and ten wolves and record their energy and fat stores.
2.
Start with 200 moose and 60 wolves with a growing season of short length. Run simulation for 500 years and record the population. a.
Randomly select ten moose and ten wolves and record their energy and fat stores.
3.
Repeat steps 1-2 two more times each to create three trials for each of the two scenarios.
4.
Conduct a T-test to find if there was a significant difference between wolf and moose populations during shorter growing seasons versus longer growing seasons.
5.
Calculated the average energy of wolf populations and fat stores of moose populations to determine the health of each population.
a.
Conduct a T-test to find if there was a significant difference between the fat stores
of the moose and the energy of the wolves.
Experimental Data:
Figure 1.1: Trial 1-Short Growth Season Results
Figure 1.2: Trial 2-Short Growth Season Results
Figure 1.3: Trial 3-Short Growth Season Results
Figure 2.1: Trial 1-Long Growth Season Results
Figure 2.2: Trial 2-Long Growth Season Results
Figure 2.3: Trial 3-Long Growth Season Results
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Figure 3:
Trial 1-2 Moose and Wolf Energy sampling example
Figure 3:
Wolf Energy sampling example
Data Analysis:
In our experiment we tested the health of wolf and moose populations over 500 years given the constraints of short and long growth seasons for the natural vegetation on Isle Royale. We conducted three trials for short growth seasons and three trails for long growth seasons using 60 wolves and 200 moose each time. Given that our hypothesis is that the total population of both gray wolves and moose will decrease because the population of grasses has not had enough time to replenish to its original numbers, thus destabilizing the animals’ population and causing the carrying capacity to fall, we must reject it due to our p-value of our wolf populations being P<0.0001, which is less than our significance level of 0.05. In our data we see that the wolves typically follow the growth and declines of the moose, and in the data collected longer growing seasons also cause the populations to go extinct. This means that a short growth season kept the balance of the predator-prey system and the long growth season actually prohibited growth of both populations as you can see in our long growth season figures above.
Figure 4.1 shows the individual t-tests and their results given the fat and energy values at 500 years when there were short growth seasons. These were used to calculate the overall health of the populations and gain a significance value when taking the means of this figure and figure 1.2 and performing a t-test.
Figure 4.2 shows the individual t-tests and their results given the fat and energy values at 500 years when there were long growth seasons. Unfortunately our data here is equal to 0 as no population in any trail lived past year 200. These were used to calculate the overall health of the
populations and gain a significance value when taking the means of this figure and figure 1.1 and
performing a t-test.
Figure 4.3 shows the averages of each trial at 500 years when there were long and short growth seasons. The data for the long season averages was 0 as no population lived past year 200. These were used to calculate the overall health of the populations and gain a significance value when performing a t-test.
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Figure 4.4 shows the t-test results for moose in long and short seasons. This was done to see if there was a significant difference in population health between short and long seasons. To get this our df = 2, =0.05, Cl = 0.95
𝛼
.
Figure 1.5 shows the t-test results for wolves in long and short seasons. This was done to see if there was a significant difference in population health between short and long seasons. To get this our df = 2, =0.05, Cl = 0.95
𝛼
.
References:
SimBiotic Software. 2020. Isle Royale Workbook [PDF]. Missoula, MT: Simbiotic Software.
SimUText (2020-2021) [Computer Software]. (2020). Missoula, MT: SimBiotic Software.