BIO120L-M7-CarryingCapacityandDemographicsLabReport-Wagner

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Feb 20, 2024

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Carrying Capacity and Demographics Dry Lab 4/15/2021

1 Data Activity 1 Data Table 1 Number in Population ( N ) Time Interval ( t ) r = 2.0 r = 1.5 r = 0.7 r = 1.0 0 5 5 5 5 1 10 7 3 5 2 20 11 2 5 3 40 16 1 5 4 80 25 1 5 5 160 37 0 5 Insert the graph for all four values of r. 0 1 2 3 4 5 0 20 40 60 80 100 120 140 160 180 Population Trends in Beans r = 2.0 r = 1.5 r = 0.7 r = 1.0 Time Interval Number in Population 1. What assumptions does the model in Activity 1 make? Give a real-world example where these assumptions would be true. © 2018 Carolina Biological Supply Company

2 The assumptions that this model makes is that the populations in these scenarios grow or decrease in size at a fixed rate without anomalies like they would in the real world. A real world example of a population increasing at a fixed rate is if there were enough births and immigrants coming into a place that counteracted the death rates within that place. Activity 2 Data Table 2A Carrying Capacity ( K ) = 96, Death Rate = 0.1 Time Interva l ( t ) Number in Populatio n ( N ) at Beginnin g of Interval Number of Breeding Pairs Birth Rate Number of Offspring Number of Deaths Number Driven Off Populatio n Growth Rate ( r ) 0 4 2 4 8 0 0 3 1 12 5 4 20 3 0 2 2 29 12 1.8 22 2 0 1 3 49 16 0.8 13 5 0 1 4 64 21 0.7 16 6 0 1 5 74 24 1 24 7 0 1 6 91 30 1 30 9 0 1 7 112 32 1 32 11 37 .8 8 96 32 1 32 9 0 1 9 119 32 1 32 11 44 .8 10 96 32 1 32 9 0 1 © 2018 Carolina Biological Supply Company

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3 Data Table 2B Carrying Capacity ( K ) = 96, Death Rate = 0.5 Time Interva l ( t ) Number in Populatio n ( N ) at Beginnin g of Interval Number of Breeding Pairs Birth Rate Number of Offspring Number of Deaths Number Driven Off Populatio n Growth Rate ( r ) 0 4 2 4 8 2 0 2.5 1 10 5 4 20 5 0 2.5 2 25 12 2.6 32 12 0 1.8 3 45 22 2.1 47 22 0 2 4 70 23 0.8 26 35 0 0.8 5 58 29 1.2 36 29 0 1.1 6 65 31 1 31 32 0 0.9 7 64 32 1 32 32 0 1 8 64 32 1 32 32 0 1 9 64 32 1 32 32 0 1 10 64 32 1 32 32 0 1 Insert the graph of the results from both simulations. © 2018 Carolina Biological Supply Company

4 0 1 2 3 4 5 6 7 8 9 10 0 20 40 60 80 100 120 140 Population Data from Data Table 2A Number in Population (N) at Beginning of Interval Number of Breeding Pairs Birth Rate Number of Offspring Number of Deaths Number Driven Off Population Growth Rate (r) Time Interval Number of Bean Birds 0 1 2 3 4 5 6 7 8 9 10 0 10 20 30 40 50 60 70 80 Population Data from Data Table 2B Number in Population (N) at Beginning of Interval Number of Breeding Pairs Birth Rate Number of Offspring Number of Deaths Number Driven Off Population Growth Rate (r) Time Interval Number of Bean Birds © 2018 Carolina Biological Supply Company

5 2. How does the shape of the curves in the graph above compare with the graph from Activity 1, where the growth rate was greater than 1? Identify whether each of these models is of exponential or logistic growth. The first graph’s population values did not increase at such a high rate as they did in the second activity. The graph values from the first activity were exponential and did not account for deaths or emigration like the logistic values from activity 2’s graph did. 3. How did changing the death rate to 0.5 alter the growth of the population in Activity 2? In the second trial of activity 2, there was a much higher growth rate, which evened out into a sort of stasis state. The population increased much faster than it did in the first trial. Since there were more deaths, the population increased faster. 4. Explain what happens to the number driven off as the death rate increases. As the death rate increases, there are less birds in the population overall, meaning that less birds are driven off due to the accommodative space created by the deaths. The number driven off drastically decreases or stays at zero if the population is never over encumbered. 5. What happens to the population in terms of carrying capacity when the death rate increases to 0.5? The carrying capacity of the island is never reached when the death rate is half of the population. 6. What are some assumptions that the model in Activity 2 makes? Do you think these assumptions are realistic? Explain your answer. Some assumptions that the model in activity 2 makes is that there are only certain amounts of birds that can stay within a territory, birds die off at a fixed rate, and that offspring also increase at a fixed rate. These assumptions add realistic factors to the equation, meaning that there is more population factors to take into consideration, but since the deaths and birth rates are fixed it is not necessarily realistic. © 2018 Carolina Biological Supply Company

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6 Activity 3 Data Table 3 Birth Year Death Year Age at Death Gender 1832 1924 92 Female 1832 1925 93 Female 1829 1914 85 Male 1819 1909 90 Female 1819 1901 82 Male 1830 1912 82 Male 1829 1921 92 Female 1858 1930 72 Female 1840 1909 69 Male 1844 1919 75 Female 1847 1930 83 Female 1849 1919 70 Male 1851 1922 71 Male 1844 1924 80 Female 1832 1903 71 Male 1846 1929 83 Female 1848 1920 72 Male 1829 1903 74 Male 1827 1909 82 Female 1822 1905 83 Female 1850 1926 76 Male 1824 1911 87 Female 1817 1905 88 Female 1836 1912 76 Male © 2018 Carolina Biological Supply Company

7 Birth Year Death Year Age at Death Gender 1842 1916 74 Male Average age at death: Female Average Age at Death: 84 years Male Average Age at Death: 75 years Data Table 4 Female Population Years Number of Deaths Crude Death Rate Number of Survivors Survivorship per 1,000 (S 1000 ) 0-10 0 0% 13 1 11-20 0 0% 13 1 21-30 0 0% 13 1 31-40 0 0% 13 1 41-50 0 0% 13 1 51-60 0 0% 13 1 61-70 0 0% 13 1 71-80 3 23.1% 10 0.76 81-90 7 53.8% 3 0.23 91-100 3 23.1% 0 0 >100 0 0% 0 0 Male Population Years Number of Deaths Crude Death Rate Number of Survivors Survivorship per 1,000 (S 1000 ) 0-10 0 0% 12 1 11-20 0 0% 12 1 21-30 0 0% 12 1 31-40 0 0% 12 1 41-50 0 0% 12 1 © 2018 Carolina Biological Supply Company

8 Years Number of Deaths Crude Death Rate Number of Survivors Survivorship per 1,000 (S 1000 ) 51-60 0 0% 12 1 61-70 2 16.7% 10 0.83 71-80 7 58.3% 3 0.25 81-90 3 25% 0 0 91-100 0 0% 0 0 >100 0 0% 0 0 Insert the graph of survivorship vs. time for each cohort below. 0-10 11-20, 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100 >100 0 0.2 0.4 0.6 0.8 1 1.2 Female Survivorship vs. Time Female Population per 1000 Time in Decades Survivorship per 1000 © 2018 Carolina Biological Supply Company

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9 0-10 11-20, 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100 >100 0 0.2 0.4 0.6 0.8 1 1.2 Male Survivorship vs. Time Male Population per 1000 Time in Decades Survivorship per 1000 7. Compare your cohorts in Activity 3. Explain the differences, if any, between your survivorship curves. Were you able to discern the effects of any remarkable events in your data set such as an epidemic or a war? The only difference I found in the survivorship curves are that the female population lived linger than the male population by an average of approximately one decade. There were no discernable or remarkable events that influenced these figures. © 2018 Carolina Biological Supply Company