Population Ecology Exercises:
Considering the following scenarios (most require Populus):
1) Using density independent growth do the following: start with an initial population
(N0) = 5, K of 500 and r = 0.5, approximately how long does it take to reach K? What if
you change r to r = 0.05? Report you answers.
2) Using continuous logistic growth, start with the following numbers; N(0) = 5, K=500,
and r = 0.2. Vary r to 0.5 and 1; any differences?
3) Using the lagged logistic, start with the following numbers: N(0) = 5, K=500, r = 0.2,
and T=2. What happens? Change r to the following: 0.5, 1, 2, 5. Discuss what changes if
any, occurred. What does this imply?
4) Using the L-V competition model, set the following parameters up: N1 = 10, r1 = 0.9,
K1 = 500 and α = 0.6; and N2 = 20, r = 0.5, K2 = 700 and β = 0.7. Run the exercise for
20 iterations. Do this for 40, 60, 80 and 100. Does it change?
Keep all the parameters the same, but lower K1 to 400. Run the same 5 time series. What
happens? Explain your results.
5) Using the L-V model,
6) Again using the L-V competition model, set the following parameters up: N1 = 10, r1
= 0.9, K1 = 500 and α = 0.6; and N2 = 20, r = 0.5, K2 = 700 and β = 0.7. Run the
exercise for 50 iterations. Now change β in increments of 0.1 (increasing) until β = 1.5.
Explain what changes, if any, have occurred and why. Do this for 40, 60, 80 and 100.
Does it change?
Go through the same iteration of β’s, but set the r to be equal. Explain how, if any, this
impacts your results and what does it mean.
7) Set all parameters equal (you can use default), but use N1(0) = 10 and N2(0) = 20.
Now change N2(0) in increments of 10 until you start with 100. How does impact your
results? Why? Now change the competition coefficient (α) to 0.8 (if β = 0.7) and run the
same initial population iterations. Comment.
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