Math Insight

Mountain nyala spatial model

Math 2241, Spring 2023
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Due date: April 26, 2023, 11:59 p.m.
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Total points: 1

At the beginning of the semester we developed a discrete dynamical system model to study the population size of mountain nyala, an endangered species of antelope.

The IUCN Red List of Threatened Species is an online database that describes the taxonomy, conservation status, and range of many species. From the IUCN webpage on mountain nyala you can see that although most nyalas are found in Bale Mountains National Park, there are also several smaller populations in other areas within Ethiopia.

The goal of this problem set is to develop a more detailed population model for mountain nyala that accounts for there being several populations.

    1. Find the dynamic rule you used to describe the population in part 2b of the mountain nyala problem set. This equation should have the parameter 'R' in it.
      $m_{t+1} = $


      To keep the model biologically realistic, we will only consider positive values of R. For what values of R will the mountain nyala population increase?

    2. Now lets consider two populations of mountain nyala at the same time. Let's use $R_1$ and $R_2$ to denote the growth rate in each of these populations and $m_t$ and $n_t$ to denote the number of mountain nyala in population 1 and 2 respectively.

      Rewrite the dynamic rule above in terms of $R_1$ to describe the number of nyalas in population 1
      $m_{t+1} = $


      For what values of $R_1$ will this first population increase?


      Write down a dynamic rule to describe the number of nyalas in population 2
      $n_{t+1} = $


      For what values of $R_2$ will this second population increase?


      Rewrite your equations for $m_{t+1}$ and $n_{t+1}$ above as a matrix model


      $=$






    3. Under what conditions (in terms of the eigenvalues $\lambda_1$ and $\lambda_2$) will the total population of mountain nyala increase?


      What are the eigenvalues of the matrix in this model?
      $\lambda_1 = $

      $\lambda_2 = $


      Under what conditions (in terms of $R_1$ and $R_2$) will the total population of mountain nyala increase?


      How do the conditions for the growth rate of the total population compare to the conditions for each population separately?



      Let's simulate this model in RStudio to check this result. Find the R code that you used to simulate the mountain nyala population model earlier in the semester. See the hint for help.

      Modify your code to simulate and plot the number of mountain nyala in each population along with the total number across both populations.

      Try plugging in different values for the model parameters until you're convinced that the above results are true.

  1. So far we have assumed that both populations are isolated and do not interact. Next we'll consider what happens if individuals disperse between the populations.
    1. Rewrite your equations for $m_{t+1}$ and $n_{t+1}$ assuming that right after growth, a fraction $d$ of the individuals in population 1 leave and move to population 2, and similarly that a fraction $d$ of the individuals in population 2 leave and move to population 1.
      $m_{t+1} = $

      $n_{t+1} = $
    2. Rewrite your R code to include dispersal and use it to determine what happens in each of the following scenarios. For each one, set tmax to 20, the initial value of the first population to 900, and the initial values of the second population to 200.

      Scenario 1: Set $R_1 = 1.04$, $R_2 = 0.9$, and $d = 0$. What happens?


      Scenario 2: Set $R_1 = 1.04$, $R_2 = 0.9$, and $d = 0.05$. What happens?


      Scenario 3: Set $R_1 = 1.04$, $R_2 = 0.9$, and $d = 0.3$. What happens?


  2. (optional) Bonus questions:
    1. Write a matrix version of your model that includes dispersal: $$\begin{bmatrix} m_{t+1} \\ n_{t+1} \end{bmatrix} = A \begin{bmatrix} m_t\\ n_t \end{bmatrix}$$ where $A = $




    2. Use the eigen command in R to calculate the dominant eigenvalue of the matrix A for each of the above three scenarios:

      Scenario 1: $R_1 = 1.04$, $R_2 = 0.9$, and $d = 0$. What is the dominant eigenvalue?
      $\lambda=$

      Scenario 2: $R_1 = 1.04$, $R_2 = 0.9$, and $d = 0.05$. What is the dominant eigenvalue?
      $\lambda=$

      Scenario 3: $R_1 = 1.04$, $R_2 = 0.9$, and $d = 0.3$. What is the dominant eigenvalue?
      $\lambda=$

      Do these values match your findings above?

    3. Now imagine you wanted to build a model to describe a set of 4 mountain nyala populations. Suppose a fraction d of individuals leave each patch, then 1/3 of these arrive at each of the other 3 patches.

      Write down a matrix version of this four patch model with growth rates $R_1$, $R_2$, $R_3$, and $R_4$ in each of the 4 populations (call them m, n, p, and q).





      $=$




















      Do the general effects of dispersal that you found in the two-patch model still hold here in the four-patch model? Try exploring different parameter values.