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In Exercises 3–6, assume that any initial vector \({x_0}\) has an eigenvector decomposition such that the coefficient \({c_1}\) in equation (1) of this section is positive.

5. In old-growth forests of Douglas fir, the spotted owl dines mainly on flying squirrels. Suppose the predator–prey matrix for these two populations is \(A = \left( {\begin{aligned}{}{.4}&{}&{.3}\\{ - p}&{}&{1.2}\end{aligned}} \right)\).Show that if the predation parameter p is .325, both populations grow. Estimate the long-term growth rate and the eventual ratio of owls to flying squirrels.

Short Answer

Expert verified

There will be around 6 spotted owls for every 13 (thousand) flying squirrels in the future.

Step by step solution

01

Find the eigenvalue

Given the value is \(A = \left( {\begin{aligned}{}{.4}&{}&{.3}\\{ - .325}&{}&{1.2}\end{aligned}} \right)\).

For finding eigenvalue,

\(\det \left( {A - \lambda I} \right) = \left( {\begin{aligned}{}{0.4 - \lambda }&{0.3}\\{ - 0.125}&{1.2 - \lambda }\end{aligned}} \right)\)

So, the characteristics equation is,

\(\)

\(\begin{aligned}{}0 &= \left( {0.4 - \lambda } \right)\left( {1.2 - \lambda } \right) - \left( {0.3} \right)\left( { - 0.125} \right)\\0 &= {\lambda ^2} - 1.6\lambda + .5775\end{aligned}\)

Solve the roots.

\(\begin{aligned}{}\lambda &= \frac{{1.6 \pm \sqrt {{{1.6}^2} - 4\left( {.5775} \right)} }}{2}\\\lambda &= \frac{{1.6 \pm \sqrt {.25} }}{2}\\\lambda &= 1.05,0.55\end{aligned}\)

Because one of the eigenvalues is greater than one, both populations expand. The entries in the eigenvector correspond to \(1.05\) define their respective sizes at the end.

02

Find the eigenvector 

So, for \(\lambda = 1.05\), find eigenvector as:

\(\begin{aligned}{}\left( {A - 1.05I} \right) &= 0\\{E_1} &= \left( {\begin{aligned}{}{ - 0.65}&{}&{0.3}&{}&0\\{ - 0.325}&{}&{.15}&{}&0\end{aligned}} \right)\\{E_1} &= \left( {\begin{aligned}{}{ - 13}&{}&6&{}&0\\0&{}&0&{}&0\end{aligned}} \right)\end{aligned}\)

An eigenvector is \({\rm{v}} = \left( {\begin{aligned}{}6\\{13}\end{aligned}} \right)\).

There will be around 6 spotted owls for every 13 (thousand) flying squirrels in the future.

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Most popular questions from this chapter

Apply the results of Exercise \({\bf{15}}\) to find the eigenvalues of the matrices \(\left( {\begin{aligned}{*{20}{c}}{\bf{1}}&{\bf{2}}&{\bf{2}}\\{\bf{2}}&{\bf{1}}&{\bf{2}}\\{\bf{2}}&{\bf{2}}&{\bf{1}}\end{aligned}} \right)\) and \(\left( {\begin{aligned}{*{20}{c}}{\bf{7}}&{\bf{3}}&{\bf{3}}&{\bf{3}}&{\bf{3}}\\{\bf{3}}&{\bf{7}}&{\bf{3}}&{\bf{3}}&{\bf{3}}\\{\bf{3}}&{\bf{3}}&{\bf{7}}&{\bf{3}}&{\bf{3}}\\{\bf{3}}&{\bf{3}}&{\bf{3}}&{\bf{7}}&{\bf{3}}\\{\bf{3}}&{\bf{3}}&{\bf{3}}&{\bf{3}}&{\bf{7}}\end{aligned}} \right)\).

Question: Find the characteristic polynomial and the eigenvalues of the matrices in Exercises 1-8.

5. \(\left[ {\begin{array}{*{20}{c}}2&1\\-1&4\end{array}} \right]\)

Question: Exercises 9-14 require techniques section 3.1. Find the characteristic polynomial of each matrix, using either a cofactor expansion or the special formula for \(3 \times 3\) determinants described prior to Exercise 15-18 in Section 3.1. [Note: Finding the characteristic polynomial of a \(3 \times 3\) matrix is not easy to do with just row operations, because the variable \(\lambda \) is involved.

14. \(\left[ {\begin{array}{*{20}{c}}5&- 2&3\\0&1&0\\6&7&- 2\end{array}} \right]\)

Question: In Exercises \({\bf{1}}\) and \({\bf{2}}\), let \(A = PD{P^{ - {\bf{1}}}}\) and compute \({A^{\bf{4}}}\).

1. \(P{\bf{ = }}\left( {\begin{array}{*{20}{c}}{\bf{5}}&{\bf{7}}\\{\bf{2}}&{\bf{3}}\end{array}} \right)\), \(D{\bf{ = }}\left( {\begin{array}{*{20}{c}}{\bf{2}}&{\bf{0}}\\{\bf{0}}&{\bf{1}}\end{array}} \right)\)

(M)Use a matrix program to diagonalize

\(A = \left( {\begin{aligned}{*{20}{c}}{ - 3}&{ - 2}&0\\{14}&7&{ - 1}\\{ - 6}&{ - 3}&1\end{aligned}} \right)\)

If possible. Use the eigenvalue command to create the diagonal matrix \(D\). If the program has a command that produces eigenvectors, use it to create an invertible matrix \(P\). Then compute \(AP - PD\) and \(PD{P^{{\bf{ - 1}}}}\). Discuss your results.

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