Classification of steady states

In summary, the conversation discusses the calculation and classification of two steady states in a population model, with one state found to be stable and the other requiring further analysis. The concept of a "harvesting term" is also introduced, and advice is given on how to approach the problem.
  • #1
sid9221
111
0
http://dl.dropbox.com/u/33103477/harvesting.png

So am I right in saying the 2 steady states are:

[tex] N_1=\frac{h}{r}, N_2=\frac{1-h}{\alpha} [/tex]

Now plugging in N_1 into the equation I get:

[tex] \frac{-h^2 \alpha}{r} < 0 [/tex]

So N_1 is stable.

But I can't quite figure out how to classify N_2

Any advice ?
 
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  • #2
No, that's not correct. In steady state, the population isn't changing; that is, it's when dN/dt=0.
 
  • #3
Exactly what I was thinking, I was shying away from doing that as they did not look "pretty" and I do not know what a "harvesting term" is.

So the steady states should be:

[tex] N_1 = \frac{r-\sqrt{r(r-4\alpha h)}}{2ar}, N_2 = \frac{r+\sqrt{r(r-4\alpha h)}}{2ar} [/tex]

N_1<N_2

?
 
  • #4
Yes, those are right.

The harvesting term is h. It could represent, say, the number of deer killed by hunting every year. The population is decreased by that amount every year.
 
  • #5
How do I classify these as if I sub them back into the differential equation I get 0 ??
 
  • #6
You need to find the correct criterion. You're trying to figure out what happens if the system is disturbed slightly from an equilibrium point. Will it move back toward that point or will it move away? It might help to plot the function dN/dt as a function of N.
 
  • #7
Hi sid9221,

Out of curiosity, did this question come from a textbook? James Murray has a good book on mathematical biology and parts are available on Google books. He discusses of linear stability here.

vela is exactly right, you need to consider the effect of a small perturbation at the steady state. In the end, all you really need to do is set ##f(N) = \frac{d N}{dt}## and consider ##f'(N)## evaluated at the steady states.
 

Related to Classification of steady states

What is the purpose of classifying steady states?

The purpose of classifying steady states is to understand the behavior of a system and predict its future behavior. By categorizing different types of steady states, we can determine which ones are stable and which ones are unstable, and make informed decisions about how to control or manipulate the system.

What are the different types of steady states?

There are three main types of steady states: stable, unstable, and neutral. A stable steady state is one where the system will return to the same state after being disturbed. An unstable steady state is one where the system will move away from the state when disturbed. A neutral steady state is one where the system will remain in the same state even when disturbed.

How are steady states classified mathematically?

Steady states can be classified mathematically by analyzing the eigenvalues of the system's Jacobian matrix. If all eigenvalues are negative, the steady state is stable. If at least one eigenvalue is positive, the steady state is unstable. If there are both positive and negative eigenvalues, the steady state is neutral.

What are the applications of classifying steady states?

The classification of steady states has various applications in different fields of science and engineering. It is commonly used in the study of biological systems, chemical reactions, and mechanical systems. It is also useful in control theory, where the behavior of a system can be manipulated to achieve a desired outcome.

Are there any limitations to classifying steady states?

One limitation of classifying steady states is that it assumes the system is in a steady state, meaning that its behavior is time-invariant. In reality, many systems are dynamic and constantly changing, making it difficult to accurately classify their steady states. Additionally, the classification is based on linear models and may not apply to nonlinear systems.

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