Deriving Logistic Population Model (ODE question)

In summary: In this case, everything will line up and you'll be able to solve for P in a straightforward manner.In summary, the problem is trying to integrate a function that has been split into partial fractions. The two fractions on the left hand side are not equivalent, so the problem has to be solved for the constant of integration.
  • #1
SirPartypants
1
0

Homework Statement


Solve the logistic population model:
[itex] dP/dt=rP(1-P/C); P(0)=P_{0}[/itex]

2. The attempt at a solution
First, I separated variables to get:
[itex]\int \! \frac{1}{P(1-P/C)} \, \mathrm{d}P = \int \! r \, \mathrm{d}t[/itex]

Then, I took the left hand side and split into partial fractions:
(1) - [itex]\int \! \frac{1}{P} \, \mathrm{d}P + \int \! \frac{1/C}{1-P/C} \, \mathrm{d}P[/itex]
If I integrate, I get the following:
[itex]\ln(P)-\ln(1-P/C)=\ln(\frac{P}{1-P/C})[/itex] (*)

However, my problem is this. If I take (1) and multiply the second integral by C/C (which should be fine, its 1), I get the following:
[itex]\int \! \frac{1}{P} \, \mathrm{d}P + \int \! \frac{1}{C-P} \, \mathrm{d}P[/itex]
Which is...
[itex]\ln(P)-\ln(C-P)=\ln(P/C-P)[/itex] (**)

However, (*) and (**) are not the same. I'm assuming there's something wrong with one of the ways that I integrated considering I came out with two different functions. Are they both correct and all that will change when I do the full problem out is the constant?
 
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  • #2
SirPartypants said:

Homework Statement


Solve the logistic population model:
[itex] dP/dt=rP(1-P/C); P(0)=P_{0}[/itex]

2. The attempt at a solution
First, I separated variables to get:
[itex]\int \! \frac{1}{P(1-P/C)} \, \mathrm{d}P = \int \! r \, \mathrm{d}t[/itex]

Then, I took the left hand side and split into partial fractions:
(1) - [itex]\int \! \frac{1}{P} \, \mathrm{d}P + \int \! \frac{1/C}{1-P/C} \, \mathrm{d}P[/itex]
If I integrate, I get the following:
[itex]\ln(P)-\ln(1-P/C)=\ln(\frac{P}{1-P/C})[/itex] (*)

However, my problem is this. If I take (1) and multiply the second integral by C/C (which should be fine, its 1), I get the following:
[itex]\int \! \frac{1}{P} \, \mathrm{d}P + \int \! \frac{1}{C-P} \, \mathrm{d}P[/itex]
Which is...
[itex]\ln(P)-\ln(C-P)=\ln(P/C-P)[/itex] (**)

However, (*) and (**) are not the same. I'm assuming there's something wrong with one of the ways that I integrated considering I came out with two different functions. Are they both correct and all that will change when I do the full problem out is the constant?

BTW, [itex]\ln(P)-\ln(C-P)=\ln(P/C-P)[/itex] should be written [itex]\ln(P)-\ln(C-P)=\ln(P/(C-P))[/itex].

Both answers are in fact equivalent. Remember that you haven't taken into account the arbitrary constant of integration. Try putting that into the LHS as [itex]\ln k[/itex] in one case and [itex]\ln k'[/itex] in the other. You'll be able to bring everything under the natural log, after which you can exponentiate both sides. Now impose the initial value condition [itex]P = P_0[/itex] at [itex]t= 0[/itex]. You'll find that no matter which form you use, the k and k' will be just right so that your final form is the same.
 
  • #3
To obviate this sort of issue, I prefer to take the definite integral on both sides. The bounds will be [itex](P_0, P(t))[/itex] on the LHS and [itex](0,t)[/itex] on the RHS.
 

Related to Deriving Logistic Population Model (ODE question)

1. What is the purpose of deriving the logistic population model?

The logistic population model is used to describe the growth of a population over time, taking into account limiting factors such as resources and competition. It can help predict the future population size and determine the carrying capacity of an environment.

2. What are the assumptions made when deriving the logistic population model?

The logistic population model assumes that the population grows exponentially in the absence of limiting factors, the environment has a finite carrying capacity, and there is no immigration or emigration.

3. How does the logistic population model differ from the exponential population model?

The exponential population model assumes unlimited growth, while the logistic population model takes into account limiting factors and ultimately reaches a stable equilibrium population size.

4. What is the significance of the carrying capacity in the logistic population model?

The carrying capacity is the maximum population size that an environment can sustain. It is a crucial factor in determining the growth and stability of a population, as it represents the point at which resources become limited and population growth slows down.

5. How is the logistic population model used in real-world applications?

The logistic population model has been used in various fields such as ecology, economics, and epidemiology to predict and manage population growth. It can also be used to study the impact of human activities on natural systems and inform conservation efforts.

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