Answer αℓєєиα♥'s Logistic Population Growth Model Q on Yahoo! Answers

In summary, αℓєєиα♥'s question at Yahoo! Answers regarding the logistic population growth model is asking how to find the values of the parameters $a$ and $b$ and what happens to the population in the long run. The function used to model the population growth is the Logistic function and the limiting number of yeast cells is 180.
  • #1
MarkFL
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αℓєєиα♥'s question at Yahoo! Answers regarding the logistic population growth model

Here is the question:

Calculus Exponential Growth Problem?

Really hating calculus right now...

The number of yeast cells in a laboratory culture increases rapidly initially but levels off eventually. The population is modeled by the function:

n = f(t) = a / (1+be^(-0.9t))

Where t is measured in hours. At time t = 0 the population is 20 cells and is increasing at a rate of 16 cells/hour.

a) Find the values of a and b.

b) According to this model, what happens to the yeast population in the long run?

If you could explain how to do this problem that'd be great. It's just that this equation of the growth is unfamiliar.

I have posted a link there to this topic so the OP can see my work.
 
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  • #2
Re: αℓєєиα♥'s question at Yahoo! Answers regarding the logistic population growth model

Hello αℓєєиα♥,

We are given the following function which models the population of yeast cells:

\(\displaystyle f(t)=\frac{a}{1+be^{-0.9t}}\)

We will need the derivative of this function, so let's compute it now:

\(\displaystyle f'(t)=\frac{0.9abe^{-0.9t}}{\left(1+be^{-0.9t} \right)^2}\)

Incidentally, this population model is the so-called Logistic function - Wikipedia, the free encyclopedia where resources are limited and competition for these resources limits the population growth.

a) To find the values of the parameters $a$ and $b$, we may take the information provided about the initial values to get two equations in two unknowns:

\(\displaystyle f(0)=\frac{a}{1+be^{-0.9\cdot0}}=\frac{a}{1+b}=20\)

\(\displaystyle f'(0)=\frac{0.9abe^{-0.9\cdot0}}{\left(1+be^{-0.9\cdot0} \right)^2}=\frac{0.9ab}{\left(1+b \right)^2}=16\)

The first equation implies:

\(\displaystyle a=20(b+1)\)

Substituting this into the second equation, we find:

\(\displaystyle \frac{0.9\left(20(b+1) \right)b}{\left(1+b \right)^2}=16\)

\(\displaystyle 18b(b+1)=16(b+1)^2\)

We may divide through by $b+1\ne0$ to obtain:

\(\displaystyle 18b=16(b+1)\)

\(\displaystyle 18b=16b+16\)

\(\displaystyle 2b=16\)

\(\displaystyle b=8\implies a=20(8+1)=180\)

Hence, we have found:

\(\displaystyle (a,b)=(180,8)\)

b) To analyze the population in the long run, we may consider:

\(\displaystyle \lim_{t\to\infty}f(t)=\lim_{t\to\infty}\frac{a}{1+be^{-0.9t}}=\frac{a}{1+b\cdot0}=a=180\)

Thus, we have found the limiting number of yeast cells is 180.

Here is a plot of the population function for the first 24 hours:

View attachment 1613
 

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  • yeastpop.jpg
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1. What is the purpose of αℓєєиα♥'s Logistic Population Growth Model Q?

The purpose of αℓєєиα♥'s Logistic Population Growth Model Q is to predict the population growth of a species over time, taking into account limiting factors such as resources and carrying capacity.

2. How does αℓєєиα♥'s Logistic Population Growth Model Q differ from other population growth models?

Unlike other population growth models, αℓєєиα♥'s model takes into account a species' carrying capacity, or the maximum population size that can be sustained by the available resources in an environment.

3. How is αℓєєиα♥'s Logistic Population Growth Model Q calculated?

The model is calculated using the equation: N(t+1) = N(t) + rN(t)[(K - N(t))/K], where N(t) is the population size at time t, r is the intrinsic growth rate, and K is the carrying capacity.

4. What are the limitations of αℓєєиα♥'s Logistic Population Growth Model Q?

One limitation is that the model assumes a constant carrying capacity, which may not always be the case in real-world populations. Additionally, the model does not take into account external factors such as predation or disease.

5. How can αℓєєиα♥'s Logistic Population Growth Model Q be used in practical applications?

The model can be used to predict and manage the population growth of species, such as in conservation efforts or in agriculture to optimize resource use. It can also be used to study the impacts of human activities on natural populations.

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