Population Growth: US Carrying Capacity & Predictions

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Discussion Overview

The discussion revolves around the logistic model of population growth, specifically focusing on the carrying capacity of the U.S. population and predictions based on historical data. Participants explore mathematical modeling, predictions for future population sizes, and the implications of carrying capacity in the context of U.S. demographics.

Discussion Character

  • Homework-related
  • Mathematical reasoning
  • Technical explanation
  • Debate/contested

Main Points Raised

  • Some participants express confusion about solving logistic growth problems and request clarification on the definitions of "logistic model" and "carrying capacity."
  • One participant explains that population growth initially follows an exponential pattern but eventually levels off as it approaches carrying capacity, introducing the differential equation for logistic growth.
  • Another participant suggests using Euler's method as an alternative to solving the differential equation directly, indicating that both approaches are valid but may vary in complexity.
  • Several participants engage in deriving the logistic equation and calculating parameters like the growth rate (k) based on given population data from different years.
  • Participants discuss estimating the carrying capacity for the U.S. population, with suggestions ranging from 400 million to 500 million, while considering the population density and resources available compared to other countries like India.
  • There is a challenge regarding how to make a reasonable estimate for carrying capacity, with some suggesting that any large number could be chosen, while others advocate for a more educated guess based on context.

Areas of Agreement / Disagreement

Participants generally agree on the framework of the logistic model and its implications for population growth, but there is no consensus on the appropriate carrying capacity for the U.S. population or the best method for solving the associated problems. Multiple competing views remain regarding the estimates and methods discussed.

Contextual Notes

Participants express uncertainty about the application of Euler's method and the derivation of the logistic equation, indicating that some mathematical steps and assumptions may be unclear or unresolved.

  • #31
b)
$2.75(11e^{-10k}+1)=30$
$11e^{-10k}+1=10.91$
$11e^{-10k}=9.91$
$e^(-10k}=0.90083$
$-10k=ln(0.90083)$
$k=0.010444$

c)
$P(110)=\frac{30}{11e^{(-0.010444)*110}+1}$
put that into wolframalpha and you get 6.69 billion

$P(210)=\frac{30}{11e^{(-0.010444)*210}+1}$
put that into wolframalpha and you get 13.5 billion

d)
$3.5=\frac{30}{11e^{-0.01044t}+1}$
solve that for t and you get 24 so 2014

did i do them right?
 
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  • #32
b) Let's use:

$$11e^{-10k}+1=\frac{120}{11}$$

$$11e^{-10k}=\frac{109}{11}$$

$$e^{-10k}=\frac{109}{121}$$

$$e^{-k}=\left(\frac{109}{121}\right)^{\frac{1}{10}}$$

Now substituting into the population function, we obtain:

$$P(t)=\frac{30}{11\left(\frac{109}{121}\right)^{\frac{t}{10}}+1}$$

c) Now, in the year 2100, when $t=110$, we find:

$$P(110)=\frac{30}{11\left(\frac{109}{121}\right)^{11}+1}\approx6.67$$

Now, recall that we chose as units, 100 million people, and so this equates to about 667 million people. We should suspect something is wrong if our answer exceeds the carrying capacity of 3 billion.

And, in the year 2200, when $t=210$, we find:

$$P(210)=\frac{30}{11\left(\frac{109}{121}\right)^{21}+1}\approx13.47$$

This equates to about 1.347 billion people.

d) Let $P(t)=3.5$ and solve for $t$:

$$3.5=\frac{30}{11\left(\frac{109}{121}\right)^{\frac{t}{10}}+1}$$

$$3.5\left(11\left(\frac{109}{121}\right)^{\frac{t}{10}}+1\right)=30$$

$$11\left(\frac{109}{121}\right)^{\frac{t}{10}}=\frac{53}{7}$$

$$\left(\frac{109}{121}\right)^{\frac{t}{10}}=\frac{53}{77}$$

$$t=10\frac{\ln\left(\frac{53}{77}\right)}{\ln\left(\frac{109}{121}\right)}\approx36$$

Thus, the year is 2026
 
  • #33
so solving for k doesn't work?

- - - Updated - - -

and where did 120/11 come from?
 
  • #34
ineedhelpnow said:
so solving for k doesn't work?

- - - Updated - - -

and where did 120/11 come from?

Solving for $k$ is fine, but recall the problem to which you linked...I had kind of forgotten that we can just solve for $e^{-k}$ instead of having to go through using the rules of exponents/logs just to get back to where we would be if we just use $e^{-k}$.

The 120/11 is the exact value of the approximation 10.91 that you used, by dividing 30 by 2.75:

$$\frac{30}{2.75}=\frac{3000}{275}=\frac{25\cdot120}{25\cdot11}=\frac{120}{11}$$
 

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