1. 8.25
0.578 years
1.155 years

3. Logistic Growth
Sec. 6.5 Part 2

4. We have used the exponential growth equation
to represent population growth.
The exponential growth equation occurs when the rate of growth is proportional to the amount present.
If we use P to represent the population, the differential equation becomes:
The constant k is called the relative growth rate.

5. The population growth model becomes:
However, real-life populations do not increase forever. There is some limiting factor such as food, living space or waste disposal.
There is a maximum population, or carrying capacity, M.
A more realistic model is the logistic growth model where growth rate is proportional to both the amount present (P) and the carrying capacity that remains: (M-P)

6. The equation then becomes:
Logistics Differential Equation
We can solve this differential equation to find the logistics growth model.

7. Logistics Differential Equation
Partial
Fractions

8. Logistics Differential Equation

9. Logistics Differential Equation

10. Logistics Growth Model

11. Logistic Growth Model Example:
Ten grizzly bears were introduced to a national park 10 years ago. There are 23 bears in the park at the present time. The park can support a maximum of 100 bears.
Assuming a logistic growth model, when will the bear population reach 50? 75? 100?

12. Ten grizzly bears were introduced to a national park 10 years ago
Ten grizzly bears were introduced to a national park 10 years ago. There are 23 bears in the park at the present time. The park can support a maximum of 100 bears.
Assuming a logistic growth model, when will the bear population reach 50? 75? 100?

13. At time zero, the population is 10.

14. After 10 years, the population is 23.

15. p We can graph this equation and use “trace” to find the solutions.
Years
Bears
We can graph this equation and use “trace” to find the solutions.
y=50 at 22 years
y=75 at 33 years
y=100 at 75 years p