The Fate of Fish Population: Analyzing the Logistic Equation with Fishing

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In summary, the conversation discusses a problem involving a lake stocked with walleye pike and the use of a logistic equation to model their population. The equation is modified to account for fishing and the equilibrium points are found and classified. The fate of the fish population is discussed using qualitative analysis and the effect of different initial population sizes is considered. Further clarification is needed on the removal of 100 fish each day in relation to the equation.
  • #1
rocomath
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Very confused!

Consider a lake that is stocked with walleye pike and that the population of pike is governed by the logistic equation:

P'=0.1P(1-P/10),

where time is measures in days and P in thousands of fish. Suppose that fishing is started in this lake and that 100 fish are removed each day.

a) Modify the logistic model to account for the fishing.

b) Find and classify the equilibrium points for your model.

c) Use qualitative analysis to completely discuss the fate of the fish population with this model. In particular, if the initial population is 1000, what happens to the fish as time passes? What will happen to an initial population having 2000 fish?

a) P'=0.1P(1-P/10)-0.1P

b) 0.1P(1-P/10)-0.1P -> -P^2/10, P=0 which is stable.

Correct so far? I think I may need a hint for (c).
 
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  • #2
Why "-0.1P"? Your problem says that "100 fish are removed each day". That has nothing to do with P. (Initially, P= 1000 and 100= 0.1(1000) but P does not STAY 1000 while the number of fish removes stays at 100.)
 
  • #3
Hey Ivy, thanks for your comment! I haven't forgotten about this post (been really busy). My exam is on Tuesday so I will come back to this problem maybe later today. I will continue working on it and let you know what I get.
 

1. What is the logistic equation?

The logistic equation is a mathematical model that describes the growth of a population over time. It takes into account the population's maximum capacity, growth rate, and current population size to predict how the population will change in the future.

2. How is the logistic equation different from other population growth models?

The logistic equation differs from other models, such as the exponential growth model, by incorporating a carrying capacity. This means that the population growth will eventually slow down and reach a stable level, instead of continuously growing without limits.

3. What is the significance of the carrying capacity in the logistic equation?

The carrying capacity, represented by the variable K, is the maximum population size that a given environment can support. In the logistic equation, this value is crucial in determining the population's growth and stability.

4. How is the logistic equation used in real-world applications?

The logistic equation has been applied in various fields such as biology, economics, and environmental science. It can be used to predict population growth and control measures for species, analyze market trends, and study the impact of resource limitations on population dynamics.

5. What are the limitations of the logistic equation?

While the logistic equation is a useful tool for predicting population growth, it has some limitations. It assumes that the population growth rate is constant and that the carrying capacity remains the same over time. In reality, these factors can change, leading to discrepancies between the predicted and actual population growth.

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