Suppose you're planting a garden filled with fruits, vegetables, and flowers. However, you notice holes and leaf bite marks on your plants. Clearly, you have a pest infestation. The obvious answer to ridding your garden of pests is using pesticides. However, you recognize the dangers to the environment and humans associated with pesticides. You know you must limit your use of harmful pesticides as much as possible. You might consider using a population model to establish a pest threshold. If the pest population increases above your threshold, you'll know to take action with pesticides. Predicting when the pest population will rise above your threshold would help you proactively minimize the damage to your garden by pests.
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Jetzt kostenlos anmeldenSuppose you're planting a garden filled with fruits, vegetables, and flowers. However, you notice holes and leaf bite marks on your plants. Clearly, you have a pest infestation. The obvious answer to ridding your garden of pests is using pesticides. However, you recognize the dangers to the environment and humans associated with pesticides. You know you must limit your use of harmful pesticides as much as possible. You might consider using a population model to establish a pest threshold. If the pest population increases above your threshold, you'll know to take action with pesticides. Predicting when the pest population will rise above your threshold would help you proactively minimize the damage to your garden by pests.
In general, population ecologists and experts use population change models to describe population and predict how it will change.
In AP Calculus, you will primarily work with two population change modes: exponential and logistic.
In AP Calculus, you will primarily work with two population change models: exponential and logistic.
The major differences between the two models include:
Exponential growth is J-shaped while logistic growth is sigmoid (S-shaped)
Exponential growth depends exclusively on the size of the population, while logistic growth depends on the size of the population, competition, and the number of resources
Exponential growth is applicable to a population that does not have any limitations for growth, while logistic growth is more applicable in the sense that it applies to any population with a carrying capacity
In the following sections, you'll learn more about the two models in depth.
Exponential growth describes a particular pattern of data that increases more and more over time. The graph of the data mirrors an exponential function and creates a J-shape.
With regards to population change, exponential growth occurs when an infinite amount of resources are available to the population. Consider our garden example. The population of pests will grow exponentially if there are no limits to how much food the pests can eat from your infinitely huge garden.
The human population currently grows at an exponential rate. However, Earth does not have an infinite amount of resources. Scientists hypothesize that we will eventually reach a "carrying capacity," which we will discuss more in the next section.
The formula for exponential growth is
where is a constant determined by the initial population, is the constant of growth and is greater than 0, and is time.
For more details on exponential growth, see our article on Exponential Growth and Decay
Logistic growth describes a pattern of data whose growth rate gets smaller and smaller as the population approaches a certain maximum - often referred to as the carrying capacity. The graph of logistic growth is a sigmoid curve.
With regards to population change, logistic growth occurs when there are limited resources available or when there is competition among animals. The population of pests will grow until we introduce pesticides. The carrying capacity allows our garden to thrive by ensuring that the pest population doesn't grow too large while limiting our use of toxic pesticides.
The formula for logistic growth is
where is the carrying capacity, is a constant determined by the initial population, is the constant of growth, and is time. All values are positive.
For details on Logistic population growth, see our article on The Logistic Differential Equation
The rate of change of an exponential growth function can be modeled by the differential equation
The rate of change of a logistic growth function can be modeled by the differential equation
The rate of change of a culture of bacteria is proportional to the population itself. When , there are 100 bacteria. Two minutes later, at , there are 300 bacteria. How many bacteria are there at 4 minutes?
We are not told of any possible carrying capacity limits in this problem, and the growth rate is proportional to the population of bacteria, so it is safe to assume that these bacteria will follow an exponential growth model.
Since the population models an exponential growth rate, we know that the population can be modeled by
To find , we can plug in our initial condition (0, 100).
To find , we can plug in the second condition (2, 300).
Therefore, at 4 minutes, the bacteria population is 900.
A population of rabbits has a rate of change of
where t is a measure in years.
From the definition of the differential form of the logistic growth model, we know that , , and at , .
We can use cross multiplication to solve for .
Plugging in and to
Now we can plug in and .
After four years, the rabbit population will be about 117. After 10 years, the rabbit population will be about 146.
So, it would take the rabbit population about 55.5 years to reach a population of 400.
Population growth can be modeled by either a exponential growth equation or a logistic growth equation.
A population's growth model depends on the environment that the population grows in.
A population growth model is made by deciding if the population has an exponential growth rate or a logistic growth rate based on the nature of the environment the population grows in. From there, the model is made by plugging in known values to solve for unknowns.
The two major types of population models are exponential and logistic.
An example of a population growth model is bacteria growing in a petri dish.
What is exponential growth?
Exponential growth describes a certain pattern of data that increases more and more with the passing of time
What is the shape of the exponential growth graph?
The graph of the data mirrors an exponential function and creates a J-shape
What is logistic growth?
Logistic growth describes a certain pattern of data whose growth rate gets smaller and smaller as the population approaches a certain maximum often referred to as the carrying capacity
What is the shape of a logistic growth graph?
The graph of logistic growth is a sigmoid curve
Exponential growth depends on _______ while logistic growth depends on __________.
the population itself
size of the population and its limiting factors
Exponential growth occurs when resources are ___________.
unlimited
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