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Logistic growth models of the form f(x)=1+Ce−kxL, showing near-exponential growth at first and then slowing toward the carrying capacity L as a horizontal asymptote.
Want a deeper conceptual understanding? Try our interactive lesson!
A logistic model describes growth that appears exponential for smaller values but slows as it approaches a carrying capacity, represented by a horizontal asymptote above the curve.
Logistic models are very powerful in scenarios where growth occurs under resource limitations. When the population is low, the logistic model behaves essentially like an exponential model. The population growth eventually slows down as it approaches the maximum the environment can support. The growth of most living organisms behaves like this.
Logistic models are given by the general equation f(x)=1+Ce−kxL, where
L is the carrying capacity, the upper limit on what an environment can support
k is the intrinsic rate, which captures the rate of growth when population is low and far from the carrying capacity
C is a consatnt that determines the initial population since f(0)=1+C1.
Nice work completing Logistic Models, here's a quick recap of what we covered:
Exercises checked off
Logistic growth models of the form f(x)=1+Ce−kxL, showing near-exponential growth at first and then slowing toward the carrying capacity L as a horizontal asymptote.
Want a deeper conceptual understanding? Try our interactive lesson!
A logistic model describes growth that appears exponential for smaller values but slows as it approaches a carrying capacity, represented by a horizontal asymptote above the curve.
Logistic models are very powerful in scenarios where growth occurs under resource limitations. When the population is low, the logistic model behaves essentially like an exponential model. The population growth eventually slows down as it approaches the maximum the environment can support. The growth of most living organisms behaves like this.
Logistic models are given by the general equation f(x)=1+Ce−kxL, where
L is the carrying capacity, the upper limit on what an environment can support
k is the intrinsic rate, which captures the rate of growth when population is low and far from the carrying capacity
C is a consatnt that determines the initial population since f(0)=1+C1.
Nice work completing Logistic Models, here's a quick recap of what we covered:
Exercises checked off