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Which of the following are variable terms in the discrete-time logistic model? rmax,d Δt Nt ΔN K t None of these

Which of the following are variable terms in the discrete-time logistic model? rmax,d Δt Nt ΔN K t None of these

Biology Today and Tomorrow without Physiology (MindTap Course List)
Biology Today and Tomorrow without Physiology (MindTap Course List)
5th Edition
ISBN:9781305117396
Author:Cecie Starr, Christine Evers, Lisa Starr
Publisher:Cecie Starr, Christine Evers, Lisa Starr
Chapter16: Population Ecology
Section: Chapter Questions
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Which of the following are variable terms in the discrete-time logistic model?

rmax,d

Δt

Nt

ΔN

K

t

None of these

 

Modeling yearly changes in a lionfish population We can use mathematical models to study how populations of lionfish, and other species, change over time. You can learn more about these types of models in Biolnteractive's Population Dynamics Click & Learn. One common population model is the logistic model, which describes how a population changes when its growth rate depends on the population's current density. This type of growth is called density-dependent. A discrete-time logistic model describes how a population with density-dependent growth changes over specific time periods. It is often used to model populations of organisms that reproduce at specific times — for example, once per year or season. An equation for this model is: ΔΝ At = Tmax,d N₁ (K=N₂) Nt This equation can also be written as: ΔΝ AN = rmax,d N₁ (1) At The table below describes the biological meaning of each symbol in the equations above.
Transcribed Image Text:Modeling yearly changes in a lionfish population We can use mathematical models to study how populations of lionfish, and other species, change over time. You can learn more about these types of models in Biolnteractive's Population Dynamics Click & Learn. One common population model is the logistic model, which describes how a population changes when its growth rate depends on the population's current density. This type of growth is called density-dependent. A discrete-time logistic model describes how a population with density-dependent growth changes over specific time periods. It is often used to model populations of organisms that reproduce at specific times — for example, once per year or season. An equation for this model is: ΔΝ At = Tmax,d N₁ (K=N₂) Nt This equation can also be written as: ΔΝ AN = rmax,d N₁ (1) At The table below describes the biological meaning of each symbol in the equations above.
Symbol t Nt At AN Tmax,d K Meaning A specific point in time in this case, the start of the time period over which we are measuring the population. The size or density of the population at time t. The symbol A (delta) means "change in," so At means the change in time for the population - in other words, the length of the time period we are using. The change in the population's size over the time period we are using. The maximum per capita growth rate, which is the growth rate of the population per individual, in the discrete-time model. This rate is a constant, and it represents how fast a population can grow when it is not limited by density-dependent factors. Its value depends on the species' physiology and life history features (rate of development, lifespan, number of offspring, frequency of reproduction, etc.). The carrying capacity of the population. K is a constant, and it is determined by factors like the availability of resources in the environment.
Transcribed Image Text:Symbol t Nt At AN Tmax,d K Meaning A specific point in time in this case, the start of the time period over which we are measuring the population. The size or density of the population at time t. The symbol A (delta) means "change in," so At means the change in time for the population - in other words, the length of the time period we are using. The change in the population's size over the time period we are using. The maximum per capita growth rate, which is the growth rate of the population per individual, in the discrete-time model. This rate is a constant, and it represents how fast a population can grow when it is not limited by density-dependent factors. Its value depends on the species' physiology and life history features (rate of development, lifespan, number of offspring, frequency of reproduction, etc.). The carrying capacity of the population. K is a constant, and it is determined by factors like the availability of resources in the environment.
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Introduction : 

Population growth that is discrete in nature is known as logistic growth. When population changes happen at regular intervals, discrete growth results.

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