This video, we're going to discuss assumptions that are made for all three of the population growth models that we introduced in our last lesson video, which are the linear, exponential, and logistic population growth models. Population growth analyses or models are often simplified by making several different assumptions, including the assumptions that you can see down below in this image. All 3 of the models that we're going to discuss moving forward in our course assume a closed population, meaning that they assume no immigration or emigration is occurring into or out of the population, or if they are occurring, that they completely offset each other so that only birth rates and death rates impact the population size. The next assumption is the assumption of a homogeneous environment, which assumes a completely uniform environment where resources are evenly distributed and all individuals in the population are able to equally access these resources. The next set of assumptions ignore the effects of several different factors, including the effects of age structure, sex ratio, and external factors affecting n or population size.

Age structure is really just a breakdown of the age groups within a population, categorizing individuals into groups such as infants, children, adolescents, adults, and elderly, for example. Age structure certainly can have a significant impact on population size and population growth. But for the sake of simplicity, these models ignore the effects of age structure. They also ignore the effects of sex ratio, which refers to the ratio or proportion of males and females. It is possible for males to significantly outnumber the females or vice versa, for females to significantly outnumber the males.

And that sex ratio certainly can have a significant impact on population size and growth. But, again, these effects are going to be completely ignored in all three of these models for the sake of simplification. Lastly, these models will also ignore the effects of external factors affecting population size, including ignoring density-independent factors such as tornadoes and hurricanes, and things of that nature. Down below, we have a very important note, which is that the assumptions offer both advantages and disadvantages to these population growth models. What you'll notice is that the advantage is certainly going to be simplification, as if these assumptions were not made, the equations in all of these models would be significantly more complex, and the disadvantages are that by making these assumptions, the models will be less accurate.

However, they're still applicable and they can still be used to get us the general idea, and so they're not totally useless when we make these assumptions. This is just something to keep in mind that these models allow us to make predictions, but those predictions are not always going to be perfect in part because of many of these assumptions that are made. So that concludes this video, and I'll see you all in our next one.