Search results
Population growth is the increase in the number of people in a population or dispersed group. Actual global human population growth amounts to around 83 million annually, or 1.1% per year. [2] The global population has grown from 1 billion in 1800 to 7.9 billion in 2020. [3] The UN projected population to keep growing, and estimates have put ...
- 73.3%
- 19.0%
- 42.8%
- 68.2%
Exponential growth works by leveraging increases in population size, and does not require increases in population growth rates. ... for the purposes of herd management.
People also ask
What is population growth?
What is the global population growth rate per year?
What does a positive growth rate mean?
Is population growth increasing or decreasing?
- Overview
- Key points:
- Introduction
- Modeling population growth rates
- Exponential growth
- Logistic growth
- What factors determine carrying capacity?
- Examples of logistic growth
- Summary
How populations grow when they have unlimited resources (and how resource limits change that pattern).
•In exponential growth, a population's per capita (per individual) growth rate stays the same regardless of population size, making the population grow faster and faster as it gets larger.
•In nature, populations may grow exponentially for some period, but they will ultimately be limited by resource availability.
•In logistic growth, a population's per capita growth rate gets smaller and smaller as population size approaches a maximum imposed by limited resources in the environment, known as the carrying capacity (K ).
•Exponential growth produces a J-shaped curve, while logistic growth produces an S-shaped curve.
•When the per capita rate of increase (r ) takes the same positive value regardless of the population size, then we get exponential growth.
•In exponential growth, a population's per capita (per individual) growth rate stays the same regardless of population size, making the population grow faster and faster as it gets larger.
•In nature, populations may grow exponentially for some period, but they will ultimately be limited by resource availability.
•In logistic growth, a population's per capita growth rate gets smaller and smaller as population size approaches a maximum imposed by limited resources in the environment, known as the carrying capacity (K ).
•Exponential growth produces a J-shaped curve, while logistic growth produces an S-shaped curve.
In theory, any kind of organism could take over the Earth just by reproducing. For instance, imagine that we started with a single pair of male and female rabbits. If these rabbits and their descendants reproduced at top speed ("like bunnies") for 7 years, without any deaths, we would have enough rabbits to cover the entire state of Rhode Island1,2,3 . And that's not even so impressive – if we used E. coli bacteria instead, we could start with just one bacterium and have enough bacteria to cover the Earth with a 1 -foot layer in just 36 hours4 !
As you've probably noticed, there isn't a 1 -foot layer of bacteria covering the entire Earth (at least, not at my house), nor have bunnies taken possession of Rhode Island. Why, then, don't we see these populations getting as big as they theoretically could? E. coli, rabbits, and all living organisms need specific resources, such as nutrients and suitable environments, in order to survive and reproduce. These resources aren’t unlimited, and a population can only reach a size that match the availability of resources in its local environment.
To understand the different models that are used to represent population dynamics, let's start by looking at a general equation for the population growth rate (change in number of individuals in a population over time):
dNdT=rN
In this equation, dN/dT is the growth rate of the population in a given instant, N is population size, T is time, and r is the per capita rate of increase –that is, how quickly the population grows per individual already in the population. (Check out the differential calculus topic for more about the dN/dT notation.)
If we assume no movement of individuals into or out of the population, r is just a function of birth and death rates. You can learn more about the meaning and derivation of the equation here:
[How we get to the population growth rate equation]
The equation above is very general, and we can make more specific forms of it to describe two different kinds of growth models: exponential and logistic.
Bacteria grown in the lab provide an excellent example of exponential growth. In exponential growth, the population’s growth rate increases over time, in proportion to the size of the population.
Let’s take a look at how this works. Bacteria reproduce by binary fission (splitting in half), and the time between divisions is about an hour for many bacterial species. To see how this exponential growth, let's start by placing 1000 bacteria in a flask with an unlimited supply of nutrients.
•After 1 hour: Each bacterium will divide, yielding 2000 bacteria (an increase of 1000 bacteria).
•After 2 hours: Each of the 2000 bacteria will divide, producing 4000 (an increase of 2000 bacteria).
•After 3 hours: Each of the 4000 bacteria will divide, producing 8000 (an increase of 4000 bacteria).
The key concept of exponential growth is that the population growth rate —the number of organisms added in each generation—increases as the population gets larger. And the results can be dramatic: after 1 day (24 cycles of division), our bacterial population would have grown from 1000 to over 16 billion! When population size, N , is plotted over time, a J-shaped growth curve is made.
Exponential growth is not a very sustainable state of affairs, since it depends on infinite amounts of resources (which tend not to exist in the real world).
Exponential growth may happen for a while, if there are few individuals and many resources. But when the number of individuals gets large enough, resources start to get used up, slowing the growth rate. Eventually, the growth rate will plateau, or level off, making an S-shaped curve. The population size at which it levels off, which represents the maximum population size a particular environment can support, is called the carrying capacity, or K .
We can mathematically model logistic growth by modifying our equation for exponential growth, using an r (per capita growth rate) that depends on population size (N ) and how close it is to carrying capacity (K ). Assuming that the population has a base growth rate of rmax when it is very small, we can write the following equation:
dNdT=rmax(K−N)KN
Let's take a minute to dissect this equation and see why it makes sense. At any given point in time during a population's growth, the expression K−N tells us how many more individuals can be added to the population before it hits carrying capacity. (K−N)/K , then, is the fraction of the carrying capacity that has not yet been “used up.” The more carrying capacity that has been used up, the more the (K−N)/K term will reduce the growth rate.
When the population is tiny, N is very small compared to K . The (K−N)/K term becomes approximately (K/K) , or 1 , giving us back the exponential equation. This fits with our graph above: the population grows near-exponentially at first, but levels off more and more as it approaches K .
Basically, any kind of resource important to a species’ survival can act as a limit. For plants, the water, sunlight, nutrients, and the space to grow are some key resources. For animals, important resources include food, water, shelter, and nesting space. Limited quantities of these resources results in competition between members of the same population, or intraspecific competition (intra- = within; -specific = species).
Intraspecific competition for resources may not affect populations that are well below their carrying capacity—resources are plentiful and all individuals can obtain what they need. However, as population size increases, the competition intensifies. In addition, the accumulation of waste products can reduce an environment’s carrying capacity.
Yeast, a microscopic fungus used to make bread and alcoholic beverages, can produce a classic S-shaped curve when grown in a test tube. In the graph shown below, yeast growth levels off as the population hits the limit of the available nutrients. (If we followed the population for longer, it would likely crash, since the test tube is a closed system – meaning that fuel sources would eventually run out and wastes might reach toxic levels).
In the real world, there are variations on the “ideal” logistic curve. We can see one example in the graph below, which illustrates population growth in harbor seals in Washington State. In the early part of the 20th century, seals were actively hunted under a government program that viewed them as harmful predators, greatly reducing their numbers5 . Since this program was shut down, seal populations have rebounded in a roughly logistic pattern6 .
•Exponential growth takes place when a population's per capita growth rate stays the same, regardless of population size, making the population grow faster and faster as it gets larger. It's represented by the equation:
dNdT=rmaxN
Exponential growth produces a J-shaped curve.
•Logistic growth takes place when a population's per capita growth rate decreases as population size approaches a maximum imposed by limited resources, the carrying capacity(K ). It's represented by the equation:
dNdT=rmax(K−N)KN
Logistic growth produces an S-shaped curve.
Apr 11, 2024 · A positive growth rate indicates a population increase, and a negative growth rate indicates a population decrease. The upper limit of a population in a given environment , referred to as the environment’s carrying capacity , is determined by the amount and availability of resources that are life-sustaining for that population.
Population growth. Population growth is the increase in the number of humans on Earth. For most of human history our population size was relatively stable. But with innovation and industrialization, energy, food, water, and medical care became more available and reliable. Consequently, global human population rapidly increased, and continues to ...
Mar 24, 2020 · The World's Growth Rate. The world's current (overall as well as natural) growth rate is about 1.14%, representing a doubling time of 61 years. We can expect the world's population of 6.5 billion to become 13 billion by 2067 if current growth continues. The world's growth rate peaked in the 1960s at 2% and a doubling time of 35 years.
Population growth is one of the most important topics we cover at Our World in Data. For most of human history, the global population was a tiny fraction of what it is today. Over the last few centuries, the human population has gone through an extraordinary change. In 1800, there were one billion people. Today there are more than 8 billion of us.
