Skip to main content. Population and Community Ecology. Search for:. Environmental Limits to Population Growth. Exponential Population Growth When resources are unlimited, a population can experience exponential growth, where its size increases at a greater and greater rate. Learning Objectives Describe exponential growth of a population size. Key Takeaways Key Points To get an accurate growth rate of a population, the number that died in the time period death rate must be removed from the number born during the same time period birth rate.
When the birth rate and death rate are expressed in a per capita manner, they must be multiplied by the population to determine the number of births and deaths.
Ecologists are usually interested in the changes in a population at either a particular point in time or over a small time interval. The intrinsic rate of increase is the difference between birth and death rates; it can be positive, indicating a growing population; negative, indicating a shrinking population; or zero, indicting no change in the population. Different species have a different intrinsic rate of increase which, when under ideal conditions, represents the biotic potential or maximal growth rate for a species.
Key Terms fission : the process by which a bacterium splits to form two daughter cells per capita : per person or individual. Logistic Population Growth Logistic growth of a population size occurs when resources are limited, thereby setting a maximum number an environment can support. Learning Objectives Describe logistic growth of a population size.
Key Takeaways Key Points The carrying capacity of a particular environment is the maximum population size that it can support. The carrying capacity acts as a moderating force in the growth rate by slowing it when resources become limited and stopping growth once it has been reached.
As population size increases and resources become more limited, intraspecific competition occurs: individuals within a population who are more or less better adapted for the environment compete for survival.
Density-Dependent and Density-Independent Population Regulation Population regulation is a density-dependent process, meaning that population growth rates are regulated by the density of a population.
Learning Objectives Differentiate between density-dependent and density-independent population regulation.
Key Takeaways Key Points The density of a population can be regulated by various factors, including biotic and abiotic factors and population size. Density-dependent regulation can be affected by factors that affect birth and death rates such as competition and predation.
Density-independent regulation can be affected by factors that affect birth and death rates such as abiotic factors and environmental factors, i. New models of life history incorporate ecological concepts that are typically included in r- and K-selection theory in combination with population age structures and mortality factors. Key Terms interspecific : existing or occurring between different species intraspecific : occurring among members of the same species fecundity : number, rate, or capacity of offspring production.
Licenses and Attributions. Things sped up considerably in the middle of the 20th century. The fastest doubling of the world population happened between and a doubling from 2.
This period was marked by a peak population growth of 2. Since then, population growth has been slowing, and along with it the doubling time. In this visualisation we have used the UN projections to show how the doubling time is projected to change until the end of this century.
By , it will once again have taken approximately years for the population to double to a predicted This visualization provides an additional perspective on population growth: the number of years it took to add one billion to the global population. This visualisation shows again how the population growth rate has changed dramatically through time.
By the third billion, this period had reduced to 33 years, reduced further to 15 years to reach four. The period of fastest growth occurred through to , taking only 12 years to increase by one billion for the 5th, 6th and 7th. The world has now surpassed this peak rate of growth, and the period between each billion is expected to continue to rise.
Two hundred years ago the world population was just over one billion. Since then the number of people on the planet grew more than 7-fold to 7. How is the world population distributed across regions and how did it change over this period of rapid global growth?
In this visualization we see historical population estimates by region from through to today. If you want to see the relative distribution across the world regions in more detail you can switch to the relative view. The world region that saw the fastest population growth over last two centuries was North America. The population grew fold.
Latin America saw the second largest increase fold. Over the same period the population Europe of increased 3-fold, in Africa fold, and in Asia 6-fold. The distribution of the world population is expected to change significantly over the 21st century.
We discuss projections of population by region here. Over the last century, the world has seen rapid population growth. But how are populations distributed across the world? Which countries have the most people? In the map, we see the estimated population of each country today. By clicking on any country, you can also see how its population has evolved over this period.
You can learn more about future population growth by country here. This series of maps shows the distribution of the world population over time. The first map — in the top-left corner — shows the world population in BC. Global population growth peaked in the early s. But how has population growth varied across the world? Migration flows are not counted. Both of these measures of population growth across the world are shown in the two charts.
You can use the slider underneath each map to look at this change since Clicking on any country will show a line chart of its change over time, with UN projections through to We see that there are some countries today where the natural population growth not including migration is slightly negative: the number of deaths exceed the number of births. When we move the time slider underneath the map to past years, we see that this is a new phenomenon. Up until the s, there were no countries with a negative natural population growth.
Worldwide, population growth is slowing—you can press the play arrow at the bottom of the chart to see the change over time. Overall, growth rates in most countries have been going down since the s. Yet substantial differences exist across countries and regions. Moreover, in many cases there has been divergence in growth rates. One of the big lessons from the demographic history of countries is that population explosions are temporary.
For many countries the demographic transition has already ended, and as the global fertility rate has now halved we know that the world as a whole is approaching the end of rapid population growth. This visualization presents this big overview of the global demographic transition — with the very latest data from the UN Population Division. As we explore at the beginning of the entry on population growth , the global population grew only very slowly up to — only 0.
In the many millennia up to that point in history very high mortality of children counteracted high fertility. The world was in the first stage of the demographic transition. Once health improved and mortality declined things changed quickly. Particularly over the course of the 20th century: Over the last years global population more than quadrupled. As we see in the chart, the rise of the global population got steeper and steeper and you have just lived through the steepest increase of that curve.
This also means that your existence is a tiny part of the reason why that curve is so steep. To provide space, food, and resources for a large world population in a way that is sustainable into the distant future is without question one of the large, serious challenges for our generation. We should not make the mistake of underestimating the task ahead of us.
Yes, I expect new generations to contribute , but for now it is upon us to provide for them. Population growth is still fast: Every year million are born and 58 million die — the difference is the number of people that we add to the world population in a year: 82 million.
In red you see the annual population growth rate that is, the percentage change in population per year of the global population. It peaked around half a century ago. Peak population growth was reached in with an annual growth of 2. This slowdown of population growth was not only predictable, but predicted. Just as expected by demographers here , the world as a whole is experiencing the closing of a massive demographic transition.
This chart also shows how the United Nations envision the slow ending of the global demographic transition. As population growth continues to decline, the curve representing the world population is getting less and less steep. By the end of the century — when global population growth will have fallen to 0. It is hard to know the population dynamics beyond ; it will depend upon the fertility rate and as we discuss in our entry on fertility rates here fertility is first falling with development — and then rising with development.
The question will be whether it will rise above an average 2 children per woman. The world enters the last phase of the demographic transition and this means we will not repeat the past. The global population has quadrupled over the course of the 20th century, but it will not double anymore over the course of this century.
We are on the way to a new balance. The big global demographic transition that the world entered more than two centuries ago is then coming to an end: This new equilibrium is different from the one in the past when it was the very high mortality that kept population growth in check.
In the new balance it will be low fertility keeps population changes small. In there were 2. Now in , there are 7. By the end of the century the UN expects a global population of This visualization of the population pyramid makes it possible to understand this enormous global transformation.
Population pyramids visualize the demographic structure of a population. The width represents the size of the population of a given age; women on the right and men to the left. The bottom layer represents the number of newborns and above it you find the numbers of older cohorts. Represented in this way the population structure of societies with high mortality rates resembled a pyramid — this is how this famous type of visualization got its name.
In the darkest blue you see the pyramid that represents the structure of the world population in Two factors are responsible for the pyramid shape in An increasing number of births broadened the base layer of the population pyramid and a continuously high risk of death throughout life is evident by the pyramid narrowing towards the top. There were many newborns relative to the number of people at older ages. The narrowing of the pyramid just above the base is testimony to the fact that more than 1-in-5 children born in died before they reached the age of five.
Through shades of blue and green the same visualization shows the population structure over the last decades up to You see that in each subsequent decade the population pyramid was fatter than before — in each decade more people of all ages were added to the world population.
If you look at the green pyramid for you see that the narrowing above the base is much less strong than back in ; the child mortality rate fell from 1-in-5 in to fewer than 1-in today. In comparing and we see that the number of children born has increased — 97 million in to million today — and that the mortality of children decreased at the same time.
Meadows et al. By , the population had increased to 1. Not only the population itself was growing, but also the doubling time was decreasing, which basically means that growth itself was growing.
This rapid growth increase was mainly caused by a decreasing death rate more rapidly than birth rate , and particularly an increase in average human age. By the population counted 6 billion heads, however, population growth doubling time started to decline after because of decreasing birth rates. The European population is now thought to decline in the future, because of a decreasing average number of children per family.
Total world population continues to grow, but less rapidly because of population dynamics in developed countries. In it was discovered that population growth in the country threatened the food supplies. Starting that year, efforts were made to control population growth, and simultaneously decrease it.
The strictest birth control programme ever was introduced. Couples were urged to marry older, and have no more than one child. People that signed contracts to have no more than one child were provided with financial aid, and free educational opportunities for the child in question. Sterilization and other birth control methods were widely provided. Between and fertility rates dropped, and the number of children born per woman decreased, as well.
But despite all the efforts made, the population still grew by 12 million heads, and it is projected to count 1. It is normally referred to as the exponential equation, and the form of the data in Figure 2 is the general form called exponential. Figure 2: Left: general form of exponential growth of a population equation 2. Right: actual numbers of Paramecium in a 1 cc sample of a laboratory culture. Any value of R can be represented in an infinite number of ways e. The constant r is referred to as the intrinsic rate of natural increase Figure 2.
All sorts of microorganisms exhibit patterns that are very close to exponential population growth. For example, in the right hand graph of Figure 2 is a population of Paramecium growing in a laboratory culture. The pattern of growth is very close to the pattern of the exponential equation. Another way of writing the exponential equation is as a differential equation, that is, representing the growth of the population in its dynamic form.
Rather than asking what is the size of the population at time t , we ask, what is the rate at which the population is growing at time t. That constant rate of growth of the log of the population is the intrinsic rate of increase. The basic relationship between finite rate of increase and intrinsic rate is. Note that Equation 6 and Equation 3 are just different forms of the same equation Equation 3 is the integrated form of Equation 6; Equation 6 is the differentiated form of Equation 3 , and both may be referred to simply as the exponential equation.
Figure 3: Hypothetical case of a pest population in an agroecosystem According to model 1 which has a relatively large estimate of R , the farmer needs to think about applying a control procedure about half way through the season.
According to model 2 which has a relatively small estimate of R , the farmer need not worry about controlling the pest at all, since its population exceeds the economic threshold only after the harvest. Clearly, it is important to know which model is correct. In this case, according to the available data blue data points , either model 1 or 2 appears to provide a good fit, leaving the farmer still in limbo.
The exponential equation is a useful model of simple populations, at least for relatively short periods of time. For example, if a laboratory technician needs to know when a bacterial culture reaches a certain population density, the exponential equation can be used to provide a prediction as to exactly when that population size will be reached.
Another example is in the case of agricultural pests. Herbivores are always potentially major problems for plants. When the plants subjected to such outbreaks are agricultural, which is to say crops, the loss can be very significant for both farmer and consumer. Thus, there is always pressure to prevent such outbreaks.
However, in recent years we have come to realize that these pesticides are extremely dangerous over the long run, both for the environment and for people. Consequently there has been a movement to limit the amount of pesticides that are sprayed to combat pests.
The major way this is done is to establish an economic threshold, which is the population density of the potential pest below which the damage to the crop is insignificant i. When the pest population increases above that threshold, the farmer needs to take action and apply some sort of pesticide, or other means of controlling the pest.
Given the nature of this problem, it is sometimes of utmost importance to be able to predict when the pest will reach the economic threshold. Knowing the R for the pest species enables the farmer to predict when it will be necessary to apply some sort of control procedure Figure 3. The exponential equation is also a useful model for developing intuitive ideas about populations. The classic example is a pond with a population of lily pads.
If each lily pad reproduces itself two pads take the place of where one pad had been each month, and it took, say, three years for the pond to become half filled with lily pads, how much longer will it take for the pond to be completely covered with lily pads? The answer, of course, is one month. Another popular example is the proverbial ancient Egyptian or sometimes Persian mathematician who asks payment from the king in the form of grains of wheat sometimes rice.
One grain on the first square of a chess board, two grains on the second square, and so forth, until the last square. The Pharaoh cannot imagine that such a simple payment could amount to much, and so agrees. But he did not fully appreciate exponential growth. Since there are 64 squares on the chess board, we can use Equation 2 to determine how many grains of wheat will be required to pay on the last square R raised to the 64th power, which is about 18,,,,,, — a lot of wheat indeed, certainly more than in the whole kingdom.
These examples emphasize the frequently surprising way in which an exponential process can lead to very large numbers very rapidly. Figure 4: Growth of the human population of the United States of America during the nineteenth century blue curve , and estimates of the intrinsic rates of increase during that period red data points Note the general tendency for r to decrease throughout the century even while the overall population is increasing.
While the exponential equation is a useful model of population dynamics i. That is, something happens to stop the growth of organisms, be they cells in the body, ciliates in ponds or lions in the savanna.
That something else is usually referred to as intraspecific competition, which means that the performance of the individuals in the population depends on how many individuals are in it, more usually referred to as density dependence.
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