You will be able to describe how ecologists measure population size and density, as well as three different patterns of population distribution, by the end of this section.
Seasonal and yearly changes in the environment, natural disasters such as forest fires and volcanic eruptions, and competition for resources between and within species are some of the factors that affect their size and composition.
Many of the tools were designed to study people.
The term "demographics" is sometimes used to mean a study of human populations, but all living populations can be studied using this approach.
A population may have a lot of people.
There are populations with a lot of people in a small area.
Population size affects the amount of genetic variation in the population.
Competition for food and the ability to find a mate can be effects of density.
The inverse relationship between population density and body size is shown by Australian mammals.
Increasing body size decreases population density.
The best way to determine population size is to count everyone in the area.
This method is not feasible when studying large areas.
This OpenStax book is available for free at http://cnx.org/content/col11487/1.9 study populations by sampling a representative portion of each habitat and use this sample to make inferences about the population as a whole.
The methods used to sample populations are usually tailored to the characteristics of the organisms being studied.
A quadrat can be used for very small and slow moving organisms.
To get an accurate count using this method, the square must be placed at random locations within the habitat.
The method will give an estimate of both population size and density.
The number and size of quadrat samples are determined by the type of organisms and their distribution.
This method involves marking a sample of captured animals and releasing them back into the environment to mix with the rest of the population; then, a new sample is captured and scientists determine how many of the marked animals are in the new sample.
The method assumes that the larger the population, the lower the percentage of marked organisms that will be captured.
The population size would be 400.
The results give us an estimate of how many people are in the original population.
The true number is usually different from this because of chance errors and possible bias.
Further information about a population can be obtained by looking at the distribution of individuals throughout their range.
People can be spread out in groups or equally spread apart.
Random, clumped, and uniform distribution patterns are what these are.
The mathematical methods used to estimate population sizes are affected by different distributions.
An example of random distribution is when dandelion and other plants have wind-dispersed seeds that fall in favorable environments.
A clumped distribution can be seen in plants that drop their seeds straight to the ground and in animals that live in social groups.
There is a uniform distribution in plants that release substances that affect the growth of nearby individuals.
It is also seen in penguins that have a defined territory.
The distribution of individuals within a population gives more information about how they interact with each other than a simple density measurement.
When compared to social species clumped together in groups, solitary species with a random distribution might have a similar difficulty in finding a mate.
There is a chance that a species has a random, clumped, or uniform distribution.
Plants with winddispersed seeds tend to be distributed randomly.
Elephants that travel in groups exhibit a clumped distribution.
penguins have a uniform distribution.
Population size and density can be used to describe a population, but they don't tell the whole story.
Birth rates, death rates, and life expectancies are all studied in demography.
Population characteristics can be seen in a life table.
Life tables give important information about the life history of an organisms and the life expectancy of individuals at each age.
They are modeled after actuarial tables used by the insurance industry.
An example of a life table can be found in Table 19.1 from a study of the Dall mountain sheep.
The population is divided into age intervals.
The mortality rate shown in column D is based on the number of individuals dying during the age interval, divided by the number of individuals surviving at the beginning of the interval.
Between the ages of three and four, 12 people die out of the 776 remaining from the original 1000 sheep.
The mortality rate per thousand is calculated by taking the number and dividing it by 1000.
A high death rate occurred when the sheep were between six months and a year old, and then increased even more from 8 to 12 years old, after which there were few survivors.
The life-expectancy numbers in column E show that a sheep in this population could live another 7.7 years on average if it survived to age one.
There are three types of curves that allow us to compare life histories.
In a type I curve, mortality is low in the early and middle years and occurs mostly in older individuals.
Organisms with a type of survivorship that produces few offspring and provides good care to the offspring increase the likelihood of their survival.
Humans and mammals have a type I survivorship curve.
In type II curves, mortality is constant throughout the entire life span, and it is equally likely to occur at any point in the life span.
An intermediate or type II survivorship curve can be seen in many bird populations.
Early ages have the highest mortality with lower mortality rates for organisms that make it to advanced years.
Large numbers of offspring can be produced by type III organisms, but they provide very little or no care for them.
A type III survivorship curve shows that trees and marine organisms that make it to an old age are more likely to live a long time.