Density can have effects on interactions within a population such as competition for food and the ability of individuals to find a mate. Smaller organisms tend to be more densely distributed than larger organisms Figure 1. Figure 1. Australian mammals show a typical inverse relationship between population density and body size. As this graph shows, population density typically decreases with increasing body size. Why do you think this is the case? The most accurate way to determine population size is to count all of the individuals within the area.
However, this method is usually not logistically or economically feasible, especially when studying large areas. Thus, scientists usually 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 to determine their size and density are typically tailored to the characteristics of the organism being studied.
For immobile organisms such as plants, or for very small and slow-moving organisms, a quadrat may be used. A quadrat is a square structure that is randomly located on the ground and used to count the number of individuals that lie within its boundaries.
To obtain an accurate count using this method, the square must be placed at random locations within the habitat enough times to produce an accurate estimate. For smaller mobile organisms, such as mammals, a technique called mark and recapture is often used. This method involves marking captured animals in and releasing them back into the environment to mix with the rest of the population.
Later, a new sample is captured and scientists determine how many of the marked animals are in the new sample. This method assumes that the larger the population, the lower the percentage of marked organisms that will be recaptured since they will have mixed with more unmarked individuals. For example, if 80 field mice are captured, marked, and released into the forest, then a second trapping field mice are captured and 20 of them are marked, the population size N can be determined using the following equation:.
These results give us an estimate of total individuals in the original population. The true number usually will be a bit different from this because of chance errors and possible bias caused by the sampling methods. In addition to measuring size and density, further information about a population can be obtained by looking at the distribution of the individuals throughout their range. A species distribution pattern is the distribution of individuals within a habitat at a particular point in time—broad categories of patterns are used to describe them.
Individuals within a population can be distributed at random, in groups, or equally spaced apart more or less. These are known as random, clumped, and uniform distribution patterns , respectively Figure 2. Different distributions reflect important aspects of the biology of the species.
They also affect the mathematical methods required to estimate population sizes. An example of random distribution occurs with dandelion and other plants that have wind-dispersed seeds that germinate wherever they happen to fall in favorable environments.
A clumped distribution, may be seen in plants that drop their seeds straight to the ground, such as oak trees; it can also be seen in animals that live in social groups schools of fish or herds of elephants.
As time progresses, some individuals die, so there are fewer and fewer individuals present each year. But when do most individuals die? Do most individuals live to old age or do many individuals die at young ages?
Ecologists use survivorship curves to visualize how the number of individuals in a population drops off with time. In order to measure a population, ecologists identify a cohort, which is a group of individuals of the same species, in the same population, born at the same time. Data is then collected on when each individual in a population dies.
Survivorship curves can be used to compare generations, populations, or even different species. Survivorship curves actually describe the survivorship in a cohort: If cohorts are similar through time, they can be considered to describe the survivorship of a population.
Because survivorship can be drastically different in different environments, this metric is not usually considered to be a property of a species. Besides the constraint of the general life history strategy of a species, the shape of survivorship curves can be affected by both biotic and abiotic factors, such as competition and temperature. Figure 2 By plotting the number of survivors per 1, individuals on a log scale versus time, three basic patterns emerge Pearl , Deevey ; Figure 1.
Individuals with Type I survivorship exhibit high survivorship throughout their life cycle. Populations with Type II survivorship have a constant proportion of individuals dying over time. Populations with Type III survivorship have very high mortality at young ages. Most real populations are some mix of these three types. For example, survivorship of juveniles for some species is Type III, but is followed by type II survivorship for the long-lived adults.
Note that survivorship curves must be plotted on a log scale to compare with idealized Type I, II, and III curves; they will look different on a linear scale.
The use of a log scale better allows a focus on per capita effects rather than the actual number of individuals dying. For example, the type II curve has a constant proportion of individuals dying each time period. Nonetheless, the same proportion of individuals died both times.
On a log scale, the relationship of survivorship with time is linear; this scale highlights that the same proportion dies in the second time period as in the first Figure 2. A lot of effort is invested in each individual, resulting in high survivorship throughout the life cycle: Most individuals die of old age.
In general, this is more typical of K-selected species, which tend to grow in stable environments where intense competition between individuals is experienced. The heavy parental investment improves competitive ability and makes it more likely that individuals will survive to reproduction. Figure 3 shows actual data from a population of Dall sheep Ovis dalii , which exhibit Type I survivorship.
For populations with Type II survivorship, the mortality of an individual does not depend on its age. Commonly listed examples of this include rodents, adult birds, and certain turtle species. Figure 4 shows actual data from a population of the slider turtle Pseudemys scripta , which exhibits Type II survivorship from ages one to fifteen years.
Most individuals in populations with Type III survivorship produce many thousands of individuals, most of whom die right away: Once this initial period is over, survivorship is relatively constant. Examples of this include fishes, seeds, and marine larvae. Relatively little effort or parental care is invested in each individual. In general, this is more typical of r-selected species.
R-selected species experience a frequent disturbance or uncertainty in their environments. Producing a large number of offspring makes it more likely that at least a few will land in favorable areas. Figure 5 shows actual data of a population of the invasive cheatgrass, Bromus tectorum , which has Type III survivorship under certain conditions.
In the same study, other populations of B. Figure 6 Demography is the study of characteristics of human populations such as births, deaths, and growth rates: Survivorship patterns are also an important part of this. Humans in developed countries have more of a Type I survivorship.
For example, Figure 6 shows the different curves of cohorts of males born in central Pennsylvania. These data were gathered from cemeteries by the Centre County Genealogical Society.
There is a general trend for survivorship to be higher in cohorts born later, perhaps due to advances in medicine. In addition, the cohort born in — experienced more mortality in the American Civil War. Survivorship curves in humans may also be strongly different in different regions or areas of the world.
After Pearl, ; Deevey, These types of survivorship curve are useful generalizations, but in practice, patterns of survival are usually more complex. Thus, in a population of Erophila verna, a very short-lived annual plant inhabiting sand dunes, survival can follow a type I curve when the plants grow at low densities; a type II curve, at least until the end of the lifespan, at medium densities; and a type III curve in the early stages of life at the highest densities Figure 4.
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