There are three types of population distribution patterns. Those three patterns are called clumped, uniform, and random. Some examples of clumped are patches of desert vegetation around springs, cottonwood trees clustered along streams, wolf packs, flocks of geese, and schools of fish. Some species maintain a fairly constant distance between individuals (uniform). By having this pattern creosote bushes in a desert have better access to scarce water resources. Organisms, like dandy lions, with a random distribution are fairly rare. Most populations live in clumps or groups. There are four main reasons why most populations live in groups. First, the resources a species needs vary greatly in availability from place to place. Second living in herds, flocks, and schools can provide some animals with better protection from predators and population declines. Third, living in packs gives some predator species such as wolves a better chance of getting a meal. Lastly, some animal species form temporary groups for matting and caring for their young.
Over time the number of individuals in a population may increase, decrease, remain about the same, or go up and down in cycles in response to changes in environmental conditions. Four variables – birth, death, immigration, and emigration – govern such changes in population size. Birth rate is the number of live births per thousand of population per year. Death rate is the ratio of deaths to the population of a particular area during a particular period of time. A population increases by birth and immigration (arrival of individuals from outside the population) and decrease by death and emigration (departure of individuals from the population) the equation is: Population Change= (Births + Immigration) - (Deaths + Emigration)
A limiting factor is a single factor that limits the growth, abundance, or distribution of the population of a species in an ecosystem. An example of a limiting factor could be food. Five rabbits may live in a habitat that has enough water, cover and space to support ten rabbits, but if there is only enough food for five rabbits, the population will not grow any larger. That shows how food is a limiting factor.
Exponential growth is growth in which some quantity, such as population size or economic output, increases at a constant rate per unit of time. An example is the growth sequence 2, 4, 8, 16, 32, 64, and so on. It starts slowly but then accelerates as the population increases because the base size of the population is increasing.
Plotting the number of individuals against time yields a j-shaped growth curve. Whether an exponential growth curve looks steep or fast depends on the time period of observation. Logistic growth involves rapid exponential population growth followed by a steady decrease in population growth with time until the population size levels off. This slowdown occurs as the population encounters environmental resistance and approaches the carrying capacity of its environment. After leveling off, population with this type of growth typically fluctuates slightly above and below the carrying capacity. A plot of the number of individuals against time yields a sigmoid, or s-shaped, logistic growth curve.
Carrying capacity is the maximum population of a particular species that a given habitat can support over given period. When a population exceeds its resource supplies, many of its members will die unless they can switch to new resources or move to an area with more resources. Some species do not make a smooth transition from exponential growth to logistic growth. Some populations use up their resource supplies and temporarily overshoot, or exceed, the carrying capacity of their environment. This occurs because of a reproductive time lag: the period needed for the birth rate to fall and the death rate to rise in response to resource overconsumption. In such cases, the population suffers a