Population Structure and Dynamics

Population ecology is the study of how and why populations change A population is a group of individuals of a single species that occupy the same general area. Individuals in a population rely on the same resources are influenced by the same environmental factors,and are likely to interact and breed with one another.

Population ecology is the study of how and why populations change Population ecology is concerned with the changes in population size factors that regulate populations over time Populations increase through birth and immigration to an area decrease through death and emigration out of an area.

Density and dispersion patterns are important population variables Population density is the number of individuals of a species per unit area or volume. Examples of population density include the number of oak trees per square kilometer in a forest or the number of earthworms per cubic meter in forest soil. Ecologists use a variety of sampling techniques to estimate population densities.

Density and dispersion patterns are important population variables Within a population’s geographic range, local densities may vary greatly. The dispersion pattern of a population refers to the way individuals are spaced within their area.

Density and dispersion patterns are important population variables Dispersion patterns can be clumped, uniform, or random. In a clumped dispersion pattern resources are often unequally distributed and individuals are grouped in patches.

Density and dispersion patterns are important population variables In a uniform dispersion pattern, individuals are most likely interacting and equally spaced in the environment.

Density and dispersion patterns are important population variables In a random dispersion pattern, individuals are spaced in an unpredictable way, without a pattern, perhaps resulting from random dispersal of windblown seeds.

Life tables track survivorship in populations Life tables track survivorship, the chance of an individual in a given population surviving to various ages. Survivorship curves plot survivorship as the proportion of individuals from an initial population that are alive at each age. There are three main types of survivorship curves. Type I survivorship curves High survival in early and middle life, followed by a rapid decline in survival later in life. Typical of species that produce few offspring but care for them well. Ex’s. humans, large mammals

Life tables track survivorship in populations Type II curves Constant mortality rate/survival is experienced regardless of age; so survivorship is independent of age. Ex. birds, some lizards, rodents Type III curves Low survivorship for the very young followed by high survivorship for those individuals that survive to a certain age. Characteristic of species that produce a large number of offspring. Ex. most marine invertebrates, fish, sea turtles

Percentage of maximum life span 100 I Table 36.3 Life table for the U.S. population in 2008 10 II Percentage of survivors (log scale) 1 III 0.1 Percentage of maximum life span

Few large offspring, low mortality until old age Figure 36.UN01 Few large offspring, low mortality until old age I Percentage of survivors Many small offspring, high mortality II III Figure 36.UN01 Reviewing the concepts, 36.3 Percentage of maximum life span

Idealized models predict patterns of population growth Exponential growth model The rate of population increase under ideal conditions is called exponential growth It can be calculated using G = rN where G is the growth rate of the population, N is the population size, and r is the per capita rate of increase (the average contribution of each individual to population growth). Eventually, one or more limiting factors will restrict population growth.

Table 36.4a Exponential growth of rabbits, r = 0.3

Idealized models predict patterns of population growth 500 450 400 350 300 250 200 150 100 50 Population size (N) Figure 36.4a-0 Exponential growth of rabbits 0 1 2 3 4 5 6 7 8 9 10 11 12 Time (months)

Idealized models predict patterns of population growth Logistic growth model Is a description of idealized population growth that is slowed by limiting factors as population size increases. Includes a new expression that describes the effect of limiting factors on an increasing population size. K stands for carrying capacity, the maximum population size a particular environment can sustain.

Breeding male fur seals (thousands) 10 8 6 4 2 Breeding male fur seals (thousands) Figure 36.4b-0 Growth of a population of fur seals 1915 1925 1935 1945 Year Data from K. W. Kenyon et al., A population study of the Alaska fur-seal herd, Federal Government Series: Special Scientific Report—Wildlife 12 (1954).

Number of individuals (N) Figure 36.4c G = rN (K − N) Number of individuals (N) K G = rN K Figure 36.4c Logistic growth and exponential growth compared Time

Multiple factors may limit population growth The logistic growth model predicts that population growth will slow (increased deaths, decreased births) and eventually stop as population density increases. Density-dependent factors = limiting factors as a result of increased density Ex. Intraspecific competition- competition between individuals of same species for limited resources (food, nutrients, nesting sites)

Figure 36.5a-0 6 5 4 3 2 1 Mean number of offspring per female Figure 36.5a-0 Declining reproductive success of song sparrows (inset) with increasing population density 0 10 20 30 40 50 60 70 80 Density of females Data from P. Arcese et al., Stability, Regulation, and the Determination of Abundance in an Insular Song Sparrow Population. Ecology 73: 805–882 (1992).

Proportional mortality Figure 36.5b-0 Kelp perch 1.0 0.8 0.6 0.4 0.2 Proportional mortality Figure 36.5b-0 Increasing mortality of kelp perch (inset) with increasing density 0 10 20 30 40 50 60 Kelp perch density (number/plot) Data from T. W. Anderson, Predator Responses, Prey Refuges, and Density-Dependent Mortality of a Marine Fish, Ecology 82: 245–257 (2001).

Evolution shapes life histories The traits that affect an organism’s schedule of reproduction and death make up its life history. Key life history traits include age of first reproduction frequency of reproduction number of offspring amount of parental care

Evolution shapes life histories Populations with r-selected life history traits grow rapidly in unpredictable environments, where resources are abundant, have a large number of offspring that develop and reach sexual maturity rapidly, and offer little or no parental care.

Evolution shapes life histories Populations with K-selected traits tend to be long-lived animals (such as bears and elephants) that develop slowly and produce few, but well-cared-for, offspring and maintain relatively stable populations near carrying capacity. Most species fall between these two extremes.