Chapter 9 Summary

CONCEPT 9.1 Life tables show how survival and reproductive rates vary with age, size, or life cycle stage.

• Cohort life tables can be constructed from data on the fates of individuals born during the same time period and used to calculate age-specific survival, survivorship, and fecundity.
• In highly mobile or long-lived organisms, a static life table may be constructed from data on the survival and fecundity of individuals of different ages during a single time period.
• In species for which age correlates poorly with survival and fecundity, life tables based on size or life cycle stage may be constructed.
• In populations with a type I survivorship curve, most individuals survive to old age. In populations with a type II survivorship curve, individuals experience a constant chance of surviving from one age to the next throughout their lives. In populations with a type III survivorship curve, death rates are very high for young individuals, but adults survive well later in life. Of the three types, type III is the most common.

CONCEPT 9.2 Life table data can be used to project the future age structure, size, and growth rate of a population.

• The age structure of a population influences the growth rate of that population over time.
• Populations eventually grow at fixed rates when age-specific survival rates and fecundities do not change over time.
• Any factor that changes age-specific survival rates or fecundities may alter the population growth rate.

CONCEPT 9.3 Populations can grow exponentially when conditions are favorable, but exponential growth cannot continue indefinitely.

• Geometric growth occurs when a population of individuals that reproduce in synchrony at discrete time periods changes in size by a constant proportion from one discrete time period to the next.
• Exponential growth occurs when a population with continuous reproduction changes in size by a constant proportion at each instant in time.
• Populations have the potential to increase rapidly in size because they grow by multiplication, not by addition.
• All populations experience limits to growth, which ensure that exponential growth cannot continue indefinitely.

CONCEPT 9.4 Population size can be determined by density-dependent and density-independent factors.

• In many species, density-independent factors, such as temperature or precipitation, play a major role in determining year-to-year changes in population size.
• When the density of any species becomes high enough, a lack of food, space, or other resources causes birth rates to decrease, death rates to increase, or dispersal to increase.
• Population regulation occurs when one or more density-dependent factors tend to increase population size when densities are low and decrease population size when densities are high.

CONCEPT 9.5 The logistic equation incorporates limits to growth and shows how a population may stabilize at a maximum size, the carrying capacity.

• In some species, changes in population size over time can be described by an S-shaped curve in which the population increases rapidly at first, then stabilizes at a maximum level, the carrying capacity.
• The logistic equation can be used to represent density-dependent population growth.
• Logistic population growth provides a close fit to the size of the U.S. population up to 1950; after that time, the growth rate of the U.S. population was considerably greater than expected in logistic growth.

CASE STUDY/CASE STUDY REVISITED Human Population Growth

• Over the past 2,000 years, the human population has increased in size even more rapidly than would occur by exponential growth.
• Estimates of the carrying capacity of the human population vary widely, from fewer than 1 billion people to more than 1,000 billion people.
• The carrying capacity concept applies poorly to human populations that import resources from outside the area in which the population is found.
• Ecological footprint analyses based on available productive land area and current patterns of resource use suggest that the global human population is 20% greater than the maximum number that could be sustained for a long time.