Summary of Chapter Concepts

Under ideal conditions, populations can grow rapidly. When populations grow at their intrinsic growth rate, they can initially increase at exponential rates, which can be modeled using either the exponential growth model or the geometric growth model.

Populations have growth limits. The limits can be due to density-independent factors, which regulate population sizes regardless of the population’s density. The limits can also be due to density-dependent factors, which affect population growth in a way that is related to the population’s density. Negative density dependence causes populations to grow more slowly as they become larger whereas positive density dependence causes populations to grow faster as they become larger. Ecologists use the logistic growth model to demonstrate negative density dependence. The logistic model mimics rapid population growth when populations are small and slow population growth when populations approach their carrying capacity. The logistic growth model has been used to predict human population growth, but human populations have exceeded these predictions due to improvements in food production, international trade, and public health.

Population growth rate is influenced by the proportions of individuals in different age, size, and life history classes. Most organisms have rates of survival and fecundity that change over their lifetime, as illustrated by survivorship curves. Life tables were developed to incorporate age-, size-, or life history-specific rates of survival and fecundity. Using life tables, we can determine survivorship (lx), net reproductive rates (R0), generation times (T), and approximations of the intrinsic growth rates (ra and λa). The data needed for life tables can be collected by following a cohort and building a cohort life table or by examining all individuals during a snapshot in time and developing static life tables.

293