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One of the most basic and milestone models of population growth was the logistic model of population growth formulated by Pierre François Verhulst in 1838. The logistic model takes the shape of a sigmoid curve and describes the growth of a population as exponential, followed by a decrease in growth, and bound by a carrying capacity due to ...
Population growth is the increase in the number of people in a population or dispersed group. The global population has grown from 1 billion in 1800 to 8.2 billion in 2025. [ 2 ] Actual global human population growth amounts to around 70 million annually, or 0.85% per year.
The beginning of population dynamics is widely regarded as the work of Malthus, formulated as the Malthusian growth model. According to Malthus, assuming that the conditions (the environment) remain constant (ceteris paribus), a population will grow (or decline) exponentially.
Original image of a logistic curve, contrasted with what Verhulst called a "logarithmic curve" (in modern terms, "exponential curve") The logistic function was introduced in a series of three papers by Pierre François Verhulst between 1838 and 1847, who devised it as a model of population growth by adjusting the exponential growth model, under the guidance of Adolphe Quetelet. [5]
P 0 = P(0) is the initial population size, r = the population growth rate, which Ronald Fisher called the Malthusian parameter of population growth in The Genetical Theory of Natural Selection, [2] and Alfred J. Lotka called the intrinsic rate of increase, [3] [4] t = time. The model can also be written in the form of a differential equation:
The UN Population Division report of 2022 projects world population to continue growing after 2050, although at a steadily decreasing rate, to peak at 10.4 billion in 2086, and then to start a slow decline to about 10.3 billion in 2100 with a growth rate at that time of -0.1%.
The Kolmogorov model addresses a limitation of the Volterra equations by imposing self-limiting growth in prey populations, preventing unrealistic exponential growth scenarios. It also provides a predictive model for the qualitative behavior of predator-prey systems without requiring explicit functional forms for the interaction terms. [5]
The Leslie matrix is a discrete, age-structured model of population growth that is very popular in population ecology named after Patrick H. Leslie. [1] [2] The Leslie matrix (also called the Leslie model) is one of the most well-known ways to describe the growth of populations (and their projected age distribution), in which a population is closed to migration, growing in an unlimited ...