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In the theory of evolution and natural selection, the Price equation (also known as Price's equation or Price's theorem) describes how a trait or allele changes in frequency over time. The equation uses a covariance between a trait and fitness, to give a mathematical description of evolution and natural selection. It provides a way to ...
The first and most common function to estimate fitness of a trait is linear ω =α +βz, which represents directional selection. [1] [10] The slope of the linear regression line (β) is the selection gradient, ω is the fitness of a trait value z, and α is the y-intercept of the fitness function.
The highest fitness payoff for the kin group is selected by natural selection. Therefore, strategies that include self-sacrifice on the part of individuals are often game winners – the evolutionarily stable strategy. Animals must live in kin-groups during part of the game for the opportunity for this altruistic sacrifice ever to take place.
The idea of a fitness landscape is a metaphor to help explain flawed forms in evolution by natural selection, including exploits and glitches in animals like their reactions to supernormal stimuli. The idea of studying evolution by visualizing the distribution of fitness values as a kind of landscape was first introduced by Sewall Wright in ...
Selection coefficient, usually denoted by the letter s, is a measure used in population genetics to quantify the relative fitness of a genotype compared to other genotypes. . Selection coefficients are central to the quantitative description of evolution, since fitness differences determine the change in genotype frequencies attributable to selecti
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The absolute fitness of a genotype is defined as the proportional change in the abundance of that genotype over one generation attributable to selection. For example, if n ( t ) {\displaystyle n(t)} is the abundance of a genotype in generation t {\displaystyle t} in an infinitely large population (so that there is no genetic drift ), and ...