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Example for a trait under positive selection. The Price equation shows that a change in the average amount of a trait in a population from one generation to the next is determined by the covariance between the amounts of the trait for subpopulation and the fitnesses of the subpopulations, together with the expected change in the amount of the trait value due to fitness, namely ():
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 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 ...
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.
When such mutations result in a higher fitness, natural selection favours these phenotypes and the novel trait spreads in the population. Established traits are not immutable; traits that have high fitness in one environmental context may be much less fit if environmental conditions change.
Selection has a dual purpose: on the one hand, it can choose individual genomes from a population for subsequent breeding (e.g., using the crossover operator). In addition, selection mechanisms are also used to choose candidate solutions (individuals) for the next generation. The biological model is natural selection.
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 ...
The fitness of a genotype is a measure of its reproductive success, often expressed as a fraction of the maximum reproductive success in the population. The formula to calculate the selection coefficient s {\displaystyle s} for a genotype is: s = 1 − W {\displaystyle s=1-W} , where W {\displaystyle W} is the relative fitness of the genotype ...