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The effective population size (N e) is the size of an idealised population that would experience the same rate of genetic drift as the real population. [1] Idealised populations are those following simple one- locus models that comply with assumptions of the neutral theory of molecular evolution .
This estimate is based on coalescent theory. Watterson's estimator is commonly used for its simplicity. When its assumptions are met, the estimator is unbiased and the variance of the estimator decreases with increasing sample size or recombination rate. However, the estimator can be biased by population structure.
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...
[5] [6] For the time of speciation of Homo sapiens, some 200,000 years ago, an effective population size of the order of 10,000 to 30,000 individuals has been estimated, with an actual "census population" of early Homo sapiens of roughly 100,000 to 300,000 individuals. [7] Estimates regarding the questions of "how many people have ever lived?"
Huff et al. (2010) rejected all models with an ancient effective population size larger than 26,000. [9] For ca. 130,000 years ago, Sjödin et al. (2012) estimate an effective population size of the order of 10,000 to 30,000 individuals, and infer an actual "census population" of early Homo sapiens of roughly 100,000 to 300,000 individuals. [10]
In population genetics and population ecology, population size (usually denoted N) is a countable quantity representing the number of individual organisms in a population. Population size is directly associated with amount of genetic drift , and is the underlying cause of effects like population bottlenecks and the founder effect . [ 1 ]
A set of random (stochastic) projections might be used to estimate the initial population size needed (based on the assumptions in the model) for there to be, (for example) a 95% or 99% probability of survival 1,000 years into the future. [4]
This estimate can be obtained directly from Kimura's 1962 work. [4] ... Average time to fixation N e is the effective population size, ...