Why is genetic drift more likely to occur in a population with few members?
A favorable variation in a large population is likely to be swallowed up to the point of having little impact in a large population.
iThere are a number of possible variations in the genetic makeup of most populations. These variations are preserved in the population.
For example skin color in humans is controlled by at least seven different genes. There is a random sorting of these genetic factors. Some people within the same family have a variation of skin colors. Interbreeding will cause these variations to average out in a large population.
In a small population the differences have a better chance of being preserved. For example the occurrence of white skin has an adaptive advantage in northern climates. The white skin allows a greater production of vitamin D in weak sunlight. The small population of iceland has allowed this genetic variation to become common in the population. White skin and blond hair are recessive traits in a large population these traits would not become common. In iceland due to genetic drift this helpful variation ( at least in that environment ) to survive and become the most common variation existing in that population.
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Genetic drift is more likely to occur in a population with few members because in smaller populations, chance events can have a greater impact on allele frequencies. With fewer individuals, genetic variation is already limited, and random fluctuations in allele frequencies due to chance events like deaths, births, or migrations can lead to significant changes in the gene pool over time. This can result in the loss of alleles or fixation of certain alleles, reducing genetic diversity and potentially impacting the population's ability to adapt to environmental changes.
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When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.
When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.
When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.
When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.
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