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Lecture 19

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Biological Sciences
Maydianne Andrade

Lecture 19/20 – Response to Selection Natural Selection – Difference in average reproduction of different phenotypes in a population - Qualitative and Quantitative traits To Measure Selection: Start by building a theory to quantify changes over time – initially is to compare the mean value of a trait before and after selection 1. Selection Differential (S) – difference between population (successful and unsuccessful individuals) and successful breeders – in mean trait value S = P* - P(bar)  initially the population was P* but then only successful ones continue the next generation so they are P(bar) The SIGN of S tells the direction of selection (negative is decrease trait value, positive is increase trait value) The MAGNITUDE of S is the strength of selection (the bigger the difference between the average selection and the average among only those who breed is the magnitude of selection) Larger values of S mean there stronger selection. Example: Artificial Selection on mouse tail length – Population of lab mice - Interested in why mice tail length varies – what physiological processes affect change in tail length. - Graph shows initial variation in tail length and the number of mice who have them – frequency distribution - Average tail length is about 3 initilally - Then they only allowed the 10 mice with the longest tails to breed – selection on population - Then they want to see how the mean trait value changes in the next generation - By looking at the babies on the individuals that they allowed to breed Evolutionary response to selection (R) - Difference in the mean trait value of the offspring of the successful breeders compared to what you would expected if the population was at equilibrium (if everyone in the population was allowed to breed). (compare selection to HW equilibrium) - R=O* - O (bar) - O(bar) is if everyone in the population was allowed to breed - How do you know O (bar)? - Estimate it as the mean trait value of a population BEFORE selection (use P(bar)) When measure selection differential we know the traits of the breeders vs the whole population. What we want to measure is the response of the offspring – so we what to know to what extent does the breeders traits translate into offspring traits- that extent is heritability So we need to incorporate heritability - So now (back to mice example) – the gray individuals are those who don’t breed, that yellow individuals are those who do breed – from parent offspring regression graph - This slope give heritability (because they controlled for environment in the lab) - The higher heritability the higher the selection differential will be expressed in the offspring - Heritability = O* - O(bar) / P* - P(bar) - Heritability = R/S - We can predict which will give strongest selection Case Study: Selection by Pollinators - Alpine Skypilot - These plants can survive in the tundra but they also survive in alpine meadows - She observed that the same flower looked different in the two different environments - Question: Could selection through pollination cause these radical changes in these populations - In alpine meadows (timberline) vs tundra have two different pollinators - Hypothesis: the original population was came from the timberline (where the original pollinator were flies (flowers smell bad)) but through time, some of them migrated to the tundra so some seeds dispersed there with the main pollinator being bees (so that cause the flowers to change color, smell, form, shape  selection from bees) - Alternative hypothesisenvironmental changes affect physical change, change in predators, founders effect, etc. - To calculate for this  calculate the evolutionary response to selection using the equation R=(h2)(S) Question 1: Is flower size heritable? - Parent-offspring regression: - She took a population of timberline (smelly hypothesized ancestral plants), she measure the flower size and collected their seed, germinated and then planted back in random places in the parent’s offspring – to control for environment – and every yeaer for 7 years went back to measure the
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