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Evolution Michael J. Watts http://mike.watts.net.nz

Evolution Michael J. Watts http://mike.watts.net.nz. Lecture Outline. Why cover evolution? What is evolution? What evolution is not Lamarckian evolution Mendellian genetics Darwinian evolution. Why Cover Evolution?. The most fundamental theory in biology

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Evolution Michael J. Watts http://mike.watts.net.nz

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  1. Evolution Michael J. Watts http://mike.watts.net.nz

  2. Lecture Outline Why cover evolution? What is evolution? What evolution is not Lamarckian evolution Mendellian genetics Darwinian evolution

  3. Why Cover Evolution? The most fundamental theory in biology For the same reason we studied biological neurons Evolutionary computation is very heavily based on biological evolutionary theory Most people do not understand evolution

  4. What is Evolution? Evolution is the change in a population over time through the inheritance of random alterations The change in frequency of alleles within the population A change in a population in response to an environmental change

  5. What Evolution is Not Survival of the fittest A random search Something that happens to individuals A quest for perfection

  6. Lamarckian Evolution Jean-Baptiste Lamarck 18th / 19th century French biologist Suggested theory of evolution though inheritance of acquired advantageous characteristics e.g., stretching necks & giraffes

  7. Lamarckian Evolution Disadvantageous changes would likely be fatal Could not be experimentally proved No mechanism known at the time for passing on the characteristics Still useful for us, though artificial environments

  8. Mendellian Genetics Gregor Mendel 19th century Austrian monk Experimented with pea plants Demonstrated that traits are passed on via discrete units of inheritance Genes

  9. Mendellian Genetics Selectively self and cross-fertilised pea plants possessing different traits Careful quantitative analysis proved that the frequency of the traits in the offspring determined solely by the frequency of traits in the parents

  10. Darwinian Evolution Central principles some organisms possess qualities that better suit them to their environment these qualities are genetic these qualities arise through mutation more suitable for environment = more fit more fit organisms have more offspring advantageous genes increase in frequency over generations

  11. Darwinian Evolution Darwinian Evolution is not survival of the fittest It does not say that the strong shall live and the weak shall die although this does happen, it’s not the point of the theory The fittest are more likely to have more offspring

  12. Darwinian Evolution Selection of alleles by nature natural selection Fitness is not just suitability to the environment Involves reproductive fitness as well a mutation is of no use if it renders the organism unable to reproduce

  13. Darwinian Evolution Most mutations are harmful don’t get passed on kill the organism Some mutations aren’t expressed recessive mutations require specific environment Expressed when environment changes e.g. pepper moth

  14. Darwinian Evolution Selective pressure an environmental condition that favours the selection of one trait over another Frequency of genes (alleles) will change in response to selective pressure e.g. sickle-cell disease

  15. Darwinian Evolution Origin of species Relies on geographic isolation of populations founder effect Over time, the populations will diverge Galapagos finches

  16. Darwinian Evolution Emergence of a new species does not require the extinction of the parent species only requires separation between the populations When the isolation ends, one species may die out Neanderthals vs. Cro Magnons

  17. Darwinian Evolution Evolution is never ending the environment is never static Changes in one species can affect change in others predator - prey evolution

  18. Summary The accumulation in a population of heritable changes that allow a species to adapt to its environment Accumulation of changes is driven by selective pressure The model of evolution provides a means of creating adaptive intelligent systems evolutionary computation

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