Evolution essay introduction
Both notes and coins are known as token money because the material in them is worth far less than the value stated on them. The quantities issued are controlled by the R. I, notes and coins are legal tender— that is, money which the law requires people throughout the country to accept as a means of payment. Thus, a shopkeeper may refuse a cheque but cannot refuse notes in payment for goods on display.
Coins are legal tender up to limited amounts. Larger amounts of small change may, of course, be accepted but the law gives the right to refuse. Though not legal tender, cheques based on bank deposits are accepted throughout the community as the normal means of making large payments. Bank deposits, therefore, come within the definition of money. In defining money, a distinction must be made between bank deposits or accounts and the cheques drawn upon them.
A cheque is an instruction to a bank to pay a stated sum of money out of a deposit in cash or transfer it into the deposit of another person named on the cheque. The cheque itself is not money but represents a sum of money in a bank deposit and is a means by which ownership of that money is transferred from one depositor to another.
In an advanced society with a developed banking system, bank deposits are the main form of money. They are convenient to hold arid, through cheques, can be easily and safely transferred in quantities of any size. It is common practice for a cheque to be crossed with two parallel lines at the top left corner requiring it to be paid into a bank account and not cashed directly over the counter. In order to carry out the functions outlined above, whatever serves as money must possess certain qualities? Money must be portable or easily carried about.
It would be very difficult to use anything large and bulky as money. Money must be able to be divided into smaller amounts to enable small purchases to take place.
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The use of large goods or animals would not facilitate divisibility. Money must be accepted as having some value. Labour must accept money in payment for services provided, and retailers must accept money as payment for their goods. Money must last a long time. It must not die, wither away or be easily defaced. Anything which is alive or perishable would not be a very good form of money. Money must be limited in supply to have any value. If money grew on trees then it would cease to have any value. Shells vary in size; they are easily damaged; large payments require much counting and carrying; and they are too easy to find.
Darwin knew nothing of genes. He was unaware of the work of Gregor Mendel, the Austrian monk who worked in his monastery garden and did experiments on the inheritance of pod-color in peas. Mendel discovered that heritable traits such as pod-color are inherited in discrete packages which he called genes. Any act of sexual reproduction of two parents with different genes results in offspring with a random distribution of the parental genes.
Heredity in any population is a random process, resulting in a redistribution of genes between parents and offspring. The numbers of genes of various types are maintained on the average from generation to generation, but the numbers in each individual offspring are random.
The Evolution of Media
Mendel had read Darwin's book, but Darwin never read Mendel's paper. In , the year when Mendel's paper was published, Darwin did a very similar experiment, using snap-dragons instead of peas, and testing the inheritance of flower-shape instead of pod-color. Like Mendel, he bred three generations of plants, and observed the ratio of normal-shaped to star-shaped flowers in the third generation.
Unlike Mendel, he had no understanding of the mathematics of statistical variations. He used only third-generation plants and obtained a value of 2. This result did not suggest any clear picture of the way flower-shapes are inherited.
He stopped the experiment and explored the question no further. Darwin did not understand that he would need a much larger sample to obtain a statistically significant result. Mendel understood statistics. His sample was sixty-four times larger than Darwin's, so that his statistical uncertainty was eight times smaller. He used plants. Mendel's essential insight was to see that sexual reproduction is a system for introducing randomness into inheritance.
In peas as in humans, inheritance is carried by genes that are handed down from parents to offspring.
His simple theory of inheritance carried by genes predicted a ratio of three between green and yellow pods in the third generation. He found a ratio of 3. This gave him confidence that the theory was correct. His experiment required immense patience, continuing for eight years with meticulous attention to detail.
Every plant was carefully isolated to prevent any intruding bee from causing an unintended fertilization. A monastery garden was an ideal place for such experiments. Unfortunately, his experiments ended when his monastic order promoted him to the rank of abbot. Obedient to his vows, he ceased to be an explorer and became an administrator. The idea of genes remained generally unknown to biologists until twenty years after Darwin's death. Darwin imagined various ways of mixing inherited traits of parents and distributing them to offspring, but he never imagined genes. Without the concept of genes, it was impossible for him to calculate correctly the rates of speciation and extinction in any natural population.
He never attempted such calculations. If he had made such calculations with a model of inheritance based on mixing, he would have got drastically wrong answers. He had the good sense not to make such calculations without a verified model of inheritance. Without experimental knowledge of the statistics of inheritance, he had no way to guess reliably how effective natural selection could be in creating new species and exterminating old ones.
At this point in the play, our second character enters, Motoo Kimura, author of the book, The Neutral Theory of Molecular Evolution , published in , more than a hundred years after Darwin's masterpiece. Kimura was a Japanese geneticist who came as a student to work with Sewall Wright at the University of Wisconsin. Sewall Wright was one of the biologists who explored the evolutionary implications of Mendel's discovery after Mendel's paper was rediscovered in I was lucky to meet Sewall Wright accidentally at the faculty club at the University of Wisconsin in I was visiting the University and went to the faculty club for lunch.
Sitting alone at a small table was a lively old man who turned out to be Sewall Wright, then 98 years old but still in full possession of his wits. He gave me a first-hand account of how he read Mendel's paper and decided to devote his life to understanding the consequences of Mendel's ideas.
Wright understood that the inheritance of genes would cause a fundamental randomness in all evolutionary processes. The phenomenon of randomness in evolution was called Genetic Drift. Kimura came to Wisconsin to learn about Genetic Drift, and then returned to Japan. After the discovery of the structure of DNA molecules by Crick and Watson in , Kimura knew that genes are molecules, carrying genetic information in a simple code.
His theory applied only to evolution driven by the statistical inheritance of molecules. He called it the Neutral Theory because it introduced Genetic Drift as a driving force of evolution independent of natural selection.
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I never met Kimura, but he was still alive when I began to study his work, and I was delighted to receive a personal message of encouragement from him before he died in Kimura did not prove that Darwin's theory was wrong. He proved that Darwin's theory was incomplete. Darwin missed Genetic Drift, which was sometimes important and sometimes unimportant. The evolutionary effects of natural selection are generally independent of the size of the evolving population, while the effects of genetic drift depend strongly on population size. Other things being equal, the rate of genetic drift is proportional to the inverse square-root of population size.
The inverse square-root is a simple consequence of the statistics of independent random variables.