Exercise 19.3

“One, on, no, to, ton, ten”: Diversity Arising from Mutation


In Chapter 19 you read about the amazing range of biodiversity that has evolved on the Earth through mutation and natural selection (or through natural selection and other evolutionary processes), and thought about some of the patterns that are inherent in that diversity. Why do herbivores tend to be so much more diverse than non-herbivores? Why have some groups like sharks and crocodiles persisted for so long while barely changing their shape or ecology? While this simulation doesn’t address these questions directly, it will provide clues to how diversity evolves from mutation. At the very least it will allow you to understand how “one” became “ten” in the title.

This simulation operates using some very simple rules. It starts with a “seed” that you choose, and then that seed is subjected to mutation and selection for 50 generations. In each generation, the following mutation probabilities apply: there is a 25% chance that a random letter will be added; there is a 25% chance that a random letter will be removed; there is a 25% chance that a random letter in the word will be replaced with a new random letter; and there is a 25% chance that two letters will switch places. The simulation will run for 50 generations, and the resulting tree of relationships can then be explored.

A mutation is selected for (the new word branches off from the old one and persists) if the word that it creates is contained in the 38,000-word dictionary that the simulation considers viable progeny. If a mutation results in a word that is not in that dictionary, it simply dies off, although the parent persists (nothing ever goes extinct in this virtual world). Note that the longer the seed word is, the less likely it will be to produce viable progeny via mutations.




Question 1. Does the sequence of words in the first part of the title for this exercise (in quotes) follow the rules outlined above?


Question 2. Of the 4 possible mutations (add, remove, swap, or replace), which occurred most often in the sequence of words leading from “one” and ending in “ten”?

Enter the word “al” into the seed box, click the Seed button, then click Start/Stop to start the simulation. Make a note of how many taxa evolve (shown in the upper right of display). Repeat this process 20 times and record the average (using a spreadsheet will be helpful with this).


Question 3. On average, how many progeny does “al” produce after 50 generations?

Repeat this process using “last” as the seed word.


Question 4. On average, how many progeny does “last” produce after 50 generations?


Question 5. Assuming there was a difference between your answers for Questions 3 and 4, propose an explanation for the difference. When answering this question, think about the selective landscape within which the simulation is operating (i.e., how fitness is defined).


Question 6. Are there evolutionary dead ends in this simulation? What happens if you seed with the word “worldly”?


Question 7. Can a seed with relatively low potential (a mediocre seed such as “al” in Question 3) ever produce large numbers of progeny?


Question 8. Using sharks as an example, make up a biological analogy to your answer to Question 7. (What would need to hypothetically happen for sharks [the “all” of Question 3] to turn into the “last” of Question 4?) As you formulate your answer, consider this question: Sharks are very successful at surviving as a group through evolutionary time, but are they very successful at diversifying?


Question 9. In this system, the evolutionary landscape is fixed (the dictionary is unchanging and never evolves). How is this different from the evolutionary landscape within which biodiversity evolves?


Question 10. Suppose that your goal was to see how much diversity you could produce by using different seeds to start this simulation. Can you think of a good tactic besides just random trials to increase your number of total taxa? How would you go about finding the best seeds to start with?