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Evolve Version 2.04 User`s Manual

1. Determine number of young of each genotype Emigration Remove emigrants Survival Adults die Immigration Add immigrants Is the number of adults above Max Reduce Population Pop Size ADULT POPULATION Is Experiment finished Figure 4 1 Outline of EVOLVE s simulation and the hypothetical life cycle Given the above life cycle the population usually will either grow or decline depending on the values you give EVOLVE If the product of percent survival and number of young is greater than 100 the population will tend to increase in numbers In order to control the size of the population you may specify upper and lower bounds to it If the population of adults exceeds the upper limit the number of adults is randomly reduced to the lower level The numbers of each of the genotypes are reduced proportionately so a population crash will not directly affect genotype or allele frequencies If survival and reproductive rates result in a negative growth rate their product is less than 100 then the population will decline to extinction regardless of the population size limits In Chapter 4 BACKGROUND 25 essence then the population may be viewed as living in a finite environment with a fixed amount of resources If the population exceeds the resources mortality is random with respect to genotype Note that given the above conditions all individuals are identical with respect to sex and age
2. Chapter 7 Advanced Exercises The exercises in this chapter are designed to help you develop a more complete understanding of the basic design of EVOLVE of the difficulties of determining what types of selection might be occurring in nature and of how one might study evolution statistically Exercise 22 The Model Underlying EVOLVE As noted in Chapter 1 theoretically minded evolutionists have continued to try to develop models of evolutionary and ecological processes despite or because of difficulties with experimentation Their models are conceptual rather than experimental often mathematically sophisticated and a complete understanding of some of them requires the use of probability calculus matrix algebra Markov Chains and or game theory Such models clearly are beyond the scope of many biology courses Nevertheless modeling is too useful a process to ignore By the time you get to this exercise you should have spent quite a bit of time using EVOLVE but you probably do not really understand how it can produce realistic results in such a wide variety of evolutionary situations What we shall do in this exercise is establish a simple intuitive model and explore the results it produces in one evolutionary situation This will give you an understanding of one approach to modeling An understanding of the basic approach of this type of model is very important in more detailed analyses of its results Before going to class consi
3. Heterozygote An individual with two different alleles at one gene locus on the pair of chromosomes present in a diploid organism Heterosis The condition of hybrid vigor the superiority of crossbred individuals over corresponding inbred individuals Sometimes used to describe a condition where heterozygotes have higher fitness than homozygotes overdominance for fitness For example in environments where malaria is prevalent GLOSSARY 81 heterozygotes for the sickle cell anemia allele exhibit heterosis because they are more resistant to malaria than normal homozygotes and do not suffer the severe anemia of sickle cell homozygotes Immigration Movement of individual organisms out of a population Incomplete dominance Pattern of inheritance in which a heterozygote shows a phenotype that is quantitatively intermediate between the phenotypes of the homozygotes In four o clock plants homozygous RR individuals have red petals flowers of homozygous rr individuals are white and heterozygous Rr individuals have pink petals Intrinsic Rate of Natural Increase The difference between Birth Rate and Death Rate often symbolized by r Usually conceived of as the rate at which a population could grow in an environment with unlimited resources K See Carrying Capacity Macroevolution The evolution of large phenotypic changes usually large enough that the changed organisms may be regarded as a distinct new genus or higher taxon M
4. Now that you have some feel for the way EVOLVE works we must take time to go over some fundamental concepts and background so you can make more effective use of it As mentioned in the Introduction simulations such as EVOLVE have a large mathematical component and you should eventually work through the material in Chapters 7 and 8 However EVOLVE can be used effectively at an introductory level without such details for it embodies an intuitively simple yet realistic model of evolution The purpose of this chapter is to give you a better intuitive feel for EVOLVE and some of the fundamental genetic and evolutionary concepts behind it Also while many evolutionary situations may be simulated with EVOLVE it has limitations and you must understand the nature of the hypothetical population The next sections discuss the genetic concepts and hypothetical organisms on which EVOLVE is built that is the assumptions inherent in the program The Hypothetical Organisms EVOLVE is not based on any particular animal or plant but on a hypothetical organism with several characteristics that make it useful for the sorts of experiments you will be doing The organisms live in a discrete habitat such as an island lake or mountain top separated from other patches of habitat and form a single local population within which mating is random The individuals in the population are diploid hermaphrodites and produce both eggs and sperm Each adult normally ma
5. Rio UEST M EOL F F Ss Library VII Evolve Version 2 04 User s Manual Frank Price Hamilton College Virginia G Vaughan BioQUEST Curriculum Consortium A BioQUEST Library VII Online module published by the BioOQUEST Curriculum Consortium The BioQUEST Curriculum Consortium 1986 actively supports educators interested in the reform of undergraduate biology and engages in the collaborative development of curricula We encourage the use of simulations databases and tools to construct learning environments where students are able to engage in activities like those of practicing scientists Email bioquest beloit edu Website http bioquest org Editorial Staff Editor John R Jungck Managing Editor Ethel D Stanley Associate Editors Sam Donovan Stephen Everse Marion Fass Margaret Waterman Ethel D Stanley Online Editor Amanda Everse Editorial Assistant Sue Risseeuw Beloit College Beloit College BioOQUEST Curriculum Consortium University of Pittsburgh University of Vermont Beloit College Southeast Missouri State University Beloit College BioQUEST Curriculum Consortium Beloit College BioOQUEST Curriculum Consortium Beloit College BioQUEST Curriculum Consortium Editorial Board Ken Brown University of Technology Sydney AU Joyce Cadwallader St Mary of the Woods College Eloise Carter Oxford College Peter Lockhart Massey University NZ Ed Louis The University of Nottingham UK Claudi
6. 100 Carrying capacity 9999 Post crash pop size 7000 ee e 0 0 Q Initial population 1711 278 11 Survival rates 20 24 24 Reproductive rates 5 6 6 Number immigrating 16 4 0 Percent emigrating 0 0 0 Title 15B Sel vs Gene Flow 5 Number immigrating 160 40 0 Title 15C Sel vs Gene Flow 50 Number immigrating 1600 400 0 Prediction enter your own Results Describe the changes in allele and genotype frequencies in these populations and compare them with the changes in Experiment 8A Conclusion Does this experiment support the hypothesis that gene flow could reduce the divergence of populations Chapter 6 Intermediate Exercises This chapter provides some additional exercises to sharpen your understanding of evolution These exercises differ from earlier ones by being more quantitative and more abstractly formulated The impact of selection on population sizes will also be examined in this chapter We assume a fair amount of sophistication on the part of the student and do not set up experiments in as much detail as in the previous chapter Because evolution is the result of the interaction of many statistical phenomenon and because EVOLVE simulates random processes one or even several runs with a particular set of variable values may not show all of the variation needed to understand the phenomena being studied Many of these exercises are best done by teams of students who divide up a number of runs and then pool
7. Carrying capacity 50 Post crash size 30 Run to generation 43 When EVOLVE stops in generation 43 go back and return the variables to the following Carrying capacity 9999 Post crash size 8000 Run to generation 100 Compare the graphs of allele frequency and total population size The allele frequencies changed relatively little during the first 40 generations when the population cycles between 8000 and 10 000 during the 3 generation crash however the 22 EVOLVE Manual allele frequencies drifted away from 0 50 Subsequently as the population grew back the generation to generation fluctuations tapered off The final population was different from the original because 1 the founders of the new larger population were a small sample from the original large population and 2 while the population was rebuilding drift continued to operate albeit to a lesser degree as the population size increased This completes our tutorial on EVOLVE We hope you have enjoyed learning to play the game and will use it extensively enough to get a good feel for the interaction of evolutionary forces The next chapters list a series of exercises that will help you use EVOLVE to explore a variety of evolutionary phenomena The last two chapters contain additional information on setting up experiments and on population genetics don t overlook them for they provide more guidance on evolution and on EVOLVE Chapter 4 Background
8. growth rate mean fitness Size of Pop Size of 0 Pop Size of 00 Pop Graphs of individual genotypes are useful at the introductory level to show what is happening to the population and to show the Hardy Weinberg relationship Some Chapter 8 PROGRAM NOTES amp SETTING UP EVOLUTIONARY EXPERIMENTS 67 students ask for graphs of one or more genotypes when they have difficulty interpreting particular runs Beyond these introductory uses genotype graphs are probably of little value to most students However the steepness of the peaks and the spacing between them clearly illustrate that what ecologists call intrinsic rate of natural increase evolves over time and is a measure of the average absolute fitness of a population The last three population variables shown above can be used to graph the numbers of a phenotype If for example is recessive then would be the recessive phenotype and 0 00 would be the dominant phenotype Each of these variables can be graphed on a logarithmic scale by selecting the Log scale box in the New Graph Window A log plot enables you to look at numbers that vary greatly in size For example if the number of in an experiment went from 0 to 4000 a linear non log plot would not allow you to distinguish changes below several hundred individuals a log plot would let you distinguish generations with only one or two individuals While actual numbers of individuals are instructive th
9. it takes the survival rate and seed you gave it and produces an actual survival rate that is multiplied by the number of young to obtain the number of adults The actual survival rates used by EVOLVE over a number of generations will have an average value very close to the value you gave it although the value of a given generation will be uncertain If you input 60 as the survival rate of a genotype the rates used in 5 consecutive generations might be 61 8 66 3 53 9 57 5 and 60 3 for an average of 59 96 If you used another seed the 5 survival rates would be different but would still average out to about 60 This may seem complicated but it is a practical way of simulating the sort of variations that occur in nature For example weather might be mild for a couple of years then harsh or predators that take advantage of one phenotype might be unusually abundant in one generation and unusually scarce in another If climate is what you expect weather is what you get you enter climate into EVOLVE s menus the random number generator gives you weather Number of Generations EVOLVE will continue an experiment for the number of generations specified by this number Although you may stop an experiment at any time it may be useful to have EVOLVE stop at a predetermined time Because it takes longer to run many generations you may wish to explore combinations of data by running for say 50 generations instead of th
10. 00 T T T T T ay Frequency D o oa E r o o o o T L L o m a Ema Pane Control J ii 1 fi 1 1 J 60 a0 Generations i Freq se Freq eo Fr 0 03 Change Params Problem Control Buttons Figure 2 2 Problem Summary Window This window allows you to run and stop experiments and display their results a o 9 pot Gen ee Pop Pop amp 2 We will refer to the labels in this picture throughout this tutorial Chapter 2 Getting Started 9 Click on the Change Params button You will see Figure 2 3 rial 1 Initial Population EJ Hardy Weinberg Equilibrium Allele Frequencies o abe Genotype Pop 20 760 7220 Total Pop 8000 Evolutionary Forces Natural Selection Genetic Drift Survival Rates Reproduction Rates Update Figure 2 3 Parameter Input Window This window allows you to change any of the variables parameters that control a trial The Change Parameter window allows you to enter and modify the parameters or variables that control a trial Parameters are contained in edit boxes Information in the window that is not visible or not enclosed in an edit box cannot be changed Initially the window contains sample default values The initial values depend on the problem selected in the Problem Selection window Figure 2 1 You will change the values to
11. 3000 1200 7700 Chapter 9 THEORETICAL NOTES 73 1 Calculate observed frequency of each genotype in generation 2 Freq of AA 3500 7700 0 455 Freq of Aa 3000 7700 0 390 Freq of aa 1200 7700 0 156 Check sum 1 001 accurate to rounding error 2 Calculate expected frequency of each genotype in generation 2 From the Hardy Weinberg equilibrium we expect the allele frequency in generation 2 to equal that in generation 1 and that the frequencies of the genotypes will be p 2pq and q a allele frequencies in generation 1 expected allele frequency in generation 2 Freq of A p 2 4000 5000 2 12000 0 542 Freq ofa q 2 3000 5000 2 12000 0 458 Check sum 1 000 b Expected genotype frequencies in generation 2 Freq f AA p 0 542 2 0 294 Freq of Aa 2pq 2 0 542 0 458 0 496 Freq ofaa q 0 458 0 210 Check sum 1 000 3 Calculate the absolute fitness of each genotype Rgenotype selection as the observed frequency divided by the expected Raa 0 455 0 294 1 548 0 390 0 496 0 746 Raa Raa 0 156 0 210 0 743 74 EVOLVE Manual 4 Calculate the relative fitness of each genotype W genotype as the absolute fitness divided by the highest absolute fitness Waa 1 548 1 548 1 000 Waa 0 746 1 548 0 508 Waa 0 743 1 548 0 480 5 Calculate the selection coefficients of each genotype s genotype as the relative fitnesses subtra
12. and choose what information you wish to look at and where and how you use that information In this version of EVOLVE Copy commands in the Edit menu are the only way information is moved These commands can be used with any of the graph or data windows to move either graphic or numeric information Copy Window will save a bit mapped copy of a window The image includes every dot in the window including its title and borders Copy Window images have only 72 dots per inch dpi and do not have smooth lines when printed on a laser printer unless the image is scaled down in size Copy Window Graph places a copy of the lines and text of a graph without the surrounding window The image is not stored as dots but as what is called a PICT and can be printed with the full resolution of the printer you are using When printed on a laser printer Copy Window Graph images are free of the jaggies produced by Copy Window images there may however be some problems with symbols and text in some situations 66 EVOLVE Manual Copy Window Data can be used to store numbers to the clipboard The numbers are separated by tab characters and can be Pasted into most statistics and spread sheet programs where they can be subjected to more sophisticated analysis and graphing They can also be copied into word processors if you need to report numerical results in a data table The Notepad Each Summary Window has a Notepad that is a mini word processor w
13. and the Carrying Capacity itself changes over time However the J shaped pattern of growth and crash illustrated in EVOLVE s population graphs does provide some measure of ecological reality as a consequence of the way limits are specified for genetic drift In addition the steepness of the Js and the spacing between them clearly illustrate that a population s intrinsic rate of natural increase evolves over time and is a measure of the average absolute fitness of a population EVOLVE S concept of gene flow the evolutionary consequence of the dispersal of individual organisms studied by ecologists is an extremely simplistic one For instance the number of individuals immigrating is unlikely to be a constant The source population s that produce immigrants will probably fluctuate when the population is low it will produce fewer immigrants for the population modeled by EVOLVE Also 76 EVOLVE Manual the size of EVOLVE s population should influence the number of immigrants that actually stay if it is large one would expect resources to be limiting and more potential immigrants to move on in search of more abundant food shelter or whatever Finally at high population densities when resources are in short supply we would expect a higher proportion of the population to emigrate Despite its simplicity EVOLVE does provide an entry into the world of theoretical population genetics Although that world has evolved quite far from the initial s
14. assumption 5 Also assumption 6 infinite population size can be disregarded if the population is fairly large over a few thousand Mutation assumption 2 may be disregarded for most genes because mutation rates are too low to affect allele frequencies significantly in the short term Over the long haul of course mutation is critically important because it is the ultimate source of all genetic variation Finally although it is usually discussed for a gene with two alleles the Hardy Weinberg formula may even be extended to genes with more than two alleles by using the polynomial expansion If there are three alleles in a population their frequencies should add up to one p q r 1 and the frequencies of the genotypes would be p g r 12 or p g 72 2pq 2pr gr 1 70 EVOLVE Manual Importance of Hardy Weinberg Equilibrium Despite its limitations and qualifications the Hardy Weinberg concept has been useful in three major ways 1 The Hardy Weinberg concept makes mathematical predictions of what allele and genotype frequencies should be in the absence of evolution It thus provides the Null Hypothesis needed for statistically rigorous tests of our ideas See the BioQUEST statistics module if you are uncertain of this If we have a way to measure those frequencies and if they do not match the predictions then we know that evolution is occurring This obviously is important because visible changes in populat
15. either registered trademarks or trademarks of Microsoft Corporation Helvetica Times and Palatino are registered trademarks of Linotype Hell The BioQUEST Library and BioQUEST Curriculum Consortium are trademarks of Beloit College Each BioQUEST module is a trademark of its respective institutions authors All other company and product names are trademarks or registered trademarks of their respective owners Portions of some modules software were created using Extender GrafPak by Invention Software Corporation Some modules software use the BioOQUEST Toolkit licensed from Project BioQUEST TABLE OF CONTENTS Acknowledgment Sissonne i eea eset ease nean ssaneuteadandaneddadesbasdaadonsajagesaalawwbeasseontanse i TABLE OFCONTEN Srania n aa a E ara aa NNER ii LIST OF FIGURES ET ERE EAEE EATE ANE E E v Part 1 LEARNING TO USE EVOLVE W000 cccc cece cc eccccecececececececececececececececececececececececececececececees 1 Preface WHAT YOU NEED TO KNOW uun o oo occ c cece cccecccecececececececececececececececececececececececececece 2 Chapter 1 INTRODUCTION cuissin dangai acca aa enna EA EEE 4 Chapter 2 GEITING STAs TEI iis coreacose cetcacs penngeaia essen te vecpectalastacaieaneactid aceoemnciiiaateutnte 6 INTRODUCTION sisee ccctececcusdighs cosdaaeedesdazescatdeahecwabonnscesdganccecnseeecastseneaesbagnecastensedessaueecestaxs 6 THE HELP SYSTEM 0 cc cece ccceccccccccececececececececececececececececececececececececececececececececececscece
16. especially a small one may result in deviations from the expected proportions of genotypes among offspring You may find it helpful to make several runs with each set of data to get a feel for chance variations Calculating Fitness and Selection Coefficients Despite the importance of measuring actual fitness and selection in nature availability of the conceptual tools provided by the Hardy Weinberg concept evolutionary biologists have had difficulty actually collecting the data Not until the advent of electrophoresis in the mid 1960 s was there a method which gave clear data on the frequency of alleles in natural populations However there is some doubt about the evolutionary significance of electrophoretic variants so even these relatively clear data 72 EVOLVE Manual are difficult to interpret Some scientists would rather look at morphological or life history traits such as length of teeth age of first reproduction that are of more obvious evolutionary value Unfortunately it is almost impossible to measure the genetic variability that underlies these phenotypes Aside from the difficulty of gathering the data exactly how fitness and intensity of selection might be calculated from real world data is a matter of considerable controversy There is a large body of literature devoted to this discussion We might point out here that our difficulties with collecting and interpreting data in no way invalidate the scientific nature of ou
17. evolutionary fate of a population showing heterosis Compare the changes in allele frequencies in a populations where the heterozygous 0 genotype is more fit than either of the homozygotes A convenient metaphor that may be helpful in planning experiments is to think of yourself as exploring a landscape on the plane illustrated in Figure 6 1 below The horizontal axis represents the absolute fitnesses of the two homozygotes On the far left the 00 homozygote s fitness is zero and the has very much higher fitness In the middle the fitness of the two homozygotes is equal On the right the has a fitness of zero and the o is higher but still less than that of the heterozygote Four runs are outlined for you on the figure and in the table below In Run 1 and Run 2 the homozygotes have equal fitnesses of 1 5 the only difference between the two is that Run 1 starts with an initial frequency of 5 while Run 2 starts with a frequency of Chapter 6 INTERMEDIATE EXERCISES 51 95 Run 3 starts with the same low allele frequency as Run 1 but the fitness of the gt o homozygote is zero In Run 4 the initial allele frequency is the same as Run 3 but the genotype has a lower but non zero fitness and the 00 genotype has a higher fitness You should make these runs and other runs of your own design to fill in the unexplored open areas of the figure 1 0 Run Run 0 8 2 4 Initial Freq 0 6 of Allele 9 4 0 2 Run Run 3 1 ot
18. examine such things as mutation rates and mutational equilibrium However it does allow you to study the fate of a mutation that has already occurred and that is the objective of this exercise Exercise 13 What Is the Fate of Advantageous Mutant Alleles You have already made runs with advantageous dominant and advantageous recessive alleles using initial advantageous allele frequencies of 5 Using the results of those runs as controls compare the fate of an advantageous recessive mutant or that of an advantageous dominant mutant and explain what happens Prediction enter your own Experiment To simulate a population in which a mutation has just occurred you will want an initial population with many s 1 0 and 0 00s The phenotypes of the dominant and recessive advantageous alleles should be the same as those used in Exercise 7 or 8 whichever will be your control You may wish to make additional runs Results Summarize the results of your runs Conclusion What is the typical fate of a new advantageous dominant mutant Most mutations that affect the phenotype are believed to be recessive and deleterious What then is the fate of most such mutations What about mutations that have no effect on the phenotype 46 EVOLVE Manual Combining Evolutionary Forces The exercises up to this point have attempted to help you gain a feel for how individual evolutionary forces operate by themselves However no real population is su
19. of the populations in Question 1 would become extinct if there were 4000 individuals the frequencies of both alleles were equal to 0 5 and the genotypes were initially in Hardy Weinberg equilibrium a b ce d e f Exercise 16 Selection via Reproduction vs Selection via Survival In our formulation of the concepts of relative and absolute fitness we multiply reproductive rate by survival rate to obtain single coefficients of fitness for each allele and genotype We then compare and standardize those coefficients by dividing by the largest While this approach is a useful and powerful one it is always worth asking if the technique used to study some phenomenon might obscure interesting points One such question is whether or not it makes a difference if a given pattern of selection is achieved by survival rate or by reproductive rate or by a combination of both For example the absolute fitness of a genotype with 20 survival and an average of 6 50 EVOLVE Manual offspring 2 x 6 1 2 The same fitness could be achieved by 40 survival and 3 young or 30 survival and 4 young or 60 survival and 2 young Would evolution proceed the same in two populations with identical fitness and selection coefficients if one achieved that pattern of selection with high survival and low reproduction and the other achieved it with low survival and high reproductive rates Write down your predictions of what you expect to happen Set up and run a
20. organisms that actually or potentially could interbreed in nature and which is reproductively isolated from other such groups the largest group within which gene flow could occur
21. rates would be input to EVOLVE The allele would be dominant and advantageous with respect to survival but incompletely dominant and deleterious with respect to reproduction What would happen to the population The 0 genotype although it has a low survival rate has a high reproductive rate Would the higher reproductive rate make up for the reduced survival Would the allele increase or decrease in the population Would it become extinct Would the allele become extinct Or would both remain in the population Multiplying survival rates by reproductive rates gives us the third row the absolute fitness Here it is clear that the high reproductive capacity of the 00 genotype does not completely compensate for the low survival for the absolute fitness of 98 is less than 100 By dividing all of the absolute fitnesses by 120 the highest you can see that the homozygotes have only 83 of the fitness of the heterozygotes while the 00 individuals have only 82 relative fitness By the time you finish your experiments with EVOLVE you should be able to predict the outcome of such an evolutionary situation by calculating the relative fitnesses 64 EVOLVE Manual Gene Flow To simulate gene flow the movement of alleles from one population to another you must enter rates of immigration arrival and emigration departure for each genotype The number immigrating may vary from 0 to 4000 adults of each genotype per generation The percent
22. sexually and are identical with respect to such factors as age and sex Chapter 9 THEORETICAL NOTES 69 2 Genes do not change from one allele to another The population is closed and alleles do not enter or leave Gametes are produced and combine randomly go e w All zygotes survive and reproduce equally 6 The population size is infinite or at least very large Evolutionary Forces In essence then the conditions necessary for Hardy Weinberg equilibrium tell us that for sexual species there are only six evolutionary forces factors processes or phenomena that change allele or genotype frequencies 1 Individuals are not equivalent for example the gene is sex linked 2 Genes change from one allele to another mutation 3 Genes move between geographic populations gene flow 4 There is nonrandom mating or gamete production and survival are not equal for example gametic mortality 5 Individuals differ in their ability to survive and or reproduce natural selection 6 Populations are of small size genetic drift Obviously populations that fit all of the above assumptions are rare if they exist at all However some assumptions may not be important in particular populations and it is often possible to relax others For example for all practical purposes populations on remote islands may be regarded as closed to immigration assumption 3 and emigration may be considered as mortality natural selection
23. the homozygote has the highest survival and reproductive rates Natural selection would favor the homozygotes As you work with EVOLVE you will gain a better feel for how these parameters interact From the start however you may easily determine the absolute fitness of a genotype by multiplying the number of young by the survival rate Products greater than 100 indicate that the genotype will tend to increase in number while products less than 100 indicate that the genotype will tend to decrease in number Thus absolute fitness tells you how the actual numbers of individual organisms are likely to change However the absolute fitness of a genotype does not necessarily tell you whether the proportion of that genotype in the population will rise that is whether that genotype is favored by natural selection The relative sizes of the absolute fitnesses of the genotypes will indicate how the proportions of particular genotypes will tend to change over time Dividing the absolute fitness of each genotype by the highest absolute fitness yields the relative fitness The maximum value of the relative fitness will of course be one Genotypes with relative fitnesses less than one will tend to decrease in frequency Take as an example the following Genotype Phenotype oe 20 Q 0 Survival rate 20 20 14 Reproductive rate 5 6 7 Absolute fitness 100 120 98 Relative fitness 0 83 1 0 0 82 In this table the survival and reproductive
24. the post crash size The population continued this saw tooth pattern of growth and crash with the crashes becoming more frequent so that after generation 24 it was crashing every other generation After generation 32 the population growth rate was So great that it grew to over 9999 and crashed in every generation Click slowly three times on the HI box The graph zooms out to its original scale then in then out again 14 EVOLVE Manual Examine any of the various graphs as much as you wish If you have time and have read through Chapter 3 you may go on to the exercises in Chapter 4 If not leave EVOLVE as follows Leaving EVOLVE Select Quit from the File Menu EVOLVE will quit and return you to the Mac s desktop You will be given an opportunity to save your data Click on the Quit button This completes our first quick look at EVOLVE If you wish to continue exploring how to use EVOLVE turn to Chapter 3 If you wish to examine some of the background concepts that lie behind EVOLVE jump to Chapter 4 then come back to Chapter 3 Chapter 3 MORE ADVANCED FEATURES OF EVOLVE 15 Chapter 3 More Advanced Features of EVOLVE Introduction Doing Experiments with EVOLVE In the last two chapters we introduced you to the most basic uses of EVOLVE setting up an experiment running it and looking at the results and to some background information on the conceptual design of EVOLVE s model of evolution In this chapt
25. their results Preliminary Exercises Like those in Chapter 5 these initial exercises begin with a few questions designed to test your understanding of some basic concepts underlying EVOLVE In this case we will be using the more abstract concepts of absolute and relative fitness studying their impact on growth of population size Use the following tables to answer Questions 1 5 a Genotype b Genotype Phenotype 0 00 0 00 Surviv rate 25 0 25 0 20 0 50 0 30 0 30 0 Reprod rate 3 0 3 0 3 0 2 0 3 0 3 0 c Genotype d Genotype Phenotype 0 00 0 00 Surviv rate 40 0 40 0 58 0 12 0 18 0 24 0 Reprod rate 1 0 2 0 3 0 9 0 9 0 9 0 e Genotype f None of above Phenotype 0 00 Surviv rate 60 0 75 0 65 0 Reprod rate 2 0 1 0 1 0 1 Calculate the absolute and relative fitnesses of each genotype in each table a Fitness b Fitness Genotype Absolute Relative Absolute Relative 0 0 Chapter 6 INTERMEDIATE EXERCISES 49 c Fitness d Fitness Genotype Absolute Relative Absolute Relative Q 0 0 e Fitness f Genotype Absolute Relative 0 0 o 2 Which of the tables in Question 1 shows dominance with respect to relative fitness a b c d e f 3 Which of the tables in Question 1 shows heterosis for relative fitness a b ce d e f 4 Which of the tables in Question 1 shows incomplete dominance for relative fitness a b ce d e f 5 Which
26. turn off once you have clicked on an item 3 To browse through all of the information available about EVOLVE Choose Help with Evolve under the menu on the far left This allows you to choose from a list of topics and display information on the topic that interests you Buttons at the bottom of the window let you move to additional topics in the list Program Input Title Be sure to enter a brief descriptive title for your experiments You will eventually accumulate many different experiments and the titles will help you keep them straight For example if a number of people are storing their results on one disk you should put your initials in the title so you won t get your results mixed up with someone else s Seed This is a whole number between 0 and 32767 It is used by the computer to simulate random mating the effects of weather and other random factors You may let EVOLVE pick the seed for you or you can type a seed in if you wish If you use the same seed in different experiments you can be sure that any variations in output are caused by changes in other variables If you use different seeds with no change in other parameters you can assess the influence of chance In essence this amounts to running the same experiment again A thorough understanding of the seed is not necessary for you to use EVOLVE you may find the following background helpful EVOLVE takes the seed you enter in the Seed box and performs a s
27. Hardy Weinberg equilibrium in the same way You may want to try some other experiments of your own devising to test your understanding Can you think of types of disequilibria that EVOLVE cannot model Exercise 6 Set up a Population in Hardy Weinberg Equilibrium In the blanks below set up another run in which the initial frequency of the o allele equals 25 the initial genotype frequencies are in Hardy Weinberg equilibrium and the population totals 4000 individuals Let the frequency of q 0 25 then use the Hardy Weinberg genotype frequencies to calculate the predicted number of each genotype Use survival and reproductive rates that produces a slowly growing population and in which there is no selection Do not use the same rates as in Exercise 5 If you wish make such arun You should be able to tell from the printout whether your initial population was in equilibrium Do you understand the results you get Title Carrying capacity Post crash pop size Initial population Survival rates Reproductive rates Number immigrating Percent emigrating In all future runs of EVOLVE you should use initial populations that are in Hardy Weinberg equilibrium why Chapter 5 ELEMENTARY EXERCISES 37 Natural Selection Natural selection is perhaps the most important of the evolutionary forces because it is the one most likely to lead to adaptation Hence we will devote the majority of the remainder of this ch
28. LENGIH IPAS a aaaea arae AEE A AE A EA AATE AEEA 77 ADVANCED TEXTS ss eesseesesssneesseeessesssessscesseressssesssessesssressoresoresosessstsssecesoreessseesessse 78 GLOSSARY sscioessreir aiene iee eE e E ENEA EE a EEEE EE EAE E EATE E eS 79 Figure 2 1 Figure 2 2 Figure 2 3 Figure 2 4 Figure 2 5 Figure 2 6 Figure 3 1 Figure 4 1 Figure 6 1 List of Figures Problem Selection Wid OW isc sdssnsteatcctaniaiatenscasacdsacrsaseltnatasataatanaesaanemealcanaaaneenas 8 Problem Summary WindoW vaciacsrassscsinileleserstmstiacersisoiideieaasteeleeeninees 8 Parameter Input Windo W sseipeniienianne aia aaia a 9 Summary Window after Trial asccpeacaras inecid coteurgsesetestatorsuatasalebaaninmnpetenestgutpecsies 10 Graph of Allele Frequencies and Heterozygote Frequency vs Time 11 Total Population SAS vs VAIS ssrorinsnirrniinatuseanatr ar 13 Outline of an EVOLVE S s5i N sissioni niia aa eiaa 15 Outline of EVOLVF s Simulation and the Hypothetical Life Cycle 24 A Metaphorical Landscape For Exploring HeteroSis ccccccccccesesesseeseees 51 Part 1 Learning To Use Evolve This manual has three major parts Part 1 teaches you to use EVOLVE Part 2 teaches you something about asking evolutionary questions through suggested exercises with EVOLVE and Part 3 contains reference material on EVOLVE and how it relates to evolutionary biology An additional manual the Getting Started Manual is av
29. Post crash 70 3 n L Survival rates Absolute fitness 0 0 0 0 0 0 1 5 2 0 0 0 Relative fitness Reproductive rates 0 0 0 0 0 0 0 of allele 0 95 Frequency of in generation 100 Initial frequency gt gt of allele 0 05 Frequency of in generation 100 Chapter 6 INTERMEDIATE EXERCISES 53 Initial Initial population frequency Run No Max pop Post crash 0 0 gt of allele 4 _ 0 95 Survival rates Absolute fitness Frequency of in 0 00 0 0 0 generation 100 0 5 2 0 1 75 Reproductive rates Relative fitness 0 0 0 0 0 0 Exercise 18 Modeling the Real World Sickle Cell Anemia It is always a good idea to test your scientific models against the real world Often data needed to do such a test are available in the scientific literature In Chapter 3 of this manual we used sickle cell anemia as an example of a somewhat complex evolutionary situation but we did not fill in our tables with actual data on survival and reproduction Do some library research and see if you can find hard data on the survival and reproductive rates of people with each of the sickle cell genotypes in areas with and without endemic malaria Use those data as inputs to EVOLVE and see if the program predicts the actual allele frequencies observed in those populations Comment on the closeness of the results and discuss factors that might have affected EVOLVE s accuracy Exercis
30. a Neuhauser University of Minnesota Angelo Collins Knowles Science Teaching Foundation Patti Soderberg Conserve School Terry L Derting Murray State University Roscoe Giles Boston University Louis Gross University of Tennessee Knoxville Yaffa Grossman Beloit College Raquel Holmes Boston University Stacey Kiser Lane Community College Daniel Udovic University of Oregon Rama Viswanathan Beloit College Linda Weinland Edison College Anton Weisstein Truman University Richard Wilson Emeritus Rockhurst College William Wimsatt University of Chicago Copyright 1993 2006 by Frank Price and Virginia G Vaughan All rights reserved Copyright Trademark and License Acknowledgments Portions of the BioOQUEST Library are copyrighted by Annenberg CPB Apple Computer Inc Beloit College Claris Corporation Microsoft Corporation and the authors of individually titled modules All rights reserved System 6 System 7 System 8 Mac OS 8 Finder and SimpleText are trademarks of Apple Computer Incorporated HyperCard and HyperTalk MultiFinder QuickTime Apple Mac Macintosh Power Macintosh LaserWriter ImageWriter and the Apple logo are registered trademarks of Apple Computer Incorporated Claris and HyperCard Player 2 1 are registered trademarks of Claris Corporation Extend is a trademark of Imagine That Incorporated Adobe Acrobat and PageMaker are trademarks of Adobe Systems Incorporated Microsoft Windows MS DOS and Windows NT are
31. ailable The Getting Started Manual contains only Part 1 Learning to Use Evolve and may be all that most students will need to begin using EVOLVE The full User s Manual should however be available in lab or computer facility Preface What You Need To Know This manual assumes that you are familiar with operation of the Macintosh including pointing clicking dragging double clicking editing text opening applications and saving and opening documents If not you should learn these basic Macintosh operations before continuing with this tutorial In Part 1 Learning To Use Evolve you will do the sample exercise in Chapter 2 Getting Started to get a feel for how to use EVOLVE Chapter 3 More Advanced Features of EVOLVE contains three more sample exercises to give you experience with all of EVOLVE s features You should do at least the first two exercises the last may be omitted unless you will need to model a changing environment You could then skim through Chapter 4 Background to get some perspective on population genetics and on the conceptual design of EVOLVE Later when you are more familiar with both EVOLVE and evolution you may find it worthwhile to reread Chapter 4 with more care Part 2 Experimenting with Evolution contains a number of sample exercises which both illustrate the capabilities of EVOLVE and demonstrate many features of evolutionary processes Your instructor may assign some of the exercise
32. allele frequencies you calculated above determine the numbers of each of the genotypes you would expect if the population were in Hardy Weinberg equilibrium No Now _ NO 00 c Is the population in Hardy Weinberg equilibrium Chapter 5 ELEMENTARY EXERCISES 33 Survival and Reproductive Rates For Questions 3 6 use the following data The tables below show possible survival and reproductive rates for five runs of EVOLVE Survival rates are measured in terms of percent of each genotype surviving from birth or hatching germinating to reproductive age Reproductive rates are measured as the average number of young born per individual of each genotype a Genotype b Genotype Phenotype 0 00 0 00 Surviv rate 25 0 25 0 20 0 50 0 30 0 30 0 Reprod rate 3 0 3 0 3 0 2 0 3 0 3 0 c Genotype d Genotype Phenotype 0 00 e 0 00 Surviv rate 40 0 40 0 58 0 12 0 18 0 24 0 Reprod rate 1 0 2 0 3 0 9 0 9 0 9 0 e Genotype f None of above Phenotype 0 00 Surviv rate 60 0 75 0 65 0 Reprod rate 2 0 1 0 1 0 3 In which of the tables is dominant for survival rate a b c de f 4 In which of the tables is recessive for reproductive rates a b c de f 5 In which of the tables are and heterotic for survival rate a b c d e f 6 In which of the tables do the alleles show incomplete dominance for reproductive rates Hardy Weinberg Equilibrium These next two exercises
33. appeared only in seeds that were homozygous for the green allele Assume further that the birds alleles have no effect on survival and all genotypes have a 22 chance of surviving to produce young To ensure that selection is the only evolutionary force operating on the population we need a large population and no gene flow We will start a population of 8000 organisms with a allele frequency of 5 If you don t know about genetic equilibrium don t worry it will come later To make the allele recessive and advantageous we will give the homozygotes a higher reproductive rate 8 than the other genotypes both of which will be 5 8 EVOLVE Manual Setting up the Experiment Look for a window similar to Figure 2 1 below If you do not see one pull down the File menu and select New Problem then click on the New button Evolve Version 2 641 1 29 97 Please choose a problem Selection for Dominant Allele Strong Sel for Dominant Allele Selection for Heterozygotes Genetic Drift Pop 88 188 Gene Flow and Selection Default Problem start Probie Figure 2 1 Problem Selection Window This window appears when you start EVOLVE or when you select the New Problem command from the File menu Click on Sel for recessive allele and then Start Problem You should see the following window Notepad icon Trial PopUp Graph Controls SZ inion for Recessive Alle Trial 1 arene i H k 1
34. apter to an examination of patterns of selection Exercise 7 What Effect Does Increasing the Strength of Selection Have on the Evolution of an Advantageous Dominant Allele Prediction Setting up two populations one with large and one with small differences between survival and or reproductive rates of the two phenotypes should show that evolution that is change in allele and genotype frequencies proceeds more rapidly when the differences are larger Experiment Use the following data for your two runs of EVOLVE 1st run Title 7A Sel for Dominant Allele 0 Number of generations 100 Carrying capacity 9999 Post crash pop size 7000 ee 0 0 Q Initial population 1711 278 11 Survival rates 20 24 24 Reproductive rates 6 6 6 2nd run Title 7A Sel for Dominant Allele 0 Number of generations 100 Carrying capacity 9999 Post crash pop size 7000 ee e 0 0 Q Initial population 1711 278 11 Survival rates 20 34 34 Reproductive rates 6 6 6 Results Fill in the following tables from the data table produced by EVOLVE Again note that these tables are provided to help you learn what to look for and how to read EVOLVE s graphs You will soon be able to see most of the clues on the screen without transcribing the data onto paper If your are experienced with spreadsheets you can also use Copy Window Data to copy the data to the Mac s clipboard Then Paste the results into a spreadsheet and generate the tables below w
35. as initially phrased was a useful one Exercise 9 How Does the Evolution of Incompletely Dominant Alleles Differ from the Evolution of Completely Dominant Alleles Not all alleles display dominance and recessiveness perhaps the majority show more complex interactions In this exercise you will look at another pattern of inheritance We will define incomplete dominance as a situation where the heterozygote is exactly intermediate between the two homozygous phenotypes Prediction enter your own Experiment You will use the results from Experiments 7A and 8A as the controls for this experiment so change the title and make the survival rate of the heterozygote 22 compared to 20 and 24 for the homozygotes leave all other variables the same Results Compare the pattern of changes of allele and genotype frequencies and of population size of this experiment with those of 7A and 8A Conclusion Summarize and explain these results Exercise 10 What Is the Evolutionary Fate of a Population in Which the Heterozygote Is the Most Fit Genotype Heterosis This question is a complex one and a complete exploration is beyond the scope of these exercises If you go on to more advanced exercises you will have a chance to study this issue in more detail here we will confine ourselves to a brief exploration with three experiments and then try to derive a general qualitative conclusion a Use the following data for your first run T
36. assodoess 64 Maximum Population and Post Crash Population Population Size 64 PROGRAM OUTPUT vise istscassaniesnnehinaainasnanbansdanneasesivounan savas ioeuinensi tanacinouanbiuednvainaniiaienth 65 The C Opry Command Sisinnio aiin e ninen neds easieneiesulanomieeesas 65 COPY WINAOW ox scsccescscrectensancacaseacssausbeveeaiiaasiaataendchashteenlanniecunctiaindauendee 65 Copy Window Graph ss sssssssssssssesesssesessressrsesrsesssesrnsssseseseseneseseseseseses 65 Copy Window Data cj iccencsscccaterssecanssssnecterinessaissacsue dasensnreumanaceassiees 66 The Notepad ecensnsiotaniii ninina E E E E A NS 66 The Variables You May Graphiniesonsesionicsnsnanstisninni 66 Chapter 9 THEORETICAL NOTES sssanioiiisoiigenrarsan i ansan iii a aia 68 THE CONCEPT OF AN EQUILIBRIUM POPULATION osssisossnssssssessserssssressressres 68 ASSUMP UOS oega e E E E E T nedlaenyntens 68 Evolutionary fofTces sarcssniienisssnecsnni ninti s 69 Importance of Hardy Weinberg Equilibrium cccscssesssseaseenensseeens 70 MODELS IN POPULATION GENETICS sis uicawcactvnsncvetcetnoanwdsasicasenuniesassenncaaveusacaazecsens 70 CALCULATING FITNESS AND SELECTION COEFFICIENTS 71 LIMITATIONS OF EVOLVE is3iccciacicocascsasvanneaastuariadatesarasatia iasshiskitiniwaaraaseentanianeaaaciene 75 aie MLO EEA a D EER cea ed ene EE EAEE EAEE E EET 77 TIT TEROIDUIC TOR VETS cocsancssdiwanicravanaqasedeaioaniansdavasiuaasweisananiansasaaienudtdasdnanddauavecnnans 77 FULL
37. ays clear cut In using these terms we are dealing with patterns of inheritance of phenotypes rather than the nature and function of genes at the molecular level Because most probably all genes have multiple effects alleles may be codominant at the molecular level dominant with respect to one phenotype recessive with respect to another and heterotic for a third EVOLVE simplifies this complexity by looking at the net effects of genes on survival and reproductive rates Again the sickle cell allele is an instructive example As discussed above the two alleles are codominant at the molecular level but with respect to the disease phenotype the s allele is recessive the S allele is dominant The s allele would seem to be disadvantageous and you might expect it to decline in frequency and eventually become extinct save for new mutations However the situation becomes more complicated and interesting when you consider additional information As you may know the s allele occurs at a high frequency over 20 in some populations Research has shown that such populations have a high incidence of malaria and that heterozygous Ss individuals those with sickle cell trait have a greater tolerance to malaria than homozygous SS individuals Here is a summary of the genotypes and their phenotypes as discussed so far Genotype Phenotype SS Ss SS Hemoglobin Normal Mixture Sickle cell Blood Normal Sickle cell trait Sickle cell anemia Ma
38. bject to only one force at a time In the following exercises you will compare the effects of previous experiments with ones in which more than one force is operating Exercise 14 Drift and Selection The question of the relative importance of genetic drift and natural selection is a hot topic among evolutionary biologists these days Here you will get a chance to see what the fuss is all about Set up an experiment which uses survival and reproductive rates from one of the experiments in Exercises 7 10 and the smallest K and post k values you used in Exercise 11 Compare the results with each of the first two which are now the controls for Exercise 14 Prediction enter your own Results Describe the overall changes in allele frequency and the generation to generation fluctuations Compare them with the allele frequency changes in the two earlier exercises Compare your results with those of your classmates Conclusions What is the effect of drift on selection Can an advantageous allele be lost as a result of drift Can a deleterious allele increase in frequency Exercise 15 Selection and Gene Flow One of the major controversies in evolution is why differing selection regimes in different environments do not cause widely spaced populations of one species to diverge from each other Chapter 5 ELEMENTARY EXERCISES 47 The Osprey for example is a predatory bird that feeds on fish and is found around seashores lakes and ri
39. cecs 6 EXERCISE 1 A Simple Experiment with Natural Selection 0 00 0 eee 7 Setting up the EXpErIM EN part ots se tds isnie oninia riesia derinin ien sansa nida ri iseinean 8 Doing the Experiment nisor eker arean E RAE 10 Lookingat Results missriieniroie ur ana A REAA 11 LEAVING EVOLVE cccesineccccedsicedessavecceseia checsadaceceteancicot AEE AAAA AAE R eaaa 14 Chapter 3 MORE ADVANCED FEATURES OF EVOLVE iscsiissuivesstasinenvsavnensitanoveeiaaniiayes 15 INTRODUCTION Doing Experiments with EVOLVE s ssssesessssrissssssesssereressesess 15 EXERCISE 2 Comparing Selection in Small and Large Populations 16 Redome the Experiment With Vatiati Gigi csisisessscisicodaaaieiarsnitumelanbincnnasianns 17 Moving Results to Paper and Elsewhere ici catecnissininmitoncnnttaulasscuatnninl iuiiostits 19 EXERCISE 3 Comparing Runs with Different Random Numbers 00004 20 EXERCISE 4 Changing the Evolutionary Situation During a Run 21 Chapters BACKGROUND iia mssseisacisssisasidascsantalgiatenanataunmanenaheaenta REEE 23 THE HYPOTHETICAL ORGANISMG occ cece cccceccccccececececececececececececececececececececececees 23 GENETIC CONCEPTS UNDERLYING THE MODE L cccccccceccccecececececececeeees 25 PRIMES INOS sacks ei R E E E AE 26 THE NATURE OF EVOLUTIONARY FITNESS 000 c cc cece cece ce cccccececececececececececececeeees 28 PART 2 EXPERIMENTING WITH EVOLUTION W000 co cc cece cece cece cccecececec
40. cted from one saa 1 000 1 000 0 000 Saa 1 000 0 508 0 492 Saa 1 000 0 480 0 520 There are a few points we should note about the concepts involved in these calculations Intuitively the selection coefficient s is the relative decrease in frequency due to natural selection In this case the Aa and aa genotypes are 49 2 and 52 0 less common than would be expected By this definition selection is not operating on the AA genotype Note that fitness and selection as typically used by evolutionary biologists are relative to the most fit genotype or allele in the population and are between 0 0 and 1 0 In every population at least one fitness coefficient must be 1 0 and the selection coefficient of that genotype must be 0 0 It is important to understand that these relative measures of the intensity of selection are intended to be used in discussing the relative changes in allele and genotype frequencies which alleles and genotypes are increasing or decreasing in frequency Because these measures are relative it is possible for a population to be declining in numbers at the same time that one or more alleles or genotypes have high relative fitness indeed one genotype must have a fitness of 1 0 Absolute fitness is the measure that tells us something about whether or not an allele or genotype can increase in numbers If none of the absolute fitnesses is greater than 1 0 then the population will become extinct St
41. der how you would model the evolutionary situation described below Discuss this assignment with others before class if you wish You are not expected to produce a finished product but should try to map out how you would approach the problem Take your notes to class and be prepared to discuss your approach In class you can set up a model and run it by hand After getting results we will see how this model relates to EVOLVE Please take a calculator to class Restrict your thinking to a species which is hermaphroditic has both male and female organs and diploid reproduces sexually and must mate with another individual Consider a life cycle where individuals are born during a restricted breeding season mature for one year mate produce young and die Consider only changes in the frequency of two alleles and 9 at one locus If it helps you visualize an abstract problem think of the o alleles producing spines which protect heterozygotes and homozygotes against predation However in homozygotes the alleles produce a shorter copulatory organ along with the spines this reduces effectiveness of copulation Consequently individuals have a higher survival rate than and 0 individuals but a lower reproductive rate Heterozygous individuals have the best 56 EVOLVE Manual of both effects protection and a high reproductive rate Start with a population with the following composition and average survival and reproductive phenot
42. des more examples of the basic patterns of inheritance Genotype Example e 20 00 Notes 1 Survival rate 30 30 20 Dominant advantageous Reproductive rate 4 4 4 gt Recessive deleterious 2 Survival rate 20 20 30 Dominant disadvantageous Reproductive rate 4 4 4 0 Recessive advantageous 3 Survival rate 30 30 20 Dominant advantageous Reproductive rate 4 4 4 o Recessive deleterious 62 EVOLVE Manual 4 Survival rate 20 25 30 Incompletely dominant disadvantageous Reproductive rate 4 4 4 o Incompletely dominant advantageous 5 Survival rate 20 20 30 Dominant disadvantageous o Recessive advantageous Reproductive rate 4 5 5 Dominant advantageous e Recessive deleterious Overall the alleles demonstrate pleiotropy multiple effects and codominance both have their effects in heterozygotes 6 Survival rate 20 40 30 Dominant disadvantageous 0 Recessive advantageous Reproductive rate 4 6 5 o Dominant advantageous e recessive deleterious Overall the alleles demonstrate overdominance with respect to fitness and are heterotic show heterosis or heterozygote superiority Z Survival rate 20 10 30 e Overdominant disadvantageous Reproductive rate 4 6 5 o Overdominant advantageous Overall the alleles demonstrate overdominance with respect to fitness and show heterozygote inferiority Population Growth Rate The relationship between reproductive rates and survival rates what evolutionary biolog
43. e 19 Plotting Aq vs q As you may know from an examination of texts on theoretical population genetics mathematical models of selection frequently derive the Aq or change in allele frequency per generation as a function of allele frequency Even though you may not have studied such derivations it is interesting to tabulate and graph these statistics Examination and discussion of sample curves for EVOLVE experiments may help you understand the reasons for the shape of allele frequency curves over time We suggest you examine the allele frequency graphs of comparable experiments for example 7A and 8A which involved selection for dominant and recessive alleles 54 EVOLVE Manual respectively You can use Copy Window Data to copy the summary data to the Mac s clipboard then paste them into a spreadsheet or statistics program Tabulate the allele frequency q of the allele that increases in frequency Subtract adjacent generations values of q to obtain Aq then do a scatter plot of Ag vs q Be sure to note the survival and reproductive rates of the experiment If members of a class each do a separate experiment you will have abundant material for discussion For example ask yourself what values of q have the highest values of Aq in Experiments 7A and 8A Can you see how the graphs of allele frequency vs time that EVOLVE produced relate to the plots of Aq vs q Do the latter show you why the steep part of the allele frequency vs time g
44. e full 200 Also there are times when you may want to change variable values on a specific schedule Starting Population These three numbers determine the composition and size of the starting adult population of generation 1 They must not total more than 8000 For example suppose you wish to study the fate of a new mutant allele 0 ina population of 1000 individuals You should use 999 1 and 0 as the initial numbers of 0 and 0 genotypes respectively A new mutation obviously would first exist in heterozygous condition If you wish to establish a population of 2000 with the frequency of the allele equal to 0 40 use 320 960 and 720 These numbers can be obtained using the Hardy Weinberg proportions you should be able to determine them See Calculation of Fitness and Selection Coefficients in Chapter 9 or your textbook if you do not know how to do this Chapter 8 PROGRAM NOTES amp SETTING UP EVOLUTIONARY EXPERIMENTS 61 Survival and Reproductive Rates Selection Pattern of Inheritance and Population Growth Rates Survival rates determine the average number of young of a particular genotype that survive to adulthood They may vary from 0 for a lethal genotype to 100 for a genotype in which 100 of the young survive to adulthood The former is not unusual in nature but the latter is very unlikely Reproductive rates determine the average number of young per individual They may range from 0 offspring per
45. e post crash population size All genotypes should of course have equal survival and reproductive rates we do not want selection to confuse our interpretation of the effects of population size Results Describe the pattern of changes of allele and genotype frequencies shown by your experiments If you did not know the data that had been used to start the experiments would you think that any of the graphs showed significant changes in allele or genotype frequencies Use your fingers to display 10 or 20 generation segments of your graphs and try to decide whether evolution occurred during that time Was there any pattern to which allele or genotypes increased in frequency Conclusions What impact does population size have on evolution 44 EVOLVE Manual Gene Flow Gene flow is the net movement of alleles from one population to another Because of uncertainty over the actual amount of gene flow in nature there is considerable debate over its actual importance Regardless of what actually happens EVOLVE can illustrate what might happen if gene flow were significant Exercise 12 What Is the Effect of Gene Flow on Evolution In this exercise we will conceive of our population as living on an island or mountain top surrounded by an inhospitable area Individuals which disperse away from our population may be regarded as having died that is having been removed by selection although they may survive and contribute to another popula
46. ececececececececececececeeees 31 Chapter 5 ELEMENTARY EXERCISES isctocssagsindsa teusenvasatamnnscetsnnantinnrnsneutanssieaeamseumeatteands 32 FUNDAMENTA LS er ceciidics crsuaceectatcetcecttccetceeaceselecuacss cna tieh ccttacs2ceadecsslbecebvs cas tistecedtlosees 32 ital Populati ti s cissie asien eosina 32 Survival and Reproductive Rates xs ienastscusricantncotenritand eco eaceenmtanhamnbmanianit 33 Hardy Weinberg EQ Orit cncasinsdcarasepianeatatcaaseedsteiaeioinancetniatontaamauiaiee 33 EXERCISE 5 How long does it take to establish Hardy Weinberg equilibrium starting with a population that is not in equilibrium eee eect eeeeeeeeeee 34 TABLE OF CONTENTS iii EXERCISE 6 Set up a population in Hardy Weinberg equilibrium 00 36 NATURAL SE LEC TIN vcsir eiin ai e aiai eieiei Eai ARE EE 37 EXERCISE 7 What effect does increasing the strength of selection have on the evolution of an advantageous dominant allele 0 0 eee 37 EXERCISE 8 Does the evolution the change of allele and genotype frequencies of an advantageous dominant allele proceed more rapidly than that of an advantageous recessive allele with comparable survival nd reproductive rat s ic assscostasutaostadyiivacastuta ts obvnaneddpanensanianeonean EET a 40 EXERCISE 9 How does the evolution of incompletely dominant alleles differ from the evolution of completely dominant alleles ccceeee 41 EXERCISE 10 What is the evolutionary fate
47. ed to lead you through elementary experiments with each of the evolutionary forces singly and in combinations The first part of the chapter reexamines fundamental concepts the second looks at Hardy Weinberg equilibrium in the context of setting up EVOLVE experiments and reading the results the third provides a series of exercises that guide you through experiments with single evolutionary processes and the final section illustrates how pairs of evolutionary forces interact Fundamentals Questions 1 6 below are intended to help you test your understanding of the fundamentals of EVOLVE s simulation and do not require that you make any computer runs We strongly recommend that you do these first six questions before you attempt any of the other exercises because for them we will assume that you know the concepts involved with these first exercises Your instructor may suggest that you treat this as a take home quiz after you finish Chapter 4 and have you bring in your answers for discussion or grading Initial Population 1 Calculate the number of each genotype in a Hardy Weinberg equilibrium population of 2330 individuals with an o allele frequency of 0 63 write the number of each genotype in the spaces below Nowe _ iO Nw _ NCW OH SL 2 Consider an initial population of 448 individuals 1238 individuals and 855 individuals a What are the frequencies of the alleles Frequency of Frequency of 0 __ _ b Given the
48. emigrating may vary from 0 for stay at homes to 100 for genotypes with wanderlust Note that immigration is a constant and is independent of the density of the simulated deme while emigration removes a constant proportion of each genotype in each generation This may seem an unusual or odd situation but it could be visualized in the following way Suppose our model population is a plant similar to a dandelion and the seeds have plumes for wind dispersal The alleles might be conceived of as affecting the length of the plumes and therefore the tendency to disperse be blown away Our model deme could be thought of as existing on a small island which is downwind of a large island or continent with a stable population In such a situation immigration could be viewed as constantly adding a particular number of individuals of each genotype with long plumed seeds arriving at a higher rate than short plumed seeds The short plumed seeds would emigrate that is be blown away from the island at a lower rate than the former Maximum Population and Post Crash Population Population Size Along with rates of survival and reproduction and gene flow if any the values you enter for maximum and post crash population determine the size of the population In EVOLVE the maximum population may range from 10 to 5000 while post crash size may range from 2 to 4000 Obviously the maximum population must be larger than the post crash size The maximum pop
49. er we will build on those foundations showing you some additional features of EVOLVE in the context of answering evolutionary questions by comparing a series of experiments Before jumping into experiments however it is important that you put experiments into their proper context Experiments should not be done haphazardly they should be done in the context of a specific question see Figure 3 1 The question should be rather specific and you should set up a set of at least two experiments to test it One or more experiments should be designated controls and used for comparisons with the other s You should also try to predict what the results will be in rather specific terms Ask Question Design Set of Experiments Designate control amp experimental runs predict results Do Set of Experiments Analyze Compare Results Answer Question Display results store set amp retrieve results Figure 3 1 Outline of an EVOLVE session Rectangular boxes represent actions performed using EVOLVE rounded boxes and ovals show where user thought is involved After the experiments are designed you will set up the first one and then do the experiment Once the results are in you may want to store them in EVOLVE s Notepad You will then revise the evolutionary situation and do the next experiment Comparing the results of the experiments may lead you to revise and refine your experiments or may give
50. eries of mathematical operations on it to produce a second random number This number is used by EVOLVE in various ways for example to randomly pick pairs of parents from the adult population and to let the survival rate vary slightly from the average values you entered in the Change Parameters Window This second number is also used as the seed for the third random number and so on These numbers are not really random because the mathematical operations will always produce the same sequence of numbers if the same seed is used the sequence of numbers is determined by the value of the initial seed However if you examine a listing of the numbers produced by such a random number generator you would not see a relationship between them so in this sense they are random This may become clearer if you consider another more commonly used random number generator a tossed coin If you knew enough physics and had enough information on the initial position size shape and mass of the coin along with the rotational velocity angle and velocity of the toss and such things as wind direction 60 EVOLVE Manual and velocity you could predict heads or tails before the coin landed In this sense the result of a coin toss is determined yet for all practical purposes we can regard the outcome as random Again consider how EVOLVE uses random numbers When the program reduces the number of young to obtain the number of adults
51. ey are often less useful than the relative frequencies of subgroups of the population EVOLVE can also calculate the following as relative proportions of the population Frequency of Frequency of 0 Frequency of 00 Because evolution may be defined as change in allele frequency a graph of allele frequency is often the single best summary of what happened to the population For EVOLVE these allele frequencies are the most relevant measures Frequency of Frequency of o The allele frequency graphs are always symmetrical about a horizontal line at 0 50 because the frequencies of the two alleles must always add up to 1 0 if p symbolizes the frequency of the allele and q symbolizes the o allele then p q 1 The genotype frequency curves are more involved but generally follow the Hardy Weinberg relationship p 2pq p 1 Although this relationship does not apply precisely when selection drift and or gene flow operate the actual frequencies are often fairly close Chapter 9 Theoretical Notes The purpose of this chapter is to provide additional perspective on some of the theoretical issues behind the use of programs like EVOLVE Many of the details such as how to derive Hardy Weinberg ratios can be found in most textbooks and will not be covered here Be sure to read the appropriate section of your text if this material seems unclear The Concept of an Equilibrium Population The backbone of our theory of evolutio
52. gth Texts Stansfield William D 1979 The Science of Evolution New York MacMillan Publishing Co Although getting old as a survey of evolutionary biology this text has a very clear derivation of a number of simple population genetic models Futuyma Douglas J 1979 Evolutionary Biology Sunderland Massachusetts Sinauer Associates Inc An excellent theoretical and experimental survey of population genetics ecology and evolution Spiess Eliot B 1977 Genes in Populations New York John Wiley amp Sons A lengthy more complete treatment of population genetics 78 EVOLVE Manual Wallace Bruce 1981 Basic Population Genetics New York Columbia University Press Another good survey of population genetics Advanced Texts Crow James F and M Kimura 1970 An Introduction to Population Genetics Theory New York Harper amp Row This is a standard mathematically oriented text that is a classic in its field Wright Sewell 1968 1978 Evolution and the Genetics of Populations Vol 1 Genetic and Biometric Foundations Vol 2 The Theory of Gene Frequencies Vol 3 Experimental Results and Evolutionary Deductions Vol 4 Variability Within and Among Natural Populations Chicago Univ of Chicago Press This series of volumes is the most advanced survey of the state of the art of population genetics Glossary Allele One of two or more differing forms that exist at one gene locus Allele frequency A numerical measure of t
53. has a 20 survival rate and produced 4 young its fitness would be higher than another B with 15 survival and 4 young The first type would increase in frequency relative to the second although its absolute numbers would decline and both would become extinct Suppose 100 young of each type were born in one generation and we followed the population for a generation or two No young No adults Frequency of type of type of type in adults Generation A B A B A B 1 100 100 20 15 0 57 0 43 2 80 60 16 9 0 64 0 36 3 64 36 13 5 0 70 0 30 4 51 22 10 3 0 76 0 24 5 41 13 8 2 0 81 0 19 Of 100 type A young in generation one 20 lived to adulthood Each of the 20 had 4 young for a total of 80 young A s in generation two There were only 60 young B s in generation two As you can see the frequency of type A increased even though its actual numbers declined You will see an example of this situation in the exercises Thus evolutionary biologists distinguish absolute fitness from relative fitness see Chapter 7 Now that you have learned some of the assumptions that underlie EVOLVE you are in a better position to work with it to design experiments that will improve your understanding of our theory of evolution within populations Part 2 Experimenting with Evolution These chapters are designed to give you a sampling of exercises that will enable you to more easily realize the major goals of EVOLVE a better understanding of evolutionary pr
54. he commonness of an allele the proportion of all alleles of a gene that are of a specified type In a population of 20 30 and 50 00 individuals the frequency of the allele would be 2 x 20 30 2 x 20 30 50 40 30 2 x 100 70 200 0 35 or 35 Carrying Capacity The number of individuals of a population that can be sustained by their environment over time often symbolized by K Codominance Pattern of inheritance where the heterozygote shows the phenotypic effects of both alleles A good example is the allele for sickle cell anemia Homozygous Hb4Hb4 individuals are normal homozygous HbsHbs have severe usually fatal sickle cell anemia Heterozygous Hb4HbsS individuals have sickle cell trait a mild anemia Deme A local population within which mating is random Diploid The condition of having two sets of chromosomes 2N one inherited from each parent The alternative condition haploid N occurs when there is only one copy of each chromosome Gametes are haploid zygotes are diploid Directional Selection Pattern of selection that changes the frequency of an allele in a constant direction toward either fixation or extinction of the allele Dominance Pattern of inheritance in which an allele the dominant expresses its phenotypic effect even when it is in heterozygous condition with another allele the recessive If allele gt is dominant then o gt and individuals will have the same genotype and h
55. he previous 2 experiments Click the New Trial button then Continue Do this 5 or 6 times This should give you a better idea of the effects of randomness in a small population Moving Results to Paper and Elsewhere A major aspect of BioQUEST and of science in general involves persuading peers of our conclusions There are several ways to move EVOLVE s results into other programs and to paper Not only can you obtain printed results hardcopy in computer jargon but you can use EVOLVE s results as input to other programs such as spreadsheets statistics programs and especially word processors Some of you may not have a printer connected to your computer If so don t worry you can do the vast majority of your work without one If you really need a summary or copies of graphs and don t have a printer you may save screens to disk files take the disk to a computer that does have a printer and print your results there If you do have a printer the Notepad is more convenient Here is the procedure for using and printing the notepad Select Copy Window Graph from the Edit menu The graph is copied to the clipboard Click on the small icon in the upper left hand corner of the summary window This opens EVOLVE s Notepad window where you can paste the contents of the clipboard and can also type in your own notes Select Paste from the Edit menu The graph appears in the Notepad Window Type afew words commen
56. here you can type in your own notes questions hypotheses predictions and reminders In addition you can paste material that you have copied from EVOLVE s graphs and tables The Notepad can be printed using the Print Notepad command in the File menu Using the Notepad is simple Just bring a Summary Window to the front click on the Notepad icon J in the upper left hand corner and start typing and pasting Click on the Notepad Window s close box to get it out of your way when you are doing other things The Variables You May Graph It is often useful to look at the results of experiments from a variety of points of view and EVOLVE is well equipped to let you examine its results in many ways Where the actual list of variables is lengthy they fall into a few distinct categories time numbers and frequencies Here is a list of the variables that can be graphed Time from the start of the experiment measured in number of generations This is so useful as the horizontal axis of graphs that it is the default The following group of variables are the actual number of adults in the total population or the number of a particular genotype or group of genotypes By selecting combinations of the following you can look either at genotypes or at phenotypes The actual variables are Total Population the sum of the number of all genotypes the total size of the population This is important when you want to look at drift or population
57. ibe oi o 1 tl gt gt o gt 4 e 4 end eon td 0 Fitness of Homozygotes 0 Heterozygote Fitness 1 0 Figure 6 1 A Metaphorical Landscape for Exploring Heterosis Make several runs in which the fitnesses of and 6 homozygotes are equal but which start with different initial allele frequencies for example Runs 1 and 2 on the table below and their corresponding numbers in the graph above Next make runs with the absolute fitnesses indicated in Runs 3 and 4 on the next page and indicated by the 3 and 4 on the graph Note the final allele frequencies of the populations and mentally summarize the results Make a prediction about the final allele frequencies at some other point on the plane and test your prediction with another run of EVOLVE In this way you can explore all of the regions on the surface before writing your answer to the question Initial Initial population frequency Run No Max pop Post crash oe 0 0 gt of allele 1 Eas 00 Survival rates Absolute fitness Frequency of in 0 0 0 0 oo generation 100 50 50 50 1 5 2 0 1 5 Reproductive rates Relative fitness 0 0 o Q 0 0 3 4 3 Initial Initial population frequency 52 EVOLVE Manual Run No Max pop Post crash gt 0 0 2 Survival rates Absolute fitness 0 0 0 0 0 0 50 50 50 1 5 2 0 1 5 Reproductive rates Relative fitness 0 0 0 0 0 Initial population Run No Max pop
58. icroevolution Evolution within a local population usually resulting in small phenotypic changes this is the level modeled by EVOLVE Mutation The process or event that produces an inheritable change in genetic material at a single locus a mutation changes one allele to another Also the allele chromosome or individual that results from the process Mutation rate The number of mutation events per gene per unit of time for example per cell generation Natural selection The various processes that result in changes in the frequencies of genes or genotypes due to differences in the ability of their phenotypes to survive and reproduce Overdominance The expression of two alleles in a heterozygote of a phenotype that is outside the range of the corresponding homozygotes see Heterosis Phenotype The physical physiological biochemical behavioral or other properties of an organism that develop through the interaction of genes and their environment Pleiotropy Condition in which a gene affects more than one phenotypic characteristic Population A group of organisms of the same species that occupy a more or less well defined region r See Intrinsic Rate of Natural Increase 82 EVOLVE Manual Recessiveness Condition in which one allele expresses its phenotype only when it is Species homozygous in heterozygous conditions the recessive allele s effect is masked by the phenotype of the dominant allele See Dominance A group of
59. implicity of the Hardy Weinberg equilibrium proposed eight decades ago that view of nature still provides a useful starting point especially for new students To the extent that you develop some intuition and feel for the interaction of evolutionary forces you may be misled into thinking you really understand evolution Should you then have to apply that intuition in real evolutionary studies you may find that it falls short Nevertheless we believe that you are better off working with EVOLVE learning to think about allele frequencies and fitness and designing and interpreting experiments than merely reading a textbook Bibliography Introductory Texts Wilson Edward O and W H Bossert 1971 A Primer of Population Biology Stamford Connecticut Sinauer Associates Inc Albeit old and dated this is still the best clearest and shortest introduction to modeling in population biology Hartl Daniel L 1981 A Primer of Population Genetics Sunderland Massachusetts Sinauer Associates Inc A more up to date elaborate introduction to population genetics patterned after Wilson and Bossert Ayala Francisco J 1982 Population and Evolutionary Genetics A Primer Menlo Park California Benjamin Cummings Another good introduction Spain James D 1982 BASIC Microcomputer Models in Biology Reading Massachusetts Addison Wesley Publishing Co A superb readable introduction to a wide variety of computer models in biology Full Len
60. ions happen so slowly 2 The Hardy Weinberg concept provides us with a conceptual framework for investigation If evolution has occurred that is if allele or genotype frequencies deviate significantly from expected values we know that one or more of the Hardy Weinberg assumptions have been violated we can proceed to determine which evolutionary force s have affected the population under study 3 Finally and perhaps most importantly the Hardy Weinberg concept provides the foundation for a mathematically rigorous theory of population genetics and for mathematical models of each of the evolutionary forces Since most textbooks of population genetics illustrate these models in detail we will not derive any here These models may be used in turn as null hypotheses to evaluate the possibility that observed evolutionary changes are due to a specific evolutionary force Thus although it paradoxically predicts no evolution the Hardy Weinberg equilibrium concept allows us to measure evolution provides a conceptual framework for investigation and serves as the foundation for the mathematics on which much of our theory of microevolution is based Models in Population Genetics As indicated above we can use the Hardy Weinberg equilibrium concept to formulate mathematical models in the form of equations that hold all factors but one constant We can then vary that one factor to investigate its effects on allele and genotype frequencies Once we
61. ists call absolute fitness determines the direction and rate of change of population size You should choose survival and reproductive rates in such a way that your populations grows slowly For example you wouldn t normally consider an experiment where all genotypes have survival rates of 65 and reproductive rates of 1 For every 100 young born there would be about 65 adults each adult would produce an average of 1 young for the next generation a total of 65 young Given enough time the population would decline to extinction In general if the product of survival rates x reproductive rates is greater than 100 the population will not become extinct Of course in most runs the survival and reproductive rates will not be the same so the exact pattern of population change will depend on the relative proportions of the various genotypes in the population as well as on the particular survival and reproductive rates Pattern of Selection This also depends on the relative values of both survival and reproductive rates of each of the genotypes what evolutionary biologists call relative fitness Suppose the survival rates were 60 40 40 and the reproductive rates were 3 2 2 for the 0 and 00 genotypes respectively The allele would be recessive because the heterozygote has the same characteristics as the 0 homozygote Chapter 8 PROGRAM NOTES amp SETTING UP EVOLUTIONARY EXPERIMENTS 63 but advantageous because
62. ith that program Enter data on rates of change of allele and genotype frequencies 38 EVOLVE Manual Run with strong selection Change in frequencies Genotype frequency Allele frequency Generation 0 00 Q 1 gt 5 6 gt 10 11 gt 15 16 gt 20 21 gt 25 31 gt 35 51 gt 55 71 gt 75 Run with weak selection Change in frequencies Genotype frequency Allele frequency Generation 0 00 Q 1 gt 5 6 gt 10 11 gt 15 16 gt 20 21 gt 25 31 gt 35 51 gt 55 71 gt 75 a Describe the pattern of change of allele frequency in the Strong selection run Weak selection run Chapter 5 ELEMENTARY EXERCISES 39 b Describe the pattern of change of genotype frequencies in the Strong selection run Weak selection run c Fill in the following table of data on population size changes using EVOLVE s data table No generations between crashes Strong selection Weak selection Generation 1 gt 1st crash 1st crash gt 2nd crash 2nd crash gt 3rd crash 3rd crash gt 4th crash Ath crash gt 5th crash 5th crash gt 6th crash Describe the pattern of population size changes in the Strong selection run Weak selection run d Which run had the fastest rate of population growth at the end of the run Run with st
63. itle 10A Sel for Heterozygotes Number of generations 100 Carrying capacity 9999 Post crash pop size 7000 e 9 0 0 Initial population 1711 278 11 Survival rates 20 24 20 Reproductive rates 6 6 6 Prediction enter your own 42 EVOLVE Manual Results record your results in the table that follows 10C b Now try an experiment with these data keep other variables the same as above Title 10B Sel for Heterozygotes oe e 0 0 Q Initial population 11 278 1711 Prediction enter your own c Now try an experiment in which one homozygote is sterile Title 10C Sel for Heterozygotes Number of generations 100 Carrying capacity 9999 Post crash pop size 7000 ee 0 0 Q Initial population 1711 278 11 Survival rates 20 24 20 Reproductive rates 6 6 0 Prediction enter your own Results What were the final allele and genotype frequencies Genotype frequency Allele frequency Experiment 0 0 0 10A 10B 10C Conclusion Summarize your three experiments what is the general fate of alleles when the heterozygote is most fit Explain Chapter 5 ELEMENTARY EXERCISES 43 Genetic Drift Genetic drift is defined as random changes of allele or genotype frequencies caused by sampling error in populations of finite size In essence the processes of survival and reproduction take some of the alleles and genotypes of a population to make up the next generation Even in a po
64. ives the disease its name The distorted blood cells interfere with circulation and cause a variety of unpleasant symptoms that usually result in painful death before puberty Heterozygous individuals with the Ss genotype do not typically show any of the symptoms of the disease although their red blood cells will show some sickling under certain conditions and they are said to have sickle cell trait Thus the disease phenotype and the s allele may be regarded as recessive to the normal phenotype produced by the S allele None of the phenotypes discussed above could be input for EVOLVE Rather the reduced survival of ss homozygotes would be modeled by giving 00 individuals a lower survival rate than and individuals Again note that EVOLVE incorporates the statistical effects of phenotypes on reproduction and survival not the phenotypes themselves No assumptions have been made as to the mode of inheritance of the characteristics of the three genotypes used by EVOLVE By choosing suitable parameters you may simulate any pattern of inheritance possible at a gene with two alleles For the sickle cell Chapter 4 BACKGROUND 27 example setting survival rates to 80 80 and 0 for the 0 and 00 genotypes respectively would simulate the recessive lethal nature of the sickle cell allele It should be clear by now that the distinctions between these different modes of inheritance of phenotypes are somewhat arbitrary and not alw
65. l not elaborate here Select Total Population from the Graph menu and remove Frequency Allele and Frequency Genotype Note that only one axis label can be displayed Select Frequency Allele to remove it Click on the next to the grid toggle The cursor changes to a Move the cursor to the 7000 line near but not on the vertical axis Press the mouse button down and drag a rectangle around the interesting part of the graph IMPORTANT the rectangle must not touch the outside lines of the graph area If it does no line will appear on the new graph The resulting graph is shown in Figure 2 6 Selection for Recessive Allele amp 20 Generations 32 1117 3404 3479 sooo 035 0o65 014 0 43 33 1556 3561 2884 s001 o42 osa 019 045 soot 048 os2 025 0 46f 35 2638 3652 1709 7999 0 56 044 033 0 46 j 36 3432 3454 1114 s000 o64 036 043 0 43 4275 3018 8001 0 72 0 53 0 38 k gt N S D Change Params Figure 2 6 Total population size vs time Observe that the population size started at 8000 and climbed to over 9500 in the 3rd generation then fell to the 8000 level in the 4 Recall that the maximum population size in the parameter window was 9999 During the experiment the population of adults in generation 4 was greater than 9999 so EVOLVE killed enough to bring the numbers down to 8000
66. l population Do all teams come up with the same ideas Going one step further what does your experience with this exercise and other EVOLVE exercises especially 22 tell you about scientists trying to explain real phenomena in nature Remember that in the real world we rarely have such good data on allele or genotype frequencies as EVOLVE provides Chapter 8 Program Notes and Setting up Experiments Introduction This chapter contains reference material on each of the parameters you may input to EVOLVE as well as notes on output and the help system The emphasis is on how each parameter relates to evolution and on practical aspects of setting up experiments There is also some discussion of how to interpret the various output graphs As with most reference works you will probably not find it useful to read through this chapter trying to absorb everything in it Rather skim through it to get an idea of its contents then refer back to it when you have a particular question Getting Help with EVOLVE There are three ways that the user can get help with the EVOLVE program 1 Information about inactive gray menu items If you do not understand why a particular menu item is not available you can click on an inactive item A small window will appear giving information on the item and indicating why it cannot be chosen at this time For example choosing the Cut item in the Edit menu displays the following message This optio
67. laria Susceptible Resistant Resistant Survival rate Low High Essentially zero Note that with respect to malarial resistance the s allele is dominant and advantageous but with respect to hemoglobin phenotype it is a deleterious recessive Overall the s allele displays heterosis is overdominant with respect to survival You might model such a population with the following inputs to EVOLVE Genotype Phenotype SS Ss Ss Survival Intermediate Highest Essentially zero Reproduction High High Essentially zero You might expect reproductive rates of Ss individuals to be somewhat lower than those of SS individuals because 25 of the children of two heterozygotes would die of sickle cell anemia However it appears that such parents often have more children to make up the difference 28 EVOLVE Manual In an environment without malaria however the following would be an appropriate table Genotype Phenotype SS Ss SS Hemoglobin Normal Mixture Sickle cell Blood Normal s c trait Sickle cell anemia Malaria Irrelevant Survival rate High High Essentially zero You could model such a population with the following inputs to EVOLVE Genotype Phenotype SS Ss SS Survival High High Essentially zero Reproduction High High Essentially zero Thus in a malaria infested environment the sickle cell allele is advantageous in heterozygotes and shows heterosis with respect to survival As you will see later alleles showing he
68. lick on an inactive item A small window will appear giving information on the item and indicating why it cannot be chosen at this time For example choosing the Cut item in the Edit menu displays the following message This option is only active when some text is selected 2 General information For help with a particular menu item or about a window on the screen you can enter Help mode by holding down the Command or _ key while typing a question mark If you have a help key on your keyboard this will have the same effect The cursor will change to a question mark Clicking on any item in a menu Chapter 2 Getting Started 7 all items are enabled in this mode gives general information about that item including what would happen if that item were chosen Similarly clicking anywhere in the front most window while in Help mode will display some general information about that window This information includes a description of the contents of the window and explains the function of any buttons or other controls on the window Help mode will automatically turn off once you have clicked on an item 3 To browse through all of the information available about EVOLVE Choose Help with Evolve under the menu on the far left This allows you to choose from a list of topics and display information on the topic that interests you Buttons at the bottom of the window let you move to additional topics in the list Exercise 1 A Simple Experi
69. lipboard Then Paste the results into a spreadsheet and generate the tables below with that program Observed frequencies Genotype frequency Allele frequency Generation 0 0 0 Generation 1 Generation 2 Generation 3 Generation 6 Generation 7 Generation 9 Generation 10 Now subtract the appropriate value in the earlier generation from the value in later generation record the result with the sign on the appropriate blank Change in frequencies Genotype frequency Allele frequency Generation 0 0 Q 1 gt 2 Z 2 gt 3 eS 6 gt 7 EE 9 gt 10 c Describe the changes in genotype frequencies from one generation to another be sure to include specific data illustrating your point d Describe the changes in allele frequencies from one generation to another be sure to include specific data illustrating your point 36 EVOLVE Manual e Were the genotype and allele frequencies stable from one generation to another be sure to give data that illustrate your point f Did the genotype and allele frequencies in generations 2 10 match your predicted values Conclusion g Explain the changes in allele and genotype frequencies in this experiment h This exercise dealt with only one form of disequilibrium the initial population consisted entirely of heterozygotes Would populations with other types of disequilibrium reach
70. llows the same pattern of relatively gradual change then rapid change Your own graph may differ significantly from that of the 1 trial Compare plots of genotype frequency for both experiments Again the two graphs are quite similar in overall shape although the small population s curves fluctuate a good deal more We should note that there are more sophisticated ways to compare these curves quantitatively and if you are an advanced student your instructor may have you make such comparisons However our purpose here is to accustom you to comparing different runs not statistical curve fitting so we will make only qualitative comparisons Plot total population size Compare the two populations You will need to zoom in or change the front most trial in the Trial popup to see the second one Plot number of homozygotes and number of 00 homozygotes Notice that there are periods early in the experiment when the genotype did not occur in the population Not until later did the genotype return for keeps Similarly the 0 homozygotes often decline to zero then reappear before disappearing for good Homozygotes after all may be generated by matings between heterozygotes even when the rare allele is too rare for significant numbers of homozygotes to mate with each other and reproduce Chapter 3 MORE ADVANCED FEATURES OF EVOLVE 19 Do a3 trial with maximum pop 50 and post crash 40 How does this differ from t
71. mathematical models are deterministic That is they do not incorporate randomness or chance Since chance plays a major role in evolution deterministic models can be misleading EVOLVE is an attempt to avoid these difficulties It is an intuitively simple yet realistic model because students have a better grasp of survival and reproductive rates than of selection coefficients Depending on the values of input parameters EVOLVE may incorporate any or all of three major evolutionary factors natural selection drift and gene flow Study of the fate of mutant alleles is also possible One of the things which people often have trouble understanding is the way in which chance events may affect evolution Mutation genetic drift and stochastic random variation of environmental factors such as weather and food supply are examples of random factors in evolution EVOLVE incorporates randomness in three ways 1 The user specifies the average survival reproductive and immigration rates of the genotypes Each time the program uses one of these parameters a random number generator is used to determine the actual value used Thus the environment of the model population may be regarded as varying slightly from generation to generation 2 The size of the population may be made small enough for genetic drift to occur Small sizes may be maintained over long periods of time or may be temporary 3 The pattern of random matings in a finite population
72. ment with Natural Selection In this exercise we will do an experiment to show the fate of an advantageous recessive allele that initially is uncommon It is often useful to envision a specific example to make an abstract exercise concrete so think of modeling a situation where a very large flock of migrating birds was blown onto an island and colonized it EVOLVE models evolution of one gene having two alleles and gt and thus three genotypes gt and 00 If individuals with the genotype lay an average of 8 eggs while the other genotypes 0 and 00 lay an average of 5 eggs the allele is an advantageous recessive The fact that the genotype produces more offspring means that it is likely to be favored by natural selection and thus to have an advantage over the other genotypes For the present we will define dominant alleles as ones that produce their full phenotypic effect even in heterozygotes Recessive alleles have their full effect only in homozygotes We will discuss these and other definitions in detail later our purpose here is to teach you how to use EVOLVE not genetics or evolution Thus because the lt genotype has the same phenotype as the 0 homozygote the allele is dominant and the allele is recessive This is like Mendel s peas he called the allele for yellow seeds dominant over the recessive green because heterozygotes looked just like seeds homozygous for yellow The recessive green trait
73. n in local populations often called microevolution is the Hardy Weinberg equilibrium concept In its simplest formulation the Hardy Weinberg concept deals with a population with two alleles and o in EVOLVE s notation of one gene that are present in frequencies p and q respectively Given such a population four predictions may be made 1 Frequencies of the two alleles will not change 2 The ratios of the frequencies of the three genotypes o and 00 will be p 2pq q2 respectively and will add up to 1 0 3 The frequencies of the genotypes will not change 4 If the genotype frequencies are not in the equilibrium ratios in one generation they will reach equilibrium in the next Note that there are within generation and between generation predictions Between generations allele and genotype frequencies should not change once equilibrium has been established Within any one generation the ratio of the genotypes should be p 2pq q 0 00 Thus the Hardy Weinberg law states that populations will remain in genetic equilibrium that is evolution will not occur Assumptions You may find it odd that the foundation of our theory of evolution states that evolution will not happen but the Hardy Weinberg concept has a number of assumptions that invalidate it for most if not all natural populations It strictly applies only when the following assumptions are true 1 Individuals are diploid reproduce
74. n is only active when some text is selected 2 General information For help with a particular menu item or about a window on the screen you can enter Help mode To enter Help mode hold down the Command or key while typing a question mark If you have a help key on your keyboard this will have the same effect The cursor will change to a question mark Clicking on any item in a menu all items are enabled in this mode gives general information about that item including what would happen if that item were chosen For example in Help mode choosing the Cut item displays the following message This will delete the selected material from a notepad and retain it in the clipboard so that it can later be pasted into another notepad or into a word processor Similarly clicking anywhere in the front most window while in Help mode will display some general information about that window This information includes a description of the contents of the window and explains the function of any buttons or other controls on the window For example clicking on the Parameter History Window while in Help mode displays the following message This is a scrollable list of all the parameters used in the experiment so far This is not editable but you can make an editable copy of it by choosing the Copy Window Data option on the Edit menu Chapter 8 PROGRAM NOTES amp SETTING UP EVOLUTIONARY EXPERIMENTS 59 Help mode will automatically
75. n you will have to re enter some of the values Change the title to a convenient title such as Trial 2 Rec small This reflects the fact that selection still favors the recessive allele and the population will be small between 80 and 100 Now we ll look more closely at EVOLVE s error checking and help system Click after the last zero in the 8000 of total population and press the delete key or backspace once to make it 800 then click on Update Note that the numbers of the genotypes change to reflect the reduced population EVOLVE checks the values you enter and will alert you if it detects any mistakes To see what happens make the following mistake Change the Total Population parameter to 10000 then click on Update You will hear a beep and a box will appear informing you that the value you entered is out of range and that you should check the help messages for specifics Click on the OK button To learn the help system and find out what the possible values are for total population do the following Delete one zero click the Update button then the Done button to return to the summary window Select Help with EVOLVE from the Apple menu Scroll the window down past the Parameters Window until you see Initial Population Click on Initial Population then click on the Open button You will see some notes about the initial population including the fact that the initial population cannot t
76. nes vanish from the graph Click on the New Trial button and the Change Parameters button The Trial number changes and the graph lines become gray All of the parameter values except title remain the same Click on the Seed button A number appears that is the random number seed for this trial The computer uses it to simulate random mating the effects of weather and other random factors EVOLVE will pick a different seed for each trial or you can type a seed in if you wish If you use the same seed in different experiments you can be sure that any variations in output are caused by changes in other variables If you use different seeds with no change in other parameters you can assess the influence of chance In essence this amounts to running the same experiment again A final point if you have a trial that you wish to repeat exactly e g to show your instructor copy the seed along with the other parameter values A thorough understanding of the seed is not necessary for you to use EVOLVE but a more thorough discussion is available in Chapter 8 of the User s Manual Click on the Done button then the Start button to run the new trial Were the results what you expected This phenomenon of random fluctuations of genotype and allele frequencies in small populations is an important controversial evolutionary force called genetic drift You should run additional trials to get a feel for the variability of result
77. ness involves both reproduction and survival you cannot look at either one alone Thus the evolutionary fitness of a genotype and its evolutionary fate may have nothing to do with whether the organism is strong swift or red in tooth and claw if that organism does not reproduce In some situations slight fragile individuals even those with seeming deficiencies may have higher fitness than normal or more robust individuals Chapter 4 BACKGROUND 29 In caves for example eyes are a decided handicap for they are potential sites of infection and require calories and nutrients to grow and maintain Since food availability in caves is usually limited individuals with mutations tending to reduce eye size would have higher survival rates This could lead to higher reproductive rates because the physiological effort saved from growing and supporting eyes could be put into egg or sperm production Therefore individuals with reduced eyes would have higher fitness than those with normal eyes In time the population would come to consist of eyeless individuals This view of fitness can even result in the seeming paradox of a population becoming extinct when it contains genotypes with high fitness By the above definition a genotype has high fitness if its percentage share of succeeding generations grows larger As a hypothetical example suppose a population consisted of two types of individuals that did not interbreed If one type A
78. ocesses and of how to study them This selection of exercises is not complete nor will it be appropriate for all students no one is likely to do all of them Rather it provides a sample of some of the ways EVOLVE may be used Each instructor should select some of these exercises to go with others of his or her own devising The exercises that may be done with EVOLVE span a tremendous range of evolutionary situations But more than that answers can be derived using methods of varying degrees of sophistication The grouping of exercises into three chapters should give students some feeling for the open ended nature of evolution and of computer models Chapter 5 is a relatively intuitive qualitative examination of Hardy Weinberg equilibrium selection the fate of mutations drift and gene flow along with combinations of drift with selection and gene flow with selection In the initial exercises we provide all inputs to EVOLVE and in succeeding exercises more and more of the values must be determined by the students This gradually more difficult series of assignments is suitable for high school and freshman or sophomore college students Chapter 6 takes a more sophisticated quantitative approach by having students consider absolute and relative fitness coefficients in explaining EVOLVE s results and the effects of evolution on mean fitness of a population and its growth rate what ecologists call intrinsic rate of natural increase Thi
79. of a population in which the heterozygote is the most fit genotype heterosis cece eee 41 GENE MC DRIF D e A E AE N e AOE 43 EXERCISE 11 What effects does population size have on allele frequencies seesi iita aia a a aas 43 C NP F OV E oeilanttntatatiee 44 EXERCISE 12 What is the effect of gene flow on evolution s s1010015 44 MUA TON E E lt a haapaieheitaieRecnan tine 45 EXERCISE 13 What is the fate of advantageous mutant alleles 45 COMBINING EVOLUTIONARY FORCES cece ceececccesssecececssssececessssescscssseeeeeesaes 46 EXERCISE 14 Drift and Selection ccecccessssccccccccsssssssssccscseeceesesssssaseeeess 46 EXERCISE 15 Selection and gene HOW css aovsssanentvestaitnuse eauitacheaearsmenanicesyen 46 Chapter 6 INTERMEDIATE EXERCISES iicvsasssidssovsiedssbnivetsicnnnanat nsvnadehonnninsnmnetesanssasaasinaesis 48 PRELIMINARY EXERCISES iisasneesessenssssessesssresssrressssreesseseessssrresssrreessreetssereessssrresent 48 EXERCISE 16 Selection via reproduction vs selection via survival ccce 49 EXERCISE 17 Exploring heterosis lt iscsisaisasaseainsaase aserssmeasaiaaousasiatoanindeassaeienaaeonaes 50 EXERCISE 18 Modelling the real world Sickle cell anemia 0ccccceeee 53 EXERCISE 19 Plotting Ag VS Gerini RE EEES 53 EXERCISE 20 Plotting Aq vs population SiZe ss sssesssesesessssesesisisrresesesrsresesiseeren 54 EXERCISE 21 Examining q at a time t for a large number of pop
80. omozygotes would have the recessive phenotype Electrophoresis A technique for separating proteins in an electrical field It enables small samples of proteins from wild organisms to be rapidly screened for differences in protein structure and hence in DNA Emigration Movement of individual organisms out of a population Evolution Broadly speaking the origin of life and gradual change and diversification of living organisms over time From the microscopic view of a single population evolution is a change over time of the genetic and phenotypic composition of the population due to selection drift gene flow nonrandom mating and mutation From the macroscopic view of many populations evolution is the splitting of populations and their gradual divergence coupled with extinction and other processes that give rise to the vast diversity of living forms that change over time 80 EVOLVE Manual Evolutionary Fitness The contribution of an allele or genotype to the gene pool of subsequent generations Absolute F Ratio of the actual numbers of an allele or genotype in one generation divided by the numbers in a subsequent generation Numbers greater than 1 0 indicate that the number of individuals with that allele or genotype is increasing Relative F Contribution of an allele or genotype to subsequent generations relative to alternate alleles or genotypes Relative fitnesses greater than 1 0 indicate that the frequency of the allele or genoty
81. onsider survival and reproduction together This is an example of pleiotropy a single gene has multiple phenotypic effects Overdominant alleles produce a heterozygote which is more extreme than either homozygote If alleles are overdominant with respect to fitness the terms heterosis or heterozygote superiority are often used Reproductive rates of 40 60 and 30 would exemplify overdominance and heterosis An Example As an example of the relationship of alleles genotypes patterns of inheritance and phenotypes to survival and reproductive rates let us consider the gene for sickle cell anemia The s allele causes the substitution of valine for glutamic acid at position 6 of the beta chain of hemoglobin People with the SS genotype have hemoglobin that is entirely normal heterozygous Ss individuals have hemoglobin that is a mixture of normal and abnormal those with the ss genotype have hemoglobin that is entirely of the sickling type In this example the fundamental effect phenotype if you will of the s allele is the production of abnormal beta chains Thus at the level of hemoglobin phenotypes the S and s alleles are codominant heterozygotes show the effects of both alleles Hemoglobin with s beta chains has reduced solubility under low oxygen concentrations and tends to crystallize in capillaries In homozygous ss individuals sharp crystals grow within red blood cells causing them to take the distorted sickle shape that g
82. otal more than 9000 Click on the window s close box to return to the summary window and click on the Change Params button to return to the parameters window 18 EVOLVE Manual The starting frequency of the allele will be the same as in Exercise 1 Now click on the Genetic Drift button to show maximum and post crash population sizes Change the post crash size to 100 and the maximum population to 80 All of this is important because we will be comparing the results of our second run with those of the first run the first run will be our experimental control If the only difference between the two experiments is size of population then we can more easily draw valid conclusions If there were other differences for example if the post crash size was not eight tenths of the maximum we could not be sure that differences in results were due to differences in population size The ratio of post crash size to maximum population might have an effect Check to make sure the other parameters are the same as those in Figure 2 2 and fix any that are not Click on the Done button then the Start button to start the experiment As the lines march across the graph try to predict what will happen next When the experiment is finished compare the allele frequency graphs from the two exercises Notice that while the trace of the small population in black is more jagged than the gray lines of the large population it generally fo
83. oviding us with good experimental models It is especially difficult to test such hypotheses as birds evolved from dinosaurs An alternative approach to experimental hypothesis testing is observational testing If we hypothesize that birds evolved from dinosaurs then we might predict the existence of fossils that show a mixture of bird like and dinosaur like characteristics Such Chapter 1 INTRODUCTION 5 observational tests of hypotheses are quite common in evolutionary biology and other historical sciences such as geology and astronomy However some aspects of evolutionary biology cannot be studied by observation or by experiment Despite or perhaps because of such difficulties biologists continue to develop models of evolutionary processes but many of their models are conceptual often mathematical rather than experimental or observational In essence we simulate some aspect of the real world in mathematical abstract form and then manipulate the simulation to investigate its consequences If the model is a good one the consequences clarify the real world and even suggest observational or experimental tests The Hardy Weinberg formula and the mathematical population genetics that evolved from it are excellent examples of such models See Chapter 8 for a detailed discussion of the Hardy Weinberg concept Many of these models can be programmed into computers which brings us to EVOLVE 6 EVOLVE Manual Chapter 2 Getting Sta
84. parent for a sterile genotype to 10 offspring per parent for a fertile one The limit of 10 young is arbitrary imposed to make EVOLVE simpler and let it run more quickly These are very important variables which determine the pattern of inheritance and of natural selection and greatly influence rate of population growth To understand population genetics and EVOLVE you absolutely must understand them thoroughly Pattern of Inheritance Choice of appropriate values for reproduction and survival will allow you to simulate any pattern of inheritance possible for a single locus with 2 alleles for example dominance and recessiveness codominance or heterozygote superiority One definition of a dominant allele is that it is one which produces the same phenotype when heterozygous as when homozygous For example if the survival rates were 20 20 and 50 for 0 and 00 genotypes respectively then the allele would be dominant and the allele would be recessive Note that dominance has nothing to do with which genotypes have the highest survival or reproductive rates only with the homozygote that the heterozygote resembles In this case the heterozygote has the same traits as the homozygous so the allele is dominant To take another example reproductive rates of 5 4 and 3 would simulate a pattern of inheritance where heterozygotes are intermediate between the homozygotes that is incomplete dominance The following table provi
85. pe is increasing Fixation Condition in which all members of a population are homozygous for one allele alternative forms of the gene are extinct Gene The fundamental unit of heredity recognizable by the variant effects of different alleles on the phenotypes of the organisms carrying them a segment of DNA at a particular location locus on a chromosome that affects some observable character s of the organism Gene frequency See Allele frequency Gene flow Net movement of individuals from one population to another due to emigration and immigration Genetic drift Random changes in allele frequencies due to sampling errors in finite populations especially common in small populations where offspring are not a random sample of the parents genes Gene pool Abstract conceptualization of a population as the sum of all alleles of a given gene or of all genes together subsequent generations are viewed as being drawn randomly from the gene pool Genotype The specific combination of alleles present in an individual cell or organism Hardy Weinberg equilibrium Condition of stability in which allele frequencies of p and q will not change and the genotype frequencies will remain in a ratio of p 2pq q2 Hardy Weinberg equilibrium requires that certain conditions be met large population size equal survival and reproduction of all genotypes no differential gene flow no differential mutation random mating and probably is rare in nature
86. pecifically the allele and genotype frequencies would remain stable from generation to generation and within one generation the genotype frequencies would approximate p for 2pq for 0 and p for 00 Experiment Make an EVOLVE run with the following data and either print a summary of each generation or examine the appropriate graphs with care Title 5 Estab of H W Equilibrium Number of generations 10 Carrying capacity 9999 Post crash pop size 8000 9 0 o Initial population 0 8000 0 Survival rates 26 26 26 Reproductive rates 4 4 4 Number immigrating 0 0 0 Percent emigrating 0 0 0 Before you do this experiment think about what you are being asked to do a What is the frequency of the allele in the initial population What should the allele frequency do from one generation to the next b What should the genotype frequencies be in a population with the above allele frequency A 00 Chapter 5 ELEMENTARY EXERCISES 35 c Why are the survival and reproductive rates equal for all genotypes d Why is the maximum population set at 9999 and the post crash size to 8000 Results Fill in the following data table from the data table displayed by EVOLVE These first few exercises contain tables like these to help you learn what to look for in EVOLVE s output we will dispense with them later If your are experienced with spreadsheets you can also use Copy Window Data to copy the data to the Mac s c
87. pulation that is not subject to selection or any other evolutionary force the laws of chance dictate that the frequencies in one generation will not be exactly the same as those of the previous or succeeding generations If the population is small then chance will play a bigger role The same principle applies when you flip coins if you tossed a coin 4 times you wouldn t be surprised to get 3 heads and 1 tail but if you tossed it 100 times you would be suspicious if you got 75 heads and 25 tails Randomness is a difficult thing for us to grasp if you tried to say 100 random digits statistical tests would show that your numbers were biased in some way Similarly looking at graphs of allele frequencies it is difficult to tell if there are random changes The next experiments should help you get a better feel for randomness Exercise 11 What Effects Does Population Size Have on Allele Frequencies Experiments Make at least two runs of EVOLVE to compare changes of allele frequencies in populations of different sizes To limit population sizes you should input appropriate values for maximum and post crash population sizes For example runs with K and post k set to 20 and 10 or 500 and 250 or 2000 and 1000 or 5000 and 2500 would permit comparison of populations of very different sizes yet all would suffer crashes of 50 Initial populations should be in Hardy Weinberg equilibrium have initial allele frequencies of 0 50 and be equal to th
88. r theory of evolution What matters is that in principal the data could be collected There are many examples in science of theories that could not be tested when they were proposed because of methodological difficulties Wegner s theory of continental drift for example was proposed before 1920 We had to wait over 40 years until scientists had data on sea floor spreading to indirectly support Wegner s hypothesis We had to wait over 50 years before we could measure distances accurately enough to measure actual rates of continental movement What follows is a simplistic approach that will give you an idea of what is involved in measuring these important parameters More importantly this approach will help you understand the derivation of the concepts and what they mean Here is an outline of the method 1 Calculate observed frequency of each genotype in generation 1 2 Calculate expected frequency of each genotype in generation 2 3 Calculate absolute fitness of each genotype R obs exp 4 Calculate relative fitness of each genotype W fitness relative to the genotype with greatest absolute fitness 5 Calculate selection coefficients of each genotype s 1 W Here is an example that uses this approach We will use the following data to calculate fitness and selection coefficients Genotype AA Aa aa Total Population in first generation before selection 4000 5000 3000 12000 Population in second generation after selection 3500
89. raphs occur early and late in the experiment Compare the results from 7A with a similar graph of 7B How does increasing the strength of selection affect Aq Comparison of other Aq vs q graphs is also revealing You might find it especially interesting to look at 10A 10B and 10C Exercise 20 Plotting Aq vs Population Size When you are studying drift it is more useful to graph Ag vs population size You should take a sample of 10 or so pairs of years from the results of each experiment you did for Exercise 11 tabulate population size and allele frequency then do a scatterplot of allele frequency vs population size You could also take the data from Exercise 4 during the period when the population was expanding it will fill in the space between the points from Exercise 11 Give some thought to whether you should plot the size of the population in the first or last year or if you should take the average of the two Exercise 21 Examining q at a Time t for a Large Number of Populations of the Same Size Another way to look at drift is to do a series of experiments like those in Exercise 11 but with various random numbers Pooling class data is especially useful here Record the allele frequency of one allele every 25 generations When you have results from 10 or more experiments of the same size make histograms of allele frequencies you see graphically that genetic drift can indeed result in significant changes in allele frequency
90. re EVOLVE runs an experiment you should try to predict what will happen on the screen Predicting the results of experiments is an essential part of science and you should practice it whenever you can Looking at Results Once the experiment is finished you can examine the results in a variety of ways Click on the Change Params button This returns to the parameters window see Figure 2 3 which shows the parameters you entered before you ran the trial Note that the initial population parameters cannot be changed they do not have edit boxes around them after the trial has been started If you forget the experiment s initial inputs you can go back to this window and refresh your memory You may also change some of the values and continue the trial Click on the Graph menu and hold the mouse button down Note that there are check marks beside the frequency of each allele plotted on the graph Select Frequency Allele it is removed from the graph Select it again and it reappears Select Frequency of Genotype This adds the check mark and the line on the graph The menu and graph should look like Figure 2 5 Selection for Recessive Allele HH Frequency Allele Frequency Allele Frequency Genotype Frequency Genotype Frequency 0 Genotype Total Population Size Population Size Oe PDL LE sias Change Params Continue o Population Size Figure 2 5 Men
91. rictly speaking these calculations apply when data are collected in one generation and again at the same stage in the life cycle of the next generation for instance just after hatching or at the start of mating Data on the young of one generation cannot be used with adults of the next A similar approach may be used for calculating fitness and selection coefficients of alleles Absolute fitness of alleles would be the ratio of the allele frequencies in generation 2 divided by their frequencies in generation 1 Relative fitnesses and selection coefficients would be calculated as shown above Chapter 9 THEORETICAL NOTES 75 It is worth noting that science has a history and that concepts developed at one time may not be relevant later The concepts of relative fitness and selection coefficients were developed in the 1920s and 1930s because they made derivation of equations for population genetics easier Given that it is difficult to measure actual coefficients in nature this conceptualization of natural selection may in fact turn out to be unusable Limitations of EVOLVE While it is important to understand the nature and value of the tools at your disposal and simulation and mathematical models are powerful tools it is also important to understand their limitations In this section we try to clarify the nature of some of EVOLVE s limitations Among the most obvious of EVOLVE s simplifications is that we can look only at one gene with t
92. rong selection Run with weak selection e Describe the differences between runs with respect to Allele frequency changes 40 EVOLVE Manual Population size changes Conclusions Finally summarize the results That is compare the evolution of dominant advantageous alleles under strong and weak selection pressure Exercise 8 Does the Evolution the Change of Allele and Genotype Frequencies of an Advantageous Dominant Allele Proceed More Rapidly Than That of an Advantageous Recessive Allele with Comparable Survival and Reproductive Rates Prediction enter your own Experiment You may use the input data and results from Experiment 7A as the control for the experiment that follows However if you wish you may repeat 7A you will gain more experience with the effects of randomness Use the following data they are the same as for 7A but the title has been changed and the advantageous allele 0 is recessive Title 8A Sel for Recessive Allele 0 Number of generations 100 Carrying capacity 9999 Post crash pop size 7000 e 9 0 0 Initial population 1711 278 11 Survival rates 20 24 24 Reproductive rates 6 6 6 Results For both runs compare the following be sure to make specific comparisons Allele frequency changes Genotype frequency changes Population size changes Chapter 5 ELEMENTARY EXERCISES 41 Conclusion Which type of allele evolved faster Explain Do you think the question as it w
93. rted Introduction Using EVOLVE is easy and will rapidly become second nature In this chapter we will take you through a simple experiment to give you a feel for the way the program works In this manual special keys on the Apple keyboard are shown by words or symbols enclosed in square brackets and For example tab indicates the tab key return denotes the key labeled as such Directions are marked witha Three parts of this manual are more important than their page numbers suggest you should look them over soon and consult them when you have questions Chapter 8 Program Notes and Setting up Evolutionary Experiments will be useful in understanding EVOLVE itself and when you need to design experiments Chapter 9 Theoretical Notes contains background material on Hardy Weinberg and population genetics conceptual models and the concepts of fitness and selection Also there is a Glossary of terms used in this manual use it Start EVOLVE If the program is not already running insert the EVOLVE disk and turn on the computer Open the disk icon if it is closed and double click on the EVOLVE icon While the program is starting continue reading The Help System If you have questions or problems about using EVOLVE help is available from within the program There are three ways to get help 1 Information about inactive gray menu items If you do not understand why a particular menu item is not available you can c
94. s Obviously chance can have a significant influence on evolution Chapter 3 MORE ADVANCED FEATURES OF EVOLVE 21 EXERCISE 4 Changing the Evolutionary Situation During a Run One of the simplifications often made in modeling evolution is to assume that the evolutionary forces are constant that is the environment doesn t change Obviously this is a gross oversimplification and EVOLVE will let you get around it by changing data values during a run In this final exercise of our tutorial you will see how to do this Suppose you wished to simulate a drastic drop in population size such as would occur if there was a catastrophe like a flood that killed most of a population and reduced their food supply for a couple of years This would simulate what is sometime called the bottleneck effect In this scenario 30 individuals are assumed to survive a disaster from a large population having both alleles in equal abundance The alleles are assumed to be selectively neutral Set up an experiment with the following data values note that only 39 generations are to be done and then run the experiment Title Ex 4 The Bottleneck Effect Post crash size 8000 Run to generation 40 Genotypes oe e 0 0 Q Initial population 2000 4000 2000 Survival rates 22 22 22 Reproductive rates 5 5 5 Immigrat emigrat 0 0 0 When the 40 generations are finished click on the Change Parameters button and revise the parameters as follows
95. s chapter concludes with an exercise aimed at getting students to use the literature to find published data on sickle cell anemia then they try to model evolution of the sickle cell allele Students also can collect data from EVOLVE runs and then examine more abstract plots of change in allele frequency vs allele frequency or examine allele frequency over time in a sampling of drifting populations with and without selection Students will begin to get a better feel for the statistical nature of evolution These exercises are appropriate for more advanced undergraduate students Chapter 7 outlines several statistical approaches to the study of evolution Plots of selection coefficients over time allow students to begin to examine the relationship of fitness and selection coefficients derived from a priori survival and reproductive rates with those that can be observed from data on changes in allele and genotype frequencies over time EVOLVE provides field data from which students try to infer the pattern of selection Students can also make statistical comparisons of EVOLVE s results with those predicted from deterministic equations of the effect of selection on allele frequency over time or of the effects of drift on mean and variance of allele frequency in a sampling of populations These exercises would be useful for mathematically sophisticated upperclass or graduate students Chapter 5 Elementary Exercises This chapter is design
96. s in Part 2 Chapters 5 7 or may have you do others of his or her design Chapter 5 Elementary Exercises examines Hardy Weinberg equilibrium and four evolutionary forces selection mutation drift and gene flow singly then in combination If you don t already know some of these technical words there is a Glossary at the end of this manual The initial exercises are spelled out in detail and subsequent exercises leave more and more to be filled in by students The intent of this chapter is to give you a rather qualitative exposure to evolution Although you will be looking at numerical measures of allele and genotype frequencies we don t expect in depth comparisons of EVOLVE s output with theoretical predictions This chapter will be the meat of EVOLVE for the majority of students up through college undergraduates Chapters 6 and 7 Intermediate Exercises and Advanced Exercises are rather brief for they are intended to point the way to additional work for advanced undergraduates and graduate students Here the intent is to illustrate how to use EVOLVE as a microcosm to provide experimental data that may be used to test quantitatively predictions generated by equations Although EVOLVE is a rather simplistic model it can rapidly generate data which can be compared with theoretical predictions Again the exercises are of gradually increasing difficulty and assume increasingly mathematical background The last exerci
97. se in Chapter 7 can be a sobering experience for it brings home the enormous difficulty of proving what is happening in a given evolutionary situation Part 3 Further Considerations contains reference information on EVOLVE s menus and screen displays setting up experiments and some more advanced topics The two chapters Setting Up Evolutionary Experiments and Theoretical Notes should be used as references when you have questions about using the program Beginning Preface What You Need To Know 3 students may wish to read this material but may find some of it heavy going More advanced students will find it useful even if it is not assigned Chapter 1 Introduction EVOLVE is a computer program that allows you to experiment with evolution and to get quick results that are impossible to do in any other way You may control the starting population overall population size natural selection pattern of inheritance and migration in a hypothetical population By experimenting with EVOLVE you will develop e a better understanding of evolutionary processes and their interactions e a firmer grasp of some important concepts of Mendelian genetics e agreater understanding of experimental design e agreater understanding of the use of models and e an appreciation for one of the many uses of computers in biology EVOLVE provides abundant opportunities to practice posing questions about evolution and to try various s
98. series of EVOLVE experiments to examine this question Be sure to examine graphs of genotype numbers and population size What do your results suggest about the usefulness of fitness and selection coefficients in studying the evolutionary biology of real organisms Ecologists studying life history patterns groups of traits related to longevity and reproduction have found correlations of traits that make up alternative life histories For example a short life span is often correlated with rapid maturation production of large numbers of small young with little parental care and a single episode of reproduction Species exhibiting such traits are often weedy colonizers of unstable habitats and are sometimes called r selected Opposite traits long life span intensive parental care of a few large young repeated reproductive attempts are associated with K selected species which often live in stable habitats How do your results bear on the ecological concepts of r and K selected populations Look up these concepts in your textbook if you need more background on these concepts Exercise 17 Exploring Heterosis In Exercise 10 you briefly examined the pattern of evolution of a population with heterosis However that did not really reveal the wealth of interesting phenomena inherent in this pattern of inheritance This exercise is designed to give youa framework for exploring the phenomena of heterosis The basic question is What is the
99. set up your experiments Proper choice of values for these parameters will allow you to establish a population and to determine e the patterns of inheritance such as dominance recessiveness e natural selection e gene flow and e population size These are the heart of EVOLVE s model of evolution The other items in this window do not affect any of the evolutionary forces but do determine how the computer manages the experiment such things as its duration and its title Note that the experiment s title box Trial 1 is selected The title is to remind you of what the experiment is about Since many of EVOLVE s parameters interact they are edited in groups A typical Macintosh edit box surrounds editable values When you first click on a box to edit its value boxes that are not part of that group turn gray to indicate that they cannot be edited Members of the same group remain white and may be edited normally When you are finished with a particular group click the Update button 10 EVOLVE Manual Make sure that Trial 1 in the Title rectangle is highlighted If you clicked elsewhere by mistake and Trial 1 is not highlighted use the mouse to select it before typing Type Trial 1 Sel For Recessive If you make a typing error use the delete and keys and correct the error Click on the Update button Note that when you update the window the gray areas disappear You should always be sure to en
100. so the hypothetical population used by EVOLVE meets the assumptions of Hardy Weinberg equilibrium Mutation does not occur and mating is random Because you may specify values for all of the other assumptions you may design a population that fits any experiment you want to do on selection genetic drift and gene flow For example since the habitat is a discrete patch you can make it closed no gene flow if you wish Genetic Concepts Underlying the Model In genetic terms EVOLVE deals with a single gene having two alleles and 0 Thus there are three genotypes and 0 The alleles may effect any or all of four characteristics survival and emigration rates of juveniles and reproductive and immigration rates of adults Rates of survival reproduction immigration and emigration are not strictly speaking phenotypes of organisms in the same way that flower color is for a plant or vestigial wings are for a fruit fly Phenotype is classically defined as an observable characteristic of an organism while the rates used by EVOLVE are statistical characteristics of populations of organisms Nevertheless because phenotypes influence the ability of their owners to survive and reproduce we might think of the two alleles of our simulation as determining the probability of individuals surviving and reproducing In a similar way the color of a flower may influence how often insects pollinate it and hence the number of young produced Among fr
101. te choice of these variables is useful in other ways Suppose you find that values for maximum and post crash of 5000 and 4000 coupled with high survival and or reproductive rates produce such rapid population growth that population crashes occur in every generation the graph of total population size would be flat and fill the screen If you wanted to get a better idea of how evolution affected rate of population growth you could set post crash to a lower value such as 1000 and it would take longer for the population to exceed the maximum population of 5000 Program Output EVOLVE provides a number of ways of looking at experiments and their results Each experiment has a Summary Window that is the control center for examining results It contains a graph of genotype frequencies against time a table of numerical results for each generation and buttons that allow users to review the input parameters and generate graphs Information from any of EVOLVE s windows can be copied to the Mac s clipboard From there the information can be Pasted into EVOLVE s Notepad the Mac s scrapbook a graphics program a spreadsheet or a word processor Additional graphs may be generated in two ways By using the Graphs menu you may select standardized plots You may construct graphs with any axes by clicking on the Make new graph button on the Summary Window The Copy Commands Rather than produce reams of printed output EVOLVE allows you to pick
102. te values of some parameter Then do one or more EVOLVE experiments that provide you with data about that situation Graph the predicted values against those provided by EVOLVE and evaluate the goodness of fit For example when selection operates against a lethal or sterile recessive that is the selection coefficient 1 and relative fitness 0 then the formula for change in gene frequency becomes Aq q2 1 q Chapter 7 ADVANCED EXERCISES 57 You might calculate the values of Ag at intervals of q between 0 and 1 according to this equation then plot the results from one or more EVOLVE experiments What statistical tests would let you test the hypothesis that the EVOLVE data resulted from a population subjected to selection against a lethal or sterile recessive Do your results refute the hypothesis Exercise 24 Inferring Pattern of Selection from Field Data Another lesson about the difficulty of studying evolution can be learned from examining EVOLVE output without seeing the input data If your instructor gives you printouts of an EVOLVE experiment either generation summaries or graphs could you tell what the input values were It is instructive to break your class or lab up into several teams and for each team to solve the puzzle You might test your ideas by making your own EVOLVE experiments to try to duplicate the result you were given Would your task be easier or harder if the printout were from a trial with a smal
103. ter a brief descriptive title for your experiments You will eventually accumulate many different experiments and their titles will help you keep them straight There is much to discuss about this window but we will come back to it later Now you should actually run the experiment Click on the Done button to return to the summary window Doing the Experiment Click on the Start button in the lower right hand corner of the window Note that it changes to Stop While the experiment is running the window will develop into something resembling Figure 2 4 Selection for Recessive Allele 8 Figure 2 4 Summary Window after Trial 1 When EVOLVE has finished the experiment for Trial 1 your summary window should look like this Note that the display in Figure 2 4 shows a graph of the frequencies of each allele on the vertical axis with time on the horizontal axis There is also a table showing numeric summaries of each generation As the experiment proceeds the graph is updated Chapter 2 Getting Started 11 If you wish to pause for thought or discussion or if you realize you have made a mistake press the Stop button It changes to Continue If you wish to display other graphs of current results or start another experiment you may do so If you decide to continue a stopped experiment click on the Continue button you may not however exceed the maximum number of generations Befo
104. terosis tend to remain in a population no matter how deleterious they are in homozygous condition In a malaria free environment the allele is recessive and deleterious with respect to survival In the latter environment you would be correct in expecting it to decrease in frequency The Nature of Evolutionary Fitness Evolutionary biologists use of the term fitness differs significantly from common usage It might have been better if someone had invented a long Latin word for this concept for people would be more cautious about assuming they know its meaning Instead people assume that evolutionary fitness is like athletic fitness robustness strength endurance Instead we will define evolutionary fitness as the ability of an allele or a genotype to gain representation in the next generation because of the ability of its phenotype to survive and reproduce Because it is critical that you understand this definition and its implications both to understand the behavior of EVOLVE and to understand evolution we will spend some time discussing it The detailed measurement of the fitness of an allele in nature is difficult for it requires understanding genotype frequencies and the probabilities of different matings along with survival and reproductive rates If you work your way through the more advanced discussion of absolute and relative fitness in Chapters 7 and 8 you will come to understand this clearly For now note that evolutionary fit
105. tes with or is pollinated by one other adult at random and both produce offspring If there is an odd number of adults in the population the last individual fertilizes itself While this characteristic of the model population may seem odd it avoids complications of sex ratios and mating patterns Actually this sort of population is fairly common among plants and even exists in a few animals The life cycle of the hypothetical organism is a simple one see Figure 4 1 for an outline of the life cycle as it relates to EVOLVE s simulation During the short breeding season all adults mate produce offspring and die All members of the next generation hatch are born released as seeds or whatever during a short time The young then mature over a period of time during which they may die or emigrate fly walk blow or be carried away At the end of the juvenile period all surviving individuals become adults and some additional adults may immigrate from surrounding populations or adults may emigrate leaving the population You may find it convenient to think of the organism as having a one year life cycle and generation time You may specify any or all of the survival reproduction emigration and immigration parameters for each of the three genotypes 24 EVOLVE Manual Enter Data Initial Population Reproductive Rates Survival Rates Emigrating Immigrating Max Pop Size Post crash Size Mating Randomly mate adults Reproduction
106. ting on the graph The text appears and can be edited in standard Macintosh fashion Make sure you have used the Chooser to select a printer and that the printer is turned on Select Print Notepad from the File menu The contents of the notepad are printed While the notepad is convenient this version of EVOLVE cannot save it when you quit the program You can copy and paste data into word processors spreadsheets and statistical packages with the Copy Window Data command in the Edit menu it cannot be pasted into the Notepad Graphics can be copied into word processors and programs that edit graphics You may also use the Macintosh Scrapbook to save graphics and data then paste them into other programs 20 EVOLVE Manual Finally the Save Window Data command in the File menu will save the entire contents of the data table to a text file that may be opened by a spreadsheet or statistical package EXERCISE 3 Comparing Runs with Different Random Numbers This exercise is designed to provide an illustration of how randomness may affect evolution Any experiment is subject to variations especially experiments with small populations We will rerun Trial 2 a second time to look at some random effects Before we do that we need to remove the clutter of Trial 1 Point to the Background Graphs box and press the mouse button A list of trials pops up Trial 1 appears with a check beside it Select Trial 1 and it is unchecked and its li
107. tion they are lost to the one we are studying Let us suppose our population initially contained only the o allele and began receiving immigrants from another population that contained a high frequency of alleles If the allele produced a phenotype which dispersed readily and had no effect on survival or reproduction then the gene flow would favor that allele that is cause it to increase in the population Set up you EVOLVE data as follows Title 12 Gene Flow Number of generations 100 Carrying capacity 9999 Post crash pop size 7000 0 0 0 Initial population 0 0 8000 Survival rates 20 20 20 Reproductive rates 6 6 6 Number immigrating 1000 100 0 Percent emigrating 0 0 0 Prediction enter your own Results Describe the changes in allele and genotype frequency Conclusion What is the effect of gene flow on allele and genotype frequencies In this experiment we neglected the fact that containing individuals would probably Chapter 5 ELEMENTARY EXERCISES 45 emigrate at higher rates than 00 individuals How would the results of this experiment differ if the emigration rates were set to 30 30 and 0 for the and 00 genotypes respectively Mutation Mutation is of great interest to biologists because it is the ultimate source of the genetic variability that is the raw material of evolution As you might expect the study of mutation is a complex one and for many reasons EVOLVE cannot be used to
108. trategies to answer those questions It also provides data and graphs that help answer the questions as well as help persuade others of the value of those answers Real experiments in evolutionary biology are difficult you just cannot evolve something in a semester or even a lifetime This point deserves emphasis because it requires the approach of evolutionary biologists to be somewhat different from that of many other biologists Even learning about evolution is difficult because students cannot get their hands dirty by doing experiments like those in for example physiology A common naive view of science is that experiments are required to test hypotheses In most scientific disciplines we note some aspect of the real world formulate hypotheses about major factors involved in that phenomenon and test those hypotheses with experiments In essence experiments are simple models we construct of the real world that hold most factors constant We then vary one or a few factors and observe the results In many areas of biology experimental design has become a sophisticated and elaborate affair of choosing such things as organisms equipment and statistical methods Evolutionary biologists can apply that approach only with difficulty We can test some hypotheses using small organisms with short life cycles Occasionally we can find a situation in nature that approaches a true experiment but it is hard to coax Ma Nature into pr
109. u and Graph of allele and heterozygote genotype frequencies vs time 12 EVOLVE Manual There is a considerable amount of information to be gleaned from comparison of graphs such as this and it will take you some time to become proficient in extracting all that there is to be seen At this time we will just mention a few significant points Point to the Freq heading of the data table and hold the mouse button down The line on the graph corresponding to the frequency of allele remains black and the others become gray Point and press on the other column headings in turn scroll the window to the right or enlarge the window to see hidden columns Each time the appropriate line appears black and the others dim to gray If a variable is not on the graph it appears as long as the mouse button is down Click slowly three times on the gridded box next to the Background Graphs pull down menu This toggles grid marks on the graph You should be able to describe what happened in graphs such as these A full a of this graph might include the following points The frequency of the recessive allele was initially low about 0 05 or 5 in generation 1 and climbed relatively slowly e After roughly generation 20 the allele reached 20 allele frequency e It then rose more rapidly becoming the most common allele after about generation 30 e After about generation 35 its rate of increase of the allele slowed abruptly as its freq
110. uency approached 100 e The dominant but disadvantageous allele followed a mirror image path and was almost extinct in generation 50 e The frequency of the heterozygotes peaked just below 50 when the alleles were equally common Note that your results will differ slightly from those shown in this manual EVOLVE incorporates the randomness of evolution hence each run will differ from others The degree of difference will depend on a number of factors and will be discussed later For this example you should see little difference You can t see precise details on graphs such as this but you can scroll back through the Results table in the Summary Window if you want to look at specific generations or frequencies Here s how Click on the pane control hold the mouse button down and drag the black rectangle up The data table is dragged up revealing a scroll bar The graph becomes shorter to accommodate the table You can now scroll through the data table to see exact figures for each generation Scroll vertically until you can see the generations after 30 Now you can see when the heterozygote frequency 0 Freq peaked roughly 46 around generations 35 in our trial There are theoretical mathematical reasons why the heterozygotes peaked and the homozygotes crossed at the time the allele frequencies l l Chapter 2 Getting Started 13 crossed They are worth discussing with fellow students or your instructor but we wil
111. uestion essentially completes the process of designing the experiment There remains only the prediction how do you think the two experiments will compare If you believe that selection will operate the same in the two populations and that population size has no effect you might predict that the genotype frequency graphs of the two experiments will be identical We will start with the experiment from Chapter 2 You will modify it to keep the population small run the experiment and compare the first and second experiments Finally you will make a third run to observe random effects If you do not have EVOLVE running start it up just as you did in Chapter 2 If you just restarted EVOLVE rerun Exercise 1 While the experiment is running read on Chapter 3 MORE ADVANCED FEATURES OF EVOLVE 17 Redoing the Experiment with Variations To redo the first exercise with a smaller population we will need to keep the survival and reproduction rates the same but change the factors related to population the initial population maximum population and post crash size We should also change the title to distinguish this from other experiments Click New Trial The graph for Trial 1 becomes gray and the trial popup changes to Trial 2 Click Change Parameters If you have reached this point directly after doing Exercise 1 the values in most of the boxes will be the same as in that experiment If you have started EVOLVE again the
112. uit flies individuals with vestigial wings cannot fly and get trapped more often in sticky food hence their survival rate is lower than normal flies You will find it easier to use EVOLVE if you make up phenotypes appropriate to the question you are studying and attach them to the genotypes as we did in Chapter 2 For the purposes of using EVOLVE use the following definitions to determine the pattern of inheritance Dominant alleles produce their full phenotypic effect even in heterozygous condition Recessive alleles have their full effect only when in homozygous condition Thus if the lt genotype has the same phenotype as the 00 homozygote then the o allele is dominant and the allele is recessive Incomplete dominance occurs when the phenotype of the heterozygote is intermediate between the phenotypes of the two homozygotes Reproductive rates of 4 6 and 8 for the 0 and 00 genotypes would simulate incomplete dominance Codominance occurs when both alleles produce their effects in heterozygotes Suppose you set survival rates to 30 30 and 40 and reproductive rates to 4 5 and 5 26 EVOLVE Manual offspring per adult The allele reduces both survival rates and reproductive rates while the allele produces higher survival and reproduction The allele is dominant with respect to survival but recessive with respect to reproduction The end result is that both alleles produce their effects in heterozygotes when you c
113. ulation is roughly equivalent to the ecologist s Carrying Capacity the greatest number of individuals of a population that can be sustained by their environment often symbolized by K In EVOLVE the maximum size is the one to which the population of adults may grow If the survival and reproductive rates and gene flow are such that the population grows and exceeds the number you typed for maximum population EVOLVE reduces the population to the size of the post crash value Mortality during the population crash is random with respect to genotype For example if the number of young were 20 000 and the survival rates were all 50 you would expect the number of adults to be about 10 000 twice the largest possible maximum population If the post crash value was 2 500 EVOLVE would multiply the number of each genotype by 2 500 10 000 to determine the actual number of adults You should choose these variables carefully to ensure that the population size is appropriate to the evolutionary situation you wish to model For example if you wish to study the effects of genetic drift in a small population of 10 20 adults let the maximum 20 and post crash 10 provided the population does not become extinct it will remain within those limits Setting maximum 5000 and post crash 4000 would permit you to simulate a population with very little random change Chapter 8 PROGRAM NOTES amp SETTING UP EVOLUTIONARY EXPERIMENTS 65 Appropria
114. ulations of the SaM ESZE eraa E E E E EEEE 54 Chapter 7 ADVANCED EXERCISES wioisisntaiiencsinnenisoneiinan easiornnauniinnaonnae 55 EXERCISE 22 The Model Underlying EVOL Eiscecsacseiestsinsacatestoslansnosstetintsstnaonicee 55 EXERCISE 23 Statistical Comparisons of EVOLVE s Results With Theory 56 EXERCISE 24 Inferring Pattern of Selection From Field Data cece 57 Chapter 8 PROGRAM NOTES and SETTING UP EXPERIMENTS cece eee 58 INTIRODUCTION roiete bateiauadeeanisadbeaiagacecaanpaainedtaatinainenbesiteedaacaientbacds 58 GETTING HELP WITH EV OU Eiescicistiscnecdicrvavteturwscniassuncdde snsectuavnesedcteacerstvdupectedaaawasern 58 PROGRAM INPU Trieda anasatsaliniaee Gcentaunccaaduindcsetdadeasucindestueadecaesiaden 59 Title A E E fentess ecuuestaseeeteis 59 Number of Generations ccccccccccccssssssscccccecscsessssccscceccecscssssesseeeseseeesessnsseeeeesens 60 Stating Populations ssnssiroer inii innn n E EAN 60 Survival and Reproductive Rates Selection Pattern of Inheritance and Population Growth Mates ssinisiirenancireiiaai anari 61 Pattern of IMCTLAN CS iss siasiassaaiasscsaedaciesaiaaieoecadacsantassvaseataciosarionvesariaes 61 Population gr wth ANG yes 5 esa ncoctcosert ciecasenbiactetactaviiehiloraemenaniedaasee 62 Pattern Of selection o oo cece eee cececccccccecesseseccccecececeesseeneccececececsesetenacceceeeens 62 iv EVOLVE Manual Gene FloW meei nee decesibdendeetsededieaa JoqssesteteccadiOeedaupentete
115. understand each of the forces by itself we can combine it with other forces and examine interactions of more than one In the absence of easy experimentation population geneticists have turned to such equations for their experiments Much of our theory of microevolution is based on such models Models permit us to explore the widest possible range of conceivable conditions the theoretical maxima and minima of evolution Thus the theory deals with all possible universes experimental and observational studies must determine which universe actually exists Chapter 9 THEORETICAL NOTES 71 Despite the importance of mathematical models in population genetics they present problems Elegant mathematical equations are intellectually stimulating and manipulating them can be instructive but they require mathematical expertise and can be time consuming Also mathematics are too often a barrier for many beginning students of evolution The advent of calculators and computers has reduced computation time but sometimes at the expense of a full understanding of the models which are hidden from students In addition most mathematical models deal only with one or two of the evolutionary forces it is difficult for students to get a feel for the way factors interact in populations The abstractness of most such models makes it hard for students to really grasp what they mean just what is a selection coefficient of 0 3 Finally most of the simple
116. vers around the world in temperate and tropical regions One would expect that natural selection over such a range of habitats must select for different characteristics yet Ospreys look the same all over the world One possibility of course is that natural selection acts the same way in all Osprey populations Many evolutionists however have felt that gene flow can act to hold populations together even though natural selection would tend to cause them to become different Other evolutionists believe that there is not enough gene flow to counteract selection and that there must be other reasons for the similarity of species over wide geographic areas Here is an experiment that addresses this controversy Experiment Consider a population on an island where selection favors a recessive allele 0 Perhaps individuals carrying the dominant allele have seeds with long hairs like milkweed that tend to be blown off the island while 0 individuals produce seeds with short hairs that fall directly to the ground The population in Experiment 8A illustrates what would happen to the population if it were isolated the alleles would decrease and the population would come to consist of plants with short haired seeds To see the effect of gene flow set up another set of experiment like the following in which hairy seeds are blown onto the island from a mainland where selection favors mobile seeds Title 15A Sel vs Gene Flow 0 5 Number of generations
117. will illustrate what is required of you and give you an introduction to the whole process In particular note the way the parameter values are set up and how to examine the graphs of results and the types of questions asked Also note that for each question we have made one or more predictions about the 34 EVOLVE Manual outcome of our experiments with EVOLVE Subsequent exercises are more abbreviated to encourage you to develop skill in using the program and in investigating problems You may wish to make several runs with each set of parameters Note that there is to be no gene flow nor will you need to change parameters during a run If you are uncertain about allele and genotype frequencies and how to calculate them read appropriate sections of your text or in Chapter 9 of this manual Also if you do not understand the Hardy Weinberg Law better referred to as Equilibrium consult your text or read Chapter 9 in this manual Exercise 5 How Long Does It Take To Establish Hardy Weinberg Equilibrium Starting with a Population That Is Not in Equilibrium Experiment and Prediction A population in obvious disequilibrium would be one consisting entirely of heterozygotes There are other ways to set up such an out of equilibrium population can you think of several On the basis of what you have learned in this manual it would be reasonable to predict that the population would reach Hardy Weinberg equilibrium in one generation More s
118. wo alleles Most evolutionarily important characteristics are influenced by many genes which often have many more than two alleles Moreover genes are not isolated there are many types of interactions between genes Even the interaction of two alleles at one locus may be affected by other loci there is abundant evidence that advantageous alleles that are initially recessive can become dominant through the influence of such modifier genes This over simplification of the genetics of our model is perhaps the biggest conceptual problem with EVOLVE For example one of the major questions in evolutionary biology is how the many diverse alleles seen in wild populations are maintained in natural populations Using EVOLVE you might find a half dozen ways to maintain two alleles in a population over a long period of time But many evolutionary biologists don t feel these sorts of mechanisms would be sufficient and have extended their analysis to three alleles This turns out to increase complexity significantly and to generate even more ways to maintain more than one allele in a population The current version of EVOLVE cannot handle three alleles although a future version will EVOLVE is also ecologically naive In the real world Carrying Capacity is rarely an absolute limit which is constant over time and which only influences a population when the limit is exceeded Many limiting factors increase in severity as the Carrying Capacity is approached
119. you enough information to answer your original question Often of course 16 EVOLVE Manual the answer to the original question will suggest additional questions and the cycle will repeat With this additional perspective in Exercise 2 you will be taken through the process of answering a question about the effect of population size on evolution In Exercise 3 you will investigate the effects of random factors on EVOLVE s results and evolution Finally in Exercise 4 you will be shown how to model more complex evolutionary situations by changing the values of EVOLVE s input parameters during a run Exercise 2 Comparing Selection in Small and Large Populations An important question in evolutionary biology has been what are the effects of population size on the evolution of populations A thorough answer to this question has required decades of work by many biologists and some aspects of the answer are still controversial However you can get a feel for some of the effects with a few experiments using EVOLVE As phrased the question is a bit too general Let us start by making it more specific Since we have already done one experiment that provided data on natural selection in a population of 8000 10 000 let us answer the more limited question Does selection for a recessive allele proceed differently in a small population of 80 100 individuals than in a large population of 8000 10 000 Note that this rephrasing of the q
120. ypes Mean Mean Genotype Number survival rate reproductive rate 245 0 2 5 1 0 210 0 3 4 6 0 0 _45 0 3 4 1 Total 500 You need not try to formulate one equation for such a population you may find it easier to consider the basic population process of birth survival mating and death Questions Bring brief specific answers to class for discussion 1 What do you predict will happen to the population size over time 2 What do you predict will happen to the frequencies of the two alleles 3 What do you predict will happen to the frequencies of the three genotypes 4 How would you set out to convince a skeptic that your prediction is correct Your instructor will help you discuss your approaches and come up with an approach to model this evolutionary scenario You can then calculate the results to see how your answers compare to the model the class develops Exercise 23 Statistical Comparisons of EVOLVE s Results with Theory One of the major difficulties scientists have is to evaluate whether data that they have gathered in experiments fit the predictions of theory Students with some background in statistics may find that EVOLVE provides an opportunity to gain experience with statistical tests of goodness of fit If you have not already done so you may want to see the BioQUEST statistics module for some approaches Pick an evolutionary situation about which you can make mathematical predictions and compu

Evolve Version 2.04 User`s Manual

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