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In the Selfish Gene, the chapter about ESS, how do the doves spread their genes?

In the Selfish Gene, the chapter about ESS, how do the doves spread their genes?



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In his explanation of the Evolutionary Stable Strategy, in the Selfish Gene, Richard Dawkins repeats a couple of times, that a population of hawk-type males would make the ground for a dove-type individual to spreat his genes, because the dove always retreats against a hawk and if an average hawk loses every second match, than he'll be worse off than the dove that always retreats and stays unhurt.

My question is - how dose a male, that does not win a single contest for a mate and therefore doesn't get to mate at all, spreat his genes? Does the ESS imply that there are ways to breed bypassing the contest?


Game theory

Your question is not as specific to biology as you may think. The hawk-dove game is a type of game in game theory, a field of mathematics. Game theory is used in biology, in economics, in psychology and many other disciplines.

The hawk-dove game is often called the chicken game. If a game is defined as a chicken game, then it has an equilibrium different from 0 or 1. Otherwise, it may not.

You need to fully specify the scenario of interest to figure our what type of game we're dealing with to know what type of game we're dealing with and what are the possible equilibriums.

For more information, have a look at the mathematical field of game theory.

You specific scenario

The scenario as written in your post is not fully discribed. In your question, you define the doves such as they have a fitness (or a payoff in game theory terms) of 0, whatever is the state of the population. For such case, of course, a frequency of doves of 1 cannot be an ESS. However, under such case, you are not dealing with a hawk-dove game. I suspect you misunderstood the game as defined by Dawkins (it is also possible that Dawkins did not fully define the game he's talking about).

In short…

In short, I can't say much else than just "read more about game theory". However, you might want to cite exactly Dawkins so that we can understand exactly how he describes the specific game at play and comment on the expected outcome.


A male that does not mate will not spread his genes. Females might, if they have the option to reproduce asexually. However, this is probably not the answer you are after though. What you need to do is to look at the assumptions behind the game theory model being used.

For instance, some of the assumptions in a basic ESS-analysis are usually:

  1. that the population size is infinite.

  2. that the game payoffs are fitness modifiers and do not determine absolute levels of fitness.

Point 1 means that the game payoffs refer to the average payoff of individuals in each type of encounter. Point 2 means that there is always a baseline level of fitness, so all strategies are able to reproduce. Sometimes, assumption 2 is reformulated in terms of asexual populations, which means that all individuals will be able to reproduce (so the hawk-dove game will strictly not the modelling access to mates).

Therefore, doves (which never escalate a contest) will be able to "spread their genes" (win the contest) 50% of the times when there is a dove-dove contest (here is a description of what appears to be the normal version of the hawk-dove game). A single dove that enters a population will also be able to reproduce, even though it will never win contests (based on assumption 2). Again, remember that the game payoffs are fitness modifiers and does not determine the absolute level of fitness.

This means that individuals that play the dove strategy will still be able to spread their genes to later generations, but this doesn't preclude that certain dove individuals never get the chance to reproduce. This also means that there isn't any need for "ways to breed bypassing the contest", since one of the assumptions is that all strategies can reproduce, and in this case all strategies also have a payout option where they sometimes win the contest (which is the case for the hawk-dove game).


You are adding assumptions that are not there.

You assume not winning equals not mating, it doesn't, if a dove meets a female by herself they mate. The example of elephant seals he uses shows this, some males fight others wait for unattended females.


Richard Dawkins, an evolutionary biologist and author, Dawkins argues that biology’s focus on organisms is misguided, and that life should instead be considered from the point of view of individual genes trying to perpetuate themselves through countless generations.

Though the book begins with the premise that biologists think too large (organisms instead of genes), it ends with the surprising idea that they think too small—that genes have much greater impacts on the world than simply creating bodies to inhabit. Dawkins offers compelling arguments for why we should think about biology as ranging from the microscopic to the wider world.

Scientists have simulated this process using computers and game theory. By assigning arbitrary point and penalty values to different outcomes such as winning a confrontation, being injured, or wasting time on a lengthy contest, and programming in various strategies for the virtual “animals” to use, the simulation can run until the population stops shifting in any significant way. These simulations help scientists to find and understand the ESS.

Limited Resources May Cause Conflicts of Interest

Because Earth is a finite world with finite resources, there’s a natural struggle between the creatures who inhabit it to get those resources. This competition extends to family members, including the struggle between parents and their children for exactly what proportion of the resources each child should get. The parent will want to distribute resources for the best possible genetic payoff—in other words, the maximum number of surviving offspring. However, each child will be interested in getting more for itself. Therefore, the child will often try to trick its parents into believing it needs more resources than it’s getting.

Also, if there can be conflicts of interest between parents and children—who share 50% of the same genes—then there should be severe conflicts of interest between mates, who have no relation to each other at all. Genetically speaking, each is only valuable to the other in terms of their shared offspring. Each wants as many surviving children as possible, but they will naturally disagree on who should have to invest the resources to raise those children.

There are benefits to each of two conflicting situations: staying with your partner for as long as possible, and abandoning them with the child before being abandoned yourself. A mated pair that stays together can split the resource cost of raising their offspring. However, a parent who abandons their mate and offspring gains a significant advantage—if they can be reasonably sure that the remaining mate will successfully raise the child or children.

Worth noting in this situation is that the female will naturally be more invested in the offspring. This is because she contributes the larger and more resource-intensive egg cell and, in many species, because she takes on the cost and risk of pregnancy and birth. It will be much more difficult for the female to produce another offspring than the male, who could easily find another mate and impregnate her.

These two situations, parent vs. offspring and male vs. female mates, have led to a huge array of evolutionary tools and strategies. A child may use various tactics to try to get more than its fair share of the resources. For example, a common tactic among young birds is to cry more loudly than the others in the nest. Since the volume of a cry normally corresponds to how hungry the bird is, a louder hatchling can trick its parents into thinking it’s hungrier than the others, causing them to give it more food at its siblings’ expense.

For mates, many species of animals have long, intricate courtships to get both the male and female heavily involved before they actually reproduce. We mentioned before that, in theory, a male could simply leave and impregnate another female right away. However, if he knows he’ll have to go through the entire courtship again, it’ll be more worth his time to stay with the mate he already has.

Group Altruism and the Evolution of Culture

Many types of animals move, or even live, together in groups. Some advantages of this are obvious. For example, prey animals gain some protection from predators by living in groups. Meanwhile, predators like hyenas can bring down much larger prey by working together, so it benefits them all even though they have to share the food.

Another example is birds, many of which fly in formation and switch leaders frequently to reduce turbulence and make travel less tiring. However, birds have also been observed giving alarm calls to warn of predators, at some risk to themselves. This apparent act of altruism may ultimately be an act of selfishness—in fact, considering the selfish gene theory, it must be.

By the simple truth of natural selection, we can infer that giving that alarm call is more beneficial to the individual’s genes than not giving it would be. There are any number of possible reasons for this.

For instance, if a bird simply flew away upon spotting a predator, it would lose the advantages of living in a flock. If it froze and hid, but the rest of the flock kept moving around and making noise, that would draw the predator closer to the individual anyway. Therefore, it would be best to call a quick warning so the entire flock can hide. Also, there’s the simple likelihood that by taking a small risk to itself, the individual giving the call can protect many of its relatives. Finally, we can infer that if one of these birds calls to warn the others, that kindness will be repaid later by the others.

This is one form of reciprocal altruism: Two or more animals showing each other mutual altruism. Another common example is communal grooming. This example is especially interesting because there is a delay between one act of altruism and the act being repaid—pulling a harmful parasite off another individual doesn’t help you until you have a parasite to be pulled yourself.

The cost of grooming another member of the population is minuscule, but it’s still greater than zero. Therefore, among species that participate in communal grooming, there must be greater benefit than cost for doing so. One possible explanation is that members of the population evolved the ability to hold a “grudge” that is, they refuse to groom selfish individuals who don’t groom others. This would naturally drive down the number of selfish individuals as they fall victim to parasites.

Ideas Spread Like Genes

Interestingly, ideas and behaviors can be observed to spread through populations and evolve much like genes do. Certain songbirds, for example, are known to learn their songs by imitating birds around them, rather than having them coded in by genes. However, sometimes birds will make a mistake and give rise to a new song. That song, in turn, is picked up by others and spreads throughout the population. If the replicator unit of biology is the gene, then the replicator unit of ideas could be called the meme—from the Greek mimema, meaning “that which is imitated.”

Among humans, the spread of ideas is more pronounced and much easier to recognize. A catchy song is a type of meme, as is a popular slogan or a political stance. God is one of the most successful memes in all of history—while it’s not clear how the idea of God originated in the “meme pool,” so to speak, it has been spread by stories, songs, art, and rituals to nearly every part of the world for thousands of years.

Culture and memes don’t seem to have any inherent survival value. It’s more likely that they’re side effects of group-focused evolutionary traits such as those discussed at the beginning of this section.

Extending the Phenotype

We began with the premise that biologists think too large (organisms instead of genes), but it’s also possible that they think too small—that genes have much greater impacts on the world than simply creating bodies to inhabit.

To look at biology in a new way requires that we consider what might be called the extended phenotype. Phenotype typically means the physical effects that genes have on the body they inhabit—for example, blue eyes or long legs. However, it’s not much of a stretch to extend the definition of phenotype beyond the individual, to include the impact on the world. This could be called an extended phenotype.

While phenotype typically refers to a creature’s physical body, genes don’t directly affect such things rather, they change the internal workings of cells, which eventually leads to different traits in the body. Therefore, saying that the organism’s body—but not its impact on the wider world—is a result of those genes is fairly arbitrary.

Some examples of this extended phenotype could be bird nests and beaver dams. Though it sounds strange to say, there are genes “for” certain building materials and construction styles—phrased another way, there are genes that cause the animals to build structures in those specific ways. Even a lake that was formed by beavers damming a river could be considered part of those beavers’ phenotypes.

It’s easy to see the obvious ways that organisms interact with each other: competing for resources, predation, mating, symbiosis, and so forth. However, with an extended phenotype, it becomes clear that there are countless different ways that organisms—or, more accurately, genes—impact each other and the world around them. The problems and opportunities that arise from this gene-centric view of the world are explored in much greater detail in Dawkins’s book The Extended Phenotype.

Biologists Often Ask the Wrong Questions

Many biologists make the mistake of focusing their questions and their studies on the organismal level: They ask why an organism does something, or behaves a certain way. In fact, it’s quite common for biologists to say that DNA and RNA are tools organisms use to replicate themselves—which, in light of what we’ve discussed so far, is the exact opposite of the truth.

Organisms don’t replicate themselves at all (except in the relatively rare case of asexual reproduction). Given that the “purpose” of life is replication, it seems clear that organisms are tools that genes use to replicate themselves.

Starting from the genetic level, then, one might ask why organisms as we know them should exist at all. The simple truth is that organisms don’t have to exist. They exist on Earth because that’s what evolution happened to favor in this particular environment.

It’s helpful to remember that, at the most basic level, we’re dealing with replicators that aren’t so different from those found in the primordial soup eons ago. The only thing that must exist in order for there to be life is some form of replicator molecule. Replication is both the beginning and the purpose of life.

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In the Selfish Gene, the chapter about ESS, how do the doves spread their genes? - Biology

Thus, accordiong to the above definition, female is the weaker sex and she should be dominated. Also see the part where he says that he is NOT doing a moral science..

The opening pages of Chapter 1

Chapter 1 - Why are people?

Darwin made it possible for us to give a sensible answer to the curious child whose question heads this chapter. ['Why are people?'] We no longer have to resort to superstition when faced with the deep problems Is there meaning to life? What are we for? What is Man?

The argument of this book is that we, and all other animals, are machines created by our genes.

This brings me to the first point I want to make about what this book is not. I am not advocating a morality based on evolution. I am saying how things have evolved. I am not saying how we humans morally ought to behave. . If you wish to extract a moral from it, read it as a warning. Be warned that if you wish, as I do, to build a society in which individuals cooperate generously and unselfishly towards a common good, you can
expect little help from biological nature. Let us try to teach generosity and altruism, because we are born selfish. Let us understand what our own selfish genes are up to, because we may then at least have a chance to upset their designs, something that no other species has ever aspired to do.

I shall argue that the fundamental unit of selection, and therefore of self-interest, is not the species, nor the group, nor even, strictly, the individual. It is the gene, the unit of heredity.

Chapter 2 - The replicators

Was there to be any end to the gradual improvement in the techniques and artifices used by the replicators to ensure their own continuation in the world? There would be plenty of time for their improvement. What weird engines of self-preservation would the millennia bring forth? Four thousand million years on, what was to be
the fate of the ancient replicators? They did not die out, for they are the past masters of the survival arts. But do not look for them floating loose in the sea they gave up that cavalier freedom long ago. Now they swarm in huge colonies, safe inside gigantic lumbering robots, sealed off from the outside world, communicating with
it by tortuous indirect routes, manipulating it by remote control. They are in you and me they created us, body and mindand their preservation is the ultimate rational for our existence. They have come a long way, those replicators. Now they go by the name of genes,and we are their survival machines.

Chapter 3 - Immortal coils

Our DNA lives inside our bodies, It is not concentrated in a particular part of the body, but is distributed among the cells. There are about a thousand million million cells making up an average human body, and, with some exceptions which we can ignore, every one of those cells contains a complete copy of that body's
DNA.

The evolutionary importance of the fact that genes control embryonic development is this: it means that genes are at least partly responsible for their own survival in the future, because their survival depends on the efficiency of the bodies in which they live and which they helped to build.

The definition that I want comes from G. C. Williams. A gene is defined as any portion of chromosomal material that potentially last for enough generations to serve as a unit of natural selection.

Individuals are not stable things, they are fleeting. Chromosomes too are shuffled to oblivion, like hands of cards soon after they are dealt. But the cards themselves survive the shuffling. The cards are the genes. The genes are not destroyed by crossing-over, they merely change partners and march on. Of course they march
on. That is their business. They are the replicators and we are their survival machines. When we have served our purpose we are cast aside. But genes are denizens of geological time: genes are forever.

Genes are competing directly with their alleles for survival, since their alleles in the gene pool are rivals for their slot on the chromosomes of future generations. Any gene that behaves in such a way as to increase its own survival chances in the gene pool at the expense of its alleles will, by definition, tautologously, tend to
survive. The gene is the basic unit of selfishness.

No doubt some of your cousins and great-uncles died in childhood, but not a single one of your ancestors did. Ancestors just don't die young!

Chapter 4 - The gene machine

opening paragraph:
Survival machines began as passive receptacles for the genes, providing little more than walls to Protect them from the chemical warfare of their rivals and the ravages of accidental molecular bombardment. In the early days they 'fed' on organic molecules freely available in the soup. This easy life came to an end when the
organic food in the soup, which had been slowly built up under the energetic influence of centuries of sunlight, was all used up, A major branch of survival machines, now called plants, started to use sunlight directly themselves to build up complex molecules from simple ones, re-enacting at much higher speed the synthetic
processes of the original soup.

The evolution of the capacity to simulate seems to have culminated in subjective consciousness. Why this should have happened is, to me, the most profound mystery facing modern biology. There is no reason to suppose that electronic computers are conscious when they simulate, although we have to admit that in the
future they may become so. Perhaps consciousness arises when the brain's simulation of the world becomes so complete that it must include a model of itself. . Whatever the philosophical problems raised by consciousness, for the purpose of this story it can be thought of as the culmination of an evolutionary trend towards the emancipation of survival machines as executive decision-takers from their ultimate masters, the
genes. Not only are brains in charge of the day-to-day running of survival machine affairs, they have also acquired the ability to predict the future and act accordingly. They even have the power to rebel against the dictates of their genes, for instance in refusing to have as many children as they are able to. But in this respect
man is a very special case, as we shall see.

The genes are the master programmers, and they are programming for their lives. They are judged according to the success of their programs in copying with all the hazards that life throws at their survival machines, and the judge is the ruthless judge of the court of survival.

Whenever a system of communication evolves, there is always the danger that some will exploit the system for their own ends. Brought up as we have been on the 'good of the species' view of evolution, we naturally think first of liars and deceivers as belonging to different species: predators, prey, parasites, and so on. However,
we must expect lies and deceit, and selfish exploitation of communication to arise whenever the interests of the genes of different individuals diverge. This will include individuals of the same species. As we shall see, we must even expect that children will deceive their parents, that husbands will cheat on wives, and that brother
will lie to brother.

Chapter 5 - Aggression: stability and the selfish machine

To a survival machine, another survival machine (which is not its own child or another close relative) is part of its environment, like a rock or a river or a lump of food. It is something that gets in the way, or something that can be exploited. It differs from a rock or a river in one important respect: it is inclined to hit back. This is
because it too is a machine that holds its immortal genes in trust for the future, and it too will stop at nothing to preserve them. Natural selection favours genes that control their survival machines in such a way that they make the best use of their environment. This includes making the best use of other survival machines, both of
the same and of different species.

This interpretation of animal aggression as being restrained and formal can be disputed. In particular, it is certainly wrong to condemn poor old Homo Sapiens as the only species to kill his own kind, the only inheritor of the mark of Cain, and similar melodramatic charges.

If only everybody would agree to be a dove, every single individual would benefit. By simple group selection, any group in which all individuals mutually agree to be doves would be far more successful than a rival group sitting at the ESS (Evolutionary Stable Strategy) ratio. Group selection theory would therefore predict a
tendency to evolve towards an all-dove conspiracy. But the trouble with conspiracies, even those that are to everybody's advantage in the long run, is that they are open to abuse. It is true that everybody does better in an all-dove group than he would in an ESS group. But unfortunately, in conspiracies of doves, a single hawk
does so extremely well that nothing could stop the evolution of hawks. The conspiracy is therefore bound to be broken by treachery from within. An ESS is stable, not because it is particularly good for the individuals
participating in it, but simply because it is immune to treachery from within.

But there are other ways in which the interests of individuals from different species conflict very sharply. For instance a lion wants to eat an antelope's body, but the antelope has very different plans for its body. This is not normally regarded as competition for a resource, but logically it is hard to see why not. The resource in
question is meat. The lion genes 'want' the meat as food for their survival machine. The antelope genes want the meat as working muscle and organs for their survival machine. These two uses for the meat are mutually incompatible, therefore there is conflict of interest.

Note: Descriptions of behavior are intended to mean general animal behavior. Human behavior may not be so clear-cut due to cultural influences. See chapters 11 & 13.

opening paragraph:
What is the selfish gene? It is not just one single physical bit of DNA. Just as in the primeval soup, it is all replicas of a particular bit of DNA, distributed throughout the world. If we allow ourselves the licence of talking about genes as if they had conscious aims, always reassuring ourselves that we could translate our sloppy language back into respectable terms if we wanted to, we can ask the question, what is a single selfish
gene trying to do? It is trying to get more numerous in the gene pool. Basically it does this by helping to Program the bodies in which it finds itself to survive and to reproduce. But now we are emphasizing that 'it' is a distributed agency, existing in many different individuals at once. The key point of this chapter is that a gene
might be able to assist replicas of itself that are sitting in other bodies. If so, this would appear as individual altruism but it would be brought about by gene selfishness. it still seems rather implausible.

Are there any plausible ways in which genes might 'recognize' their copies in other individuals.' ? The answer is yes. It is easy to show that close relatives--kin--have a greater than average chance of sharing genes. It has long been clear that this is why altruism by parents towards their young is so common.

To save the life of a relative who is soon going to die of old age has less of an impact on the gene pool of the future than to save the life of an equally close relative who has the bulk of his life ahead of him.

. individuals can be thought of as life-insurance underwriters. An individual can be expected to invest or risk a certain proportion of his own assets in the life of another individual. He takes into account his relatedness to the other individual, and also whether the individual is a 'good risk' in terms of his life expectancy compared
with the insurer's own. Strictly we should say 'reproduction expectancy' rather than 'life expectancy', or to be even more strict, 'general capacity to benefit own genes in the future expectancy'.

Although the parent/child relationship is no closer genetically than the brother/sister relationship, its certainty is greater. It is normally possible to be much more certain who your children are than who your brothers are. And you can be more certain still who you yourself are!

One sometimes hears it said that kin selection is all very well as a theory, but there are few examples of its working in practice. This criticism can only be made by someone who does not understand what kin selection means. The truth is that all examples of child protection and parental care, and all associated bodily organs,
milk secreting glands, kangaroo pouches, and so on, are examples of the working in nature of the kin-selection principle. The critics are of course familiar with the widespread existence of parental care, but they fail to understand that parental care is no less an example of kin selection than brother/sister altruism.

Chapter 7 - Family Planning

It is a simple logical truth that, short of mass emigration into space, with rockets taking off at the rate of several million per second, uncontrolled birth-rates are bound to lead to horribly increased death-rates. It is hard to believe that this simple truth is not understood by those leaders who forbid their followers to use effective contraceptive methods. They express a preference for 'natural' methods of population limitation, and
a natural method is exactly what they are going to get. It is called starvation.

Wild animals almost never die of old age: starvation, disease, or predators catch up with them long before they become really senile. Until recently this was true of man too. Most animals die in childhood, many never get beyond the egg stage.

Individuals who have too many children are penalized, not because the whole population goes extinct, but simply because fewer of their children survive. There is no need for altruistic restraint in the birth-rate, because there is no welfare state in nature. Any gene for overindulgence is promptly punished: the children
containing that gene starve. Contraception is sometimes attacked as 'unnatural'. So it is, very unnatural. The trouble is, so is the welfare state. I think that most of us believe the welfare state is highly desirable. But you cannot have an unnatural welfare state, unless you also have unnatural birthcontrol, otherwise the end result
will be misery even greater than that which obtains in nature.

Chapter 8 - Battle of the Generations

Note: Descriptions of behavior are intended to mean general animal behavior. Human behavior may not be so clear-cut due to cultural influences. See chapters 11 & 13.

I am treating a mother as a machine programmed to do everything in its power to propagate copies of the genes which ride inside it.

Now look at it from the point of view of a particular child. He is just as closely related to each of his brothers and sisters as his mother is to them. The relatedness is 1/2 in all cases. Therefore he 'wants' his mother to invest some of her resources in his brothers and sisters. Genetically speaking, he is just as altruistically disposed to them as his mother is. But again, he is twice as closely related to himself as he is to any brother or
sister, and this will dispose him to want his mother to invest in him more than in any particular brother or sister, other things being equal. . Selfish greed seems to characterize much of child behaviour.

. But they certainly do not lack ruthlessness. For instance, there are honeyguides who, like cuckoos, lay their eggs in the nests of other species. The baby honeyguide is equipped with a sharp, hooked beak. As soon as
he hatches out, while he is still blind, naked, and otherwise helpless, he scythes and slashes his foster brothers
and sisters to death: dead brothers do not compete for food!

The sight ofher child smiling, or the sound ofher kitten purring, is rewarding to a mother, in the same sense as food in the stomach is rewarding to a rat in a maze. But once it becomes true that a sweet smile or a loud purr are rewarding, the child is in a position to use the smile or the purr in order to manipulate the parent, and gain
more than its fair share of parental investment.

Chapter 9 - Battle of the Sexes

Note: Descriptions of behavior are intended to mean general animal behavior. Human behavior may not be so clear-cut due to cultural influences. See chapters 11 & 13.

The strategy of producing equal numbers of sons and daughters is an evolutionary stable strategy, in the sense that any gene for departing fiom it makes a net loss.

Each individual wants as many surviving children as possible. The less he or she is obliged to invest in any one of those children, the more children he or she can have. The obvious way to achieve this desirable state of affairs is to induce your sexual partner to invest more than his or her fair share of resources in each child, leaving you free to have other children with other partners. This would be a desirable strategy for either sex,
but it is more difficult for the female to achieve.

Of course in many species the father does work hard and faithfully at looking after the young. But even so, we must expect that there will normally be some evolutionary pressure on males to invest a little bit less in each child, and to try to have more children by different wives.

By insisting on a long engagement period, a female weeds out casual suitors, and only finally copulates with a male who has proved his qualities of fidelity and perseverance in advance. Feminine coyness is in fact very common among animals, and so are prolonged courtship or engagement periods.

Mine Aysen Doyran
PhD Student
Department of Political Science
SUNY at Albany
Nelson A. Rockefeller College
135 Western Ave. Milne 102
Albany, NY 12222
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Chapter 4 - The gene machine

Survival machines began as passive receptacles for the genes, providing little more than walls to Protect them from the chemical warfare of their rivals and the ravages of accidental molecular bombardment. In the early days they 'fed' on organic molecules freely available in the soup. This easy life came to an end when the organic food in the soup, which had been slowly built up under the energetic influence of centuries of sunlight, was all used up, A major branch of survival machines, now called plants, started to use sunlight directly themselves to build up complex molecules from simple ones, re-enacting at much higher speed the synthetic processes of the original soup.

The evolution of the capacity to simulate seems to have culminated in subjective consciousness. Why this should have happened is, to me, the most profound mystery facing modern biology. There is no reason to suppose that electronic computers are conscious when they simulate, although we have to admit that in the future they may become so. Perhaps consciousness arises when the brain's simulation of the world becomes so complete that it must include a model of itself. . Whatever the philosophical problems raised by consciousness, for the purpose of this story it can be thought of as the culmination of an evolutionary trend towards the emancipation of survival machines as executive decision-takers from their ultimate masters, the genes. Not only are brains in charge of the day-to-day running of survival machine affairs, they have also acquired the ability to predict the future and act accordingly. They even have the power to rebel against the dictates of their genes, for instance in refusing to have as many children as they are able to. But in this respect man is a very special case, as we shall see.

The genes are the master programmers, and they are programming for their lives. They are judged according to the success of their programs in copying with all the hazards that life throws at their survival machines, and the judge is the ruthless judge of the court of survival.

Whenever a system of communication evolves, there is always the danger that some will exploit the system for their own ends. Brought up as we have been on the 'good of the species' view of evolution, we naturally think first of liars and deceivers as belonging to different species: predators, prey, parasites, and so on. However, we must expect lies and deceit, and selfish exploitation of communication to arise whenever the interests of the genes of different individuals diverge. This will include individuals of the same species. As we shall see, we must even expect that children will deceive their parents, that husbands will cheat on wives, and that brother will lie to brother.


Why are people?

The following is an extract from Richard Dawkins’ seminal book, The Selfish Gene. The title of this post is incidentally the name of the first chapter, while the text below is of the second chapter. Brushing such inconsistencies aside, the purpose here is to enjoy this beautiful piece of writing, without preamble or introduction (which hopefully shall come later, I shall be linking to this post often, I hope). The aim is to encourage readers to assimilate the most legible, sound, plausible and obvious theory of creation I have ever read.

In the beginning was simplicity. It is difficult enough explaining how even a simple universe began. I take it as agreed that it would be even harder to explain the sudden springing up, fully armed, of complex order — life, or a being capable of creating life. Darwin’s theory of evolution by natural selection is satisfying because it shows us a way in which simplicity could change into complexity, how unordered atoms could group themselves into ever more complex patterns until they ended up manufacturing people. Darwin provides a solution, the only feasible one so far suggested, to the deep problem of our existence. I will try to explain the great theory in a more general way than is customary, beginning with the time before evolution itself began.

Darwin’s ‘survival of the fittest’ is really a special case of a more general law of survival of the stable. The universe is populated by stable things. A stable thing is a collection of atoms that is permanent enough or common enough to deserve a name. It may be a unique collection of atoms, such as the Matterhorn, that lasts long enough to be worth naming. Or it may be a class of entities, such as rain drops, that come into existence at a sufficiently high rate to deserve a collective name, even if any one of them is short-lived. The things that we see around us, and which we think of as needing explanation — rocks, galaxies, ocean waves — are all, to a greater or lesser extent, stable patterns of atoms. Soap bubbles tend to be spherical because this is a stable configuration for thin films filled with gas. In a spacecraft, water is also stable in spherical globules, but on earth, where there is gravity, the stable surface for standing water is flat and horizontal. Salt crystals tend to be cubes because this is a stable way of packing sodium and chloride ions together. In the sun the simplest atoms of all, hydrogen atoms, are fusing to form helium atoms, because in the conditions that prevail there the helium configuration is more stable. Other even more complex atoms are being formed in stars all over the universe, ever since soon after the ‘big bang’ which, according to the prevailing theory, initiated the universe. This is originally where the elements on our world came from.

Sometimes when atoms meet they link up together in chemical reaction to form molecules, which may be more or less stable. Such molecules can be very large. A crystal such as a diamond can be regarded as a single molecule, a proverbially stable one in this case, but also a very simple one since its internal atomic structure is endlessly repeated. In modern living organisms there are other large molecules which are highly complex, and their complexity shows itself on several levels. The haemoglobin of our blood is a typical protein molecule. It is built up from chains of smaller molecules, amino acids, each containing a few dozen atoms arranged in a precise pattern. In the haemoglobin molecule there are 574 amino acid molecules. These are arranged in four chains, which twist around each other to form a globular three-dimensional structure of bewildering complexity. A model of a haemoglobin molecule looks rather like a dense thorn bush. But unlike a real thorn bush it is not a haphazard approximate pattern but a definite invariant structure, identically repeated, with not a twig nor a twist out of place, over six thousand million million million times in an average human body. The precise thorn bush shape of a protein molecule such as haemoglobin is stable in the sense that two chains consisting of the same sequences of amino acids will tend, like two springs, to come to rest in exactly the same three-dimensional coiled pattern. Haemoglobin thorn bushes are springing into their ‘preferred’ shape in your body at a rate of about four hundred million million per second, and others are being destroyed at the same rate.

Haemoglobin is a modern molecule, used to illustrate the principle that atoms tend to fall into stable patterns. The point that is relevant here is that, before the coming of life on earth, some rudimentary evolution of molecules could have occurred by ordinary processes of physics and chemistry. There is no need to think of design or purpose or directedness. If a group of atoms in the presence of energy falls into a stable pattern it will tend to stay that way. The earliest form of natural selection was simply a selection of stable forms and a rejection of unstable ones. There is no mystery about this. It had to happen by definition.

From this, of course, it does not follow that you can explain the existence of entities as complex as man by exactly the same principles on their own. It is no good taking the right number of atoms and shaking them together with some external energy till they happen to fall into the right pattern, and out drops Adam! You may make a molecule consisting of a few dozen atoms like that, but a man consists of over a thousand million million million million atoms. To try to make a man, you would have to work at your biochemical cocktail-shaker for a period so long that the entire age of the universe would seem like an eye-blink, and even then you would not succeed. This is where Darwin’s theory, in its most general form, comes to the rescue. Darwin’s theory takes over from where the story of the slow building up of molecules leaves off.

The account of the origin of life that I shall give is necessarily speculative by definition, nobody was around to see what happened. There are a number of rival theories, but they all have certain features in common. The simplified account I shall give is probably not too far from the truth.

We do not know what chemical raw materials were abundant on earth before the coming of life, but among the plausible possibilities are water, carbon dioxide, methane, and ammonia: all simple compounds known to be present on at least some of the other planets in our solar system. Chemists have tried to imitate the chemical conditions of the young earth. They have put these simple substances in a flask and supplied a source of energy such as ultraviolet light or electric sparks — artificial simulation of primordial lightning. After a few weeks of this, something interesting is usually found inside the flask: a weak brown soup containing a large number of molecules more complex than the ones originally put in. In particular, amino acids have been found — the building blocks of proteins, one of the two great classes of biological molecules. Before these experiments were done, naturally-occurring amino acids would have been thought of as diagnostic of the presence of life. If they had been detected on, say Mars, life on that planet would have seemed a near certainty. Now, however, their existence need imply only the presence of a few simple gases in the atmosphere and some volcanoes, sunlight, or thundery weather. More recently, laboratory simulations of the chemical conditions of earth before the coming of life have yielded organic substances called purines and pyrimidines. These are building blocks of the genetic molecule, DNA itself.

Processes analogous to these must have given rise to the ‘primeval soup’ which biologists and chemists believe constituted the seas some three to four thousand million years ago. The organic substances became locally concentrated, perhaps in drying scum round the shores, or in tiny suspended droplets. Under the further influence of energy such as ultraviolet light from the sun, they combined into larger molecules. Nowadays large organic molecules would not last long enough to be noticed: they would be quickly absorbed and broken down by bacteria or other living creatures. But bacteria and the rest of us are latecomers, and in those days large organic molecules could drift unmolested through the thickening broth.

At some point a particularly remarkable molecule was formed by accident. We will call it the Replicator. It may not necessarily have been the biggest or the most complex molecule around, but it had the extraordinary property of being able to create copies of itself. This may seem a very unlikely sort of accident to happen. So it was. It was exceedingly improbable. In the lifetime of a man, things that are that improbable can be treated for practical purposes as impossible. That is why you will never win a big prize on the football pools. But in our human estimates of what is probable and what is not, we are not used to dealing in hundreds of millions of years. If you filled in pools coupons every week for a hundred million years you would very likely win several jackpots.

Actually a molecule that makes copies of itself is not as difficult to imagine as it seems at first, and it only had to arise once. Think of the replicator as a mould or template. Imagine it as a large molecule consisting of a complex chain of various sorts of building block molecules. The small building blocks were abundantly available in the soup surrounding the replicator. Now suppose that each building block has an affinity for its own kind. Then whenever a building block from out in the soup lands up next to a part of the replicator for which it has an affinity, it will tend to stick there. The building blocks that attach themselves in this way will automatically be arranged in a sequence that mimics that of the replicator itself. It is easy then to think of them joining up to form a stable chain just as in the formation of the original replicator. This process could continue as a progressive stacking up, layer upon layer. This is how crystals are formed. On the other hand, the two chains might split apart, in which case we have two replicators, each of which can go on to make further copies.

A more complex possibility is that each building block has affinity not for its own kind, but reciprocally for one particular other kind. Then the replicator would act as a template not for an identical copy, but for a kind of ‘negative’, which would in its turn remake an exact copy of the original positive. For our purposes it does not matter whether the original replication process was positive-negative or positive-positive, though it is worth remarking that the modern equivalents of the first replicator, the DNA molecules, use positive-negative replication. What does matter is that suddenly a new kind of ‘stability’ came into the world. Previously it is probable that no particular kind of complex molecule was very abundant in the soup, because each was dependent on building blocks happening to fall by luck into a particular stable configuration. As soon as the replicator was born it must have spread its copies rapidly throughout the seas, until the smaller building block molecules became a scarce resource, and other larger molecules were formed more and more rarely.

So we seem to arrive at a large population of identical replicas. But now we must mention an important property of any copying process: it is not perfect. Mistakes will happen. I hope there are no misprints in this book, but if you look carefully you may find one or two. They will probably not seriously distort the meaning of the sentences, because they will be ‘first generation’ errors. But imagine the days before printing, when books such as the Gospels were copied by hand. All scribes, however careful, are bound to make a few errors, and some are not above a little wilful ‘improvement’. If they all copied from a single master original, meaning would not be greatly perverted. But let copies be made from other copies, which in their turn were made from other copies, and errors will start to become cumulative and serious. We tend to regard erratic copying as a bad thing, and in the case of human documents it is hard to think of examples where errors can be described as improvements. I suppose the scholars of the Septuagint could at least be said to have started something big when they mistranslated the Hebrew word for ‘young woman’ into the Greek word for ‘virgin’, coming up with the prophecy: ‘Behold a virgin shall conceive and bear a son . . .’ Anyway, as we shall see, erratic copying in biological replicators can in a real sense give rise to improvement, and it was essential for the progressive evolution of life that some errors were made. We do not know how accurately the original replicator molecules made their copies. Their modern descendants, the DNA molecules, are astonishingly faithful compared with the most high-fidelity human copying process, but even they occasionally make mistakes, and it is ultimately these mistakes that make evolution possible. Probably the original replicators were far more erratic, but in any case we may be sure that mistakes were made, and these mistakes were cumulative.

As mis-copyings were made and propagated, the primeval soup became filled by a population not of identical replicas, but of several varieties of replicating molecules, all ‘descended’ from the same ancestor. Would some varieties have been more numerous than others? Almost certainly yes. Some varieties would have been inherently more stable than others. Certain molecules, once formed, would be less likely than others to break up again. These types would become relatively numerous in the soup, not only as a direct logical consequence of their ‘longevity’, but also because they would have a long time available for making copies of themselves. Replicators of high longevity would therefore tend to become more numerous and, other things being equal, there would have been an ‘evolutionary trend’ towards greater longevity in the population of molecules.

But other things were probably not equal, and another property of a replicator variety that must have had even more importance in spreading it through the population was speed of replication or ‘fecundity’. If replicator molecules of type A make copies of themselves on average once a week while those of type B make copies of themselves once an hour, it is not difficult to see that pretty soon type A molecules are going to be far outnumbered, even if they ‘live’ much longer than B molecules. There would therefore probably have been an ‘evolutionary trend’ towards higher ‘fecundity’ of molecules in the soup. A third characteristic of replicator molecules which would have been positively selected is accuracy of replication. If molecules of type X and type Y last the same length of time and replicate at the same rate, but X makes a mistake on average every tenth replication while Y makes a mistake only every hundredth replication, Y will obviously become more numerous. The X contingent in the population loses not only the errant ‘children’ themselves, but also all their descendants, actual or potential.

If you already know something about evolution, you may find something slightly paradoxical about the last point. Can we reconcile the idea that copying errors are an essential prerequisite for evolution to occur, with the statement that natural selection favours high copying-fidelity? The answer is that although evolution may seem, in some vague sense, a ‘good thing’, especially since we are the product of it, nothing actually ‘wants’ to evolve. Evolution is something that happens, willy-nilly, in spite of all the efforts of the replicators (and nowadays of the genes) to prevent it happening. Jacques Monod made this point very well in his Herbert Spencer lecture, after wryly remarking: ‘Another curious aspect of the theory of evolution is that everybody thinks he understands it!

To return to the primeval soup, it must have become populated by stable varieties of molecule stable in that either the individual molecules lasted a long time, or they replicated rapidly, or they replicated accurately. Evolutionary trends toward these three kinds of stability took place in the following sense: if you had sampled the soup at two different times, the later sample would have contained a higher proportion of varieties with high longevity/fecundity/copying-fidelity. This is essentially what a biologist means by evolution when he is speaking of living creatures, and the mechanism is the same — natural selection.

Should we then call the original replicator molecules ‘living’? Who cares? I might say to you ‘Darwin was the greatest man who has ever lived’, and you might say ‘No, Newton was’, but I hope we would not prolong the argument. The point is that no conclusion of substance would be affected whichever way our argument was resolved. The facts of the lives and achievements of Newton and Darwin remain totally unchanged whether we label them ‘great’ or not. Similarly, the story of the replicator molecules probably happened something like the way I am telling it, regardless of whether we choose to call them ‘living’. Human suffering has been caused because too many of us cannot grasp that words are only tools for our use, and that the mere presence in the dictionary of a word like ‘living’ does not mean it necessarily has to refer to something definite in the real world. Whether we call the early replicators living or not, they were the ancestors of life they were our founding fathers.

The next important link in the argument, one that Darwin himself laid stress on (although he was talking about animals and plants, not molecules) is competition. The primeval soup was not capable of supporting an infinite number of replicator molecules. For one thing, the earth’s size is finite, but other limiting factors must also have been important. In our picture of the replicator acting as a template or mould, we supposed it to be bathed in a soup rich in the small building block molecules necessary to make copies. But when the replicators became numerous, building blocks must have been used up at such a rate that they became a scarce and precious resource. Different varieties or strains of replicator must have competed for them. We have considered the factors that would have increased the numbers of favoured kinds of replicator. We can now see that less-favoured varieties must actually have become less numerous because of competition, and ultimately many of their lines must have gone extinct. There was a struggle for existence among replicator varieties. They did not know they were struggling, or worry about it the struggle was conducted without any hard feelings, indeed without feelings of any kind. But they were struggling, in the sense that any mis-copying that resulted in a new higher level of stability, or a new way of reducing the stability of rivals, was automatically preserved and multiplied. The process of improvement was cumulative. Ways of increasing stability and of decreasing rivals’ stability became more elaborate and more efficient. Some of them may even have ‘discovered’ how to break up molecules of rival varieties chemically, and to use the building blocks so released for making their own copies. These proto-carnivores simultaneously obtained food and removed competing rivals. Other replicators perhaps discovered how to protect themselves, either chemically, or by building a physical wall of protein around themselves. This may have been how the first living cells appeared. Replicators began not merely to exist, but to construct for themselves containers, vehicles for their continued existence. The replicators that survived were the ones that built survival machines for themselves to live in. The first survival machines probably consisted of nothing more than a protective coat. But making a living got steadily harder as new rivals arose with better and more effective survival machines. Survival machines got bigger and more elaborate, and the process was cumulative and progressive.

Was there to be any end to the gradual improvement in the techniques and artifices used by the replicators to ensure their own continuation in the world? There would be plenty of time for improvement. What weird engines of self-preservation would the millennia bring forth? Four thousand million years on, what was to be the fate of the ancient replicators? They did not die out, for they are past masters of the survival arts. But do not look for them floating loose in the sea they gave up that cavalier freedom long ago. Now they swarm in huge colonies, safe inside gigantic lumbering robots, sealed off from the outside world, communicating with it by tortuous <20>indirect routes, manipulating it by remote control. They are in you and in me they created us, body and mind and their preservation is the ultimate rationale for our existence. They have come a long way, those replicators. Now they go by the name of genes, and we are their survival machines.


Culture and Memes Theme Analysis

Dawkins argues that even though humans are simply “survival machines” that house genes, there is still something that makes humans different from all the other types of “survival machines” that contain genes (such as flowers, seagulls, or elephants). The difference is that there are two kinds of evolution going on in the case of humans. One kind of evolution is the same as in every other living thing on earth, and it’s the evolution of genes. But the second kind of evolution that happens when humans are in the picture is the evolution that happens to bits of human culture. This cultural evolution is what makes humans “exceptional.”

Language, for example evolves over time, as made clear by the fact that it’s harder to understand “English” written by the 14th century writer Geoffrey Chaucer than it is to understand “English” words that a modern writer might use. In this argument about cultural evolution, ideas, or “ memes ”—meaning ideas that spread easily from one person to another—are the things “replicating.” Dawkins argues that these ideas—or memes—are, in a sense, “copied” from one person’s mind to another, but sometimes slightly imperfectly. Dawkins writes: “Examples of memes are tunes, ideas, catch-phrases, clothes fashions, ways of making pots or of building arches. Just as genes propagate themselves in the gene pool by leaping from body to body via sperms or eggs, so memes propagate themselves in the meme pool by leaping from brain to brain via a process which, in the broad sense, can be called imitation.” For example, if a scientist hears a good theory, they will talk about it with their students, write about it in their academic papers, and discuss it with their colleagues. The “copies” of the meme that arise (in students’ minds, in people’s minds who read academic papers, and in colleagues’ minds) can then be shared with other minds. If an imperfect copy of the original meme is more memorable, or has a stronger “psychological appeal,” then that variant of the meme is the one that will survive to be shared with another mind.

Like genes, memes live much longer than people do. This is why ideas that Socrates thought about some two thousand years ago are still going strong. One difference between memes and genes, however, is that memes replicate much faster than genes do. In fact, it would take millions of years to observe the same amount of evolution in genes that a mere century of cultural evolution can expose. Dawkins argues this cultural kind of evolution (and its speed) provides a viable avenue to facilitate altruistic behavior in humans: not through biology, but through the spread of the idea—or meme—of altruism. “Our genes may be selfish” Dawkins writes, “but we are not necessarily compelled to obey them all our lives.”

Ultimately, since humans are compelled by our thinking—our ideas—as well as our biology, the story of the evolution on humanity is incomplete without both. In other words, humans should not feel bad that, biologically, we are merely “ survival machines ” for genes, because there is something that makes humans “exceptional.” That thing is humanity’s capacity to generate rapidly evolving ideas (or memes). This is what enables us—unlike other organisms—to extend beyond the blind programming of our genes, and choose to behave in ways we are not genetically programmed to.


Evolutionarily Stable Strategies and Behavior

Evolutionary biologists imagine a time before a particular trait emerges. Then, they postulate that a rare gene arises in an individual, and they ask what circumstances would favor the spread of that gene throughout the population. If natural selection favors the gene, then the individuals with the genotypes incorporating that particular gene will have increased fitness. A gene must compete with other genes in the gene pool, and resist any invasion from mutants, to become established in a population’s gene pool.

In considering evolutionary strategies that influence behavior, we visualize a situation in which changes in genotype lead to changes in behavior. By ‘the gene for sibling care’ we mean that genetic differences exist in the population such that some individuals aid their siblings while others do not. Similarly, by ‘dove strategy’ we mean that animals exist in the population that do not engage in fights and that they pass this trait from one generation to the next.

At first sight, it might seem that the most successful evolutionary strategy will invariably spread throughout the population and, eventually, will supplant all others. While this does occur, it is far from always being so. Sometimes, there is no single dominant strategy. Competing strategies may be interdependent in that the success of one depends upon the existence of the other and the frequency with which the population adopts the other. For example, the strategy of mimicry has no value if the warning strategy of the model is not efficient.

Game theory belongs to mathematics and economics, and it studies situations where players choose different actions in an attempt to maximize their returns. It is a good model for evolutionary biologists to approach situations in which various decision makers interact. The payoffs in biological simulations correspond to fitness—comparable to money in economics. Simulations focus on achieving a balance that evolutionary strategies would maintain. The Evolutionarily Stable Strategy (ESS), introduced by John Maynard Smith in 1973 (and published in 1982), is the most well known of these strategies. Maynard Smith used the hawk-dove simulation to analyze fighting and territorial behavior. Together with Harper in 2003, he employed an ESS to explain the emergence of animal communication.

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An evolutionarily stable strategy (ESS) is a strategy that no other feasible alternative can better, given that sufficient members of the population adopt it. The best strategy for an individual depends upon the strategy or strategies that other members of the same population adopt. Since the same applies to all individuals in that particular population, a mutant gene cannot invade an ESS successfully.

The traditional way to illustrate this problem is by simulating the encounter between two strategies, hawk and dove. When a hawk meets a hawk, it wins on half of the occasions, and it loses and suffers an injury on the other half. Hawks always beat doves. Doves always retreat against hawks. Whenever a dove meets another dove, there is always a display, and it wins on half of the occasions. Under these rules, populations of only hawks or doves are no ESS because a hawk can invade a population made up entirely of doves, and a dove can invade a population of hawks only. Both would have an advantage and would spread in the population. A hawk in a population of doves would win all contests, and a dove in a population of hawks would never get injured because it wouldn’t fight.

However, it is possible for a mixture of hawks and doves to provide a stable situation when their numbers reach a certain proportion of the total population. For example, with payoffs as winner +50, injury -100, loser 0, display -10, a population comprising hawks and doves (or individuals adopting a mixed strategy of alternating between playing hawk and dove strategies) is an ESS whenever 58,3% of the population are hawks and 41,7% doves or when all individuals behave at random as hawks in 58,3% of the encounters and doves in 41,7%. The percentages (the point of equilibrium) depend on costs and benefits (or the pay-off, which is equal to benefits minus costs).

Evolutionarily stable strategies are not artificial constructs. They exist in nature. The Oryx, Oryx gazella, have sharp pointed horns, which they never use in contests with rivals, except in a ritualised manner, and only in defense against predators. They play the dove strategy. They hawk strategy is rarely seen in nature except when competing for mating partners. However, up to 10% per year of Musk Ox, Ovibos moschatus, adult males die because of injuries sustained while fighting over females.

An ESS is a modified form of a Nash equilibrium. In most simple games, the ESSes and Nash equilibria coincide perfectly, but some games may have Nash equilibria that are not ESSes. Furthermore, even if a game has pure strategy Nash equilibria, it might be that none of those pure strategies are ESSes. We can prove both Nash equilibria and ESS mathematically (see references).

Peer-to-peer file sharing is a good example of an ESS in our modern society. Bit Torrent peers use Tit-for-Tat strategy to optimize their download speed. They achieve cooperation exchanging upload bandwidth with download bandwidth.

Evolutionary biology and sociobiology attempt to explain animal behavior and social structures (humans included), primarily in terms of evolutionarily stable strategies.

References

  • Brockmann, H. J. and Dawkins, R. (1979). Joint nesting in a digger wasp as an evolutionarily stable preadaptation to social life.Behaviour 71, 203-245.
  • Hines, W.G.S. (1982b), Mutations, perturbations and evolutionarily stable strategies, J. Appl. Probab. 19, 204–209. https://doi.org/10.2307/3213929.
  • McFarland, D. (1999). Animal Behavior. Pearson Prentice Hall, England. 3rd ed. ISBN-10: 0582327326.
  • Maynard Smith, J. (1972). Game Theory and The Evolution of Fighting. On Evolution. Edinburgh University Press. ISBN0-85224-223-9.
  • Maynard Smith, J. and Price, G.R. (1973). The logic of animal conflict. Nature. 246 (5427): 15–18. doi:10.1038/246015a0. S2CID4224989.
  • Maynard Smith, J. (1982). Evolution and the Theory of Games. ISBN0-521-28884-3.
  • Maynard Smith, J. and Harper, D. (2003) Animal Signals. Oxford Series in Ecology and Evolution. ISBN: 9780198526858
  • Møller A.P. (1993). Developmental stability, sexual selection, and the evolution of secondary sexual characters. Etologia3:199—208. ISBN : 978-3-0348-9813-3
  • Nash, J. F. (May 1950). Non-Cooperative Games (PDF). PhD thesis. Princeton University. Retrieved May 24, 2015 .
  • Parker, G.A. (1984) Evolutionarily Stable Strategies. In Krebs, J.R. and Davis, N.B. (eds), Behavioral Ecology , 2nd ed. Blackwell Scientific Pub., Oxford.
  • Reynolds, P. (1998). Dynamics and Range Expansion of a Reestablished Muskox Population. The Journal of Wildlife Management,62(2), 734-744. doi:10.2307/3802350.
  • Walther F.R. (1980). Aggressive behavior of oryx antelope at water-holes in the Etosha National Park. Madoqua11:271-302.

Featured image: The traditional way to illustrate Evolutionarily Stable Strategies is the simulation of the encounter between two strategies, the hawk and the dove.

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The Selfish Gene | Richard Dawkins | Book Summary

Over 3.5 billion years ago, in a primordial soup of molecules, the first, simplest form of life on earth came to be: a molecule able to copy itself, a replicator.

Molecular replicators are made up of long chains of smaller building-block molecules in the same way that a word is made up of a string of letters. Replicators copy themselves by attracting other ‘letters’ and acting as a template for them to match up to.

The first replicator automatically had a competitive advantage over all the other molecules in the primordial soup because they could not copy themselves, and hence the replicator became more numerous than any other type of molecule.

However, mistakes in the copying process led to ‘daughter’ replicators that had a slightly different configuration than their ‘parent.’ These new configurations meant that some ‘daughters’ were able to copy themselves faster, or more accurately, giving them a competitive advantage over their ‘parent.’

More and more replicators were built from the finite supply of building-block molecules in the primordial soup, and these molecules were gradually used up.

These two concepts – a population in which ability varies and an environment of limited resources – are the basic requirements for the process we know as evolution.

As time went on, further mistakes in copying resulted in new advantageous characteristics, such as the capacity to break down other replicators and use their building blocks for replication: the first carnivores. Through the creation of new variations, and the survival of the replicators with the most useful advantages, more complex life forms emerged, eventually resulting in the variety of organisms we see today.

Evolution is driven by varying abilities and limited resources.

The Selfish Gene Key Idea #1: The basic unit of evolution is the gene, because it can exist as multiple copies and is therefore near-immortal.

Evolution occurs through differential survival: in a given population of entities with differing abilities, some survive and propagate while others die out.

But contrary to what is often thought, the basic units that evolution acts on are not individual organisms but genes: short snippets of DNA, the replicator molecule that is the basis of all life on Earth.

The reason for this is that genes fulfill an important criterion that evades individual organisms: genes are not unique and can exist as copies in many different bodies. For example, all blue-eyed people have in their cells a copy of the gene for blue eyes.

Most organisms, on the other hand, cannot replicate themselves as identical copies. This is because sexual reproduction does not produce copies but rather combines the parents’ genetic makeup to create new, unique individuals.

The fact that genes exist as copies makes them near-immortal. While individual organisms tend to survive for no more than a few decades, genes can live for thousands or even millions of years. Consider that while your ancestors are long dead, you no doubt carry plenty of their genes in your cells and will in turn pass on at least some of them to your descendants.

It is the genes’ multiplicity and potential for immortality that makes them candidates for evolution to act upon.

The basic unit of evolution is the gene, because it can exist as multiple copies and is therefore near-immortal.

The Selfish Gene Key Idea #2: Genes are selfish by definition

A gene is ‘selfish’: it acts in a way that promotes its own survival at the expense of other competing entities. However, genes themselves have no conscious motives it is simply their behavior that we can describe as seemingly selfish. Similarly, while the process of evolution could appear to be motivated towards creating entities that are suited to particular environments, it is not consciously trying to achieve this.

To understand why genes seem selfish, we must examine the physical environment they exist in: Genes come in packages called chromosomes, which are sheltered within the cells that make up an organism. Chromosomes come in pairs: humans have 23 pairs (46 chromosomes in total). Both chromosomes in a pair have the same organizational structure, so if an area on one chromosome houses the gene for eye color, then the other chromosome will have a gene for eye color in the same location. However, the versions of these genes may not be the same: one might be for blue eyes and the other for brown. Different versions of genes for the same characteristic are called alleles for example, there are several alleles of the eye-color gene.

Because the different alleles try to occupy exactly the same spot on a chromosome, any survival advantage an allele gains is automatically selfish: it decreases the survival prospects of the other alleles.

Genes are selfish by definition: their survival success comes at the expense of other genes.

The Selfish Gene Key Idea #3: A gene’s phenotype – the way its code is manifested in its environment – determines its survival.

Physically, all genes are fairly similar: they are all snippets of DNA. Where they differ is the information they encode.

DNA is basically a long molecular chain constructed of four types of molecules denoted by the letters A, T, C and G. Just as every word in the English language can be constructed from the 26 letters in the alphabet, these four basic building blocks can be combined into so many different and elaborate DNA sequences as to describe every feature of an organism.

This code is translated into the instructions for how to build an organism’s body. Small differences in the code are expressed as characteristics like longer legs, a survival advantage for, for example, an antelope running away from a cheetah. The long-legged antelope escapes and lives to bear offspring with copies of the gene – the code – for longleggedness. Thus, the gene survives through its effect on the body of the antelope. This bodily manifestation of the gene is known as its phenotype.

However, the effects of genes are not necessarily limited to the body they belong to. Virus genes don’t have their own bodies: their codes affect the cells of the body they infect for example, they can cause the host body to sneeze, which helps the virus to spread and thus enables its genes to survive.

A gene’s phenotype – the way its code is manifested in its environment – determines its survival.

The Selfish Gene Key Idea #4: The survival success of a gene is dependent on its particular environment – both physical and genetic.

Good camouflage for a tiger is very bad camouflage for a polar bear, because of the fundamentally different environments. A gene for tiger camouflage would have minimal chances of surviving in an icy environment.

Genes are not just affected by their physical environment but also by the genes around them: all the variations (alleles) of a species’ genes in the same gene pool. This includes both the specialized genes that only certain species have, like genes for building wings or carnivorous teeth, and the shared genes that different species have in common.

The success or failure of a gene – no matter how useful – depends largely on what other genes share its gene pool. For example, if a gene for sharp carnivore teeth was introduced to the gene pool of a herbivorous species, it would most likely not be successful since the pool lacks other genes necessary for a carnivore to survive, such as a gene that allows the species to actually digest meat.

On an individual level, sexual reproduction entails the constant mixing of genes, so every individual of a species ends up with a unique set of alleles. Some allele combinations prove more advantageous than others. Consider a bird species in which there is an allele that increases wingspan and another that lengthens tail feathers. An individual bird with both alleles will fly faster, while a bird with only one of these alleles may be unbalanced and fly more slowly. In this case, each allele is only successful in the presence of the other.

The survival success of a gene is dependent on its particular environment – both physical and genetic.

The Selfish Gene Key Idea #5: Organisms are machines built by groups of genes that cooperate only because they share a reproductive mechanism.

A gene affects a characteristic of the organism it belongs to – e.g. its speed, strength or camouflage. When this effect is advantageous, the organism is more likely to produce offspring that carry copies of the gene, and thus the gene survives.

However, one gene alone can’t build an organism. It requires tens of thousands of genes all working together to construct something as complex as a human body. But if genes are fundamentally selfish, then why would they cooperate in this manner?

The answer is that the genes within a single organism share a reproductive mechanism and hence have a common goal: they are all trying to maximize the production and survival prospects of the organism’s eggs or sperm. By the same token, although a parasite like a tapeworm inhabits the host’s body, the tapeworm’s genes do not cooperate with the host genes, because they do not share a reproductive mechanism.

The cooperation of genes manifests itself as a complete organism: the sum of their collected phenotypes. The genes basically build a machine – the organism – around themselves, and this machine produces offspring who carry copies of those same genes, thus helping them survive.

While genes within an organism cooperate to ensure their survival, we should not expect individual organisms within a group to cooperate with each other, because their genes do not share a single common pathway of reproduction. Rather, under the direction of its genes, each individual should work towards the production and survival of its own eggs or sperm and should therefore act selfishly towards other individuals in its group. This, however, is not always the case, as we will see later on when examining the phenomenon of altruism.

Organisms are machines built by groups of genes that cooperate only because they share a reproductive mechanism.

The Selfish Gene Key Idea #6: Genes program the brains they build with behavioral strategies that help their survival.

It can take generations for one gene’s phenotype – for example, longer legs – to prove more successful than another. However, to survive, the bodies that genes build need to be able to react much faster to environmental stimuli – to eat, fight or flee in mere seconds. To facilitate this, genes build brains that allow organisms to respond to rapidly changing factors in their environment. We call these reactions “behavior.”

The natural environment can present an infinite number of different situations, so there is no way for an organism to have a prepared response to each one. Instead, behavioral responses are guided by ‘rules,’ which are encoded by the genes in a way that is analogous to how a computer is programmed. For example, two such rules could be for an organism to regard sweet-tasting things as rewarding and to repeat actions that lead to this reward.

The problem with such rule-based programming is that it cannot always adapt to radical environmental changes. An attraction to sweet-tasting things was a survival aid for early hunter-gatherer humans but is a driver of the obesity epidemic in today’s calorie-loaded world.

Intelligent organisms can minimize the negative impact of such outdated rules with two strategies: learning and simulation. Learning means trying an action to find out if it’s a good idea, and then remembering the outcome simulation means modeling the outcome of an action before taking it, which not only saves effort but also helps avoid potentially dangerous actions. For example, an organism that knows beforehand that jumping off a cliff is a bad idea has a survival advantage over an organism that must try it to find out.

Genes program the brains they build with behavioral strategies that help their survival.

The Selfish Gene Key Idea #7: Competition between strategies results in a stable behavioral pattern in a population.

Members of the same species are in direct competition with each other for resources, which can be expected to lead to confrontations between individuals. These confrontations can be dealt with via different behavioral strategies, ranging from fleeing to fighting to the death.

Behavioral strategies, like any other characteristic of an organism, can be expected to vary, and some are going to be better for the survival of the organism – and its genes – than others. In the same way that the success of a gene is determined by its environment, the success of an organism’s behavioral strategy is determined by how all the other organisms around it behave.

For example, take a population of birds with three behavioral approaches to confrontations:

  1. “Doves,” which flee if attacked
  2. “Hawks,” which always attack and fight until severely wounded
  3. “Retaliators,” which behave as Doves until attacked, after which they respond as Hawks.

In a population of Doves, an invading Hawk is very successful because no Dove stands up to it. Thus, Hawk genes increase in the population. However, when the population has become predominantly Hawks, the proportion of Doves begins to increase, because Hawks are more frequently injured in ferocious fighting with other Hawks, which are now abundant in the population. Neither the Hawk nor Dove is an evolutionarily stable strategy, because a population of either could be successfully invaded by the other.

Retaliators, on the other hand, aren’t injured through unnecessary aggression, but they do defend themselves if necessary (unlike the Dove). Therefore, in a population of Retaliators, neither Hawks nor Doves would be successful the Retaliator’s strategy is evolutionarily stable.

Competition between strategies results in a stable behavioral pattern in a population.

The Selfish Gene Key Idea #8: The selfish survival drive of genes explains apparently altruistic behavior like parental care.

As pointed out earlier, because genes control behavior, and genes are selfish, then we can expect organisms within a group to behave selfishly toward each other.

However, there are many examples of behaviors in nature that appear altruistic, not least of which are the many examples of extremely devoted parental care, such as a mother bird feigning a broken wing to lead a fox away from her young. Altruism here can be defined as behaving in a way that reduces one’s own chances of survival for another’s benefit.

This apparent contradiction disappears when considered in the light of one of the basic characteristics of genes: they exist as multiple copies in multiple organisms. Thus, genes program behaviors that benefit their copies in other organisms, even at the expense of their own organism – but only if it produces a greater overall survival benefit to the gene.

How does a gene ‘know’ that another organism is carrying copies of its genes? It doesn’t: genes aren’t conscious and don’t ‘know’ anything. But organisms that are kin do share copies of genes. Hence, genes that program organisms to aid their kin gain a survival advantage, and thus lead those behaviors to survive, too.

Altruism is not necessarily reciprocated equally, though. Parents and children are equally closely related, but parents behave with greater altruism towards their children than vice versa. This is because in order for their genes to survive beyond one generation, the parents must ensure their children survive to reproductive age. For the children, on the other hand, the survival and well-being of their parents is far less relevant, hence the asymmetry in altruistic behavior.

The selfish survival drive of genes explains apparently altruistic behavior like parental care.

The Selfish Gene Key Idea #9: Mutually altruistic behaviors are often successful, because they benefit the host’s genes more than purely selfish behaviors do.

When characterizing interactions between organisms, a useful principle is the idea of the zero-sum or non-zero-sum ‘game.’ Basically, a zero-sum situation is one where one side wins and the other loses for example, in the case of a cheetah chasing an antelope, either the antelope dies or the cheetah starves.

In contrast, a non-zero-sum game is one where both ‘sides’ are playing against a ‘bank’ that holds the resources. One player winning does not mean the other has to lose. The players can stab each other in the back to gain a bigger share of the bank’s resources, but, depending on the rules, they can also cooperate to outwit it.

In nature, organisms generally compete for resources in their environments. Although there are many situations where the competition is a zero-sum game, such as in the case of the cheetah and the antelope, in other cases it can pay for the organisms to cooperate, either with members of their own species or even with other species.

For example, ants “milk” insects called aphids for the sweet secretions they produce. The aphids might appear to be exploited in this arrangement, but in fact they gain significant protection from predation by having battle-ready ants around to protect them. Sometimes ants even raise and protect baby aphids inside anthills. Therefore, this cooperation benefits the survival of both ant genes and aphid genes. The end result – an increase in survival – satisfies a selfish motive, but the pathway to it is mutual altruism.

Mutually altruistic behaviors are often successful, because they benefit the host’s genes more than purely selfish behaviors do.

The Selfish Gene Key Idea #10: Human culture is also subject to evolution, and its basic unit is the meme.

One of the most distinctive traits of humans is culture: the aspects of our lives that are neither instinctive nor purely have to do with survival, for example, language, dress, diet, ceremonies, customs and art. Although basic human psychology and interests can probably be traced to the survival benefits of mutual altruism and aiding kin, these aren’t enough to explain the complexity and variety of culture.

Instead, culture can be considered the equivalent of a gene pool, with the basic unit of cultural evolution being a meme instead of a gene. A meme is the smallest piece of culture with potential immortality, for example, a tune, an idea or a YouTube clip of a dancing cat. The methods of transmission are the methods of human communication: speech, writing, the Internet.

Like genes, memes are in competition with one another. Some are in direct opposition – for example, evolutionary theory and creationism –, but all compete for human attention and memory. In the same way that genes cooperate to form complex organisms, memes also form complex entities: the Catholic Church is an aggregation of ideas, rituals, clothing and architecture around the central meme of an omnipotent God.

Separating culture from biology helps explain some of humanity’s more peculiar expressions, such as celibacy, which goes counter to biological imperatives. If culture is its own evolutionary system with its own replicators, then those replicators need only survive within that system. They aren’t necessarily influenced by factors outside of the meme pool, such as biological survival. As with their gene equivalents, the success of memes is determined by their environment – from which we can conclude that the Internet is a supportive environment for clips of dancing cats!

Human culture is also subject to evolution, and its basic unit is the meme.

The Selfish Gene Key Idea #11: Conscious human foresight can help us overcome the downsides of biological gene selfishness.

Models of behavioral strategies show that populations tend to end up with a stable strategy, and that populations engaging in a mutually altruistic strategy tend to do well, even though each individual is motivated by the best interests of their genes.

But in some cases an even more optimal solution for all can be reached by forgoing the immediate survival interests of the genes. Consider a population in which there are two species with two different confrontation strategies: the Hawks, who always attack in confrontations and will fight until death or serious injury and the Doves, who run away if attacked. Hawks will always win against individual Doves, but in the long run their strategy is actually less beneficial due to the injuries they sustain from fighting other Hawks. The solution that most benefits all the individuals is the ‘conspiracy of Doves,’ where all individuals in a population agree to be Doves, forgoing the short-term benefits of behaving like a Hawk in order to reap the long-term benefits of living peacefully and avoiding serious injury and death.

Genes are not conscious and do not have foresight, so they will never be able to partake in a conspiracy of Doves, even if it would be in their best interests in the end.

Humans, on the other hand, are capable of conscious foresight. Our culture, if thought of in terms of memes, has already divorced itself from biological imperatives. We may not be genetically or intrinsically altruistic, but we can use our foresight to counter gene selfishness and, at the very least, to enter into the conspiracy of Doves for our own future benefit. We may even be able to attain the true altruism that does not exist in nature.

Conscious human foresight can help us overcome the downsides of biological gene selfishness.

In Review: The Selfish Gene Book Summary

The key message in this book is:

Evolution occurs through the action of natural selection on genes, not on individuals or species. Genes are selfish by definition in that genes that promote their own survival at the expense of other genes tend to be more successful. All animal behaviors can be traced to selfishness on the part of their genes.

The questions this book answered:

In this summary of The Selfish Gene by Richard Dawkins, and how are genes central to this?

  • Evolution is driven by varying abilities and limited resources.
  • The basic unit of evolution is the gene, because it can exist as multiple copies and is therefore near-immortal.
  • Genes are selfish by definition: their survival success comes at the expense of other genes.
  • A gene’s phenotype – the way its code is manifested in its environment – determines its survival.
  • The survival success of a gene is dependent on its particular environment – both physical and genetic.

How does selfishness at the level of the gene influence behavior at the level of the organism?

  • Organisms are machines built by groups of genes that cooperate only because they share a reproductive mechanism.
  • Genes program the brains they build with behavioral strategies that help their survival.
  • Competition between strategies results in a stable behavioral pattern in a population.
  • Mutually altruistic behaviors are often successful, because they benefit the host’s genes more than purely selfish behaviors do.

What application does this theory have for human behavior and cultural development?


Postneodarwinistic Theories of Evolution - From the Selfish Gene to Frozen Evolution - PowerPoint PPT Presentation

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The Selfish Gene

This chapter is devoted to debunking the idea that animals regulate the size of their families for the good of the species and to prevent over population. He says instead that animals regulate the size of the children born in order to maximize the number of children successfully reared. If the mother spreads her resources too thin amongst her children then less may survive then if she'd had less children.
He claim there is simply no need for group population control because there is no welfare state in nature (I knew he'd talk about welfare states.) If the mother has to many children it won't hurt the species by leading to over population, they'll simply starve to death. A mother will have less children if she knows the population has large numbers not for the good of the group but because she realizes she and her children will be competing for fewer resources so she "optimizes" her litter amount.
He argues the reason why humanity suffers from such extreme over population is because we have departed from nature's model. If a woman has too many children the state will feed and care for the children instead of allowing them to starve as they would in nature. Of course, over population will eventually lead to the trimming down of the species through starvation, we're simply delaying the process.

Chapter 6 Genesmanship

Chapter 5 Agression: Stability and the Selfish Machine

Chapter 4 The Gene Machine

In which Dawkin's explains the psychology of a puppet

Dawkin's definition of behavior is a little different from any I've heard before. He explains it as "the trick of rapid movement largely exploited by the animal branch of survival machines." I understand that Dawkin's is trying to shake us up with his unique definitions, and I'm all for breaking things down into simpler forms to enhance understanding, but to me this seems a little too simplified. First of all, is behavior only movement? Isn't laying perfectly still also behavior? Or maybe that trully doesn't exist because the body is moving rapidly, transporting nutrients, beating the heart, all the minor movements that make life possible. Is behavior only possible from animals? Don't plants behave? They grow towards sunlight, they transport nutrients, isn't this movement and behavior? Is it not behavior for plants because they don't have a conscious mind directing them? Cockroaches don't have conscious mind and he's still classifying their movement as behavior. For me this definition seems to raise far more questions then its worth.
Dawkin's theorizes that the brain was developed by the genes in order to control muscle movements and interpret sensory information because if the genes tried to directly control the "survival machine" the time lag would be too great to function. While its undeniably true that the main function of the brain is to control the muscles and react to stimulus I don't know if its even possible to prove why the genes don't control these things themselves. There could be a million reasons why genes don't take control of these functions. They may simply be incapable or a gene capable of doing it may simple have not evolved yet. It seems like pointless posturing to try and guess the why here.
The genes extremely simplistic "programming" of our brains has some interesting consequences. Yes, you can get a rush from a job well done, an orgasm with a mate, a healthy meal, or exercise. This is how the genes enforce our survival. There are a lot of people that want to skip the middle man however. Why go for that jog? Why not just inject yourself with heroin? Do you not get the same end result? In fact, in Dawkins term you could say that the heroin addict is living no less of a fulfilling life then a "normal", "sane" person so long as they're able to reproduce. So why should we jump through the hurdles that our genes create for us in order to benefit from our pre-programmed rewards? If the executive decision maker has grown to be independent of the genes why not rejoice in that independence by telling our genes to get stuffed and rewarding ourselves with ingested chemicals? Life that exists solely to propagate its genes is extremely rewarding to the genes and entirely futile to the organism. Who is more the slave, the heroin addict or the puppet of the genes?
Dawkin's also theorizes that for as long as there has been communication there have been entities that exploit that communication. This is part of a larger point that any system will be exploited as the temptation to not exploit it will be impossible to resist.


Watch the video: 5 3 Αλληλόμορφα (August 2022).