The Selfish Gene shows that all forms of life on Earth begin with genes, and that the purpose of life is to make sure those genes survive. While many biologists would say that the purpose of life is to survive and reproduce at the organismal level, Dawkins argues that there are things that the organismal approach can’t explain, such as the prevalence of sexual reproduction when it leads to offspring that are substantially different from the parents. Therefore, it makes more sense to look at life from the perspective of a selfish gene doing anything it can to reproduce itself because, outside of random mutations, genes pass from one generation to the next unchanged.
Any form of life anywhere in the universe must begin with some type of replicating molecule. That molecule first arises by chance, as atoms randomly bump into each other in some primordial soup. Once formed, however, that replicator quickly copies itself and spreads throughout its environment. Copying itself is that molecule’s only purpose.
Sooner or later, the environment runs out of freely available resources, and then the molecules will have to compete. Those that can’t effectively replicate themselves will be squeezed out of the population, while those that can undergo various mutations during the copying process. Some of those mutations, by pure chance, are helpful, and the molecules carrying them replicate more effectively than others. New mutations build on top of old ones to create ever-more effective and elaborate vehicles to carry those replicators. On Earth, those replicators became DNA and evolution led to the complex organisms we have today.
Genes are like a blueprint for the bodies they create and inhabit. Genes can’t control their bodies directly, so they create structures like the brain and muscles to coordinate and execute all of the many processes required for life.
However, for all of the complex structures and systems they give rise to, genes are still replicator molecules doing whatever they can to keep replicating and survive through the generations. This is the meaning of “selfish gene,” and the reason all biology should be considered from the perspective of genes, not individuals.
While the driving force behind biology may be genes attempting to replicate, in modern times many must do so through the behaviors of their hosts. Behavior is how scientists describe specific actions that creatures take. A behavior is something quick and definite, so only animals can really be said to have them—some plants do move, but not in a fast or purposeful way.
Selfish behaviors in nature are easy to explain: Animals would naturally be expected to behave in ways that benefit themselves at the expense of others, given that the purpose of life is to survive and reproduce. However, altruistic behavior—helping others at cost to oneself—seems counterintuitive.
One possible explanation for altruistic behavior is group selection: the idea that natural selection acts on groups of creatures, rather than on the individual level. While the commonly accepted theory today is that individuals compete for the ability to reproduce, group selection says that animals will instinctively act for the good of their local population, or even their entire species. If true, it would make altruistic behavior very easy to explain; risking oneself to help others of one’s species would then be the default, not the exception.
However, group selection is a fatally flawed theory. There are many ways to rebut it, but the simplest is to recognize that a population of altruistic individuals can be easily exploited by a selfish one. The selfish individual will accept all the help that other members of the population offer, while taking on no risks or costs to itself. Therefore, a selfish individual in an altruistic population will inevitably be more successful than the average creature in that population.
That selfish creature would quickly spread its genes—and therefore its selfishness—until a large portion of the population turns selfish. In other words, the individual will succeed at the expense of the group, and therefore group selection can’t be true.
The other explanation for altruistic behavior is gene selection. The key to understanding gene selection is recognizing that close relatives, by definition, share many of the same genes. For example, in a typical mammal that reproduces sexually, an individual’s offspring and siblings will both have 50% of its genes. However, there’s no way for a gene to actively recognize itself in another organism, so it has to play the odds. If another organism carries 50% of the same genes, then there’s a 50% chance that it carries a copy of the gene in question.
Therefore, from the perspective of a selfish gene, siblings and offspring should be considered 50% as valuable as the organism that gene happens to be in. So, to give an extreme example, if an organism could save more than two of its siblings or children by sacrificing its own life, selfish gene theory dictates that it should do so. Genes don’t need one particular organism to survive, as long as organisms likely to be carrying them are able to keep reproducing.
Since genes themselves aren’t living organisms, it may be confusing to talk about their “survival”; substituting the word “stability” might help to clarify the matter. By definition, something that’s unstable—whether it’s a single molecule or a population of animals—will keep changing until it finds a stable form. For primordial molecules, this happens by chance; atoms randomly bump into each other until they happen to land in a form that sticks.
In animal populations, it’s a lot more complex. As we’ve discussed, a population of altruistic animals could be easily overtaken by selfish individuals, and therefore can’t be considered stable. Similarly, a population of all selfish animals will be unstable because it’ll fight against itself, inevitably growing weaker until it’s overwhelmed by other types of individuals.
However, there is a ratio of selfish to altruistic animals where the population will be stable. This is called the Evolutionarily Stable Strategy (ESS). In reality, there are countless details that go into forming an ESS, not just altruism and selfishness, but this simplified version will do.
Any deviation from the ESS will be punished: If too many selfish animals emerge, they will compete against and weaken each other until the balance is restored. If too many altruistic animals enter the population, they will be exploited by the selfish ones until that ideal ratio is reached again. The best situation for a selfish gene is a balanced population that will allow it to keep reproducing itself indefinitely—which is to say, the ESS.
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.
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.
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.
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.
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.
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.
The Selfish Gene is a long essay arguing that biology should be considered from the perspective of individual genes, not entire organisms. Dawkins points out flaws in the organism-centric biology of his day and proposes that many of the apparent paradoxes in nature could be explained by genes, rather than creatures, trying to replicate themselves.
One major paradox is the prevalence of sexual reproduction in nature. If, as Dawkins argues, the main purpose of life is to replicate itself, then sexual reproduction doesn’t make much sense. The offspring produced by sexual reproduction will be inherently different from their parents, so it’s not really a form of replication at all. This apparent contradiction is explored in Chapter 3.
Most of the essay, but especially Chapters 5, 8, and 9, explore competition in nature and how it leads to evolution. Genes that survive at the expense of others will naturally reproduce more effectively and come to outnumber the less successful ones. In Chapters 5 and 12, we’ll also dip into game theory, the mathematical study of decision-making, to help explain some of the more complex behaviors that animals exhibit.
The Selfish Gene ends with the rather surprising proposal that we should stretch our concept of the impact that genes have beyond individual creatures, and consider the world at large. For example, a beaver dam could be considered an effect of those beavers’ genes. So, overall, the essay aims to start from a microscopic level (genes) and expand readers’ concepts of biology beyond the usual macro level (organisms).
The purpose of life is one of the greatest philosophical questions in the world, but the answer is quite simple: The purpose of life is to replicate itself. In biological terms, selfish and altruistic acts only refer to whether they will help a creature achieve that purpose, or help others to achieve it at some cost to the creature performing the act. There’s no relation to the more common definitions of the words, which are based on psychology rather than biology.
Selfishness and altruism both have roots in biology and evolution. Several famous and influential books, such as Robert Ardrey’s The Social Contract and Konrad Lorenz’s On Aggression, have already explored selfishness and altruism in nature. However, those books are fatally flawed because the authors misunderstood the point of evolution. Ardrey, Lorenz, and others thought that evolution existed for the good of the entire species. However, the common belief among biologists today is that evolution is about the survival of the individual.
(Shortform note: The terminology is a bit confusing here, since evolution works on the population level and not the individual level. However, as a population evolves, each individual in it has a better chance to survive and pass on its genes.)
“The good of the species” is a common misconception. It comes about because most of an animal’s life is devoted to reproduction, and most of the selfless acts an animal performs are for its offspring. Therefore, it seems like creatures act as they do in order to continue the species.
Furthermore, by slightly twisting Darwin’s theory of evolution, a logical—but wrong—conclusion can be drawn: If only the fittest animals survive and reproduce, that strengthens the species as a whole. Thus everything creatures do, including competing with each other, has the ultimate goal of continuing the species. This is the theory of group selection.
However, group selection can’t be right because of a simple truth of nature: Even in altruistic groups, selfish individuals will have an advantage. They’ll outcompete the altruistic ones, and reproduce until the population is overrun with selfish individuals. If left unchecked, this would eventually cause the whole population to collapse.
Actually, the spread of selfish individuals probably wouldn’t get that far; as we’ll explain later with the concept of Evolutionarily Stable Strategies, the population would eventually reach an equilibrium where further shifts toward selfishness or altruism would be disadvantageous, so they’d naturally balance themselves out.
However, the point is that creatures’ ultimate goal can’t be the survival of the species as a whole, or such selfish behaviors wouldn’t exist in nature. The truth is that nature is fiercely competitive, with members of the same population having to fight each other for limited resources—and, therefore, for survival. This is called natural selection: Organisms who are fit enough to survive and reproduce in their environments will be the ones to pass on their genes to the next generation.
In summary, while continuing the species may be a consequence of competition and reproduction, it’s not why animals do those things.
All behaviors in nature lead back to genes trying to copy themselves. Selfishness and altruism can both be explained by animals acting to protect either themselves or their relatives (who will, by definition, share many of their genes).
Note that, due to countless variables, it’s impossible to say exactly what effect a behavior will have on a creature’s long-term chance of survival. Therefore, all of the examples throughout this essay are presented with what we assume the effects of those actions will be.
Emperor penguins demonstrate selfish behavior when they push each other into the water to check for predators before diving in themselves. Meanwhile, bees demonstrate altruistic behavior when they sting to defend their hives—while they may drive off creatures that would have eaten the hive’s food source, the honey, the bees themselves often die in the process.
However, selfishness and altruism aren’t always immediate life-or-death acts. For example, a bird that gives an alarm call upon seeing a predator is being altruistic, because the bird might draw that predator’s attention to itself. It’s a relatively small risk compared to that of a bee stinging an intruder, but it still counts as altruism.
For all the earlier talk of creatures reproducing, it must be understood that the gene is the unit of inheritance—not the creature, species, or population. Therefore, creatures’ selfishness and altruism are both rooted in gene selfishness.
Animals, including humans, are essentially organic machines built by genes, and genes are designed to survive and reproduce. Genes are selfish—not consciously, of course, but those that still exist have out-competed countless other genes. This is ultimately selfish behavior—that is, behavior that benefits the individual at the expense of others.
Genes also show their selfishness because of the fact that altruism toward outside groups is rare, and toward different species is almost unheard of. For example, a human killing another human is one of the worst crimes possible, but we kill animals every day for food, in self-defense, or simply for sport.
Humans are something of a special case when it comes to selfishness and altruism. Unlike other animals, we can be taught altruism and be convinced to go against our basic selfish nature—although to exactly what extent is part of the ongoing nature vs. nurture debate.
Everything that we observe in the universe, from genes to organisms to populations, is stable: either long-lived enough or common enough that we think it deserves a name. For example, atoms will naturally arrange themselves in stable configurations because, by definition, anything unstable will keep changing until it’s stable. This is why salt crystals tend to be cubical: Cubes are a stable way to stick a lot of chloride and sodium together.
Everything from the simplest molecules to the first organisms was created by that same simple process: Unstable things just kept shifting around until they became stable. In fact, that could be seen as the first type of natural selection: Nature continually rejecting unstable forms until stable ones emerged.
At some point in the very, very distant past, a molecule that had the ability to replicate itself happened to form. It’s extremely unlikely for such a “replicator” molecule to appear but, when dealing with timeframes of hundreds of millions of years, what humans would consider unlikely is almost bound to happen at some point.
With its only competition being molecules created from atoms that happened to bump together in the right ways, this replicator molecule would have spread extremely quickly (relatively speaking) through the primordial soup of the time. Eventually, though, all the materials that make that molecule would have been used up, which would seem to leave us stuck in a sea of identical molecules with nowhere to go from there.
The reason that didn’t happen is that replication isn’t perfect. Small mistakes can happen. Then, when imperfect copies are made from other imperfect copies, the mistakes add up until you have something completely different from the original. With the massive amounts of time involved in Earth’s early history, it was almost inevitable that such mistakes would happen and build on top of each other.
Some of these molecules were more “successful” than others—that is, they lasted longer, or replicated more quickly or more accurately. The more successful molecules would naturally start to outnumber the less successful ones.
Since there was not an infinite amount of material to create new molecules, eventually they would have started competing for it. Molecules that were better able to replicate themselves, or prevent competitors from replicating themselves, would become more numerous while those that were out-competed would decline. This would have been the first instance of competition and evolution.
The mechanisms that these molecules created (still purely by chance) became more and more complex as new changes built on top of previous successes. In fact, this was likely how the first cells formed: Some molecules created protective shells of protein around themselves, which continued to grow bigger and more elaborate as time went on. By this point, the molecules that could continue to exist and replicate were the ones that created complex mechanisms—relatively speaking—to protect themselves.
Now, billions of years later, those first replicators have evolved into every form of life we know today. Consider this: A human is nothing but a highly complex and stable survival mechanism for those ancient replicator molecules.
(Shortform note: As you read, it’s worth keeping in mind that evolution, genes, and so forth aren’t conscious entities and therefore can’t “seek” or “want” anything. A gene doesn’t want to replicate itself, nor does it actively look for the most efficient way to do so. Replicating is just what genes do.)
In this chapter, we’ll explore what genes are, how they’re formed, how they reproduce, and why all of that has such an impact on how organisms behave.
To start at a basic level, the replicator that all complex life forms host is DNA. DNA is a nucleic acid, a polymer made up of many molecules called nucleotides. There are only four types of nucleotides in DNA: adenine (A), cytosine (C), guanine (G) and thymine (T). Those nucleotides are identical no matter what kind of creature has them: You’ve got the same four nucleotides as your pet cat, or the birds outside. The only difference between different species is how those nucleotides are arranged. To a much lesser extent, they are also arranged differently between different people (except for identical twins).
Those nucleotides are then organized into genes. The genes are like blueprints for proteins, which are used for everything from creating tissue to regulating chemical processes. It’s a complex process to go from nucleotide to protein, but in simple terms, DNA is like a building plan for a living creature.
Whether a gene survives depends on whether the organism it helped create is able to survive and reproduce. How quickly “bad” genes die out depends on how strong the selection is—that is, how much of a disadvantage that gene will be.
In relatively safe environments, even disadvantageous genes can persist for many generations. For example, genes for albinism in humans have survived because, while they can cause serious health problems, the people carrying them don’t die in our current environment.
There are a number of factors that affect how long a given gene lasts, even if the creature does successfully reproduce. These are detailed in the next subsection. Theoretically, a gene could replicate itself through countless generations and “survive” indefinitely.
In short, it could be said that genes are responsible for their own reproductive success. Going one step further, it could be argued that replication is the very purpose of genes, dating back to those first primordial replicators.
If genes truly exist to replicate themselves, it would seem like sexual reproduction isn’t the best way to do it. Sexual reproduction takes a great deal of time and resources and, most significantly, only allows each parent to pass on half of their genes. This apparent paradox leads many people back to the group-focused idea of evolution, wherein the good of the species is the ultimate goal.
However, if there are individual genes that do well in an environment of sexual reproduction (such as genes for qualities that help attract mates), that in itself could explain why sex exists and resolve the paradox. Therefore, from the viewpoint of a selfish gene, sexual reproduction may make sense after all.
Furthermore, the diversity gained from sexual reproduction is favorable enough that it has become prominent in nature. Remember the primordial atoms, randomly bumping into each other and combining until one molecule happened to be more successful than the others? This demonstrates that the more diversity there is, the more chances there are that something will succeed.
During sexual reproduction, chromosomes (collections of genes) can swap parts with each other to give rise to new combinations of genes, different from anything found in the parent. This is called crossing over. This process means that a sperm or egg cell contains a mosaic of that creature’s parents’ genes, rather than just direct copies of their chromosomes. Crossing over is a key method of increasing diversity in a population.
The other main mechanism for diversity is mutation, which can happen in various ways. Point mutation is when a single nucleotide is swapped for another due to a replication error. Inversion is when a piece of a gene detaches, becomes completely flipped around, and reattaches backwards. Sometimes, though rarely, it can even reattach in a completely different place.
Many mutations have no effect or are harmless, but some are devastating. For example, cystic fibrosis in humans is the result of a mutation. Sometimes, by pure chance, a mutation will be beneficial. For example, perhaps a muscle gets changed in a way that makes it slightly stronger or more efficient. Those mutations tend to pass themselves on and become part of the gene pool.
Smaller genes have fewer nucleotides, and therefore fewer chances to mutate. Since genes that mutate are no longer the same genes, it could be said that smaller genes have an evolutionary advantage over large ones—that is, they will survive through more generations.
Sexual reproduction is complicated for many reasons, not least because it, too, seems to contradict the selfish gene theory.
Some people believe that a gene-centric view of evolution is misguided because it’s the individuals—and all the thousands of genes they contain—that live or die, not the genes themselves. These people argue that biology should be examined at the individual level, not the gene level.
It’s true that, unlike primordial replicators, genes no longer succeed or fail on their own. An organism has thousands of genes contributing to its genetic makeup. Those genes overlap and interact in such complex ways that it would seem more reasonable to refer to them as a collective, like a gene network or something along those lines—in other words, an individual organism.
In fact, that would make sense for everything except sexual reproduction, which gives rise to distinctly different organisms. However, while sexual reproduction rearranges genes, it doesn’t normally change them (there are a couple of exceptions to this, which we’ll get to shortly). Therefore, it’s an effective way for individual genes to survive through multiple generations.
Further complicating the process, at least in humans, is the fact that we have two versions of each gene. Human genes are arranged into 23 chromosomes, but we have two copies of each chromosome—one from each parent (except for X and Y chromosomes in males).
While each gene from each parent codes for the same type of trait, like eye color, the trait itself may be different, such as having brown vs. blue eyes. Different versions of genes that code for the same type of trait are called alleles. Conflicting alleles may result in one being dominant over the other, or in both being expressed to some extent in the organism.
All of these apparent complications can be resolved with a simple comparison: Just as a successful sports team needs to be made of strong players, a successful individual needs to be made of strong genes: genes that enable that creature to survive and reproduce.
At the genetic level, altruism must be bad and selfishness must be good. Alleles (different versions of the same gene, such as for blue vs. brown eyes) are in direct competition with each other. Therefore, by definition, alleles that succeed at the expense of others will tend to survive.
However, when it comes to genes that are not alleles to one another, the way they interact is extremely complicated. For example, there’s no single gene for “long legs.” Rather, there are many, and each of them has some sort of influence on leg length. In an environment where long legs are beneficial, all of the alleles which contribute to that trait will be favored by natural selection.
This isn’t an absolute truth—favorable alleles can still fail if they’re in an organism with other disadvantages, or simply due to bad luck. However, in the long term, the frequency of a given gene in the population is (usually) directly proportional to how beneficial that gene is—that’s how evolution works.
There are very few genetic qualities that are objectively good or bad. For example, an herbivore with a gene for sharp, pointed teeth would be at a disadvantage, since such teeth aren’t as effective at tearing and grinding plant matter. A carnivore with that same gene would be much more successful. Most advantages and disadvantages are environmental. For a gene, the environment is other genes—such as what kind of animal a gene for sharp teeth is in.
Keep all of this in mind when considering altruistic or selfish behaviors in an individual. The ultimate question is what effect those behaviors will have, in the long term, on the frequencies of certain genes in the population.
In this chapter, we'll discuss how both our genes and our consciousness affect our behavior. First, we’ll explore how genes prompt the behaviors that are the most likely to lead to an animal’s survival. Then, we’ll look at how animals, most notably humans, have developed the ability to work against some of these genetically programmed behaviors and pursue our own desires.
Evolution is ultimately driven by need. For example, when the “food” molecules of the early primordial soup were used up, the things inhabiting it needed new energy sources in order to survive.
Some organisms were able to use the energy from sunlight to build the molecules they needed to survive. These would become plants. Other types, which would become animals, were able to get energy from eating the plants or other animals.
As the environment became more competitive, survival mechanisms became more complex by necessity. Therefore, genes that allowed cooperation and centralized control within the body would have been favored over those that allowed mechanisms to work independently. In modern organisms the systems work so well together that they’re seen as a single being, rather than a collection of genes and their survival mechanisms.
There’s a case to be made either way—individual organism or colony of genes that are each themselves alive—but the difference is an academic one. For all practical purposes, a modern survival system functions as a single individual. Treating one as a collection of genes would be like talking in terms of protons and electrons while discussing how a car works.
Therefore, for convenience’s sake, “behavior” will refer to actions taken by one complete organism toward another.
Behavior, as defined by biologists, happens quickly. A behavior is a single action that can be observed. Therefore, plants can’t be said to have behaviors. Animals, on the other hand, undertake many behaviors every day. They have evolved to do this by developing muscles, which can move quickly and repeatedly by using chemical fuel.
One might question, if the body is really just a complex survival machine for genes, why they don’t control it directly. However, they can’t do that because the lag would be much too great. As mentioned in Chapter 3, genes code for proteins. By the time those proteins were made and incorporated into the body, whatever stimulus they were responding to would be long over.
Therefore, muscle movements are controlled and coordinated by the brain, which is like the processing unit of a computer. Like a computer, the brain interprets complex inputs and determines the appropriate responses.
The movements are then timed by neurons, or nerve cells, which control and transmit signals a bit like transistors do in electronics. Neurons are specialized cells with long, thin projections that carry signals. There is often a long central projection called an axon, which bundles with other axons to form nerves. (Shortform note: The Selfish Gene uses the older spelling “neurone,” but it refers to the same thing.)
One of the most notable things about animal behavior is that it seems purposeful—that is, the behaviors aren’t just programmed responses designed to aid survival, there seem to be desires or emotions behind them. In humans, those desires and emotions have evolved into what we call consciousness.
There’s no way of knowing whether non-human animals or man-made machines experience something similar to consciousness, but for the purposes of this book, it’s convenient to talk about animals and machines behaving as if they’re driven by some purpose. Whether they’re actually conscious like humans are is immaterial; the behaviors are what matter.
Like programming a computer, genes code general guidelines and patterns into the creature that carries them, and the brain then determines how best to carry out those instructions. The gene “programming” is gambling on what kind of situations the animal is likely to run into, and how to minimize risk.
For example, an animal who needs to use a watering hole might reduce risk by waiting until it’s extremely thirsty, then taking a single long drink to last for a while. That lowers the number of trips it has to take, but it increases how long it’s helpless with its head down in the water. Alternatively, maybe it would be better to snatch quick drinks many times throughout the day. The genes determine the best gamble based on many generations’ worth of natural selection.
Note that this programming doesn’t take every conceivable situation into account. For example, humans are programmed to enjoy sweet tastes because sugar is necessary for survival. However, that programming hasn’t adapted to our modern world of artificial sweeteners and excessive sugar consumption.
Because simple input-output programming isn’t always enough to cope with the real world, many animals have the ability to learn. They’re coded to recognize desirable things such as pleasant tastes and comfortable temperatures, as well as undesirable things like nausea and extreme temperatures.
These animals learn what behaviors lead to pleasant things, and will repeat those behaviors. They will also avoid behaviors that have led to unpleasant things before. In short, learning is the process of using past experiences to predict the future.
One excellent method of predicting the future is simulation. Just trying everything to see what works could be disastrous—imagine if an animal tried walking straight past a predator to see what would happen. Simulation allows for low-stakes trials of what could happen in certain situations.
In living creatures, simulation takes the form of imagination. By imagining what might happen in a variety of situations, humans (and possibly other advanced animals) can skip time-consuming trials and costly errors. The imagined situations will never match reality perfectly, but they’re much better than blind guesses.
This ability to imagine and predict seems to have resulted in what we recognize as consciousness, though exactly how that happened is one of the biggest mysteries in biology. It may have something to do with creatures coming up with simulations that recognize and involve the creatures themselves—in other words, self-awareness.
However it came about, this self-awareness could be seen as the liberation of an organism from the control of its genes. For example, genes demand that a creature have as many offspring as is feasible, but a creature with self-awareness and imagination might come up with reasons not to reproduce at all. This is especially prevalent in humans—many people choose not to have children.
All this talk of brains and consciousness is background, so you understand that animal behaviors are controlled by genes only in an indirect—though still very real—way. As brains became more advanced, developing imagination and what we might call consciousness, they took more and more control away from the genes.
Taking this process to the extreme, it’s possible that at some point in the distant future, the only genetic command hardwired into a species will be survival. All of the behaviors to accomplish it will be purely up to the brain.
In this chapter, we’ll explore different behavioral styles in animals. It seems logical that strong, aggressive animals will have an advantage in nature, and therefore all animals should selfishly try to take as many resources as they can for themselves. However, that isn’t always true.
A population of animals actually needs a particular balance of aggression and pacifism in order to be stable—too many aggressive (selfish) individuals will constantly fight each other, and too many peaceful individuals will be easily overpowered and exploited by a few aggressive ones. A stable population is the best situation for selfish genes trying to survive through as many generations as possible, without being overwhelmed by other types of animals.
Animals will naturally compete with one another—there are only so many resources to go around, so only a limited number of genes’ hosts can reproduce. Members of different species may compete for various things—for instance, blackbirds and moles might compete for earthworms—but members of the same species will be in much more direct competition. This is because they tend to live in the same environment and need the same things, including food sources and mates.
Given that fact, it seems logical that the best way to preserve one’s own genes is to kill—and possibly eat—your rivals. However, while murder and cannibalism do happen in nature, it’s not as common as an uninitiated observer might think.
The problem is that fighting has great costs associated with its potential benefits. First of all, fighting takes a great deal of energy that might be better spent looking for food or breeding. It also naturally carries the risk that you’ll wind up dead or maimed instead of your rival. A less direct, but still very real risk, is that by eliminating one rival you accidentally help another who was also competing with the individual you killed.
Therefore, before animals fight in earnest, they have to somehow weigh the risk against the benefits. Fighting another member of one’s own species is extremely risky, since they’re likely to have similar physical abilities. In fact, animals of the same species usually “fight” in a way that’s comparable to boxing or fencing: There are rules, it’s clear when the bout is over and who won it, and (barring an accident) neither party gets seriously hurt.
(Shortform note: Game theory is the study of strategic decision-making through mathematical models.)
Populations of animals will naturally tend toward an Evolutionarily Stable Strategy, or ESS. The ESS of a population is the most stable possible configuration of members; by definition, any member of the population who doesn’t conform to the ESS will not be as successful as others.
For example, imagine that a hypothetical species has two possible strategies when confronted with a rival: Fight or bluff. Furthermore, imagine that each member of that species engages in only one of those behaviors—the same one every time without fail.
If two fighters meet, they will fight until one is severely injured or killed. If a fighter meets a bluffer, the bluffer will run and the fighter will win without suffering injuries. If two bluffers meet, they will engage in a drawn-out contest until one backs down.
We can apply Game Theory to find the ESS for this species by assigning arbitrary point values to the outcomes. Let’s say that being injured is -100 points, wasting time on a lengthy contest is -10 points, and winning a contest (whether fighting or bluffing) is worth +50 points. In a more realistic model the numbers would be based on a huge number of factors, but this arbitrary setup will do as an example.
At a glance, it would seem that the ESS is for every member of the species to be a bluffer. Each contest between two bluffers, or peaceful individuals, would then result in each member losing 10 points due to wasting time; however, the winner would also gain 50 points, for a total gain of 40. Neither one would suffer the penalty for being injured, because such a contest wouldn’t turn to violence.
Assuming that each creature has a 50/50 chance of winning any given contest, all members of the species would gain an average of 15 points per contest—50 points for winning one, minus 20 for the cost of engaging in two contests, divided by two. This is the best possible outcome for the entire population.
(Shortform note: For a real-world example of a bluffing contest, think about two dogs meeting: They may stare each other down, bare their teeth, and growl, but it would be very unusual for them to immediately start fighting. Each is trying to get the other to back down.)
However, this all-bluffing strategy could only work if evolution existed for the good of the species, rather than the individual. This is because a single selfish individual could easily take advantage of the situation.
In a population of bluffers, a single fighter would win the full 50 points for every contest it participates in, making it vastly more successful than its bluffing counterparts. Plus, it would only be a matter of time before a mutant or deviant member of the population became a fighter and began spreading that strategy through its offspring. Therefore, while having everyone be a bluffer is the best strategy, it is not the stable strategy.
Having every member be a fighter would also be highly unstable, because every member of the population would lose an average of 25 points per contest. Assume again that each creature has a 50/50 chance of winning a fight. Then, in two fights you could expect it to win one (+50 points) and lose one (-100 points for being injured). -50 points across two fights averages out to -25 per fight.
Right now it might seem like there isn’t a stable strategy; that the population is bound to oscillate between bluffers and fighters as the situation keeps changing. However, this hypothetical species can reach an equilibrium.
After doing a lot of math, it turns out that the ideal composition for this arbitrary population is a 5:7 ratio of bluffers to fighters. The average gain from a contest in that population is 6.25 for fighters and bluffers alike. While that’s clearly much lower than the 15 average in a population of all bluffers, the population will be stable.
If, by chance, the number of fighters starts to increase, they will encounter and injure each other more often, so the bluffers will gain an advantage until equilibrium is restored. Similarly, if the number of bluffers happens to increase, fighters will gain an advantage until the population is back to that 5:7 ratio.
The model works equally well if we assume that—instead of being a pure fighter or pure bluffer—every member of the population can act as either. As long as they perform those behaviors in the same 5:7 ratio, the population will be just as stable.
The previous model assumes that there are only two possible strategies, but in reality there are several others besides pure fighting and pure bluffing. For instance, a bully will act like a fighter unless the target fights back, in which case it runs like a bluffer. A retaliator is just the opposite—it acts like a bluffer unless it’s attacked, in which case it will fight back. A prober-retaliator usually acts like a retaliator, but will occasionally try to escalate the fight to see if its target runs. These are called conditional strategies: Strategies that depend on what the other creature does.
Interestingly, retaliation is the only strategy that, by itself, leads to a stable population. If two retaliators engage in a contest, it won’t escalate to a real fight. However, if a fighter emerges in a population of retaliators, it won’t be successful because every target will fight back. Prober-retaliator is almost, but not quite, as stable as true retaliation, simply because it leads to fights and injuries slightly more often.
The retaliator strategy explains why so many animals engage in contests that aren’t true fights—they bluff unless their opponent tries to escalate to a real fight, in which case they fight back.
There are other factors besides simple strategy that can determine whether a creature will attack or retreat. A few important ones are the animal’s size, age, and strength compared to its opponent.
However, one of the most notable factors in nature is territory. A strategy where creatures aggressively protect their own territory, and run away if they invade another’s territory, is quite common in nature. This by itself could be an ESS (Evolutionarily Stable Strategy)—if all members of the population stick to it, contests will rarely (if ever) result in injury or wasted time.
The opposite strategy—resident retreats, intruder attacks—would also be stable if the whole population followed it, but this is much rarer in nature. There are obvious flaws with that strategy. For example, it has residents constantly running and shifting territories, which is an enormous waste of time and energy.
Biologists often wonder what advantage there is to territorial behavior, since it runs the risk of injuring both the resident and the intruder. However, in light of ESS, this may be the wrong question to ask; perhaps animals simply defend their territory because that’s the ESS that has arisen.
The ESS is one more example of how genes that work well within their environment tend to be favored by natural selection. This is just as important, if not more so, than whether those genes are individually “better” than their rival alleles.
Now we’ll explore how and why animals show altruistic behaviors, especially toward their family members. Genes don’t just act to protect the individual they’re inside of. We know this because animals frequently help their offspring and relatives, even at risk to themselves. This makes sense if we consider a “selfish gene” to be all copies of that gene across the entire population. Then we can assume that individuals will act to protect other individuals who are likely to have the same gene.
This perceived likelihood could come from a physical characteristic that the gene gives. For example, if there were a gene for purple hair, you might expect one purple-haired person to act altruistically toward another. However, the odds of a single gene providing both “purple hair” and “altruism toward purple hair” characteristics are astronomical—remember that genes aren’t conscious, and can’t choose what effects they have on their hosts. Granted, it’s possible that those two genes might tend to be inherited together, as they provide a mutually beneficial environment.
However, a much easier way for genes to “recognize” themselves in others is through family relations. By definition, close family members will share a lot of the same genes. While it would be very unlikely for a gene to code both for a trait and for altruism toward that same trait, a gene that codes for altruism toward relatives would be successful all on its own.
Therefore, it should be expected that animals will be altruistic to their family—the more closely related they are, the more altruistic they’ll be. Assuming sexual reproduction, an animal’s offspring will share half of its genes. A sibling will, on average, also share half of the same genes.
Therefore, from a purely logical standpoint, an animal should consider its child or sibling to be worth half as much as its own life, in terms of preserving genes. That value will go down with more distant relatives. For example, a grandchild will only have 1/4 of the animal’s genes, so should only be valued at 1/4 of the creature’s life. You could calculate the “relatedness” of any animal to another by creating a family tree, and counting how many branches you have to move up and down the tree to get from one to the other.
If g is the number of branches traveled, the relatedness would be (1/2)g
That equation assumes only one common ancestor. If there are more, multiply the result by the number of common ancestors in the most recent generation that has them.
Naturally, the previous section raises the question of how animals recognize their relatives—or even whether they do. It’s possible that some animals recognize each other simply by appearance, and act altruistically toward animals that resemble them. Others might act altruistically toward any member of their species that happens to be nearby. In that case, we could assume that the odds of any given member of the species being a relative are good enough to make the altruism worth the risk. These behaviors arose due to common situations in nature, and they can misfire—or be made to misfire, like when farmers make nesting hens sit on eggs that aren’t their own.
An interesting evolutionary arms race can be seen between certain species of songbirds and cuckoos who lay eggs in their nests, trying to trigger just such a misfire. Cuckoos try to trick the songbirds into hatching their eggs by laying them in the nest, which takes advantage of the songbirds’ natural altruism toward eggs and small birds in their own nests.
Those songbirds who recognize the imposters and throw them out will naturally contribute more to the next generation’s gene pool, because they aren’t wasting resources raising cuckoos. Therefore, the next generation will be better at recognizing the cuckoo eggs. On the other hand, those cuckoos whose eggs more closely resemble songbird eggs will have their offspring survive and contribute their genes to the next generation. This is a perfect example of selfishness (from the cuckoos) and altruism (from the songbirds) and the struggle between them.
It’s likely that, in addition to the relatedness value, an animal will also have to consider how certain it is of that relationship. The songbirds from the previous example must be quite certain that the cuckoos are actually their offspring—of course, in that case it turns out that they’re mistaken.
However, it’s usually much easier for most animals to recognize their own offspring than a brother or sister. Therefore, even though a sibling should have the same degree of relation as a child, parent-offspring altruism is much more common than sibling altruism in nature. By that same token, an animal is always 100% certain of its relation to itself, which can often weight decisions in favor of helping itself even over close relatives.
In reality, there are many considerations other than just relatedness and life vs. death that go into calculating how altruistic to be toward another member of the same species. For example, if an elderly animal can protect a younger relative who has a longer reproductive period still ahead of it, that might shift the decision in favor of altruism. And, naturally, not all acts of altruism result in saving the recipient’s life at the cost of the altruist’s. Risk and reward must be calculated accordingly. This tendency to act altruistically toward your relatives is sometimes called kin selection, though kin altruism may be a more accurate term.
Of course, animals don’t consciously calculate all of this before acting; it’s done instinctively and almost instantly. It’s similar to a person predicting where a ball will go so that he or she can catch it, even though the math involved in that prediction should be extremely complex.
There’s a mathematical representation of kin altruism called Hamilton’s Rule. It says that altruism is favored when rB > C, (r times B is greater than C) where r is the relatedness between the two parties, B is the benefit to the recipient, and C is the cost to the altruist.
Because benefit is multiplied by relatedness—which is a fraction, as shown earlier—individuals will weigh benefit proportionally to how closely they’re related vs. cost to themselves. If the recipient isn’t related at all, then r = 0 and altruism will never be favored (remember that any number multiplied by zero is zero). This equation also accounts for such things as an older animal risking its life to save a younger one—in that case, the benefit to the recipient is greater than the cost to the altruist.
How, when, and why do animals choose to reproduce? All of those decisions are designed to maximize their offsprings’ chance of survival. There are two competing theories for how animal populations control their reproduction: an altruistic theory put forth by group-selection theorists, and a selfish theory that Dawkins believes is true.
Animals often have to choose between reproducing and taking care of children that have already been born (bearing vs. caring). There are advantages and disadvantages to each choice, from the perspective of a selfish gene. Bearing more children creates more opportunities for genes to be passed on and survive, but often involves a great deal of risk and resource spending. Caring for already-living family members is less resource-intensive than bearing new ones, but doesn’t create more vessels for genes to inhabit.
Reaching an ESS usually (though not always) involves some balance of both—in fact, the only strategy that can never be an ESS is a pure caring strategy. This is because a population of pure carers, who rarely or never have offspring of their own, would quickly be invaded by another species turning the carers’ altruism to their own advantage.
How animals decide when to reproduce is a complicated question. Some scientists, most notably zoologist Vero Copner Wynne-Edwards, believe that animals control their reproduction rates to avoid overpopulating an area. However, this would be a group-selection based theory, which doesn’t seem to mesh with the idea of the selfish gene. It’s worth noting that Wynne-Edwards was a prominent champion of the group-selection theory of evolution, and his ideas are influential enough to be worth considering—even if only to refute them.
Whatever the reason, it’s clear that animal populations don’t grow at the incredible rates they’d be theoretically capable of. Many populations remain fairly stable, with birth and death rates roughly matching each other. Others, like lemmings, grow rapidly and then decline sharply, sometimes to the point of total extinction in a particular area.
Starvation is one major factor in keeping animal populations under control. If animals reproduce too quickly for an area to support, naturally many of them will starve. However, starvation cannot fully explain how animal populations stay under control. If starvation were the only control set on population size, scientists would expect all creatures to work like lemmings do: Their numbers would increase exponentially until the region couldn’t support them, then suddenly crash as most of them starved.
Therefore, it’s clear that there are methods limiting birth rates as well as death rates—animals don’t have infinite numbers of offspring. The question is not whether birth rates are controlled, but why they are controlled.
The group-selection theory would say the reason is altruistic: Animals regulate their birth rates for the good of the entire population. The selfish gene theory would say that it’s selfish: Animals regulate their birth rates because it gives them and their offspring the best chance of survival.
Wynne-Edwards’s theory says that animals have natural rules and guidelines that keep their populations in check. He takes observed territorial and hierarchical behaviors as evidence that animals follow certain rules for the good of the whole species.
He notes that males of many species will not even try to reproduce if they don’t have territories of their own. Since there is a limited amount of territory, that naturally limits the number of new births there can be. Similarly, among many species, males with low social status will not be able to reproduce—either females will not mate with them, or higher-ranking males will prevent lower-ranking ones from accessing the females. As with territoriality, in many species the low-ranking males will not even try to breed. These contests over territory and social status take the place of direct contests over females, which could result in wasted energy or injuries.
The most remarkable part of this theory may be epideictic behavior, which is a term that Wynne-Edwards himself created. Many animals tend to gather in large groups, and there are clear evolutionary advantages to doing so, such as protection from predators. However, epideictic behavior suggests another explanation: Animals gather in this way to conduct a sort of informal census of the population.
By seeing how large and dense the herd or flock is, animals can then determine whether they need to restrain their reproduction. Overcrowding is a clear sign that famine may be imminent, and the animals will need to adjust accordingly. This decision isn’t made consciously, but seeing a dense enough population will trigger natural responses in the animals that lead to lower birth rates, according to this theory.
There are costs as well as benefits to reproducing: remember bearing vs. caring. Therefore, even from a purely selfish standpoint, having as many children as possible isn’t usually the best strategy. For example, swifts have a standard clutch size of three eggs. That suggests that three is the ideal number of offspring for a swift to raise at one time. Having more than three at a time may mean the offspring wouldn’t get enough of their parents’ time and resources, and could die. Fewer than three, naturally, would mean that there are fewer offspring to pass those genes on to the next generation.
A selfish gene would want the animal to produce as many successful offspring as possible, given the resources available. Therefore, it’s selfishness, not altruism, that leads animals to limit their reproduction; having too many children would make it less likely for each to survive. Similarly selfish explanations can be made for the other aspects of Wynne-Edwards’s theory as well.
Animals who stop competing for territory or social dominance may have determined that their best bet is to hope that one of the others dies, rather than waste energy and risk injury with repeated contests that it has little chance of winning. The fact that these gambles often don’t pay off doesn’t necessarily mean that they were bad gambles. The chances of it working are slim, but perhaps the chances of winning such a contest and successfully defending a new position are even slimmer.
Even so-called epideictic behavior can be explained in selfish terms. Animals may lower their breeding rates during times of overcrowding because it gives them, personally, the greatest chance of raising the most surviving offspring. If resources become more limited, such as during a famine, a selfish gene should encourage the animal to have fewer children to split those resources among.
In practice, the altruistic vs. selfish reproduction theories are nearly identical. The only difference is whether animals practice population control for the good of the species as a whole, or purely for selfish reasons. Right now there’s no definitive way to tell which is correct, but—as previously shown—pure altruism is not a stable strategy since it’s bound to be taken over by selfish individuals. Therefore, it currently appears that the selfish reproduction theory is the stronger of the two.
Because Earth is a finite world with finite resources, there’s a natural struggle between the creatures who inhabit it to get those resources. In this chapter we discuss various ways that family members compete with each other—their own selfish interests conflict with their shared desires to have their offspring and siblings survive. We’ll also explore the natural conflict between mates, each of whom would benefit from the other contributing more resources to their offspring.
Finally, we examine the role of sexual attractiveness, especially among species where the male doesn’t engage in this conflict between mates, but simply leaves to find another female to impregnate. Sexual attraction is especially important for such species, because there’s no chance that the mate will stick around to contribute to raising the offspring. In that case, all that matters is finding the best, most fit mates through which animals can pass on their genes.
Every animal has a limited amount of resources to invest in furthering its genes. This limit represents the total amount of food that animal can gather or make, as well as the total energy it can expend in caring for and protecting others. That natural limit raises the question of whether parents (and other relatives) can have favorites—not in the human sense of “liking” one child more than another, but just in the sense of distributing those resources unevenly among its children.
While it might seem like there’s no genetic reason to do so—all of an animal’s offspring have 50% of its genes—wise investments can maximize the number of surviving offspring. For instance, if forced to choose between the lives of an older child and a younger one, the animal should pick the elder. It will need less care (and therefore fewer resources) to reach maturity and pass on its genes. However, if forced to choose to feed one or the other—not in an immediate life-or-death situation—oftentimes animals will choose to feed their younger children because the older ones are more likely to fend for themselves.
Also, many animals will not care for the “runt” of a litter, because it is less likely to survive and reproduce than others. In extreme cases parents may even feed the runt to its siblings, or eat it themselves. Though it seems contradictory, a selfish gene may even cause runts to give up and die in favor of their stronger siblings, so as not to drain resources from individuals with better chances of survival.
There comes a time when it makes sense, from a selfish gene’s perspective, for the parent to stop having children and focus on raising more distant relatives. If a child would have less than a 50% chance of survival—such as if the animal is too old to effectively raise more offspring—then mathematically the animal should devote its efforts to raising a grandchild instead. The grandchild is more distantly related, but has a much better chance of surviving to reproduce. Of course the animals don’t consciously calculate these odds, these behaviors are programmed by genes that have survived and outcompeted their alleles. As a side note, this may be a genetic explanation for menopause in humans.
This logic also applies to siblings who have to compete with one another for food and care. If a sibling would receive more than double the benefit that the individual itself would—for instance, if the sibling is too young to find its own food and needs the parents’ care to survive—selfish gene theory dictates that the individual should want those resources to go to the sibling instead. The “double” cutoff is because the sibling has half the relation that the individual does to itself—50% instead of 100%.
There’s a natural 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. The child, as previously stated, will be selfish up until its siblings get more than double the benefit it would receive from taking those resources itself. Therefore, the child will often try to trick its parents into believing it needs more resources than it’s getting.
A child may use various tactics to try to get more than its fair share of the resources. A common tactic, especially among birds, is to cry more loudly than the others in the nest. Since the volume of a cry corresponds to how hungry the bird is, a louder hatchling can trick its parents into believing that it’s hungrier than its siblings.
One species of bird, the honeyguide, has a more extreme strategy: It lays eggs in other birds’ nests like cuckoos do. Upon hatching, the newborn honeyguide will kill all the other hatchlings in the nest, thereby eliminating them as competition. Since it has no genetic relationship to its “foster siblings,” this strategy has no downside for the honeyguide’s selfish genes.
Honeyguides aside, this struggle between parent and child causes an apparent paradox: A child that takes more than its fair share will pass those genes on to its own offspring, lowering the number of children it can successfully raise because each child will demand more resources. In other words, being more successful as a child will make it less successful as an adult.
However, the animal has different purposes during the different phases of its life. Therefore, there’s no paradox between the child attempting to trick its parent into giving it more resources, and the parent attempting to see through those deceptions. All it means is that we must take the cost to future offspring as well as current siblings into account when considering the selfish behavior. If the total cost (to siblings and offspring combined) is less than double the benefit to the individual, then the genes causing that behavior will naturally be selected for.
If there can be conflicts of interest between parents and children, then there should be a severe conflict of interests 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. Therefore, though each wants to end up with as many surviving children as possible, they’ll 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 one’s partner for as long as possible, and abandoning them with the child before being abandoned oneself. A mated pair that stays together can split the resource cost of raising their offspring. However, a parent that abandons their mate and offspring gains a significant advantage—if they can be reasonably sure that the remaining mate will successfully raise the child.
In either situation, it’s to an individual’s advantage to keep his or her partner around. This simple fact goes a long way toward explaining the courtship behavior seen in many species of animals. Long, elaborate courtship rituals force both partners to invest a lot of resources into the future child before mating has even occurred. Knowing that future relationships will require similar periods of investment makes the partners less likely to abandon their current mates. The male also gets the benefit of knowing that the female is not already pregnant by someone else, if the courtship lasts long enough.
Females naturally have a larger investment in their offspring than males do, at least among mammals. Females, by definition, have larger gametes that are more costly to produce. Gametes are also known as sex cells—sperm and eggs, in animals. They also have to carry the child, and produce milk for it after birth. Therefore, it seems reasonable that a male could abandon his mate and go on to impregnate other females in order to produce the maximum number of offspring possible.
In some species this does indeed happen, but in many it doesn’t. In fact, a few species like beavers and wolves form lifelong monogamous pairs. In those species, there must have been some sort of pressure working against the mate-abandoning strategy—for example, females were unable to raise the children on their own, became adept at spotting males likely to abandon them, or would abandon the children if left alone in spite of the genetic cost.
An interesting side note: In some species of fish this pattern is reversed. Female fish deposit their eggs and leave immediately. Male fish come along later to fertilize the eggs, and are then left to raise the children themselves.
We can apply game theory to this male vs. female situation, as we did to the fighting and bluffing birds earlier. We may assume that there are two male strategies: faithfulness and unfaithfulness. A faithful male will stay with his mate, while an unfaithful one will leave as soon as possible. There are also two female strategies: coyness and forwardness. A coy female will insist on a lengthy courtship, a forward female will mate with any male immediately.
By assigning a point value to a successfully raised child, and penalties to the resources invested in courtship and raising the child, we could come up with a stable ratio of each of these strategies to find the ESS. As before, any numbers we assign would be purely arbitrary, and the exact ESS would depend on which numbers we pick. Therefore, the actual result of this exercise is less important than the fact that it can be done—more scientific, less arbitrary applications of game theory can reveal a lot about the behaviors and strategies of individuals.
Contrary to the previous section, wherein females tried to ensure that their partners would stick around and contribute to raising the offspring, in some species they’ll completely set aside the idea of a long-term partner. In such species, females will simply look for males with the most desirable traits and breed with them. An interesting side effect of this is that sexual attractiveness becomes an extremely important characteristic, regardless of its survival value. An attractive male could breed with many different females and spread his genes very quickly.
This leads to what could be considered “fashion.” Even if the attractive quality is objectively harmful, such as excessively long tail feathers in certain bird species (which take more resources to grow and could make the bird easier for predators to spot and catch), females who don’t bear children with that quality have less of a chance of their genes continuing to survive, because their offspring will not reproduce as successfully as other members of the species.
An alternative theory to sexual attractiveness states that these handicaps evolved because they are handicaps—males who survive with such handicaps are demonstrating that their other genes must be very strong. However, scientists haven’t been able to work this handicap theory into a logical model of evolution.
In some species such as elephant seals, this leads to situations where a single male can have an enormous harem of females, while many other males do not breed at all. In the case of elephant seals, the harem holder becomes such simply by fighting off all other males. By breeding with attractive or strong males, the females are more likely to produce offspring who will themselves be successful breeders, thereby keeping the selfish genes alive.
Given that one male can impregnate many females, it would seem like the ideal sex distribution would be skewed heavily toward females. However, the ESS in mammals is roughly 50% male to 50% female, and the selfish gene theory can explain why.
First of all, sex is determined by a single chromosome: The presence of a Y chromosome makes an animal male, and a father has a 50% chance of passing on his Y chromosome to his offspring. A female has two X chromosomes, and will always pass one on to her offspring.
(Shortform note: There are genetic conditions where a mammal may have something other than the typical XX or XY setup, but these rare cases don’t change the main point of this section.)
It’s theoretically possible that genes could evolve that favor X chromosomes, skewing the sex ratio in favor of females. However, if that happened, parents of males would be at a huge genetic advantage. Due to a shortage of males their offspring would probably mate with many different females, giving them a huge number of grandchildren compared to parents of females. The number of Y chromosomes in the population would then increase until the sex distribution was back to the roughly 50/50 balance we see in nature.
As a result of this 50/50 distribution, in many species females are highly sought after, meanwhile there are many more males than necessary. This often leads to males being colorful, flashy, and loud, because they have to compete for mates while females can afford to be picky.
In these chapters, we explore why many animals live in groups. We also explore some unexpected outcomes of group living, including various shared behaviors, and even what one might call culture. Strangely, culture spreads much like genes do: Ideas act as non-physical replicator “molecules,” and reproduce themselves in individuals’ minds.
Many types of animals move, or even live, together in groups. Some advantages of this are obvious. For instance, prey animals gain some protection from predators. 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 afterward. Birds fly in formation and switch leaders frequently to reduce turbulence and make travel less tiring. There are countless other examples in nature.
In Chapter 1, we discussed birds who give alarm calls to warn of predators, at some risk to themselves. However, this act of altruism may ultimately be an act of selfishness—in fact, considering the selfish gene theory, it must be. By the simple fact 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 reasons this could be the case. If a single 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 anyway, so it would be best to call a quick warning so the entire flock can hide. Finally, there’s the simple likelihood that by taking a small risk to itself, the individual giving the call can protect many of its relatives. Warning calls are a classic example of altruism.
Grooming is an example of reciprocal altruism: Two or more animals showing each other mutual altruism. Grooming is especially interesting because there’s 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. The obvious explanation is that the benefit of having a parasite pulled off of you is much greater than the cost of pulling one off of another individual. However, another possibility is that members of the population evolved the ability to hold a grudge; that is, they’ll refuse to groom selfish individuals who don’t groom others. Such behavior would naturally drive down the number of selfish individuals as they fall victim to parasites.
Much more extreme examples of altruism are seen in social insects like ants and bees. In a beehive, for instance, the vast majority of the bees are workers who can’t breed and will give their lives to protect the hive.
From the perspective of a selfish animal, such behavior makes no sense. However, from the perspective of a selfish gene, it is easily explained with two key facts. First, the workers are sterile—they can’t pass their genes on directly, so dying is no great loss. Second, the entire hive is descended from the same mother: the queen. Therefore, they’re all relatives and will act to protect each others’ genes. If this still seems strange, it may be helpful to think of the entire hive as a single organism, and the individual insects as specialized cells. For example, the workers who die defending the hive from intruders are acting like the hive’s immune system. The function of the entire hive is to ensure that the breeders survive and continue passing on their genes, just as the function of an animal’s entire body is to ensure that it reproduces.
A less-appealing comparison would be to a farm; the workers are using the queen to “farm” their own genes, despite not being able to breed themselves. This makes more sense than it seems to at first glance, because insects have a number of complex inheritance mechanisms that often mean they’re much more closely related to each other than other types of animals are.
Thus far, all the examples of reciprocal altruism that we’ve explored have been between kin. However, not all reciprocal altruism is between family members—sometimes it’s found even between entirely different species.
Continuing the farming analogy, some species of ants will actually “farm” certain types of fungus. The ants feed the fungus leaves and weed out competing species, which benefits the fungus. In return for this, the ants get a steady food supply. Ants have also been observed “milking” aphids for a sugar-rich excretion that the aphids produce while feeding. In return, the ants protect the aphids from other insects that might eat them.
When it occurs between members of different species, this type of reciprocal altruism is called mutualism or symbiosis. Symbiosis refers to creatures who spend a great deal of time—sometimes their entire lives—benefiting each other, while mutualism refers to specific, short-term interactions between organisms.
Reciprocal altruism, especially delayed reciprocal altruism such as communal grooming, raises a number of interesting thoughts about humans. We have long memories and can recognize one another, which would seem to suggest that reciprocal altruism should have played a large role in our evolution. Our ability to reason—and possibly a great number of other aspects of our psychology like gratitude, jealousy, and guilt—may be highly evolved versions of mechanisms for helping each other and recognizing selfish individuals.
It’s even possible that, with human capacity for foresight, we can develop a culture of pure altruism and protect it from selfish individuals. Remember that in the example of the fighting or bluffing birds, the single best outcome for each individual bird was for them all to be bluffers; the system only falls apart because it’s easily exploited by a single fighter. Humans may have the capacity to move beyond the commands of the selfish gene and build a culture that benefits everybody, with defenses against selfish people who would try to take advantage of such altruism.
Unfortunately, while fun to think about, this is currently nothing but speculation.
Not all replicators are biological—ideas can be observed to spread through populations like genes do. This is likely not a direct result of gene survival, but more of a side effect of how brains are wired to learn.
If the unit of biological inheritance is the gene, it could be said that the unit of idea inheritance is the meme. The word is based on the Greek word mimeme, meaning “something that is imitated.”
(Shortform note: The Selfish Gene is the origin of the word meme, though its meaning was quite different from the funny captioned images it refers to today.)
Genes tend to survive if they give advantages to the creatures that carry them. Memes, on the other hand, survive if they can take root in people’s minds. Like genes, memes are self-replicating units.
A “successful” meme is one that reaches more people and survives in the cultural consciousness for long periods of time. A catchy song, for example, will be successful in the sense that it replicates itself and survives as people spread it. A song will likely spread through imitation, recognized by hearing people sing or whistle the song.
Also like genes, memes have to compete with one another for limited resources. In this case, the resources are people’s time and attention.
The one area memes seem to suffer in the comparison to genes is accuracy. If a selfish gene wishes to pass itself on, by definition it wants to create exact copies of itself. However, memes do not seem to be copied accurately at all—like a game of telephone, everyone the meme passes to will put their own interpretations, spins, and mistakes on it before passing it on again.
On the other hand, many genetic traits appear to be blended or overwritten during inheritance, but that doesn’t mean the genes themselves were. The genes are unchanged, but express differently depending on what other genes are present. It’s possible that ideas work the same way.
The idea of God is one of the most successful memes ever. It’s not clear how the idea entered the “meme pool,” but it has survived through almost all of human history. One explanation is that the idea of God has great psychological value—it’s comforting to think that there’s order to the universe, and that injustices suffered in life will be repaid after death.
The God meme is spread through word of mouth, writing, music, art, and religious ceremonies. Over time the God meme has become linked with the Hell meme, which also has deep psychological impact—although for very different reasons. The two co-adapted memes reinforce each other and help ensure each others’ survival, just as some genes do.
Religions tend to last for a very long time, reach a huge number of people, and be slow to change. In other words, they meet all the requirements of a successful meme—or gene. Biologists, therefore, may be inclined to wonder how memes such as God came to exist in humans. They would ask, “What is the survival value of believing in God?”
However, it may be a mistake to think of memes in terms of survival or reproductive value. They may simply be a side effect of how human brains developed—or, to further the comparison to genes, they may be naturally evolving replicators that exploit how our brains work. While cultures and fads can be seen to change and adapt in a way that mimics biological evolution, there is no reason to believe the two processes are connected.
As an interesting side note, cultural inheritance has also been observed—to a much lesser extent—in certain animals. Some species of songbirds learn their songs by mimicking other birds, not through genetics. Occasionally new songs are created when birds incorrectly copy each other. These new songs are taken up by other individuals, spreading like a meme spreads through a human population.
Memes (in the sense that Dawkins uses the word, a self-replicating idea) have enormous impact on our day-to-day lives.
Think about your day. Identify one meme that had an impact on it. (For example, a song that got stuck in your head, or an idea that you couldn’t stop thinking about.)
How did that meme spread to you?
Have you spread that meme on to other people? In other words, have you been a vehicle for the meme’s reproduction? How so?
Why do you think this meme has survived as long as it has, and how much longer do you expect it to survive? What qualities does the meme have that make you think so?
This chapter is about another way to use game theory to explain behaviors, especially at the population level. By using game theory, scientists can determine effective behavioral strategies. They can also find—or at least approximate—an ESS for a population made up of such behaviors.
The Prisoner’s Dilemma is a logistical riddle closely tied to game theory. In the Prisoner’s Dilemma there are two players, each with two options: Cooperate and Betray. Neither player knows which option the other has chosen, and they are not allowed to influence the other’s choice in any way.
If both players choose Cooperate, they each get a significant payout—but a smaller one than in the next situation. If one player Cooperates and the other Betrays, the betrayer gets a large payout while the cooperative player suffers a large penalty. If both players Betray, they each suffer a small penalty. Cooperation and betrayal are altruistic and selfish actions, respectively. Therefore, everything we know about the Dilemma could be compared to nature.
In any single instance of the game, the logical choice is to simply pick Betray. If your opponent chose Cooperate, you’ll get a larger payout than if you’d also chosen Cooperate. If your opponent chose Betray, you’ll suffer a smaller penalty than if you’d chosen Cooperate.
However, the strategy becomes much more complex if you play over and over again. Now one Always-Betray strategy can get stuck in a penalizing loop with another one, while more cooperative strategies have the chance to reap mutual benefits. Of course, an Always-Cooperate strategy will still lose every time to an Always-Betray strategy.
Professor Robert Axelrod once invited programmers to create programs that use Prisoner’s Dilemma strategies, which he then entered into a virtual “tournament.” In this tournament, each program played 200 rounds of Prisoner’s Dilemma with each of the others, including a copy of itself. Whichever program had the highest total score at the end was the winner.
There were a number of complex strategies submitted for this tournament, some of which were quite cutthroat. However, the surprising winner of the tournament was a simple program called Tit for Tat. This program always played Cooperate on the first round, then for each round after that it simply copied what its opponent had done last. This made it so cooperative strategies were rewarded, while aggressive strategies were punished. Afterward, Axelrod calculated that a so-called “Tit for Two Tats” program would have done even better; such a program wouldn’t Betray until having been betrayed twice in a row itself, and would therefore have avoided some penalizing loops that Tit for Tat got caught in.
Out of 15 programs submitted, eight of them were programmed to never Betray first, and those eight “nice” programs had the highest scores. The aggressive strategies all scored significantly lower than their cooperative counterparts. The weakest of the top eight was an “unforgiving” program, which played Cooperate until the first time it was betrayed, and then played Betray every round after. This meant that it couldn’t break out of penalizing loops the way the other cooperative programs could.
Professor Axelrod held a second tournament after announcing the results of the first. Many programmers submitted “nice” programs for this second contest, reasoning that cooperation must be a winning strategy since it had done so well the last time. One entrant was the theorized Tit for Two Tats that would have won the previous tournament. Others tried submitting more aggressive, cutthroat strategies, hoping to take advantage of the cooperative field.
Once again, Tit for Tat had the highest score, beating even the Tit for Two Tats program that would have won the first tournament. The fact that Tit for Two Tats did not do as well in this tournament as it would have in the last one demonstrates an important point: The best strategy depends on what others around you are doing. Similarly, while Tit for Tat does well against a wide range of opponents in a diverse field, it would not succeed if the field were too aggressive, because its first Cooperate play would put it at an immediate disadvantage.
Axelrod held a third tournament using the same programs from the second. However, this time he tried to mimic biology by paying winners not in points, but in “offspring” who would go on to the next round. After around 1,000 “generations,” the proportions of offspring stopped shifting in any meaningful way. That is to say, the field had reached its Evolutionarily Stable Strategy.
Axelrod ran this simulation six times. Tit for Tat was the most successful in five of them, with similar cooperative-but-retaliatory programs also doing quite well. Aggressive programs tended to do well at first, but decline and die out as they drove their “prey” to “extinction.”
However, Tit for Tat alone—or any program that never Betrays first—can’t be considered a true ESS. Such a population could be infiltrated by a mutant program that never picks Betray. As long as there are no aggressive programs in the field, that new program can spread. That would leave the entire population vulnerable if an aggressive program were later introduced. Axelrod coined the term “Collectively Stable Strategy” to describe this situation (remember that an ESS cannot be invaded by another strategy).
We could consider Axelrod’s system to have two stable points. One is the Tit for Tat dominance (or similar cooperative-but-retaliatory strategies) we saw. The other is Always-Betray dominance—in a field dominated by Always-Betray programs, no other program could do better because no strategy can beat Always-Betray in a head-to-head match.
Which stable point the system goes to depends on which programs are present at the start, and what—in a computer simulation—could be called chance. However, if we shift to thinking about nature, we can come up with better explanations than pure luck.
In nature, most animals tend to cluster together with others of their kind—not only because of the advantages of doing so, but also because most organisms don’t stray very far from where they were born. This is called viscosity.
Tit for Tat does best when surrounded by similar strategies. On the other hand, Always-Betray does particularly badly when surrounded by other aggressive strategies, as they get locked into penalizing loops. Therefore, a cluster of Tit for Tat will prosper, while a cluster of Always-Betray will suffer.
While it will be difficult for another strategy to invade a population of Always-Betray individuals, it’s almost inevitable that it will happen eventually. A population of creatures with the Always-Betray strategy will continually weaken itself, while a population of more cooperative individuals will prosper and spread. Sooner or later the balance will tip back toward the cooperative population.
Therefore, while Always-Betray is technically an Evolutionarily Stable Strategy (in the sense that no other program could do better in a population of Always-Betray), and Tit for Tat is technically not an ESS (because it could be invaded by a mutant program and eventually overthrown), it could be said that Tit for Tat has a long-term stability that Always-Betray lacks.
Aggressive strategies have a quality that Tit for Tat lacks, which may explain this difference. This quality could be called envy, or perhaps competitiveness. The key difference is that Tit for Tat is not concerned with “beating” its opponent—in fact, it can’t possibly get a higher score than its opponent, since it will never Betray unless it’s betrayed first. Tit for Tat’s only concern is for scoring points, not for scoring more than anyone else.
Aggressive strategies, on the other hand, seek to “win” their matches by beating down their opponents. This is why, when a field is dominated by aggressive programs, they inevitably suffer for it. The mistake aggressive strategies make is treating Prisoner’s Dilemma like a zero sum game: a game in which one player’s win must be another player’s loss, such as chess. However, in Prisoner’s Dilemma—and, arguably, in nature—both players can do quite well if they’re not concerned about “winning.” This is the very nature of reciprocal altruism.
This chapter is a bit of a smorgasbord—it talks briefly about several different topics that didn’t fit anywhere else in The Selfish Gene. First, it discusses the impact that genes have not only on the creatures they inhabit, but also on the world around them. Then it discusses a strange quirk of reproduction: How most organisms begin as single cells, and why that fact is important—possibly necessary—for stability and evolution.
So far we have discussed biology and behavior in terms of genes; but, of course, there is a difference between a gene and an organism. Most 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, one might ask why organisms as we know them should exist at all. (Shortform note: This key question is partially answered in Chapter 2.)
However, the simple truth is that organisms don’t have to exist. They exist on Earth because that’s what evolution happened to favor in Earth’s particular environment. The only thing that must exist in order for there to be life is some form of replicator molecule.
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 organisms that contain those replicators are simply vehicles doing all the things the replicators can’t: perceiving, eating, acting, and so on.
To look at biology in a new way, starting from the genetic level, requires that we consider what might be called the extended phenotype. The usual definition of phenotype is the effect that a particular gene has upon the body it’s housed in—for example, blue eyes or wrinkled peas. However, phenotypes should really be considered in terms of the total effect they have on the world.
It may be the case that a particular gene only impacts the body it’s in, but there’s no reason why that should be key to the definition of phenotype. Whatever effect genes have on physical characteristics is incidental—their real impact is on the chemical processes inside the body (remember that a gene’s true function is to act as a blueprint for a protein). Therefore, going one step further by talking about the effects of genes on the world around them is not as much of a stretch as it first seems.
Examples of phenotypes that extend beyond the bodies they’re in are bird nests and beaver dams. Though it sounds odd to us, biologists should think in terms of genes “for” certain building materials and styles of nest, dam, and so on. Genes that caused the organisms to build structures in those specific ways must have been selected for at some point, which is why those genes exist today. Therefore, a lake created by beaver dams should be considered a part of that phenotype as much as the beavers’ physical characteristics.
Some genes even influence other living organisms, for better or worse. For example, there is a certain type of parasite that causes snails to grow unusually thick shells. While this thicker shell helps protect the snail (and therefore the parasite), it’s costly to make, and takes resources from the snail that it might otherwise have used to reproduce and pass on its genes. The parasite, of course, isn’t concerned with the snail’s reproduction, only its own. Therefore, causing its host to produce a thicker shell makes evolutionary sense.
However, if a “parasite’s” reproduction is aided by its host’s reproduction, as is the case in certain species of beetles, we could expect to see the relationship grow from parasitic to mutualistic or even symbiotic. From a certain point of view, genes themselves could be seen as symbiotes with the body that contains them.
As a side note, extended phenotypes and this idea of genes-as-parasites can also help establish once and for all why group selection isn’t a sound theory. Parasites only help their hosts when they reproduce by the same method—that is, helping the host reproduce also helps the parasite to reproduce. Animals in a group clearly do not have that kind of symbiosis; far from helping each other to reproduce, they often have to compete for the chance to do so.
Group selection, where some animals out-compete others for the good of the species, doesn’t make sense from the perspective of a selfish gene. For any given gene, there would always be the chance that it’s one of the ones that gets out-competed and eliminated from the gene pool. Therefore, if the selfish gene theory is correct, group selection can’t be.
However, even though group selection is a fatally flawed theory, it can’t be denied that extended phenotypes interact with and impact each other in countless ways. A great deal about the natural world can be explained in terms of selfish genes if extended phenotypes are taken into account.
We’ll leave the topic of extended phenotypes for now, and consider an interesting quirk of reproduction. Basically, there are three key questions to consider when discussing how life evolved into the complex organisms we have today: Why did replicators group up into cells; why did cells group up into bodies; and why do bodies begin as single cells, with the purpose of creating more single-celled bodies? In other words, why is the life cycle bottlenecked down to a single cell at each end?
The first two questions have been addressed already. In short, complex organisms developed because that was the most stable strategy for their environments. The third question is related to the first two; clearly this bottlenecking strategy must be helpful, since it’s so ubiquitous.
In fact, it could be argued that the genetic bottleneck is key to creating individual organisms as we know them. For convenience’s sake, forget about sexual reproduction and all the genetic complications that come with it while considering this topic.
In an asexual species, any offspring should be exact clones of the parent, except for random mutations. If an organism did not reproduce by sending out single cells—for example, if it regrew from a broken piece of itself like many plants can—those individual mutated cells would be unlikely to have any impact on the offspring. Natural selection would be impossible under these circumstances, since it can only act when there’s diversity in the population. Furthermore, those mutated genes will now want to duplicate only themselves, rather than the entire organism they’re found in. In other words, the organism’s cells may end up competing against each other.
However, an organism that reproduces by sending out single-celled spores, for instance, would have that mutation copied in every cell of the new organism. Natural selection and evolution would be possible in this case. Also, since the cells within the organism all share the same genes, they’ll more readily cooperate with each other to make sure that organism survives and reproduces.
The orderly timeframes that are imposed by such a life cycle also make tight regulation of certain processes possible. It gives the organism clear phases of life, during which time-specific processes can happen. An organism that reproduces by breaking off and regrowing would not have such clear-cut life stages, which would make it difficult if not impossible for such processes to happen cleanly and efficiently. The fact that an organism begins as a single cell, and develops as countless copies of that cell, may be the very reason why organisms exist as distinct individuals.
In conclusion, let’s summarize the long path that life has taken, and why the gene should be considered the basis of all life. The origin of life anywhere in the universe, no matter what form it takes, must be some sort of replicating molecule. That molecule will first be formed by chance, but then will copy itself indefinitely. On Earth, that molecule happens to be DNA, which arranges itself into genes.
The replication process isn’t perfect, and various mutations emerge. Some of these mutations end up being helpful, and the molecules possessing them replicate more effectively. Less effective replicators are eventually squeezed out of the population due to lack of resources.
Mutations build on top of mutations, and the vehicles that house these replicators become more and more complex. The effects of genes become more and more widespread, reaching beyond their vehicles to impact the world around them, and even other organisms. Those countless extended phenotypes, which all originate with those ancient replicator molecules, create the living world as we know it.
The effects of extended phenotypes—things created or influenced by living organisms—are all around you. Take a look out the nearest window.
What can you identify that an animal created? Remember that humans are animals too!
Pick one object from the previous question. How does it impact your life?
How does it impact the world around it?