Chapter 8 Chapter 6 Genetic Morality

What is the selfish gene?It is not just a single physical piece of DNA.As in the primordial soup, it is all replicas of a particular piece of DNA, distributed throughout the world.If we can understand genes as if they had a conscious purpose, and if we feel confident reducing our overly popular language to formal terms when necessary, then we can ask the question: what is the purpose of a selfish gene? what is itIts purpose is to try to expand its ranks in the gene pool.Basically, it does this by helping the individuals it inhabits to program them to survive and reproduce.But what we need to emphasize now is that it is a distributed agency, existing in many different individuals at the same time.The main idea of ​​this chapter is that it is possible for a gene to help copies of itself that exist in some other individual.If so, the situation would look like individual altruism, but such altruism is due to genetic selfishness.

Let us assume that there is such a gene, which is an albino gene (albino) in humans.There are actually several genes that may cause albinism, but I'm just talking about one of them.It is recessive, that is, two albinism genes must be present to make an individual suffer from albinism.It happens to about one in 20,000 people, but about one in seventy of us has a single albino gene in us.These people do not suffer from albinism.Since the albino gene is distributed among many individuals, in theory, it can program these individuals to show altruistic behavior towards other individuals with the albino gene, thereby promoting its own existence in the gene pool, because Other albinos contain the same gene.If some of the individuals inhabited by the albino gene die, and their death allows some other individuals with the same gene to survive, then the albino gene should be quite happy.If an albino gene enables one of its individuals to save the lives of ten albinos, then even if the altruist dies as a result, his death is fully compensated for by the increased number of albino genes in the gene pool.

Can we therefore expect albinos to be particularly friendly to each other?In reality that probably won't be the case.To get to the bottom of this question, it is necessary to temporarily abandon the metaphor of genes as conscious agents.Because here, the analogy is sure to be misleading.We must again use formal, if somewhat lengthy, terms.Albino genes don't really want to survive or help other albino genes.But if the albino gene happens to cause some of its individuals to behave altruistically toward some other albino, then the albino gene tends to naturally flourish in the gene pool as a result, whether it wants to or not.But for this to happen, the gene must have two separate effects on some of its individuals.Not only does it confer on some of its individuals an influence that would normally produce a very pale complexion, it also confers on individuals a tendency to exhibit selective altruistic behavior toward other individuals with a very pale complexion.A gene with both influences, if it existed, would surely be very successful in the population.

As I emphasized in Chapter 3, it is true that genes do have multiple effects.From a purely theoretical point of view, it is possible to have a gene that would confer on an individual a distinctly visible external mark, such as pale skin, green beard, or other conspicuous things, as well as to other Individuals with these signs have a particularly friendly tendency.Such a scenario could happen, though unlikely.Green beards may also be related to a tendency to grow ingrown toenails or other traits, and a penchant for green beards may also co-exist with a physical defect of not being able to smell freesia.It is unlikely that the same gene produces both the correct markers and the correct altruistic behavior.However, this phenomenon, which we might call the green beard altruistic effect, is theoretically possible.

An arbitrary mark of choice like a green beard is just one way a gene can identify copies of itself in other individuals.Is there any other way?Below is probably a very straightforward approach.Individuals with altruistic genes can be identified based on their altruistic behavior alone.If a gene could say the equivalent of this, hello!If A tries to rescue a drowning person and is about to drown himself, and jumps down to rescue A, this gene will flourish in the gene pool, because most of A's body contains the same life-saving altruistic gene. The fact that A is trying to rescue other individuals is itself a sign equivalent to a green beard.Even though the logo isn't as outlandish as the green beard, it's still a little bit unbelievable.Do genes have some plausible way of recognizing copies of themselves that exist in other individuals?

The answer is yes.It is easy to show that close relatives more than likely share the same genes.It has been argued that this is apparently the reason why parent-offspring altruism is so common, according to Fisher, J. B. S. Haldane, and especially Hamilton.The same applies to other close brothers, sisters, nephews and nieces and cousins ​​by blood.If an individual dies to save ten close relatives, one copy of the gene that manipulates the individual's altruistic behavior toward relatives may be lost, but a large number of copies of the same gene are preserved. Much of this statement is very ambiguous, as is close relatives.Actually we could be more precise, as Hamilton showed.His two papers on the ecology of social entities, published in 1964, are among the most important to date.I have always struggled to understand why some individual ecologists were so careless as to ignore these two papers (the 1970 editions of the two major textbooks on individual ecology did not even index Hamilton's name).Fortunately, there have been signs of renewed interest in his views in recent years.His thesis employs fairly abstruse mathematics, but it is not difficult to grasp its basic principles intuitively rather than through precise calculations, although doing so would oversimplify some issues.What we need to calculate is probability, the chance that two individuals, say two sisters, share a particular gene.

For brevity, I assume we are talking about some rare genes in the entire gene pool.Most people share the gene not to be albino, whether they are related or not.The reason such genes are so common is that albinos are more likely to die in nature than non-albinos.This is because, for example, sunlight dazzles them, making them more likely to lose sight of an approaching predator.It is not necessary for us to explain the reasons why the albinos in the gene pool do not form albinos, which are obviously good genes, so they gain an advantage.We are interested in why genes succeed because they exhibit altruistic behavior.Therefore, we can assume that, at least early in this evolutionary process, these genes were rare.Remarkably, genes that are rare in the population as a whole are common in a family.I have genes in me that are rare to the population, and you have genes in you that are rare to the population.The chances of both of us sharing these same rare genes are slim to none.But the chances are good that my sister and I share a specific rare gene.Likewise, the chances of your sister sharing the same rare gene as you are equally good.In this example, the chances are exactly fifty percent.The reason for this is not difficult to explain.

Assume that you have one copy of the gene G in your body, which must have been inherited from your father or mother (for convenience, we ignore the unusual possibilities that G is a new variant, or that your Both parents have the gene, or your father or mother had two copies).Say your father passed on the gene to you, and every normal somatic cell in his body contains a copy of G.Now you have to remember that when a man produces a sperm, he gives half of his genes to that sperm.So the chance that the sperm that made your sister or sister got the gene G is 50 percent.On the other hand, if your gene G came from your mother, by the same reasoning, half of her eggs contained G.Likewise, your older sister has a fifty percent chance of getting gene G.This means that if you have a hundred siblings, about fifty of them will have any one of your specific rare genes.It also means that if you have a hundred rare genes, any one of your brothers or sisters may have about fifty of them.

You can calculate the order of any kinship by this calculus.The relationship between parent and offspring is important.If you have one copy of gene H, there is a 50 percent chance that one of your offspring will have this copy because half of your sex cells contain H and any offspring is made up of one such sex cell bred.If you have one copy of gene J, there is a 50 percent chance that your father had one because you got half of your genes from him and half from your mother.For the convenience of calculation, we use a relatedness index, which is used to indicate the chance of sharing a gene between two relatives.The relatedness index between two brothers is 1/2 because either half of their genes are shared by the other.This is an average: some brothers may share more than half or less than half the genes due to the chance of meiosis.But the kinship between parents and offspring is always one/two, neither more nor less.However, it would be too troublesome to calculate from the beginning every time.Here is a simple method for you to use to calculate the relatedness of any two individuals A and B.You might find this helpful if you're making a will or need to explain why certain members of your family are so alike.Under normal circumstances, this method is effective, but it is not applicable in the case of interbreeding between blood races.Certain species of insects are also not suitable for this method, which we will discuss below.

First, find out who all common ancestors of A and B are.For example, the common ancestor of a pair of first cousins ​​is their shared grandfather and grandmother.After finding a common ancestor, it is of course logical that all his ancestors are also the common ancestor of A and B.For us, though, it is enough to pinpoint the most recent common ancestor.In this sense, first cousins ​​have only two common ancestors.If B is a direct relative of A, for example, his great-grandson, then the common ancestor we are looking for is A himself. After finding the common ancestor of A and B, calculate the generation distance as follows.Starting from A, trace its ancestors along its family tree until you find the ancestor that he and B have in common, and then count from this common ancestor to the next generation to B.Thus, the total number of generations on the family tree from A to B is the generation distance.For example, if A is B's uncle, then the generation distance is three, and the common ancestor is A's father, that is, B's grandfather.Starting from A, you only need to go up one generation to find the common ancestor, and then count down two generations from this common ancestor to get B.Therefore, the generation interval is one + two = three.

After finding the generation distance between A and B through a certain common ancestor, then calculate the part of the relationship between A and B that is related to this common ancestor.The method is like this, each generation distance is 1/2, and if there are several generation distances, the number of 1/2 is multiplied by itself.The resulting product is the kinship index.If the generation interval is three, the exponent is one/two X one/two X one/two or (one/two) three; The relationship index is (one/two) nine. But this is only a partial value of the relatedness between A and B.If they have more than one common ancestor, we add up all the values ​​of kinship through each ancestor.In general, the generation distance is the same for all common ancestors of a pair of individuals.So after working out how related A and B are to any one common ancestor, you actually just multiply by the number of ancestors.For example, first cousins ​​have two common ancestors, and their generation distance from each ancestor is four, so their relatedness index is two (one/two) four = one/eight.If A is a great-grandson of B, the generation distance is three, and the number of common ancestors is one (that is, B itself), so the exponent is one X (one/two) three = one/eight.In terms of genetics, your first cousin is the equivalent of a great-grandchild.Likewise, you are as much like your uncle (kinship is two X (one/two) three = one/four) as you are like your grandfather (kinship is one X (one/two) two = one/four) . As for the kinship as far as third-generation cousins ​​or sisters (two X ((one/two) eight = one/one hundred and twenty-eight), it should be close to the lowest probability, that is, it is equivalent to any individual in the population Possibility of possessing a gene in A. A third-generation cousin is about as related as a complete stranger to an altruistic gene. A second-generation cousin (relationship 1/30 2) A little bit special, first cousins ​​are even more special (1/8), sibling siblings, parents and children are very special (1/2), identical twin siblings (1) are exactly the same as themselves The relationship between uncle and aunt, nephew and niece or niece, grandparent and grandchild, half-brother or half-sister is one-fourth. Now we can talk in much more precise terms about genes that exhibit kin altruism.A gene that manipulates its individual to save five cousins ​​at the expense of itself will not thrive in the population, but a gene that saves five brothers or ten first cousins ​​will.For an altruistic gene prepared to sacrifice itself to be successful, it must save at least two or more siblings (children or parents), or four or more half-siblings (uncles, aunts, nephews, nieces, grandparents, grandchildren) or eight or more first cousins, etc.On average, such genes are likely to survive in the individuals saved by the altruist in sufficient numbers to compensate for the altruist's own death. If an individual can be sure that a certain person is his identical twin brother or sister, he should be concerned about the welfare of the twin brother or sister exactly as he cares about his own welfare.Any genes that manipulate a twin's or sister's altruistic behavior are present in the twin's or sister's body at the same time.Therefore, if one dies heroically to save the life of the other, the gene will survive.Nine-banded armadillos have litters of four.As far as I know, there has never been a story of heroic sacrifice by a baby armadillo.But it was pointed out that they must have some kind of strong altruistic behavior.If someone can go to South America and observe their life, I think it will be worth it. We can now see that parental love is no more than a special case of kin altruism.From the point of view of genetics, an adult individual should care for his own younger brother in the same way he cares for his own children.For it, the relative index of the little brother and the child is exactly the same, that is, one/two.According to genetic selection, the gene that manipulates individuals to exhibit elder sister altruism and the gene that manipulates individuals to exhibit parental altruism should have the same chance of reproduction in the population.In fact, this statement is an oversimplification in several respects, as we shall see below, and sibling love is far less common in nature than parental love.But the point I am trying to make here is that from a genetic point of view, the parent/child relationship is nothing more special than the brother/sister relationship.Although it is actually parents who pass genes on to their children, this does not happen between sisters.However, this fact is irrelevant to the present question.This is because both sisters are identical copies of the same genes inherited from the same father and mother. Some people use the term kin selection to distinguish this natural selection from group selection (differential survival of groups) and individual selection (differential survival of individuals).Kin selection is the cause of intra-family altruism.The closer the relationship, the stronger the selection.There is nothing inherently wrong with the term; unfortunately, we may have to discard it, because recent misuse has produced abuses that will confuse biologists for many years to come.E. O. Wilson's Sociobiology: The New Synthesis, an excellent work in every respect, describes kin selection as a special form of group selection.A diagram in the book clearly shows that he understands kin selection in the traditional sense, the sense I used in Chapter 1, as an intermediate form between individual selection and group selection.Group selection, even according to Wilson's own definition, refers to the differential survival among different groups of individuals.It is true that, in a sense, a family is a special kind of group.But the whole implication of Wilson's argument is that the dividing line between familial and nonfamilial is not set in stone, but is a matter of mathematical probability.Hamilton's theory doesn't suggest that animals should exhibit altruistic behavior in all members of their family.And show selfish behavior towards other animals.There is no clear dividing line between familial and non-familial.We do not have to decide, for example, whether second cousins ​​should be included in the family circle.We just think second-generation cousins ​​can accept as much altruism as one-sixteenth the amount of altruism a child or brother would.Certainly kin selection is not a special manifestation of group selection, it is a special consequence of genetic selection. Wilson's definition of kin selection has an even more serious flaw.He consciously excludes his children: they are not close relatives!Of course he knows very well that children are the flesh and blood of their parents, but he does not want to invoke the theory of kin selection to explain the altruistic care parents have for their offspring.Of course he has the right to define a word as he likes, but this definition is very easy to confuse people.I would rather hope that Wilson revises the definition in the second edition of his incisive and far-reaching work.From a genetic point of view, both parental love and brother/sister altruism can be explained for exactly the same reason: the presence of the altruistic gene in the beneficiary is highly likely. I hope readers will forgive this somewhat offensive comment above.And I'm going to quickly turn around and get back to business.So far, I've oversimplified the problem to a certain extent, and now I'm going to make the problem more specific.Above I spoke in plain language of the gene for self-sacrifice for the rescue of a certain number of close relatives with a certain kinship.Obviously, in real life we ​​cannot assume that animals actually count how many relatives they are rescuing.Even if they had a way of knowing exactly who their brothers or cousins ​​were, we couldn't assume that animals were performing Hamiltonian calculations in their heads.In real life, certain suicide behaviors and certain rescue behaviors must be replaced by statistical risks of the death of oneself and other individuals.Even third-generation cousins ​​are worth saving if the risk to yourself is minimal.Besides, you and the relative you're trying to save will all die someday, and every individual has an estimated lifespan estimated by an insurance statistician, although that estimate may be subject to error.If you have two equally close blood relatives, one of whom is dying and the other is a young man, saving the life of the latter will have a greater impact on the future gene pool than saving the life of the former big. Those neat symmetric calculus need further tweaking when we calculate the kinship index.In terms of genetics, grandparents and grandchildren treat each other altruistically for the same reasons, because they share a quarter of their genes.But if the life expectancy of the grandchildren is longer, genes that manipulate altruistic behavior of grandparents towards grandchildren are more favorably selected than genes that manipulate altruistic behavior of grandchildren towards grandparents.The net benefit from aiding a young distant relative is likely to outweigh the net benefit from aiding an older close relative (by the way, grandparents do not necessarily have shorter life expectancy than grandchildren, of course. High infant mortality In species, the opposite may be the case). Extending the analogy of insurance statistics a little, we can think of individuals as underwriters of life insurance.An individual can use part of the property he owns as funds to invest in the life of another individual.He considers the kinship between himself and the individual, and whether the individual is a good insurance policy compared to himself in terms of life expectancy.Strictly speaking, we should use the term expected reproductive capacity rather than estimated lifespan, or more strictly, the general ability to benefit one's genes for the foreseeable future.Then, in order for altruistic behavior to develop, the risk borne by the altruistic actor must be less than the product of the beneficiary's net benefit and the kinship index.Risks and benefits have to be calculated in what I call complex insurance statistics. But how can we expect such complex calculations from poor survival machines!Especially in a hurry, let alone.Even the great mathematical biologist Haldane (who predated Hamilton in his 1955 paper by postulating the reproduction of genes by rescuing drowning kin) said, I have twice put I had no time at all for the calculations in doing so by rescuing potentially drowning persons (at little risk to myself).But: Haldane is also well aware that fortunately we need not assume that survival machines are performing these calculations consciously in their own heads.Just as we use a slide rule without realizing that we are actually working with logarithms.Animals may be born in such a way that they act as if they have performed a complex calculation. This situation is actually not difficult to imagine.A person throws a ball high into the air and then catches it as if he had previously solved a set of differential equations predicting the trajectory of the ball.He probably doesn't know anything about differential equations and doesn't want to know what differential equations are, but that doesn't affect his throwing and catching skills.On a certain subconscious level, he performed something that was functionally equivalent to a mathematical calculation.Similarly, if a person wants to make a difficult decision, he first weighs the various pros and cons, and considers all the consequences he can imagine that this decision may cause.His decisions are functionally equivalent to a series of weighted calculations, like those performed by a computer. If we were to program a computer to simulate how a typical survival machine would decide whether to behave altruistically or not, we would proceed roughly like this: Make a list of all possible behaviors that the animal could do, and then A separate weighting algorithm is programmed for each of these modes of behavior.All kinds of benefits are given positive signs, and all kinds of risks are given negative signs.Weighting is then carried out, that is, each benefit and risk is multiplied by an appropriate index of kinship.Then add up the obtained numbers. For the convenience of calculation, we do not consider the weight of other aspects such as age and health status at the beginning.Since an individual has a kinship index of one to himself (that is, he has 100% of his own genes which is self-evident), all risks and benefits to him need not be discounted, that is, given full weight in the calculation .In this way, the sum total of each possible behavior pattern is roughly like this: the net benefit of the behavior pattern = the benefit to oneself - the risk to oneself + the benefit of one/two pairs of brothers - the risk of one/two pairs of brothers + one/ Two benefits to another brother - 1/2 risk to another brother + 1/8 benefits to cousins ​​- 1/8 risks to cousins ​​+ 1/2 benefits to children - 1/2 benefits to children Risk +. This sum is called the Net Benefit Score for that behavior pattern.The model animal then calculates a score for each alternative behavior pattern on the list.In the end, it decides to act on the pattern of behavior with the greatest net benefit.Even if all the scores are negative, it should still choose according to this principle, that is, choose the behavior mode with the least harm.It should be remembered that any practical action necessarily involves the expenditure of energy and time that could be used for other things.If the calculus shows that the net benefit of doing nothing is the greatest, then the model animal does nothing. Here is a very simple example, in the form of a self-monologue rather than a computer simulation.I am an animal and found eight mushrooms growing together.Taking their nutritional value first in my mind, and taking into account the modest risk that they might be poisonous, I estimate that each mushroom is worth about + six units (these units were chosen arbitrarily, as in the previous chapter).Due to the large size of the mushrooms, I could only eat three at most.Shall I yell for food and tell the other animals what I have found?Who can hear me shout?Brother B (who is related one/two to me), cousin C (who is related one/eighth) and D (who is not really related, so that his relatedness index to me is so small that in fact can be used as).If I keep quiet, every mushroom I can eat nets me +6, and eating them all is +18.If there is a cry for food, then I have to figure out how much net gain I have.The eight mushrooms are divided into four equal parts. For me, the one I eat is equivalent to net gain + twelve, but the two mushrooms each eaten by my brother and cousin will also bring benefits to me, because they have Have the same genes as me.The actual total score is (one X twelve) + (one/twenty X twelve) + (one/eight X twelve) + (x twelve) = nineteen.Five, while the net gain from the selfish act is eighteen.Although the difference is small, the gains and losses are clear.So I'm going to give a shout out that there's food.In this case, my altruistic behavior pays off to my selfish genes. In the simplified example above, I assumed that the individual animal was able to figure out what the best interests of its genes were.What actually happens is that the gene pool is full of genes that exert an influence on the individual, as a result of which the individual acts as though this calculus had been performed beforehand. In any case, the result of this calculation is only a preliminary, first approximation, and it is still far from the ideal answer.This calculation method ignores many things, including factors such as the age of the individual.Also, if I've just had a full meal and can only eat at most one mushroom now, the net benefit of yelling that there's food will be much greater for me than it would be if I were hungry.The quality of this calculus can be incrementally improved indefinitely for every possible ideal situation.But animals don't live in ideal environments, and we can't expect real animals to consider every detail when making the most appropriate decisions.We must discover by observation and experiment in nature how close real animals come to the ideal in their analysis of gains and losses. In order not to digress too far by giving some examples of subjective imagination, let us use the language of genes again for a moment.A living body is a machine programmed by the genes that survive.The genes that survive do so under certain conditions.These conditions, generally speaking, tend to characterize the former environment of the species.Estimates of gains and losses are thus based on past experience, just as humans make decisions.However, the experience mentioned here has the special meaning of gene experience, or more specifically, the conditions of previous gene survival (since genes also endow survival machines with the ability to learn, we can say that some estimates of gains and losses may also be based on individual experience).As long as conditions do not change dramatically, these estimates are reliable, and survival machines generally tend to make correct decisions.If conditions change drastically, a survival machine often makes bad decisions, and its genes pay the price.Humans, too, make decisions based on outdated data that are more likely to be wrong. Estimates of kinship can also be erroneous and unreliable.In some of our simplified calculations above, survival machines were said to know who was related to them, and how close that relationship was.In actual life it is sometimes possible to know exactly what is going on in this respect, but in general affinity can only be estimated as an average.For example, we assume that A and B may be half-brothers or half-brothers, or they may be full-brothers.The kinship index between them is 1/4 or 1/2. Since we cannot be sure of their exact relationship, the effective index available is their average, ie 3/8.If it is certain that they were all born to one mother, but the probability of being born to one father is only 1/10, then the probability of them being half brothers is 90% and the probability of full brothers is 10%, so valid The exponent is one/ten X one/two + nine/ten X one/four =.Two hundred and seventy-five. But when we say the probability is ninety percent, who made that estimate?Do we mean a human naturalist long engaged in field studies, or do we mean the animals themselves?If you happen to be lucky, the results of the two estimates may not be very different.To understand this, we have to consider how animals estimate who their closest relatives are in real life. We know who our relatives are because we are told, because we have names for them, because we are in the habit of officially marrying, and because we have records and a good memory.Many social anthropologists are concerned with kinship in the societies they study.They are not referring to true genetic kinship but to subjective, bred notions of kinship.Human customs and tribal rituals often emphasize kinship; ancestor worship is widespread, and family obligations and loyalties dominate human life.Clan vendettas and inter-family feuds are easily explained on the basis of Hamiltonian genetics.The incest taboo suggests a deep sense of kinship in humans, although the genetic benefits of the incest taboo have nothing to do with altruism.It is presumably related to the deleterious effects of recessive genes that inbreeding can produce. (For some reason, many anthropologists dislike this explanation.) How can wild beasts know who their kin are?In other words, what code of conduct do they follow to obtain what appears to be knowledge of kinship indirectly?To propose the maxim of being kin-friendly means making an argument based on unproven assumptions, since in fact the question of how to identify kin is unresolved.The beasts must have taken from their genes a simple rule of action: a rule that does not involve a full knowledge of the ultimate goal of action, but is practicable, at least under ordinary conditions.We humans are not alien to codes, which are so binding that if we are short-sighted, we blindly obey them even when we clearly see that they are not good for us or anyone else .例如，一些信奉正教的猶太人或伊斯蘭教徒情願餓死而不違反不吃豬肉的準則。在正常的情況下，野獸可以遵循什麼樣的準則以便間接地使它們的近親受益呢？ 如果動物傾向於對外貌和它們相像的個體表現出利他行為，它們就可能間接地為其親屬做一點好事。當然這在很大程度上要取決於有關物種的具體情況。不管怎樣，這樣一條準則會導致僅僅是統計學上的正確的決定。如果條件發生變化，譬如說，如果一個物種開始在一個大得多的類群中生活，這樣的準則就可能導致錯誤的決定。可以想像，人們有可能把種族偏見理解為是對親屬選擇傾向不合理地推而廣之的結果：即把外貌和自己相像的個體視為自己人、並歧視外貌和自己不同的個體的傾向。 在一個其成員不經常遷居或僅在小群體中遷居的物種中，你偶然遇到的任何個體很可能是你的相當接近的近親。在這樣的情況下，對你所遇見的這個物種的任何成員一律以禮相待這條準則可能具有積極的生存價值，因為凡能使其個體傾向於遵循這條準則的基因，可能會在基因庫中興旺起來。經常有人提到猴群和鯨群中的利他行為，道理即在於此。鯨魚和海豚如果呼吸不到空氣是要淹死的。幼鯨以及受傷的鯨魚有時無力游上水面，為了援救它們，鯨群中的一些同伴就會把它們托出水面。有人曾目睹過這種情景。鯨魚是否有辦法識別它們的近親，我們無從知道，但這也許無關緊要，情況可能是，鯨群中隨便哪一條都可能是你的近親，這種總的概率是如此之大，使利他行為成為一種合算的行為。順便提一下，曾經發生過這樣一件事：一條野生海豚把一個在游泳的快要淹死的人救了起來，這個傳聞據說非常可靠。這種情況我們可以看作是魚群錯誤地運用了援救快要淹死的成員這條準則。按照這條準則的定義，魚群裡快要淹死的成員可能是這樣的：掙扎在接近水面處一條長長的快要窒息的東西。 據說成年的狒狒為了保護它的夥伴免受豹子之類食肉獸的襲擊而甘冒生命的危險。一般說來，一隻成年的雄狒狒大概有相當多的基因儲存在其他狒狒體內。一個基因如果這樣說：喂，如果你碰巧是一個成年的雄狒狒，你就得保衛群體，打退豹子的進攻，它在基因庫中會興旺起來。許多人喜歡引用這個例子；但在這裡，我認為有必要補充一句，至少有一個受到尊敬的權威人士所提供的事實同此卻大有逕庭。據她說，一旦豹子出現，成年雄狒狒總是第一個逃之夭夭。 雛雞喜歡跟著母雞在雞群中覓食。它們的叫聲主要有兩種。除了我上面提到過的那種尖銳的吱吱聲外，它們在啄食時會發出一種悅耳的嘁嘁喳喳聲。吱吱聲可以喚來母雞的幫助，但其他雛雞對這種吱吱聲卻毫無反應。另一方面，嘁嘁喳喳聲能引起其他小雞的注意。就是說，一隻雛雞找到食物後就會發出嘁嘁喳喳聲把其他的雛雞喚來分享食物。按照前面假設的例子，嘁嘁喳喳聲就等於是有食物的叫聲。像那個例子一樣，雛雞所表現的明顯的利他行為可以很容易地在近親選擇的理論裡找到答案。在自然界裡，這些雛雞都是同胞兄弟姐妹。操縱雛雞在發現食物時發出嘁嘁喳喳聲的基因會擴散開來，只要這只雛雞由於發出叫聲後承擔的風險少於其他雛雞所得淨收益的一半就行了。由於這種淨收益由整個雞群所共享，而雞群的成員在一般情況下不會少於兩隻，不難想見，其中一隻在發現食物時發出叫聲總是合算的。當然，在家裡或農場裡，養雞的人可以讓一隻母雞孵其他母雞的蛋，甚至火雞蛋或鴨蛋。這時，這條準則就不靈了。但母雞和它的雛雞都不可能發覺其中底細的。它們的行為是在自然界的正常條件影響下形成的，而在自然界裡，陌生的個體通常是不會出現在你的窩裡的。 不過，在自然界裡，這種錯誤有時也會發生。在那些群居的物種中，一隻怙恃俱失的幼獸可能被一隻陌生的雌獸所收養，而這只雌獸很可能是一隻失去孩子的母獸。猴子觀察家往往把收養小猴子的母猴稱為阿姨。在大多數情況下，我們無法證明它真的是小猴子的阿姨或其他親屬。如果猴子觀察家有一點基因常識的話，他們就不會如此漫不經心地使用像阿姨之類這樣重要的稱呼。收養幼獸的行為儘管感人至深，但在大多數情況下我們也許應該把這種行為視為一條固有準則的失靈。這是因為這只慷慨收養孤兒的母獸並不給自己的基因帶來任何好處。它在浪費時間和精力，而這些時間和精力本來是可以花在它自己的親屬身上，尤其是它自己未來的兒女身上。這種錯誤大概比較罕見，因此自然選擇也認為不必操心去修訂一下這條準則，使母性具有更大的選擇能力。再說，這種收養行為在大多數情況下並不常見，孤兒往往因得不到照顧而死去。 有一個有關這種錯誤的極端例子，也許你可能認為與其把它視為違反常情的例子，倒不如把它視為否定自私基因理論的證據。有人看見過一隻失去孩子的母猴偷走另外一隻母猴的孩子，並撫養它。在我看來，這是雙重的錯誤，因為收養小猴的母猴不但浪費自己的時間，它也使一隻與之競爭的母猴得以卸掉撫養孩子的重擔，從而能更快地生育另一隻小猴子。我認為，這個極端的例子值得我們徹底探究。我們需要知道這樣的情況具有多大的普遍性，收養小猴的母猴和小猴之間的平均親緣關係指數是多少；這個小猴的親生母親的態度怎樣它們的孩子竟會被收養畢竟對它有好處；母猴是不是故意蒙哄憨直的年輕雌猴，使之樂於撫養它們的孩子？（也有人認為收養或誘拐小猴子的雌猴可以從中獲得可貴的撫養小孩的經驗。） 另外一個蓄意背離母性的例子，是由布谷烏及其他寄孵鳥（brood-parasites）在其他鳥窩生蛋的鳥提供的。布谷鳥利用鳥類親代本能地遵守的一條準則：對坐在你窩裡的任何小鳥以禮相待。且莫說布谷鳥，這條準則在一般情況下是能夠產生其預期效果的，即把利他行為的受益者局限在近親的範圍之內；這是因為鳥窩事實上都是孤立的，彼此之間總有一段距離，在你自己窩裡的幾乎可以肯定是你生育的小鳥。成年的鯖鷗（herring gulls）不能識別自己所生的蛋，它會愉快地伏在其他海鷗的蛋上，有些做試驗的人甚至以粗糙的土製假蛋代替真蛋，它也分辨不出，照樣坐在上面。在自然界，蛋的識別對海鷗而言並不重要，因為蛋不會滾到幾碼以外的鄰居的鳥窩附近。不過，海鷗還是識別得出它所孵的小海鷗。和蛋不一樣，小海鷗會外出溜躂，弄得不好，可能會走到大海鷗的窩附近，常常因此斷送了性命。這種情況在第一章裡已經述及。 另一方面，海鳩卻能根據蛋上小斑點的式樣來識別自己的蛋。在孵卵時，它們對其他鳥類的蛋絕不肯一視同仁。這大概由於它們築巢於平坦的岩石之上，蛋滾來滾去有混在一起的危險。有人可能要問，它們孵蛋時為什麼要區別對待呢？如果每一隻鳥都不計較這是誰家的蛋，只要有蛋就孵，結果還不是一樣嗎？這其實就是群體選擇論者的論點。試設想一下，如果一個把照管小鳥作為集體事業的集團得到發展，結果會怎樣呢？海鳩平均每次孵一卵，這意味著一個集體照管小鳥的集團如果要順利發展，那麼每一隻成年的海鳩都必須平均孵一隻蛋。假使其中一隻弄虛作假，不肯孵它那隻蛋，它可以把原來要花在孵蛋上的時間用於生更多的蛋，這種辦法的妙處在於，其他比較傾向於利他行為的海鳩自然會代它照管它的蛋。利他行為者會忠實地繼續遵循這條準則：如果在你的鳥窩附近發現其他鳥蛋，把它拖回來並坐在上面。這樣，欺騙基因得以在種群中興旺起來，而那些助人為樂的代管小鳥的集團最終要解體。 有人會說，如果是這樣的話，誠實的鳥可以採取報復行動，拒絕這種敲詐行為，堅決每次只孵一蛋，絕不通融。這樣做應該足以挫敗騙子的陰謀，因為它們可以看到自己的蛋依然在岩石上，其他的鳥都不肯代勞孵化。它們很快就會接受教訓，以後要老實一些。可惜的是，事情並不是這樣。根據我們所作的假設，孵蛋的母鳥並不計較蛋是誰家生的，如果誠實的鳥把這個旨在抵制騙子的計劃付諸實施的話，那些無人照管的蛋既可能是騙子的蛋，但同樣也可能是它們自己的蛋。在這種情況下，騙子還是合算的，因為它們能生更多的蛋從而使更多的後代存活下來。誠實的海鳩要打敗騙子的唯一辦法是：認真區分自己的蛋和其他的鳥蛋，只孵自己的蛋。也就是說，不再做一個利他主義者，僅僅照管自己的利益。 用史密斯的話來說，利他的收養策略不是一種進化上的穩定策略。這種策略不穩定，因為它比不上那種與之匹敵的自私策略。這種自私策略就是生下比其他鳥來得多的蛋，然後拒絕孵化它們。但這種自私的策略本身也是不穩定的，因為它所利用的利他策略是不穩定的，因而最終必將消失。對一隻海鳩來說，唯一具有進化意義的穩定策略是識別自己的蛋，只孵自己的蛋，事實正是這樣。 經常受到布谷鳥的寄生行為之害的一些鳴禽種類作出了反擊。但它們並不是學會了從外形上識別自己的蛋，而是本能地照顧那些帶有其物種特殊斑紋的蛋。由於它們不會受到同一物種其他成員的寄生行為之害，這種行為是行之有效的。但布谷鳥反過來也採取了報復措施，它們所生的蛋在色澤上、體積上和斑紋各方面越來越和寄主物種的相像。這是個欺詐行為的例子，這種行徑經常取得成效。就布谷鳥所生的蛋而言，這種形式的進化上的軍備競賽導致了擬態的完美無缺。我們可以假定，這些布谷鳥的蛋和小布谷鳥當中會有一部分被識破，但未被識破的那部分畢竟能存活並生下第二代的布谷鳥蛋。因此，那些操縱更有效的欺詐行為的基因在布谷鳥的基因庫中興旺起來。同樣，那些目光敏銳，能夠識別布谷鳥蛋的擬態中任何細小漏洞的寄主鳥類就能為它們自己的基因庫作出最大的貢獻。這樣，敏銳的、懷疑的目光就得以傳給下一代。這是個很好的例子，它說明自然選擇如何能夠提高敏銳的識別力，在我們這個例子裡，另一個物種的成員正竭盡所能，企圖蒙蔽識別者，而自然選擇促進了針對這種蒙蔽行為的識別力。 現在讓我們回過頭來對兩種估計進行一次比較：第一種是一隻動物對自己與群體其他成員之間的親緣關係的估計；第二種是一位從事實地研究的內行的博物學家對這種親緣關係的估計。伯特倫（B．Bertram）在塞侖格提國家公園研究獅子生態多年。以他在獅子生殖習慣方面的知識為塞礎，他對一個典型獅群中各個體之間的平均親緣關係進行了估計。他是根據如下的事實進行估計的：一個典型的獅群由七隻成年母獅和兩隻成年雄獅組成。母獅是獅群中比較穩定的成員，雄獅是流動的，經常由一個獅群轉到另一個獅群。這些母獅中約有一半同時產仔並共同撫育出生的幼獅。因此，很難分清哪一隻幼獅是哪一隻母獅生的。一窩幼獅通常有三隻，獅群中的成年雄獅平均分擔做父親的義務。年輕的母獅留在獅群中，代替死去的或出走的老母獅。年輕的雄獅一到青春期就被逐出家門。它們成長後三三兩兩結成一夥，到處流浪，從一個獅群轉到另外一個獅群，不大可能再回老家。 以這些事實以及其他假設為依據，你可以看到我們有可能算出一個典型獅群中兩個個體之間的親緣關係的平均指數。伯特倫演算的結果表明，任意挑選的一對雄獅的親緣關係指數是．二十二，一對母獅是．十五。換句話說，屬同一獅群的雄獅平均比異父或異母兄弟的關係稍為疏遠一些，母獅則比第一代堂姐妹接近一些。 當然，任何一對個體都可能是同胞兄弟，但伯特倫無從知道這一點，獅子自己大概也不會知道。另一方面，伯特倫估計的平均指數，在某種意義上說，獅子是有辦法知道的。如果這些指數對一個普通的獅群來說真的具有代表性，那麼，任何基因如能使雄獅自然傾向於以近乎對待其異父或異母兄弟的友好方式對待其他雄獅，它就具有積極的生存價值。任何做得過分的基因，即以更適合於對待其同胞兄弟那樣的友好方式對待其他雄獅的話，在一般情況下是要吃虧的，正如那些不夠友好的，把其他雄獅當作第二代堂兄弟那樣對待的雄獅到頭來也要吃虧一樣。如果獅子確實像伯特倫所講的那樣生活，而且這一點也同樣重要它們世世代代一直是這樣生活的，那麼，我們可以認為，自然選擇將有利於適應典型獅群的平均親緣關係那種水平的利他行為。我在上面講過，動物對親緣關係的估計和內行的博物學家的估計到頭來是差不多的，我的意思就在於此。 我們因此可以得出這樣的結論：就利他行為的演化而言，真正的親緣關係的重要性可能還不如動物對親緣關係作出的力所能及的估計。懂得這個事實就懂得在自然界中，父母之愛為什麼比兄弟／姐妹之間的利他行為普遍得多而且真誠得多，也就懂得為什麼對動物而言其自身利益比甚至幾個兄弟更為重要。簡單地說，我的意思是，除了親緣關係指數以外，我們還要考慮肯定性的指數。儘管父母／子女的關係在遺傳學的意義上說，並不比兄弟／姐妹的關係來得密切，它的肯定性卻大得多。在一般情況下，要肯定誰是你的兄弟就不如肯定誰是你的子女那麼容易。至於你自己是誰，那就更容易肯定了。 我們已經談論過海鳩之中的騙子，在以後的幾章裡，我們將要談到說謊者、騙子和剝削者。在這個世界上，許多個體為了本身的利益總是伺機利用其他個體的親屬選擇利他行為，因此，一個生存機器必須考慮誰可以信賴，誰確實是可靠的。如果B確實是我的小弟弟，我照顧它時付出的代價就該相當於我照顧自己時付出的代價的一半，或者相當於我照顧我自己的孩子時付出的代價。但我能夠像我肯定我的兒子是誰那樣肯定它是我的小弟弟嗎？我如何知道它是我的小弟弟呢？ 如果C是我的同卵孿生兄弟，那我照顧它時付出的代價就該相當於我照顧自己的任何一個兒女的兩倍，事實上，我該把它的生命看作和我自己的生命一樣重要。但我能肯定它嗎？當然它有點像我，但很可能我們碰巧共有同樣的容貌基因。不，我可不願為它犧牲，因為它的基因有可能全部和我的相同，但我肯定知道我體內的基因全部是我的。因此，對我來說，我比它重要。我是我體內任何一個基因所能肯定的唯一的一個個體。再說，在理論上，一個操縱個體自私行為的基因可以由一個操縱個體利他行為，援救至少一個同卵孿生兄弟或兩個兒女或兄弟或至少四個孫子孫女等的等位基因所代替，但操縱個體自私行為的基因具有一個巨大的優越條件，那就是識別個體的肯定性。與之匹敵的以親屬為對象的利他基因可能搞錯對象，這種錯誤可能純粹是偶然的，也可能是由騙子或寄生者蓄意製造的。因此，我們必須把自然界中的個體自私行為視為是不足為奇的，這些自私行為不能單純用遺傳學上的親緣關係來解釋。 在許多物種中，做母親的比做父親的更能識別誰是它們的後代。母親生下有形的蛋或孩子。它有很好的機會去認識它自己的基因傳給了誰。而可憐的爸爸受騙上當的機會就大得多。因此，父親不像母親那樣樂於為撫養下一代而操勞，那是很自然的。在第九章即《兩性之間的爭鬥》那一章裡，我們將看到造成這種情況還有其他的原因。同樣，外祖母比祖母更能識別誰是它的外孫或外孫女，因此，外祖母比祖母表現出更多的利他行為是合乎情理的。這是因為它能識別它的女兒的兒女。外祖父識別其外孫或外孫女的能力相當於祖母，因為兩者都是對其中一代有把握而對另一代沒有把握。同樣舅舅對外甥或外甥女的利益應比叔父或伯父更感關切。在一般情況下，舅舅應該和姑母一樣表現出同樣程度的利他行為。確實，在不貞行為司空見慣的社會裡，舅舅應該比父親表現出更多的利他行為，因為它有更大的理由信賴同這個孩子的親緣關係。它知道孩子的母親至少是它的異父或異母姐妹。合法的父親卻不明真相。我不知道是否存在任何證據，足以證明我提出的種種臆測。但我希望，這些臆測可以起到拋磚引玉的作用，其他的人可以提供或致力於搜集這方面的證據。特別是，社會人類學家或許能夠發表一些有趣的議論吧。 現在回過頭來再談談父母的利他行為比兄弟之間的利他行為更普遍這個事實。看來我們從識別問題的角度來解釋這種現象的確是合理的，但對存在於父母／子女關係本身的根本的不對稱性卻無法解釋。父母愛護子女的程度超過子女愛護父母的程度，儘管雙方的遺傳關係是對稱的，而且親緣關係的肯定性對雙方來說也是一樣的。一個理由是父母年齡較大，生活能力較強，事實上處於更有利的地位為其下一代提供幫助。一個嬰孩即使願意飼養其父母，事實上也沒有條件這樣做。 在父母／子女關係中還有另一種不對稱性，而這種不對稱性不適用於兄弟／姐妹的關係。子女永遠比父母年輕。這種情況常常，如果不是永遠，意味著子女的估計壽命較長。正如我在上面曾強調指出的那樣，估計壽命是個重要的變量。在最最理想的環境裡，一隻動物在演算時應考慮這個變量，以決定是否需要表現出利他行為。在兒童的平均估計壽命比父母長的物種裡，任何操縱兒童利他行為的基因會處於不利地位，因為這些基因所操縱的利他性自我犧牲行為的受益者都比利他主義者自己的年齡大，更近風燭殘年。在另一方面，就方程式中平均壽命這一項而言，操縱父母利他行為的基因則處於相對的有利地位。 我們有時聽到這種說法：親屬選擇作為一種理論是無可非議的，但在實際生活中，這樣的例子卻不多見。持這種批評意見的人只能說是對何謂親屬選擇一無所知。事實上，諸如保護兒童、父母之愛以及有關的身體器官、乳分泌腺、袋鼠的肚囊等等都是自然界裡親屬選擇這條原則在起作用的例子。批評家們當然十分清楚父母之愛是普遍存在的現象，但他們不懂得父母之愛和兄弟／姐妹之間的利他行為同樣是親屬選擇的例子。當他們說他們需要例證的時候，他們所要的不是父母之愛的例證，而是另外的例證。應該承認，這樣的例子是不那麼普遍的。我也曾提出過發生這種情況的原因。我本來可以把話題轉到兄弟／姐妹之間的利他行為上事實上這種例子並不少。但我不想這樣做。因為這可能加深一個錯誤的概念（我們在上面已經看到，這是威爾遜贊成的概念）即親屬選擇具體地指父母／子女關係以外的親緣關係。 這個錯誤概念之所以形成主要有其歷史根源。父母之愛有利於進化之處顯而易見。事實上我們不必等待漢密爾頓指出這一點。自達爾文的時代起，人們就開始理解這個道理。當漢密爾頓證明其他的親緣關係也具有同樣的遺傳學上的意義時，他當然要把重點放在這些其他的關係上。特別是他以螞蟻、蜜蜂之類的群居昆蟲為例。在這些昆蟲裡，姐妹之間的關係特別重要，我們以後還要談到這個問題。我甚至聽到有些人說，他們以為漢密爾頓的學說僅僅適用於昆蟲！ 如果有人不願意承認父母之愛是親屬選擇行為的一個活生生的例子，那就該讓他提出一個廣義的自然選擇學說，這個學說在承認存在父母的利他行為的同時卻不承認存在旁系親屬之間的利他行為。我想他是提不出這樣的學說的。