Chapter 8 Chapter 6 Genetic Morality

What is the selfish gene?It's not just a single, tangible piece of DNA.As in the primordial soup, it is all copies 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 rather 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 cancer.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 actors.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 for a gene to arise that confers on an individual a distinctly visible external "mark" such as pale skin, a green beard, or something else striking, and Tendency to be particularly friendly towards other individuals bearing these signs.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 "recognizes" 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, "Hey! If A tries to rescue a drowning person and he's about to sink, jump down and save A" that gene would thrive in the gene pool because most of the 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 quite as outlandish as the green beard, it's still a little 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 thought that this is apparently the reason why altruistic behavior of parents towards offspring is so common, Fisher, Haldane (J. BS Haldane), especially Hamilton.The same applies to other close relatives - brothers, sisters, nephews and nieces and cousins.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.

The term "substantial" is 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 two major 1970 editions of textbooks on individual ecology didn't 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.We don't need to explain the reason why the gene pool does not form albino, which is obviously a "good" gene, so it has 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.

Assuming you have one copy of the gene G in your body, this copy must have been inherited from your father or mother (for convenience, we ignore all kinds of unusual possibilities-such as G is a new variant, or Both of your 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 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 relationship between parent and offspring is always 1/2, 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 3, 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 distance is 1+2=3. 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, multiply several 1/2 by itself.The resulting product is the kinship index.If the generation distance is 3, then the index is 1/2X1/2X1/2 or (1/2)^3; if the generation distance calculated through a common ancestor is 9, the kinship index of that part of the ancestor is (1/2)^9. 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-generation cousins ​​have two common ancestors, and their generation distance from each ancestor is 4, so their relatedness index is 2(1/2)^4 = 1/8.If A is a great-grandson of B, the generation distance is 3, and the number of common "ancestors" is 1 (that is, B itself), so the exponent is 1X(1/2)^3=1/8.In terms of genetics, your first cousin is the equivalent of a great-grandchild.Similarly, you are "like" your uncle [kinship is 2X(1/2)^3=1/4] and you are "like" your grandfather [kinship is 1X(1/2)^2=1 /4] are equal. As for the kinship as far as third-generation cousins ​​or sisters [2X[(1/2)^8=1/128], it should be close to the lowest probability, which is equivalent to any individual in the population having a certain possibility of a gene.A third-generation cousin is about as closely related to an altruistic gene as a complete stranger.A second-generation cousin (kinship 1/32) is slightly special, a first-generation cousin is somewhat special (1/8), siblings, parents and children are very special (1/2), Identical twin siblings (1) are exactly like themselves.Uncles and uncles, nephews and nieces or nieces, grandparents and grandchildren, half-brothers and half-sisters are 1/4. 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 just as concerned about the welfare of that twin brother or sister as he is concerned about his own.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 relatedness index of the little brother and the child is exactly the same, that is, 1/2.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.EOW Wilson's Sociobiology: A New Synthesis, an excellent work in every respect, presents 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 by 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 does not suggest that an animal should behave altruistically towards all its "family members" and be selfish 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 that second-generation cousins ​​can accept 1/16 as much altruistic behavior as children or brothers.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 have 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 "saving" behaviors must be replaced by statistical risks of 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 are trying to save will all die someday. Every individual has an "estimated life expectancy" estimated by an insurance statistician, although this estimate may have errors.If you have two equally close blood relatives, one of whom is dying and the other a young man, saving the life of the latter will have more impact on the future gene pool than saving the life of the former. Come 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" instead of "estimated lifespan", or, more strictly, we could use "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 don't have time to do the calculations in doing this (at very little risk to myself) who might be drowning." But: Haldane is well aware, too, that luckily we don't need to assume survival The machine performs these calculations consciously in its own mind.Just as we use a slide rule without realizing that we are actually working with logarithms.Animals may be so born that they behave as if they had performed a complex calculation. This situation is actually not difficult to imagine.When a person throws a ball high into the air and then catches it again, he seems to have solved a set of differential equations predicting the trajectory of the ball in advance.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's kinship index to himself is 1 (that is, he has 100% of his own genes—this is self-evident), all risks and benefits to him need not be discounted, that is, given All weights.In this way, the sum of each possible behavior pattern is roughly like this: the net benefit of the behavior pattern = benefit to self - risk to self + 1/2 benefit to brother - 1/2 risk to brother + 1/ 2 benefit to another brother - 1/2 risk to another brother + 1/8 benefit to cousin - 1/8 risk to cousin + 1/2 benefit to child - 1/2 risk to child 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 +6 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 "There's food" and tell the other animals what I've found?Who can hear me shout?Brother B (who is 1/2 related to me), cousins ​​C (who are 1/8 related) and D (who are not really related, so their relatedness index to me is so small that in fact can be used as 0).If I keep quiet, every mushroom I can eat gives me a net gain of +6, and eating them all is +18.If I yell "There's food," then I have to figure out how much net gain I have left.The eight mushrooms are divided into four equal parts. For me, the one I eat is equivalent to a net gain of +12, but the two mushrooms each eaten by my brother and cousin will also benefit me, because they have Same gene as me.In fact the total score is (1X12) + (1/2X12) + (1/8X12) + (0x12) = 19.5, and the net benefit from the selfish behavior is +18.Although the difference is small, the gains and losses are clear.So I'm going to yell "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.The actual situation is that the gene pool is full of genes that exert influence on the individual, and because of this influence, the individual acts as if he had performed this calculation 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 now eat at most one mushroom, the net benefit of yelling "There's food" will be much greater for me than 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.Therefore, "estimates" about gains and losses are 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 practice, it is sometimes possible to know exactly what is going on in this respect, but generally, he says, 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 available effective index is the 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 that they are half brothers is 90%, and the probability of full brothers is 10%, so it is valid The exponent is 1/10X1/2 +9/10X 1/4=0.275. But when we say the probability is 90%, 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 don't like this explanation.) How could wild animals "know" who their kin were?In other words, what code of conduct do they follow to obtain what appears to be knowledge of kinship indirectly?To put forward the maxim of "friendliness with kinship" means to base an argument on unproven assumptions, since in fact the question of how to identify kinship remains 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 .For example, some Orthodox Jews or Muslims would rather starve to death than violate the rule of not eating pork.What rules can wild beasts follow in order to indirectly benefit their next of kin under normal circumstances?If animals tend to show altruistic behavior toward individuals who look like them, they might indirectly be doing their kin a little favor.This of course depends to a large extent on the specific circumstances of the species concerned.In any case, such a criterion would lead to only statistically "correct" decisions.如果条件发生变化，譬如说，如果一个物种开始在一个大得多的类群中生活，这样的准则就可能导致错误的决定。可以想象，人们有可能把种族偏见理解为是对亲属选择倾向不合理地推而广之的结果：即把外貌和自己相象的个体视为自己人、并歧视外貌和自己不同的个体的倾向。 在一个其成员不经常迁居或仅在小群体中迁居的物种中，你偶然遇到的任何个体很可能是你的相当接近的近亲。在这样的情况下，"对你所遇见的这个物种的任何成员一律以礼相待"这条准则可能具有积极的生存价值，因为凡能使其个体倾向于遵循这条准则的基因，可能会在基因库中兴旺起来。经常有人提到猴群和鲸群中的利他行为，道理即在于此。鲸鱼和海豚如果呼吸不到空气是要淹死的。幼鲸以及受伤的鲸鱼有时无力游上水面，为了援救它们，鲸群中的一些同伴就会把它们托出水面。有人曾目睹过这种情景。鲸鱼是否有办法识别它们的近亲，我们无从知道，但这也许无关紧要，情况可能是，鲸群中随便哪一条都可能是你的近亲，这种总的概率是如此之大，使利他行为成为一种合算的行为。顺便提一下，曾经发生过这样一件事：一条野生海豚把一个在游泳的快要淹死的人救了起来，这个传闻据说非常可靠。这种情况我们可以看作是鱼群错误地运用了援救快要淹死的成员这条准则。按照这条准则的"定义"，鱼群里快要淹死的成员可能是这样的："挣扎在接近水面处一条长长的快要窒息的东西。"据说成年的狒狒为了保护它的伙伴免受豹子之类食肉兽的袭击而甘冒生命的危险。一般说来，一只成年的雄狒狒大概有相当多的基因储存在其他狒狒体内。一个基因如果这样"说"："喂，如果你碰巧是一个成年的雄狒狒，你就得保卫群体，打退豹子的进攻"，它在基因库中会兴旺起来。许多人喜欢引用这个例子；但在这里，我认为有必要补充一句，至少有一个受到尊敬的权威人士所提供的事实同此却大有径庭。据她说，一旦豹子出现，成年雄狒狒总是第一个逃之夭夭。 雏鸡喜欢跟着母鸡在鸡群中觅食。它们的叫声主要有两种。除了我上面提到过的那种尖锐的吱吱声外，它们在啄食时会发出一种悦耳的嘁嘁喳喳声。吱吱声可以唤来母鸡的帮助，但其他雏鸡对这种吱吱声却毫无反应。另一方面，嘁嘁喳喳声能引起其他小鸡的注意。就是说，一只雏鸡找到食物后就会发出嘁嘁喳喳声把其他的雏鸡唤来分享食物。按照前面假设的例子，嘁嘁喳喳声就等于是"有食物"的叫声。象那个例子一样，雏鸡所表现的明显的利他行为可以很容易地在近亲选择的理论里找到答案。在自然界里，这些雏鸡都是同胞兄弟姐妹。操纵雏鸡在发现食物时发出嘁嘁喳喳声的基因会扩散开来，只要这只雏鸡由于发出叫声后承担的风险少于其他雏鸡所得净收益的一半就行了。由于这种净收益由整个鸡群所共享，而鸡群的成员在一般情况下不会少于两只，不难想见，其中一只在发现食物时发出叫声总是合算的。当然，在家里或农场里，养鸡的人可以让一只母鸡孵其他母鸡的蛋，甚至火鸡蛋或鸭蛋。这时，这条准则就不灵了。但母鸡和它的雏鸡都不可能发觉其中底细的。它们的行为是在自然界的正常条件影响下形成的，而在自然界里，陌生的个体通常是不会出现在你的窝里的。 不过，在自然界里，这种错误有时也会发生。在那些群居的物种中，一只怙恃俱失的幼兽可能被一只陌生的雌兽所收养，而这只雌兽很可能是一只失去孩子的母兽。猴子观察家往往把收养小猴子的母猴称为"阿姨"。在大多数情况下，我们无法证明它真的是小猴子的阿姨或其他亲属。如果猴子观察家有一点基因常识的话，他们就不会如此漫不经心地使用象阿姨之类这样重要的称呼。收养幼兽的行为尽管感人至深，但在大多数情况下我们也许应该把这种行为视为一条固有准则的失灵。这是因为这只慷慨收养孤儿的母兽并不给自己的基因带来任何好处。它在浪费时间和精力，而这些时间和精力本来是可以花在它自己的亲属身上，尤其是它自己未来的儿女身上。这种错误大概比较罕见，因此自然选择也认为不必"操心"去修订一下这条准则，使母性具有更大的选择能力。再说，这种收养行为在大多数情况下并不常见，孤儿往往因得不到照顾而死去。 有一个有关这种错误的极端例子，也许你可能认为与其把它视为违反常情的例子，倒不如把它视为否定自私基因理论的证据。有人看见过一只失去孩子的母猴偷走另外一只母猴的孩子，并抚养它。在我看来，这是双重的错误，因为收养小猴的母猴不但浪费自己的时间，它也使一只与之竞争的母猴得以卸掉抚养孩子的重担，从而能更快地生育另一只小猴子。我认为，这个极端的例子值得我们彻底探究。我们需要知道这样的情况具有多大的普遍性，收养小猴的母猴和小猴之间的平均亲缘关系指数是多少；这个小猴的亲生母亲的态度怎样--它们的孩子竟会被收养毕竟对它有好处；母猴是不是故意蒙哄憨直的年轻雌猴，使之乐于抚养它们的孩子？（也有人认为收养或诱拐小猴子的雌猴可以从中获得可贵的抚养小孩的经验。）另外一个蓄意背离母性的例子，是由布谷鸟及其他"寄孵鸟"（brood-parasites）--在其他鸟窝生蛋的鸟--提供的。布谷鸟利用鸟类亲代本能地遵守的一条准则："对坐在你窝里的任何小鸟以礼相待。"且莫说布谷鸟，这条准则在一般情况下是能够产生其预期效果的，即把利他行为的受益者局限在近亲的范围之内；这是因为鸟窝事实上都是孤立的，彼此之间总有一段距离，在你自己窝里的几乎可以肯定是你生育的小鸟。成年的鲭鸥（herring gulls）不能识别自己所生的蛋，它会愉快地伏在其他海鸥的蛋上，有些做试验的人甚至以粗糙的土制假蛋代替真蛋，它也分辨不出，照样坐在上面。在自然界，蛋的识别对海鸥而言并不重要，因为蛋不会滚到几码以外的邻居的鸟窝附近。不过，海鸥还是识别得出它所孵的小海鸥。和蛋不一样，小海鸥会外出溜达，弄得不好，可能会走到大海鸥的窝附近，常常因此断送了性命。这种情况在第一章里已经述及。 另一方面，海鸠却能根据蛋上小斑点的式样来识别自己的蛋。在孵卵时，它们对其他鸟类的蛋绝不肯一视同仁。这大概由于它们筑巢于平坦的岩石之上，蛋滚来滚去有混在一起的危险。有人可能要问，它们孵蛋时为什么要区别对待呢？如果每一只鸟都不计较这是谁家的蛋，只要有蛋就孵，结果还不是一样吗？这其实就是群体选择论者的论点。试设想一下，如果一个把照管小鸟作为集体事业的集团得到发展，结果会怎样呢？海鸠平均每次孵一卵，这意味着一个集体照管小鸟的集团如果要顺利发展，那么每一只成年的海鸠都必须平均孵一只蛋。假使其中一只弄虚作假，不肯孵它那只蛋，它可以把原来要花在孵蛋上的时间用于生更多的蛋，这种办法的妙处在于，其他比较倾向于利他行为的海鸠自然会代它照管它的蛋。利他行为者会忠实地继续遵循这条准则："如果在你的鸟窝附近发现其他鸟蛋，把它拖回来并坐在上面。"这样，欺骗基因得以在种群中兴旺起来，而那些助人为乐的代管小鸟的集团最终要解体。 有人会说，"如果是这样的话，诚实的鸟可以采取报复行动，拒绝这种敲作行为，坚决每次只孵一蛋，绝不通融。这样做应该足以挫败骗子的阴谋，因为它们可以看到自己的蛋依然在岩石上，其他的鸟都不肯代劳孵化。它们很快就会接受教训，以后要老实一些。"可惜的是，事情并不是这样。根据我们所作的假设，孵蛋的母鸟并不计较蛋是谁家生的，如果诚实的鸟把这个旨在抵制骗子的计划付诸实施的话，那些无人照管的蛋既可能是骗子的蛋，但同样也可能是它们自己的蛋。在这种情况下，骗子还是合算的，因为它们能生更多的蛋从而使更多的后代存活下来。诚实的海鸠要打败骗子的唯一办法是：认真区分自己的蛋和其他的鸟蛋，只孵自己的蛋。也就是说，不再做一个利他主义者，仅仅照管自己的利益。 用史密斯的话来说，利他的收养"策略"不是一种进化上的稳定策略。这种策略不稳定，因为它比不上那种与之匹敌的自私策略。这种自私策略就是生下比其他鸟来得多的蛋，然后拒绝孵化它们。但这种自私的策略本身也是不稳定的，因为它所利用的利他策略是不稳定的，因而最终必将消失。对一只海鸠来说，唯一具有进化意义的稳定策略是识别自己的蛋，只孵自己的蛋，事实正是这样。 经常受到布谷鸟的寄生行为之害的一些鸣禽种类作出了反击。但它们并不是学会了从外形上识别自己的蛋，而是本能地照顾那些带有其物种特殊斑纹的蛋。由于它们不会受到同一物种其他成员的寄生行为之害，这种行为是行之有效的。但布谷鸟反过来也采取了报复措施，它们所生的蛋在色泽上、体积上和斑纹各方面越来越和寄主物种的相象。这是个欺诈行为的例子，这种行径经常取得成效。就布谷鸟所生的蛋而言，这种形式的进化上的军备竞赛导致了拟态的完美无缺。我们可以假定，这些布谷鸟的蛋和小布谷鸟当中会有一部分被"识破"，但未被识破的那部分毕竟能存活并生下第二代的布谷鸟蛋。因此，那些操纵更有效的欺诈行为的基因在布谷鸟的基因库中兴旺起来。同样，那些目光敏锐，能够识别布谷鸟蛋的拟态中任何细小漏洞的寄主鸟类就能为它们自己的基因库作出最大的贡献。 这样，敏锐的、怀疑的目光就得以传给下一代。这是个很好的例子，它说明自然选择如何能够提高敏锐的识别力，在我们这个例子里，另一个物种的成员正竭尽所能，企图蒙蔽识别者，而自然选择促进了针对这种蒙蔽行为的识别力。 现在让我们回过头来对两种估计进行一次比较：第一种是一只动物对自己与群体其他成员之间的亲缘关系的"估计"；第二种是一位从事实地研究的内行的博物学家对这种亲缘关系的估计。伯特伦（B.Bertram）在塞仑格提国家公园研究狮子生态多年。以他在狮子生殖习惯方面的知识为塞础，他对一个典型狮群中各个体之间的平均亲缘关系进行了估计。他是根据如下的事实进行估计的：一个典型的狮群由七只成年母狮和两只成年雄狮组成。母狮是狮群中比较稳定的成员，雄狮是流动的，经常由一个狮群转到另一个狮群。这些母狮中约有一半同时产仔并共同抚育出生的幼狮。因此，很难分清哪一只幼狮是哪一只母狮生的。一窝幼狮通常有三只，狮群中的成年雄狮平均分担做父亲的义务。年轻的母狮留在狮群中，代替死去的或出走的老母狮。年轻的雄狮一到青春期就被逐出家门。它们成长后三三两两结成一伙，到处流浪，从一个狮群转到另外一个狮群，不大可能再回老家。 以这些事实以及其他假设为依据，你可以看到我们有可能算出一个典型狮群中两个个体之间的亲缘关系的平均指数。伯特伦演算的结果表明，任意挑选的一对雄狮的亲缘关系指数是0.22，一对母狮是0．15。换句话说，属同一狮群的雄狮平均比异父或异母兄弟的关系稍为疏远一些，母狮则比第一代堂姐妹接近一些。 当然，任何一对个体都可能是同胞兄弟，但伯特伦无从知道这一点，狮子自己大概也不会知道。另一方面，伯特伦估计的平均指数，在某种意义上说，狮子是有办法知道的。如果这些指数对一个普通的狮群来说真的具有代表性，那么，任何基因如能使雄狮自然倾向于以近乎对待其异父或异母兄弟的友好方式对待其他雄狮，它就具有积极的生存价值。任何做得过分的基因，即以更适合于对待其同胞兄弟那样的友好方式对待其他雄狮的话，在一般情况下是要吃亏的，正如那些不够友好的，把其他雄狮当作第二代堂兄弟那样对待的雄狮到头来也要吃亏一样。 如果狮子确实象伯特伦所讲的那样生话，而且--这一点也同样重要--它们世世代代一直是这样生活的，那么，我们可以认为，自然选择将有利于适应典型狮群的平均亲缘关系那种水平的利他行为。我在上面讲过，动物对亲缘关系的估计和内行的博物学家的估计到头来是差不多的，我的意思就在于此。 我们因此可以得出这样的结论：就利他行为的演化而言，"真正的"亲缘关系的重要性可能还不如动物对亲缘关系作出的力所能及的估计。懂得这个事实就懂得在自然界中，父母之爱为什么比兄弟／姐妹之间的利他行为普遍得多而且真诚得多，也就懂得为什么对动物而言其自身利益比甚至几个兄弟更为重要。简单他说，我的意思是，除了亲缘关系指数以外，我们还要考虑"肯定性"的指数。尽管父母／子女的关系在遗传学的意义上说，并不比兄弟／姐妹的关系来得密切，它的肯定性却大得多。在一般情况下，要肯定谁是你的兄弟就不如肯定谁是你的子女那么容易。至于你自己是谁，那就更容易肯定了。 我们已经谈论过海鸠之中的骗子，在以后的几章里，我们将要谈到说谎者、骗子和剥削者。在这个世界上，许多个体为了本身的利益总是伺机利用其他个体的亲属选择利他行为，因此，一个生存机器必须考虑谁可以信赖，谁确实是可靠的。 如果B确实是我的小弟弟，我照顾它时付出的代价就该相当于我照顾自己时付出的代价的一半，或者相当于我照顾我自己的孩子时付出的代价。但我能够象我肯定我的儿子是谁那样肯定它是我的小弟弟吗？我如何知道它是我的小弟弟呢？如果C是我的同卵孪生兄弟，那我照顾它时付出的代价就该相当于我照顾自己的任何一个儿女的两倍，事实上，我该把它的生命看作和我自己的生命一样重要。 但我能肯定它吗？当然它有点象我，但很可能我们碰巧共有同样的容貌基因。不，我可不愿为它牺牲，因为它的基因有可能全部和我的相同，但我肯定知道我体内的基因全部是我的。因此，对我来说，我比它重要。我是我体内任何一个基因所能肯定的唯一的一个个体。再说，在理论上，一个操纵个体自私行为的基因可以由一个操纵个体利他行为，援救至少一个同卵孪生兄弟或两个儿女或兄弟或至少四个孙子孙女等的等位基因所代替，但操纵个体自私行为的基因具有一个巨大的优越条件，那就是识别个体的肯定性。与之匹敌的以亲属为对象的利他基因可能搞错对象，这种错误可能纯粹是偶然的，也可能是由骗子或寄生者蓄意制造的。因此，我们必须把自然界中的个体自私行为视为是不足为奇的，这些自私行为不能单纯用遗传学上的亲缘关系来解释。 在许多物种中，做母亲的比做父亲的更能识别谁是它们的后代。母亲生下有形的蛋或孩子。它有很好的机会去认识它自己的基因传给了谁。而可怜的爸爸受骗上当的机会就大得多。因此，父亲不象母亲那样乐于为抚养下一代而操劳，那是很自然的。在第九章即《两性之间的争斗》那一章里，我们将看到造成这种情况还有其他的原因。同样，外祖母比祖母更能识别谁是它的外孙或外孙女，因此，外祖母比祖母表现出更多的利他行为是合乎情理的。这是因为它能识别它的女儿的儿女。外祖父识别其外孙或外孙女的能力相当于祖母，因为两者都是对其中一代有把握而对另一代没有把握。同样舅舅对外甥或外甥女的利益应比叔父或伯父更感关切。在一般情况下，舅舅应该和勇母一样表现出同样程度的利他行为。确实，在不贞行为司空见惯的社会里，舅舅应该比"父亲"表现出更多的利他行为，因为它有更大的理由信赖同这个孩子的亲缘关系。它知道孩子的母亲至少是它的异父或异母姐妹。"合法的"父亲却不明真相。我不知道是否存在任何证据，足以证明我提出的种种臆测。但我希望，这些臆测可以起到抛砖引玉的作用，其他的人可以提供或致力于搜集这方面的证据。特别是，社会人类学家或许能够发表一些有趣的议论吧。 现在回过头来再谈谈父母的利他行为比兄弟之间的利他行为更普遍这个事实。看来我们从"识别问题"的角度来解释这种现象的确是合理的，但对存在于父母／子女关系本身的根本的不对称性却无法解释。父母爱护子女的程度超过子女爱护父母的程度，尽管双方的遗传关系是对称的，而且亲缘关系的肯定性对双方来说也是一样的。一个理由是父母年龄较大，生活能力较强，事实上处于更有利的地位为其下一代提供帮助。一个婴孩即使愿意饲养其父母，事实上也没有条件这样做。 在父母／子女关系中还有另一种不对称性，而这种不对称性不适用于兄弟／姐妹的关系。子女永远比父母年轻。这种情况常常，如果不是永远，意味着子女的估计寿命较长。正如我在上面曾强调指出的那样，估计寿命是个重要的变量。在最最理想的环境里，一只动物在"演算"时应考虑这个变量，以"决定"是否需要表现出利他行为。在儿童的平均估计寿命比父母长的物种里，任何操纵儿童利他行为的基因会处于不利地位，因为这些基因所操纵的利他性自我牺牲行为的受益者都比利他主义者自己的年龄大，更近风烛残年。在另一方面，就方程式中平均寿命这一项而言，操纵父母利他行为的基因则处于相对的有利地位。 我们有时听到这种说法：亲属选择作为一种理论是无可非议的，但在实际生活中，这样的例子却不多见。持这种批评意见的人只能说是对何谓亲属选择一无所知。事实上，诸如保护儿童、父母之爱以及有关的身体器官、乳分泌腺、袋鼠的肚囊等等都是自然界里亲属选择这条原则在起作用的例子。批评家们当然十分清楚父母之爱是普遍存在的现象，但他们不懂得父母之爱和兄弟／姐妹之间的利他行为同样是亲属选择的例子。当他们说他们需要例证的时候，他们所要的不是父母之爱的例证，而是另外的例证。应该承认，这样的例子是不那么普遍的。我也曾提出过发生这种情况的原因。我本来可以把话题转到兄弟／姐妹之间的利他行为上--事实上这种例子并不少。但我不想这样做。因为这可能加深一个错误的概念（我们在上面已经看到，这是威尔逊赞成的概念）--即亲属选择具体地指父母／子女关系以外的亲缘关系。 这个错误概念之所以形成主要有其历史根源。父母之爱有利于进化之处显而易见。事实上我们不必等待汉密尔顿指出这一点。自达尔文的时代起，人们就开始理解这个道理。当汉密尔顿证明其他的亲缘关系也具有同样的遗传学上的意义时，他当然要把重点放在这些其他的关系上。特别是他以蚂蚁、蜜蜂之类的群居昆虫为例。在这些昆虫里，姐妹之间的关系特别重要，我们以后还要谈到这个问题。我甚至听到有些人说，他们以为汉密尔顿的学说仅仅适用于昆虫！如果有人不愿意承认父母之爱是亲属选择行为的一个活生生的例子，那就该让他提出一个广义的自然选择学说，这个学说在承认存在父母的利他行为的同时却不承认存在旁系亲属之间的利他行为。我想他是提不出这样的学说的。