Helping and Genetic Relatedness
Helping can be defined as a voluntary act which directly or indirectly benefits an individual; the helper may be rewarded or unrewarded or pay a price for helping. In evolutionary psychology, for these forms of prosocial behavior the concept of altruism is used. Altruism differs from helping in that there is no expectation of a return. In other words, altruism is behavior which increases the fitness of the recipient at a cost to the actor (reducing the fitness of the actor), who does not expect to be rewarded (Barcaly 2011). Altruism is an evolutionary puzzle: a trait that appears to reduce the fitness of the individual who possess it. One would expect that natural selection operates against helping others at a cost to oneself, because such behavior probably reduces the resources the altruistic actor has available for survival or for reproduction. The mechanism by which altruism could have evolved is puzzling.
Hamilton was the first to demonstrate that a fitness-reducing trait could spread in populations if it had sufficient extended phenotypic effects; in other words if a trait produces beneficial outcomes for other members of the same species, who presumably possess the same trait due to genetic relatedness, it can be adaptive. Thus, Hamilton connected kinship to altruism, suggesting a new perspective on evolutionary success: inclusive fitness. The evolutionary success of a gene depends on the number of copies of itself it leaves in the next generation, i.e., the maximum number of viable, direct offspring of the individual possessing the gene. Hamilton argued that, to some extent, other members of the population share identical genes so a gene may also increase the number of its copies by indirect reproduction. More specifically, according to Hamilton our genetic relatives (e.g., not only parents, siblings but aunts, uncles, etc.) have the same version of genes or alleles we have in proportion to the ratio of our common ancestors. The support of the reproduction and survival of individuals who may possess the same genes (traits) as oneself (i.e., family members or genetic relatives) increases one’s evolutionary success. Without doubt close relatives or kin have the highest number of identical genes. Inclusive fitness can be defined as the result of the number of offspring produced directly by an individual plus his or her contribution to the reproductive success of genetic relatives (Hamilton 1964). For example, the alarm call of belding ground squirrels can be explained by this model. An individual squirrel gives an alarm call to warn others in the local group of the presence of a predator; this act puts the alarm-sounding squirrel at a disadvantage because the call signals its location to predators, increasing the likelihood that it will be killed; however, by sounding the alarm the squirrel protects its relatives and others in the local group. Belding’s ground squirrels live as groups of close genetic relatives, and in this context sounding the alarm can enhance the reproductive success of kin (who share the trait/gene for giving alarm calls) by protecting them from the predator, thus resulting in more offspring with the alarm-sounding trait in the next generation. Of course, altruistic behaviors are only favored by natural selection if they lead to more copies of the gene (trait) concerned being passed on than would be achieved by direct reproduction (Mateo 1996).
As well as developing the concept of inclusive fitness Hamilton suggested a formula to define the conditions under which altruism could spread in a population: C < r x B. This inequality is also known as Hamilton’s rule. C represents the cost of the altruistic individual, like time, effort, and resources utilized for helping, which limits the survivorship or reproduction of the helper. The recipient’s possible benefits derived from the altruistic act are represented with B and r is the degree of relatedness between actor (altruist) and recipient (individual in need). As explained above, kin probably share common genes, because they have one or more common ancestors or are ancestors or descendants of each other. Accordingly, the degree of relatedness is an arithmetic formula for the probability of sharing genes with relatives. In effect, Hamilton’s rule describes the two major factors defining the evolutionary consequences of kin altruism. Accordingly, altruism can be an evolutionarily stable strategy, if (1) the probability that the helper shares genes with the individual in need (r) is significant and (2) if the fitness benefit to the helped kin exceeds the fitness cost to the altruist (B > C) (Dawkins 1982).
Kinship is privileged in all cultures, and in certain cases (emergency situations) individuals will give precedence to even the weakest kinship bond over the most beneficial nonkin relationship. Nevertheless, altruism toward kin and reciprocity with nonkin may have common genetic roots because of their functional correspondence. Individuals have to recognize each other and remember the history of their relationship; consequently, humans have to be able to memorize individuals and discriminate them from others according to certain cues or features. Moreover, they have to remember previous outcomes of the relationship, that is, individuals have to be able to calculate the costs and benefits of that particular relationship. The evaluation of a relationship is affected by the frequency of social exchange with a particular individual. Frequent social exchange may lead to creation of a sense of familiarity, and familiarity implies genetic relatedness because in evolutionary environments close and distant relatives lived near to each other. This means that kin altruism is inherently error prone because of the difficulties of evaluating degree of relatedness as well as judging the costs and benefits of altruism, especially in emergency situations, when decisions have to be made rapidly (Burnstein 2005). This problem raises some important questions: How can we assess the benefits and costs of an altruistic act and how we evaluate degree of relatedness?
Hamilton (1964) also suggested the existence of evolved mechanisms enabling individuals to discriminate kin from nonkin. Subsequent work was dedicated to whether and how animals and humans recognize kin, even collateral kin (e.g., siblings, nieces, nephews, aunts, and uncles). These studies showed that humans are able to recognize kin but the interpretation of evidence is ambiguous, because it depends on how we define kin recognition. The broadest definition of kin recognition describes it as the facility for distinguishing kin from nonkin or recognizing kin. In the case of altruism, it is important to have reliable cues for identifying relatives and avoiding deceivers (think of the birds that care for a cuckoo’s chick because they use spatial signals to identify their own offspring, assuming “all chicks in my nest are my own”). Evaluations of genetic relatedness should be based on genetic similarity or on signals associated with kinship (Penn and Frommen 2010).
Estimating Genetic Similarity
Hamilton (1964) proposed that it was possible to evolve for a gene that is capable of recognizing copies of itself in other individuals and that such a gene would trigger behaviors designed to benefit individuals who shared it. This signaling function is also known as the green beard effect (Dawkins 1976). Thus, a greenbeard gene (1) produces a rare phenotypic trait (e.g., a green beard), (2) enables the recognition of that trait/phenotype in others, and (3) promotes altruistic behavior towards individuals carrying that trait. The evolution of such greenbeard genes is highly improbable, and it has in fact been observed in only a few species. This rarity is presumably because such genes are vulnerable to cheating: individuals may fake the phenotype in order to gain benefits without acting altruistically (Penn and Frommen 2010). Several mathematical simulations (e.g., Jansen and van Baalen 2006) have shown that genes enabling altruism must continuously change their phenotypical cues to avoid exploitation by defectors or social parasites. Thus, it is plausible to suggest that this continual alteration may lead to more stable evolutionary dynamics of greenbeard genes.
In addition to theoretical assumptions discussed above there are several studies with humans suggesting a genetic locus for kin recognition cues, namely the major histocompatibility complex (MHC), a group of genes that control immunological self/non-self-recognition and are thought to be associated with kin recognition mechanisms (Brown and Eklund 1994). Body odor is influenced by MHC genes, which differ between families, and may therefore act as a kin recognition label. In a double-blind study women were asked to rate T-shirts worn for a few days by men to indicate how attractive they found the men on the basis of their body odor. Women found men with different MHCs more attractive than men with more MHC similarity but only if they were ovulating. The reverse effect was found in women taking oral contraceptive, that is, the odor of MHC-similar men was rated more attractive than the odor of MHC-dissimilar males (Wedekind et al. 1995). Apparently, women are able to recognize nonkin men and find them desirable in cases where being genetically nonrelated reduces the chances of inbreeding. The reverse effect suggests that detecting MHC similarities facilitate the formation of cooperative bonds.
These findings suggest that evaluations of genetic relatedness are based, to varying degrees, on judgments of phenotypic similarity which involve comparison of a stimulus (e.g., the phenotype/trait of an individual) and a standard. Kin recognition mechanisms can be distinguished according to the source of the standard: familiarity or its ecological correlate, proximity requires that individuals memorize traits/phenotypes of kin and compare this memory trace with their perception of another person’s trait/phenotype in order to judge relatedness. Another mechanism, phenotype matching uses self-referential cues for the comparison between stimulus and standard. The individual develops a “kin template” based on phenotypic cues learned through self-observation or from relatives it was reared with. The phenotypic cues presented by others are compared with this kin template to make kin recognition judgments (Penn and Frommen 2010). Both these mechanisms require similar operations and templates derived from experience with others, self-observations or genetic programming. This means that in certain circumstances it is not possible to distinguish between the effects of greenbeard genes and familiarity or phenotype matching. For example, there is a greater genetic similarity in blood antigens between spouses than between randomly chosen couples, and likewise long-term friends have more similar blood antigens than unacquainted pairs (Holland 2012). However, individuals of similar ethnicity and nationality tend to live near one another, even in modern societies (Glazer 1975), and these cues (i.e., ethnicity and nationality) predict blood group and are associated with proximity, which is a reliable predictor of relationship choices, so spouses and friends could share the same blood type whether or not they are able to detect genetic relatedness.
Familiarity-Dependent Kin Recognition
In species where young individuals stay with parents and other family members during the first period of their life – as humans do – offspring learn kin phenotypes and use the information later on to recognize kin (e.g., Westermarck 1921). The Westermarck effect was the demonstration of this kind of discrimination in humans: children who live in close proximity during the first few years of life become negatively imprinted and consequently in adulthood they reject each other as sexual partners.
There is a large body of evidence suggesting that social learning influences human kin recognition, principally in where matching abstract, alterable phenotypes such as personality traits is concerned. Some studies have shown that infants are able to identify kin even after limited experience: they can distinguish the voices of their mother and an unrelated woman a day after birth. Several weeks after birth infants are able to discriminate between their mother and unrelated women on the basis of their faces while mothers can identify their child from a set of photographs five hours after birth (see Bjorklund and Pellegrini 2002 for a review).
The other group of kin recognition mechanisms is based on evaluation of self-resemblance, i.e., individuals compare the cues presented by others with their own cues for a given trait. The most salient social cues for humans are facial characteristics, and it is therefore assumed that facial resemblance plays an importance role in the detection of genetic relatedness.
Studies investigating the effects of facial resemblance use facial morphing techniques, such as merging images of two different faces to give a “compound face” (i.e., a morph) that shares features of both original faces. Facial morphs which are intermediate between the two original faces enable researchers to compare the impact of self-morphs (i.e., composite faces combining the subject’s face and a stranger’s face) and non-self-morphs (i.e., compound faces combining the facial features of two strangers) on social judgments. A considerable body of experimental evidence confirms that individuals are able to detect self-resemblance in faces and that they treat such faces differently; subjects trust self-morphs more than non-self-morphs, even when the non-self-morph is familiar. Facial morphs of celebrities provide familiarity but no self-resemblance. Subjects favor self-resembling morphs over non-self-resembling faces and even over familiar non-self-morphs (DeBruine 2002). Moreover, Bressan and Zucchi (2009) found that both dizygotic (DZ) and monozygotic (MZ) twins preferred self-morphs over morphs based on the face of their twin.
Assessing Costs and Benefits of Altruism
Several factors were identified to have influence on fitness costs and benefits of helping. For example, helping only occurs, if the actor has available resources or control over required resources or skills. Another significant factor is the value of the recipient, which is defined by several characteristics of the individual (e.g., age, sex, status, etc.). Accordingly, for example, age of the recipient can change the cost-benefit ratio: Older individuals have less capacity and opportunities to use help efficiently and convert to reproductive success than younger individuals. Consequently, evaluating cost and benefits depends on contextual parameters and on the characteristics of the recipient (Kurland and Gauiln 2005).
Field studies have provided some evidence for the existence of kin altruism, showing, for example, that genetic relatedness influences resource distribution: For example, when fishermen divide their catch they give a bigger share to close relatives than to others (see Burnstein 2005 for more examples). Nevertheless, beside field observations, experimental analyses could provide some insight into the proximate mechanisms to evaluate the ability of individuals to benefit the group and their willingness to help/cooperate.
The prisoner’s dilemma (PD) is an experimental game used as a model for cooperative behavior (and other real-life interpersonal situations). In a basic PD, two interacting individuals (A and B) have to decide whether to cooperate or betray and the amount of money they win will depend on the decisions both parties make. If A and B both betray each other both lose a moderate amount of money; if one of them betrays and the other offers cooperation the betrayer will win a certain amount of money while the cooperator loses more than in the previous scenario (betray-betray); if both opt to cooperate they will both win a modest amount. Most studies use an iterative PD in which the same individuals play each other repeatedly as thus have opportunities to punish the other player for his or her previous decisions. It has been shown that the most effective strategy is “tit-for-tat”(TFT), i.e., making the decision one’s partner made in the previous round. The evidence suggests that in most cases individuals display a systematic bias towards cooperative behavior, which is not compatible with the predictions of a simple model of self-interested action (Nowak and Highfield 2011; Stewart and Plotkin 2012). Hamilton’s inclusive fitness theory predicts that PD pairs should be more trusting and cooperative if they are genetically related. Studies on facial resemblance provide some indirect support for this (e.g., studies of DeBruine 2002): Subjects were more trusting and altruistic towards self-morphs than non-self-morphs. A study by Segal and Hershberger (1999) provided more direct evidence of cooperation between kin. They compared the performance of MZ and DZ twins in PD game and found that MZ pairs exhibited noticeably more cooperation than DZ pairs. In general, familiarity encourages individuals to display trust and altruism in individuals: For example, subjects judgments about whether a person is typically altruistic or not were improved if they had watched a video clip of that person telling the Little Red Riding Hood story, which created familiarity (experiment 1 in Brown et al. 2003).
Other studies have shown that genetic relatedness has a systematic impact on assessments of the costs and benefits of altruism. Generally, higher genetic relatedness is associated with a higher probability of helping, in accordance with Hamilton’s rule: The larger the benefit-to-cost ratio, the more likely altruists will discriminate and favor close kin (see Burnstein et al. 1994). Moreover, individuals prefer to distribute their help so as to maximize the reproductive return, based on genetic relatedness (i.e., they will choose to help two siblings rather than one but will prefer to help one sibling rather than two cousins etc.). For example, Wang (2002) asked subjects to imagine situations in which their decisions affect a six-member kin group, containing two close relatives of the same sex, two distant relatives of the opposite sex, and two unspecified relatives. Subjects have to choose one of two options: a medical procedure which certainly saves two male or two female kin (either close or distant kin) and a procedure with a 33 % probability to save the whole six-kin group. Additionally, half the subjects were asked to imagine that the group was made up of their own relatives and half that it was made up of another person’s relatives. When subjects were making decisions about their own relatives 40 % of them chose the certain procedure to save close relatives but only 20 % did so to save a pair of distant relatives.
Hamilton’s theory of inclusive fitness offers an explanatory account of the evolutionary stability of the altruism; according to Hamilton’s model altruism occurs when the costs do not exceed the reproductive benefits, which are weighted according to the genetic relatedness of altruist and recipient (C < r x B). Hamilton’s rule is supported by ethnographic and experimental research showing that in line with the predictions of inclusive fitness theory individuals unequivocally favor kin over nonkin and prefer close kin over distant kin. Furthermore, these preferences are stronger in emergency situations, i.e., when (reproductive) cost-benefit ratio is more salient. Under this model, kin altruism depends critically on how accurately individuals are able to estimate genetic relatedness and evaluate the costs and benefits for helping. Despite a large number of studies, the computational mechanisms underlying these processes remain unclear. There is some evidence suggesting that individuals use a genetically programmed template to recognize familiarity; however, co-rearing or early childhood experiences could also generate an inner representation of a “family schema” via social learning mechanisms. Familiarity-based kin recognition could also occur via phenotype matching, that is, on the basis of assessing resemblance to self. Whatever the cues used for kin recognition, it seems plausible that individuals have some mechanism for taking into account degree of genetic relatedness when evaluating the costs and benefits of altruism. In conclusion, altruism towards kin is based on complex calculations and assessments which are affected by familiarity, situational cues, and the reproductive “value” of the recipient (based on age, health, etc.).
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