Altruists are trusted based on non-verbal cues

The identification of altruists based on non-verbal cues might offer a solution to the problem of subtle cheating. Previous studies have indicated that the ability to discriminate altruists from non-altruists emerges during evolution. However, behavioural differences with regard to social exchanges involving altruists and non-altruists have not been studied. We investigated differences in responses to videotaped altruists and non-altruists with the Faith Game. Participants tended to entrust real money to altruists more than to non-altruists, providing strong evidence that cognitive adaptations evolve as counter-strategies to subtle cheating.     

Altruism Can Be Assessed Correctly Based on Impression

Detection of genuine altruists could be a solution to the problem of subtle cheating. Brown et al. (Evol Psychol 1:42–69, 2003) found that humans could detect altruists using nonverbal cues. However, their experiments can be improved upon in several ways, and further investigation is needed to determine whether altruist-detection abilities are human universals. In our experiment, we used video clips of natural conversations as the stimulus. We asked a sample of Japanese undergraduates to rate their own level of altruism and then to estimate the videotaped targets’ altruism using the same scale. The perceivers were able to estimate the targets’ altruism levels accurately. Perceivers’ altruism score did not affect their ability to discriminate between altruists and non-altruists. Perceivers’ impressions of the altruist and non-altruist targets were also found to be different. Coding of nonverbal behavior of the targets revealed that altruists exhibited more “felt smiles” than non-altruists, which also supports the results of the previous study.     

Kin recognition and the evolution of altruism

In 1964, Hamilton formalized the idea of kin selection to explain the evolution of altruistic behaviours. Since then, numerous examples from a diverse array of taxa have shown that seemingly altruistic actions towards close relatives are a common phenomenon. Although many species use kin recognition to direct altruistic behaviours preferentially towards relatives, this important aspect of social biology is less well understood theoretically. I extend Hamilton's classic work by defining the conditions for the evolution of kin-directed altruism when recognizers are permitted to make acceptance (type I) and rejection (type II) errors in the identification of social partners with respect to kinship. The effect of errors in recognition on the evolution of kin-directed altruism depends on whether the population initially consists of unconditional altruists or non-altruists (i.e. alternative forms of non-recognizers). Factors affecting the level of these error rates themselves, their evolution and their long-term stability are discussed.     

Migration promotes mutator alleles in subdivided populations

Mutator alleles that elevate the genomic mutation rate may invade nonrecombining populations by hitchhiking with beneficial mutations. Mutators have been repeatedly observed to take over adapting laboratory populations and have been found at high frequencies in both microbial pathogen and cancer populations in nature. Recently, we have shown that mutators are only favored by selection in sufficiently large populations and transition to being disfavored as population size decreases. This population size‐dependent sign inversion in selective effect suggests that population structure may also be an important determinant of mutation rate evolution. Although large populations may favor mutators, subdividing such populations into sufficiently small subpopulations (demes) might effectively inhibit them. On the other hand, migration between small demes that otherwise inhibit hitchhiking may promote mutator fixation in the whole metapopulation. Here, we use stochastic, agent‐based simulations and evolution experiments with the yeast Saccharomyces cerevisiae to show that mutators can, indeed, be favored by selection in subdivided metapopulations composed of small demes connected by sufficient migration. In fact, we show that population structure plays a previously unsuspected role in promoting mutator success in subdivided metapopulations when migration is rare.     

Green beards in the light of indirect genetic effects

The green‐beard effect is one proposed mechanism predicted to underpin the evolution of altruistic behavior. It relies on the recognition and the selective help of altruists to each other in order to promote and sustain altruistic behavior. However, this mechanism has often been dismissed as unlikely or uncommon, as it is assumed that both the signaling trait and altruistic trait need to be encoded by the same gene or through tightly linked genes. Here, we use models of indirect genetic effects (IGEs) to find the minimum correlation between the signaling and altruistic trait required for the evolution of the latter. We show that this correlation threshold depends on the strength of the interaction (influence of the green beard on the expression of the altruistic trait), as well as the costs and benefits of the altruistic behavior. We further show that this correlation does not necessarily have to be high and support our analytical results by simulations.     

Selection for altruism through random drift in variable size populations

ABSTRACT: BACKGROUND: Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel) show that altruistic behaviors can have 'hidden' advantages if the 'common good' produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. RESULTS: Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of "selfish" alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. CONCLUSIONS: The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.     

EVOLUTION OF ALTRUISM IN KIN-STRUCTURED AND RANDOM SUBDIVIDED POPULATIONS

A. population structure favorable to the evolution of an altruistic trait is studied by Monte Carlo simulation. The model is based on a small-scale nonindustrial human society but seems generalizable to other highly social mammals. Three hierarchical levels are recognized: 1) the ecologically isolated local group (hamlet) which may be composed of kin and/or unrelated individuals; 2) the deme (settlement) comprising several such groups which interbreed; and 3) the set of demes (metapopulation) among which gene flow occurs. The first two levels of the model are based on D. S. Wilson's structured deme concept; the third allows for gene flow among demes in the metapopulation and for the structured diffusion of alleles across a wider area than might be included within the scope of a single deme. The simulation models genetic drift by a process of hamlet formation which may be random, or variously kin-structured. Hamlets may then become extinct based on a probability function of their gene frequencies. Individual selection within settlements is modeled deterministically, and gene flow among settlements is modeled as two-dimensional steppingstone migration of random or kin-structured groups. Results of the simulations show that, with realistic values for group sizes, moderate extinction rate, and high rates of migration (m > 27%), disadvantageous alleles (s = 10% and 25%) may increase markedly due to differential hamlet extinction over the course of 50 generations. The greater the degree of kin-structuring of founder groups, the higher the variance among hamlets and the faster the rate of increase of the allele for altruism. Nonetheless, even in some randomly founded groups, a clear increase in the altruism gene frequency occurred. It is also notable that kin-structured group selection by hamlet extinction may be effective when the initial frequency of altruism genes is very low (average of one per deme) and among a relatively small number of demes (25). Thus the process of group extinction in a hierarchically structured population allows rapid increase of an allele for altruism under plausible demographic conditions.     

Not only states but traits — Humans can identify permanent altruistic dispositions in 20 s

Humans behave altruistically in one-shot interactions under total anonymity. In search of explanations for such behavior, it has been argued that at least some individuals have a general tendency to behave altruistically independent of profitability. In fact, a stable altruistic trait would be adaptive if it were recognizable. Then, altruists could choose each other in order to retain benefits through mutual cooperation. Previous research has shown that individuals can predict the degree of altruistic behavior of strangers by reading signs of emotions evoked in significant social decisions. However, the identification of benevolent emotional states is no guarantee of the existence of permanent altruistic traits, though permanent traits are the preferable criterion for selection of good interaction partners. In this study, we tested whether individuals are able to identify altruistic traits. Judges watched 20-s silent video clips of unacquainted target persons and were asked to estimate the behavior of these target persons in a money-sharing task. As the videotapes of the target persons had been recorded in a setting unrelated to altruistic behavior, the judges could not base their estimates on situational cues related to the money-sharing task but instead had to draw on stable signals of altruism. Estimates were significantly better than chance, indicating that individuals can identify permanent altruistic traits in others. As this mechanism raises opportunities for selective interactions between altruists, our findings are discussed with respect to their relevance for explaining the evolution of altruism through assortment.     

Adaptive Dynamics of Altruistic Cooperation in a Metapopulation: Evolutionary Emergence of Cooperators and Defectors or Evolutionary Suicide?

We investigate the evolution of public goods cooperation in a metapopulation model with small local populations, where altruistic cooperation can evolve due to assortment and kin selection, and the evolutionary emergence of cooperators and defectors via evolutionary branching is possible. Although evolutionary branching of cooperation has recently been demonstrated in the continuous snowdrift game and in another model of public goods cooperation, the required conditions on the cost and benefit functions are rather restrictive, e.g., altruistic cooperation cannot evolve in a defector population. We also observe selection for too low cooperation, such that the whole metapopulation goes extinct and evolutionary suicide occurs. We observed intuitive effects of various parameters on the numerical value of the monomorphic singular strategy. Their effect on the final coexisting cooperator–defector pair is more complex: changes expected to increase cooperation decrease the strategy value of the cooperator. However, at the same time the population size of the cooperator increases enough such that the average strategy does increase. We also extend the theory of structured metapopulation models by presenting a method to calculate the fitness gradient in a general class of metapopulation models, and try to make a connection with the kin selection approach.     

Joint evolution of dispersal and inbreeding load

Inbreeding avoidance is often invoked to explain observed patterns of dispersal, and theoretical models indeed point to a possibly important role. However, while inbreeding load is usually assumed constant in these models, it is actually bound to vary dynamically under the combined influences of mutation, drift, and selection and thus to evolve jointly with dispersal. Here we report the results of individual-based stochastic simulations allowing such a joint evolution. We show that strongly deleterious mutations should play no significant role, owing to the low genomic mutation rate for such mutations. Mildly deleterious mutations, by contrast, may create enough heterosis to affect the evolution of dispersal as an inbreeding-avoidance mechanism, but only provided that they are also strongly recessive. If slightly recessive, they will spread among demes and accumulate at the metapopulation level, thus contributing to mutational load, but not to heterosis. The resulting loss of viability may then combine with demographic stochasticity to promote population fluctuations, which foster indirect incentives for dispersal. Our simulations suggest that, under biologically realistic parameter values, deleterious mutations have a limited impact on the evolution of dispersal, which on average exceeds by only one-third the values expected from kin-competition avoidance.     

Population viscosity and the evolution of altruism

The term population viscosity refers to limited dispersal, which increases the genetic relatedness of neighbors. This effect both supports the evolution of altruism by focusing the altruists' gifts on relatives of the altruist, and also limits the extent to which altruism may emerge by exposing clusters of altruists to stiffer local competition. Previous analyses have emphasized the way in which these two effects can cancel, limiting the viability of altruism. These papers were based on models in which total population density was held fixed. We present here a class of models in which population density is permitted to fluctuate, so that patches of altruists are supported at a higher density than patches of non-altruists. Under these conditions, population viscosity can support the selection of both weak and strong altruism.     

Multilevel selection and human altruism

Views on the evolution of altruism based upon multilevel selection on structured populations pay little attention to the difference between fortuitous and deliberate processes leading to assortative grouping. Altruism may evolve when assortative grouping is fortuitously produced by forces external to the organism. But when it is deliberately produced by the same proximate mechanism that controls altruistic responses, as in humans, exploitation of altruists by selfish individuals is unlikely and altruism evolves as an individually advantageous trait. Groups formed with altruists of this sort are special, because they are not affected by subversion from within. A synergistic process where altruism is selected both at the individual and at the group level can take place.     

The loss of adaptive plasticity during long periods of environmental stasis

Adaptive plasticity allows populations to adjust rapidly to environmental change. If this is useful only rarely, plasticity may undergo mutational degradation and be lost from a population. We consider a population of constant size N undergoing loss of plasticity at functional mutation rate m and with selective advantage s associated with loss. Environmental change events occur at rate theta per generation, killing all individuals that lack plasticity. The expected time until loss of plasticity in a fluctuating environment is always at least tau, the expected time until loss of plasticity in a static environment. When mN > 1 and N theta > 1, we find that plasticity will be maintained for an average of at least 10(8) generations in a single population, provided tau > 18/theta. In a metapopulation, plasticity is retained under the more lenient condition tau > 1.3/theta, irrespective of mN, for a modest number of demes. We calculate both exact and approximate solutions for tau and find that it is linearly dependent only on the logarithm of N, and so, surprisingly, both the population size and the number of demes in the metapopulation make little difference to the retention of plasticity. Instead, tau is dominated by the term 1/(m+s/2).     

Altruism and mental disorders

Data suggest that the theories of kin selection and reciprocal altruism are viable working models to explain altruistic behavior. It remains to be demonstrated if these models can explain the behavior of persons with mentaL disorders for whom altruistic behavior is reported to be reduced. This paper addresses this issue. Part I reviews proximate factors that are thought to influence both altruistic decision making and interindividual variation in altruistic behavior. The focus is on trait signaling by potential beneficiaries and the evaluation of signals and altruistic decision making by potential altruists. In Part II, points developed in Part I are combined with clinical and empirical findings to analyze data on personality disorders and dysthymic disorder. The analysis leads to three causal hypotheses: Reduced altruistic behavior may be an evolved strategy, a consequence of dysfunctional recognition systems or algorithms, and/or a secondary response to an increase in symptoms. Different disorders and features of disorders are explained by each hypothesis.     

Effects of metapopulation processes on measures of genetic diversity

Many species persist as a metapopulation under a balance between the local extinction of subpopulations or demes and their recolonization through dispersal from occupied patches. Here we review the growing body of literature dealing with the genetic consequences of such population turnover. We focus our attention principally on theoretical studies of a classical metapopulation with a 'finite-island' model of population structure, rather than on 'continent-island' models or 'source-sink' models. In particular, we concern ourselves with the subset of geographically subdivided population models in which it is assumed that all demes are liable to extinction from time to time and that all demes receive immigrants. Early studies of the genetic effects of population turnover focused on population differentiation, such as measured by F(ST). A key advantage of F(ST) over absolute measures of diversity is its relative independence of the mutation process, so that different genes in the same species may be compared. Another advantage is that F(ST) will usually equilibrate more quickly following perturbations than will absolute levels of diversity. However, because F(ST) is a ratio of between-population differentiation to total diversity, the genetic effects of metapopulation processes may be difficult to interpret in terms of F(ST) on its own, so that the analysis of absolute measures of diversity in addition is likely to be informative. While population turnover may either increase or decrease F(ST), depending on the mode of colonization, recurrent extinction and recolonization is expected always to reduce levels of both within-population and species-wide diversity (piS and piT, respectively). One corollary of this is that piS cannot be used as an unbiased estimate of the scaled mutation rate, theta, as it can, with some assumptions about the migration process, in species whose demes do not fluctuate in size. The reduction of piT in response to population turnover reflects shortened mean coalescent times, although the distribution of coalescence times under extinction colonization equilibrium is not yet known. Finally, we review current understanding of the effect of metapopulation dynamics on the effective population size.     

An evolutionary analysis of the relationship between spite and altruism

We investigate the selective pressures on a social trait when evolution occurs in a population of constant size. We show that any social trait that is spiteful simultaneously qualifies as altruistic. In other words, any trait that reduces the fitness of less related individuals necessarily increases that of related ones. Our analysis demonstrates that the distinction between "Hamiltonian spite" and "Wilsonian spite" is not justified on the basis of fitness effects. We illustrate this general result with an explicit model for the evolution of a social act that reduces the recipient's survival ("harming trait"). This model shows that the evolution of harming is favoured if local demes are of small size and migration is low (philopatry). Further, deme size and migration rate determine whether harming evolves as a selfish strategy by increasing the fitness of the actor, or as a spiteful/altruistic strategy through its positive effect on the fitness of close kin.     

Evolution of altruism under group selection in large and small populations in fluctuating environments

A continuous, graded form of group selection which does not involve extinction of demes can effectively oppose selection on the individual level against an altruistic allele under fluctuating environments in infinitely large demes among which uniform mixing occurs every generation. Although group selection cannot alter the conditions necessary for the initial increase of altruistic alleles, group selection can significantly influence the stationary distribution of gene frequency which is attained once stochastic forces have allowed theirintroduction. Drift is a more effective source of variation than fluctuations in selection when the variance in selection is moderate to small. High numbers of demes promote polymorphism under both graded group selection and extinction group selection.     

Spotting altruistic dictator game players and mingling with them: the elective assortation of classmates

Altruism can evolve through assortation if the selfish advantage of egoistic individuals is outcompeted by the benefits of mutual cooperation between altruists. This selection process is possible if (a) individuals can distinguish altruists from egoists and (b) altruists cooperate electively with other altruists, leaving egoists no chance but to mingle with each other. This study investigates whether these two conditions are fulfilled in a natural setting. One hundred twenty-two students of six secondary school classes (age 10 to 19 years) played an anonymous dictator game, which functioned as a measure of altruism. Afterwards and unannounced, the students had to estimate their classmates' decisions and did so better than chance. Sociometry revealed that the accuracy of predictions depended on social closeness. Friends and disliked classmates were judged more accurately than liked classmates or those met with indifference. Moreover, altruists were friends with more altruistic persons than were egoists. The results confirm the existence of the two prerequisites for the evolution of altruism through assortation: the predictability of altruistic behavior and the association of altruists.     

Genetic load,inbreeding depression and heterosis in an age‐structured metapopulation

In a metapopulation, the process of recurrent local extinction and recolonization gives rise to an age structure among demes. Recently established demes will tend to differ from older demes in terms of the levels of genetic diversity found within them and the way this diversity is distributed among demes in the same and different ages. The effects of population turnover on average levels of genetic diversity among demes in a metapopulation have been the focus of much attention, both for neutral and nonneutral loci, but much less is known about the distribution of nonneutral genetic diversity among demes of different ages. In this paper, we used computer simulations to study the distribution of genetic load, inbreeding depression and heterosis in an age‐structured metapopulation. We found that, for mildly deleterious mutations, within‐deme inbreeding depression increased, whereas heterosis and genetic load decreased with deme age following severe colonization bottlenecks. In contrast, recessive lethal alleles tended to be purged during colonization, with older populations showing higher genetic load and higher within‐deme inbreeding depression. Heterosis caused by recessive lethal alleles and resulting from gene flow among different demes tended to be greatest for young demes, because the mutations responsible tended to be purged in the first few generations after colonization, but its effects increased again as populations grow older as a result of immigration. Our results point to a need for estimates of genetic diversity, genetic load, within‐deme inbreeding depression and heterosis in demes of different age classes separately.     

Competitive altruism: from reciprocity to the handicap principle

Current work on cooperation is focused on the theory of reciprocal altruism. However, reciprocity is just one way of getting a return on an investment in altruism and is difficult to apply to many examples. Reciprocity theory addresses how animals respond dynamically to others so as to cooperate without being exploited. I discuss how introducing differences in individual generosity together with partner choice into models of reciprocity can lead to an escalation in altruistic behaviour. Individuals may compete for the most altruistic partners and non-altruists may become ostracized. I refer to this phenomenon as competitive altruism and propose that it can represent a move away from the dynamic responsiveness of reciprocity. Altruism may be rewarded in kind, but rewards may be indirectly accrued or may not involve the return of altruism at all, for example if altruists tend to be chosen as mates. This variety makes the idea of competitive altruism relevant to behaviours which cannot be explained by reciprocity. I consider whether altruism might act as a signal of quality, as proposed by the handicap principle. I suggest that altruistic acts could make particularly effective signals because of the inherent benefits to receivers. I consider how reciprocity and competitive altruism are related and how they may be distinguished.