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.     

"Runaway" social evolution: reinforcing selection for inbreeding and altruism.

Kin selection theory predicts that altruistic behaviors, those that decrease the fitness of the individual performing the behavior but increase the fitness of the recipient, can increase in frequency if the individuals interacting are closely related. Several studies have shown that inbreeding therefore generally increases the effectiveness of kin selection when fitnesses are linear, additive functions of the number of altruists in the family, although with extreme forms of altruism, inbreeding can actually retard the evolution of altruism. These models assume that a constant proportion of the population mates at random and a constant proportion practices some form of inbreeding. In order to investigate the effect of inbreeding on the evolution of altruistic behavior when the mating structure is allowed to evolve, we examined a two-locus model by computer simulation of a diploid case and illustrated the important qualitative features by mathematical analysis of a haploid case. One locus determines an individual's propensity to perform altruistic social behavior and the second locus determines the probability that an individual will mate within its sibship. We assumed positive selection for altruism and no direct selection at the inbreeding locus. We observed that the altruistic allele and the inbreeding allele become positively associated, even when the initial conditions of the model assume independence between these loci. This linkage disequilibrium becomes established, because the altruistic allele increases more rapidly in the inbreeding segment of the population. This association subsequently results in indirect selection on the inbreeding locus. However, the dynamics of this model go beyond a simple "hitch-hiking" effect, because high levels of altruism lead to increased inbreeding, and high degrees of inbreeding accelerate the rate of change of the altruistic allele in the entire population. Thus, the dynamics of this model are similar to those of "runaway" sexual selection, with gene frequency change at the two loci interactively causing rapid evolutionary change.     

Conditions for the evolution of altruism under darwinian selection

A model of population structure is discussed which under certain circumstances allows for evolution of altruistic traits, beyond the classical restrictions imposed by kin selection theory and related concepts such as reciprocal altruism. Essentially, the model sees a large population as socially subdivided into small groups without any barriers, however, to free random mating. An altruistic trait is defined as lowering, locally, the fitness of a carrier below that of noncarriers within the same group; but the local fitness of an individual randomly chosen in a group increases with the number of altruists. It is shown that altruism can evolve even if the groups are randomly formed. The conditions for such evolution are contrasted with those prevailing when the groups are formed either with some phenotypic assortment between the members or on the basis of kinship. It is shown that any possibility of evolution tends to rapidly disappear as groups become large, unless there is complete positive assortment or individuals in the groups are kin. The example of alarm calls is also considered, and the two extremes of random and sib-groups are contrasted, using a model by Maynard Smith. It is shown that alarm calls can evolve in small groups of unrelated individuals under conditions qualitatively similar but quantitatively more rigorous than those prevailing for sib-groups.     

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.     

The robustness of Hamilton's rule with inbreeding and dominance: kin selection and fixation probabilities under partial sib mating

Assessing the validity of Hamilton's rule when there is both inbreeding and dominance remains difficult. In this article, we provide a general method based on the direct fitness formalism to address this question. We then apply it to the question of the evolution of altruism among diploid full sibs and among haplodiploid sisters under inbreeding resulting from partial sib mating. In both cases, we find that the allele coding for altruism always increases in frequency if a condition of the form rb>c holds, where r depends on the rate of sib mating alpha but not on the frequency of the allele, its phenotypic effects, or the dominance of these effects. In both examples, we derive expressions for the probability of fixation of an allele coding for altruism; comparing these expressions with simulation results allows us to test various approximations often made in kin selection models (weak selection, large population size, large fecundity). Increasing alpha increases the probability of fixation of recessive altruistic alleles (h<1/2), while it can increase or decrease the probability of fixation of dominant altruistic alleles (h>1/2).     

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.     

Selfishness and altruism can coexist when help is subject to diminishing returns

Altruism and selfishness are 30-50% heritable in man in both Western and non-Western populations. This genetically based variation in altruism and selfishness requires explanation. In non-human animals, altruism is generally directed towards relatives, and satisfies the condition known as Hamilton's rule. This nepotistic altruism evolves under natural selection only if the ratio of the benefit of receiving help to the cost of giving it exceeds a value that depends on the relatedness of the individuals involved. Standard analyses assume that the benefit provided by each individual is the same but it is plausible in some cases that as more individuals contribute, help is subject to diminishing returns. We analyse this situation using a single-locus two-allele model of selection in a diploid population with the altruistic allele dominant to the selfish allele. The analysis requires calculation of the relationship between the fitnesses of the genotypes and the frequencies of the genes. The fitnesses vary not only with the genotype of the individual but also with the distribution of phenotypes amongst the sibs of the individual and this depends on the genotypes of his parents. These calculations are not possible by direct fitness or ESS methods but are possible using population genetics. Our analysis shows that diminishing returns change the operation of natural selection and the outcome can now be a stable equilibrium between altruistic and selfish alleles rather than the elimination of one allele or the other. We thus provide a plausible genetic model of kin selection that leads to the stable coexistence in the same population of both altruistic and selfish individuals. This may explain reported genetic variation in altruism in man.     

WHEN HAWKS GIVE RISE TO DOVES: THE EVOLUTION AND TRANSITION OF ENFORCEMENT STRATEGIES

The question of how altruism can evolve despite its local disadvantage to selfishness has produced a wealth of theoretical and empirical research capturing the attention of scientists across disciplines for decades. One feature that has remained consistent through this outpouring of knowledge has been that researchers have looked to the altruists themselves for mechanisms by which altruism can curtail selfishness. An alternative perspective may be that just as altruists want to limit selfishness in the population, so may the selfish individuals themselves. These alternative perspectives have been most evident in the fairly recent development of enforcement strategies. Punishment can effectively limit selfishness in the population, but it is not free. Thus, when punishment evolves among altruists, the double costs of exploitation from cheaters and punishment make the evolution of punishment problematic. Here we show that punishment can more readily invade selfish populations when associated with selfishness, whereas altruistic punishers cannot. Thereafter, the establishment of altruism because of enforcement by selfish punishers provides the ideal invasion conditions for altruistic punishment, effectively creating a transition of punishment from selfishness to altruistic. Thus, from chaotic beginnings, a little hypocrisy may go a long way in the evolution and maintenance of altruism.     

Altruists Proliferate Even at a Selective Disadvantage within Their Own Niche

The evolutionary origin of altruism is a long-standing puzzle. Numerous explanations have been proposed, most prominently based on inclusive fitness or group selection. One possibility that has not yet been considered is that new niches will be created disproportionately often when altruism appears, perhaps by chance, causing altruists to be over-represented in such new niches. This effect is a novel variant of group selection in which altruistic groups benefit by discovering unoccupied niches instead of by competing for the limited resources within a single niche. Both an analytical population genetics model and computational simulations support that altruism systematically arises due to this side effect of increased carrying capacity even when it is strongly selected against within any given niche. In fact, even when selection is very strongly negative and altruism does not develop in most populations, it can still be expected to be observed in a consistent fraction of species. The ecological structure provided by niches thereby may be sufficient for altruists to proliferate even if they are always at a disadvantage within each niche considered individually.     

Fixation of new alleles and the extinction of small populations: drift load, beneficial alleles, and sexual selection

With a small effective population size, random genetic drift is more important than selection in determining the fate of new alleles. Small populations therefore accumulate deleterious mutations. Left unchecked, the effect of these fixed alleles is to reduce the reproductive capacity of a species, eventually to the point of extinction. New beneficial mutations, if fixed by selection, can restore some of this lost fitness. This paper derives the overall change in fitness due to fixation of new deleterious and beneficial alleles, as a function of the distribution of effects of new mutations and the effective population size. There is a critical effective size below which a population will on average decline in fitness, but above which beneficial mutations allow the population to persist. With reasonable estimates of the relevant parameters, this critical effective size is likely to be a few hundred. Furthermore, sexual selection can act to reduce the fixation probability of deleterious new mutations and increase the probability of fixing new beneficial mutations. Sexual selection can therefore reduce the risk of extinction of small populations.     

Why kin and group selection models may not be enough to explain human other-regarding behaviour

Models of kin or group selection usually feature only one possible fitness transfer. The phenotypes are either to make this transfer or not to make it and for any given fitness transfer, Hamilton's rule predicts which of the two phenotypes will spread. In this article we allow for the possibility that different individuals or different generations face similar, but not necessarily identical possibilities for fitness transfers. In this setting, phenotypes are preference relations, which concisely specify behaviour for a range of possible fitness transfers (rather than being a specification for only one particular situation an animal or human can be in). For this more general set-up, we find that only preference relations that are linear in fitnesses can be explained using models of kin selection and that the same applies to a large class of group selection models. This provides a new implication of hierarchical selection models that could in principle falsify them, even if relatedness--or a parameter for assortativeness--is unknown. The empirical evidence for humans suggests that hierarchical selection models alone are not enough to explain their other-regarding or altruistic behaviour.     

FOUNDER EFFECTS AND PEAK SHIFTS WITHOUT GENETIC DRIFT: ADAPTIVE PEAK SHIFTS OCCUR EASILY WHEN ENVIRONMENTS FLUCTUATE SLIGHTLY

Two similar evolutionary theories, the shifting balance theory and founder-flush models, invoke random genetic drift to allow evolution on complex adaptive landscapes. These models, in their usual incarnations, deal with fitness as a static entity, and the probability of transition from one form to another is predicted to be quite small by analysis of these models. Fitness itself can change, however, and the amount of change in the parameters of the fitness functions required to allow deterministic evolution to new adaptive peaks is very small. The probability of environmental changes sufficient to allow substantial morphological evolution or reproductive isolation is large relative to the probability that similar changes could occur by processes requiring genetic drift, even with very small population sizes. The rapid evolution or speciation following a population founding event is more closely linked with environmental changes than genetic drift.     

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.     

Neoproterozoic 'snowball Earth' glaciations and the evolution of altruism

We hypothesize that a demographic and ecological effect of Neoproterozoic ‘snowball Earth’ glaciations was to increase the fitness of group‐level traits and consequently the likelihood of the evolution of macroscopic form. Extreme and repeated founder effects raised genetic relatedness – and therefore the influence of kin selection on the individuals within a group. This was permissive for the evolution of some highly costly altruistic traits, including those for macroscopic differentiation. In some eukaryotic species, the harsh and fluctuating abiotic conditions made a macroscopic physiology advantageous, perhaps necessary, for collective survival. This caused population‐wide group viability selection, whereby non‐altruist ‘cheat’ genotypes killed the groups they were in, and therefore themselves, by reaching fixation. Furthermore, dispersal between refugia would reach zero under anything near a ‘hard snowball’, which would protect altruists at high local frequency from the influx of cheats from neighbouring groups. We illustrate our hypothesis analytically and with a simple spatial model. We show how removal of between‐group dispersal, in a population with initial between‐group variation in cheat frequency, causes the relative frequency of altruists to increase while the population as a whole decreases in size, as a result of group death caused by cheat invasion. This may be of particular relevance to animal multicellularity because irreversible differentiation (highly altruistic in that it imposes a high fitness cost on the individual cell) is more prevalent than in other multicellular eukaryotes. The relevance of our hypothesis should be scaled by any future consensus on the severity of snowball Earth, but it is theoretically plausible that global‐scale glaciations had a systematic influence on the level of selection during Earth history.     

The effects of migration and drift on local adaptation to a heterogeneous environment

Local adaptation experiments are widely used to quantify the levels of adaptation within a heterogeneous environment. However, theoretical studies generally focus on the probability of fixation of alleles or the mean fitness of populations, rather than local adaptation as it is commonly measured experimentally or in field studies. Here, we develop mathematical models and use them to generate analytical predictions for the level of local adaptation as a function of selection, migration and genetic drift. First, we contrast mean fitness and local adaptation measures and show that the latter can be expressed in a simple and general way as a function of the spatial covariance between population mean phenotype and local environmental conditions. Second, we develop several approximations of a population genetics model to show that the system exhibits different behaviours depending on the rate of migration. The main insights are the following: with intermediate migration, both genetic drift and migration decrease local adaptation; with low migration, drift decreases local adaptation but migration speeds up adaptation; with high migration, genetic drift has no effect on local adaptation. Third, we extend this analysis to cases where the trait under selection is continuous using classical quantitative genetics theory. Finally, we discuss these results in the light of recent experimental work on local adaptation.     

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.     

Genetics and adaptation in structured populations: sex ratio evolution in Silene vulgaris

Theoretical models suggest that population structure can interact with frequency dependent selection to affect fitness in such a way that adaptation is dependent not only on the genotype of an individual and the genotypes with which it co-occurs within populations (demes), but also the distribution of genotypes among populations. A canonical example is the evolution of altruistic behavior, where the costs and benefits of cooperation depend on the local frequency of other altruists, and can vary from one population to another. Here we review research on sex ratio evolution that we have conducted over the past several years on the gynodioecious herb Silene vulgaris in which we combine studies of negative frequency dependent fitness on female phenotypes with studies of the population structure of cytoplasmic genes affecting sex expression. This is presented as a contrast to a hypothetical example of selection on similar genotypes and phenotypes, but in the absence of population structure. Sex ratio evolution in Silene vulgaris provides one of the clearest examples of how selection occurs at multiple levels and how population structure, per se, can influence adaptive evolution.     

On the relationship between evolutionary and psychological definitions of altruism and selfishness

I examine the relationship between evolutionary definitions of altruism that are based on fitness effects and psychological definitions that are based on the motives of the actor. I show that evolutionary altruism can be motivated by proximate mechanisms that are psychologically either altruistic or selfish. I also show that evolutionary definitions do rely upon motives as a metaphor in which the outcome of natural selection is compared to the decisions of a psychologically selfish (or altruistic) individual. Ignoring the precise nature of both psychological and evolutionary definitions has obscured many important issues, including the biological roots of psychological altruism.     

Rapid evolutionary escape by large populations from local fitness peaks is likely in nature

Fitness interactions between loci in the genome, or epistasis, can result in mutations that are individually deleterious but jointly beneficial. Such epistasis gives rise to multiple peaks on the genotypic fitness landscape. The problem of evolutionary escape from such local peaks has been a central problem of evolutionary genetics for at least 75 years. Much attention has focused on models of small populations, in which the sequential fixation of valley genotypes carrying individually deleterious mutations operates most quickly owing to genetic drift. However, valley genotypes can also be subject to mutation while transiently segregating, giving rise to copies of the high fitness escape genotype carrying the jointly beneficial mutations. In the absence of genetic recombination, these mutations may then fix simultaneously. The time for this process declines sharply with increasing population size, and it eventually comes to dominate evolutionary behavior. Here we develop an analytic expression for N(crit), the critical population size that defines the boundary between these regimes, which shows that both are likely to operate in nature. Frequent recombination may disrupt high-fitness escape genotypes produced in populations larger than N(crit) before they reach fixation, defining a third regime whose rate again slows with increasing population size. We develop a novel expression for this critical recombination rate, which shows that in large populations the simultaneous fixation of mutations that are beneficial only jointly is unlikely to be disrupted by genetic recombination if their map distance is on the order of the size of single genes. Thus, counterintuitively, mass selection alone offers a biologically realistic resolution to the problem of evolutionary escape from local fitness peaks in natural populations.     

Note on the computation of critical effective population sizes.

This work extends the work of Whitlock in examining the critical effective population sizes from the fixation of both deleterious and beneficial mutations under drift and selection to prevent mutation breakdown of the population. The validity of approximations for the probability of fixation depends on the nature of the assumed distribution for the fitness effect of both types of mutations. Using no approximation for the probability of fixation and assuming a heavy tailed fitness effect distribution, the current model indicates that the coefficients of variation for the fitness effect distributions of both types of mutations and the fitness effect distribution mean for the beneficial mutations are important predictors of the critical effective population size. The current model further predicts that very small populations can be sustained if the fitness effect variances for both types of mutations and the mean for beneficial mutations are large.