Genetic relatedness in viscous populations

Summary Hamilton's inclusive fitness rule shows that the evolution of altruism is facilitated by high genetic relatedness of altruists to their beneficiaries. But the evolution of altruism is inhibited when the beneficiaries are also close competitors of the altruist, as will often be true in structured or viscous populations. However, Hamilton's rule still gives the correct condition for the evolution of altruism if relatedness is measured with respect to the local competitive neighbourhood.     

The evolution of altruism: game theory in multilevel selection and inclusive fitness

Although the prisoner's dilemma (PD) has been used extensively to study reciprocal altruism, here we show that the n-player prisoner's dilemma (NPD) is also central to two other prominent theories of the evolution of altruism: inclusive fitness and multilevel selection. An NPD model captures the essential factors for the evolution of altruism directly in its parameters and integrates important aspects of these two theories such as Hamilton's rule, Simpson's paradox, and the Price covariance equation. The model also suggests a simple interpretation of the Price selection decomposition and an alternative decomposition that is symmetrical and complementary to it. In some situations this alternative shows the temporal changes in within- and between-group selection more clearly than the Price equation. In addition, we provide a new perspective on strong vs. weak altruism by identifying their different underlying game structures (based on absolute fitness) and showing how their evolutionary dynamics are nevertheless similar under selection (based on relative fitness). In contrast to conventional wisdom, the model shows that both strong and weak altruism can evolve in periodically formed random groups of non-conditional strategies if groups are multigenerational. An integrative approach based on the NPD helps unify different perspectives on the evolution of altruism.     

Distinctions among reciprocal altruism,kin selection,and cooperation and a model for the initial evolution of beneficent behavior

Reciprocal altruism is usually regarded as distinct from kin selection. However, because reciprocators are likely to establish long-term relations and to deliver most of their aid to other individuals genetically predisposed to reciprocation, most acts of reciprocal altruism should involve indirect increments to inclusive fitness, at least as regards alleles for reciprocation. Thus, as usually defined, reciprocal altruism is not clearly distinct from kin selection because both involve indirect increments to inclusive fitness. We propose a new definition for reciprocal altruism that makes the phenomenon distinct from kin selection and allows for reciprocation between nonrelatives in which current costs exceed future benefits returned to the reciprocal altruist. Cooperation and reciprocal altruism are often considered synonymous or different only in the timing of donating and receiving aid. We show, however, that there are other critical differences between reciprocal altruism and other forms of cooperation, most importantly, the latter often involve no clearly identifiable aid. We propose a four-category system to encompass the range of cooperative and beneficent behaviors that occur in nature (reciprocal altruism, pseudoreciprocity, simultaneous cooperation and by-product beneficence). Reciprocal altruism must involve aid that is returned to an original donor as a result of behavior that has a net cost to an original recipient. Our simplest category of cooperative/beneficent behavior, “by-product beneficence,” occurs when a selfish act also benefits another individual and requires no prior or subsequent interactions between the individuals involved. By-product beneficence may be the primitive state from which more complicated types of cooperative/beneficent behavior evolved. We show via simple models that by-product beneficence can allow for the initial increase of helping behavior in a completely unstructured population although the individuals showing such behavior pay all the costs while sharing the benefits with other individuals. Previous models that attempted to explain the initial increase of cooperative/beneficent behavior were much more complex and were based on the prisoner's dilemma, which does not accurately reflect most forms of cooperation and beneficence that occur in nature.     

Effects of information and group structure on evolution of altruism: analysis of two-score model by covariance and contextual analyses

An altruistic individual has to gamble on cooperation to a stranger because it does not know whether the stranger is trustworthy before direct interaction. Nowak and Sigmund (Nature 393 (1998a) 573; J. Theor. Biol. 194 (1998b) 561) presented a new theoretical framework of indirect reciprocal altruism by image scoring game where all individuals are informed about a partner's behavior from its image score without direct interaction. Interestingly, in a simplified version of the image scoring game, the evolutionarily stability condition for altruism became a similar form of Hamilton's rule, i.e. inequality that the probability of getting correct information is more than the ratio of cost to benefit. Since the Hamilton's rule was derived by evolutionarily stable analysis, the evolutionary meaning of the probability of getting correct information has not been clearly examined in terms of kin and group selection. In this study, we applied covariance analysis to the two-score model for deriving the Hamilton's rule. We confirmed that the probability of getting correct information was proportional to the bias of altruistic interactions caused by using information about a partner's image score. The Hamilton's rule was dependent on the number of game bouts even though the information reduced the risk of cooperation to selfish one at the first encounter. In addition, we incorporated group structure to the two-score model to examine whether the probability of getting correct information affect selection for altruism by group selection. We calculated a Hamilton's rule of group selection by contextual analysis. Group selection is very effective when either the probability of getting correct information or that of future interaction, or both are low. The two Hamilton's rules derived by covariance and contextual analyses demonstrated the effects of information and group structure on the evolution of altruism. We inferred that information about a partner's behavior and group structure can produce flexible pathways for the evolution of altruism.     

A rule is not a rule if it changes from case to case (a reply to Marshall's comment)

This is a reply to “Queller's rule ok: Comment on van Veelen ‘when inclusive fitness is right and when it can be wrong’ ” by James Marshall in the Journal of Theoretical Biology, in this issue.In order to circumvent the disagreement about the Price equation and focus on the issue of the predictive power of inclusive fitness for group selection models, I derive Queller's and Marshall's rule without the Price equation. Both rules however need a translation step in order to be able to link them to the group selection model in van Veelen (2009). Queller's rule applies to games with 2 players and 2 strategies, and is general. Marshall's rule on the other hand applies only to a small subset of 3-player games. His rule is correct, but for other, similarly small subsets we would get other rules. This implies that if we want a rule that applies to all symmetric games with 3 players and 2 strategies, it will have to use a vector of dimension 2 that represents population structure. More in general: for group selection models with groups of size n, a correct and general prediction will need to use a vector of dimension n−1 that represents population structure.     

Kin selection and frequency dependence: a game theoretic approach

Game theory models show that the evolution of interactions between relatives is determined by two kinds of fitness effects: Hamilton's inclusive fitness effect, and a frequency-dependent synergistic effect. The latter arises when an individual's behaviour has different effects on the fitness of interactants, depending on whether or not they perform the same behaviour. Knowing the sign of the synergistic effect is sufficient to understand most of the qualitative features of genetic models that show departures from Hamilton's rule. Since this synergistic effect does not depend on the interactants being related, it is best viewed as something distinct from kin selection. In this view, Hamilton's rule is basically correct for describing kin selection, and most deviations from it are due to the distinct process of synergistic selection.     

A quantitative test of Hamilton's rule for the evolution of altruism

The evolution of altruism is a fundamental and enduring puzzle in biology. In a seminal paper Hamilton showed that altruism can be selected for when rb - c > 0, where c is the fitness cost to the altruist, b is the fitness benefit to the beneficiary, and r is their genetic relatedness. While many studies have provided qualitative support for Hamilton's rule, quantitative tests have not yet been possible due to the difficulty of quantifying the costs and benefits of helping acts. Here we use a simulated system of foraging robots to experimentally manipulate the costs and benefits of helping and determine the conditions under which altruism evolves. By conducting experimental evolution over hundreds of generations of selection in populations with different c/b ratios, we show that Hamilton's rule always accurately predicts the minimum relatedness necessary for altruism to evolve. This high accuracy is remarkable given the presence of pleiotropic and epistatic effects as well as mutations with strong effects on behavior and fitness (effects not directly taken into account in Hamilton's original 1964 rule). In addition to providing the first quantitative test of Hamilton's rule in a system with a complex mapping between genotype and phenotype, these experiments demonstrate the wide applicability of kin selection theory.     

Relatedness with different interaction configurations

In an inclusive fitness model of social behaviour, a key concept is that of the relatedness between two interactants. This is typically calculated with reference to a “focal” actor taken to be representative of all actors, but when there are different interaction configurations, relatedness must be constructed as an average over all such configurations. We provide an example of such a calculation in an island model with local reproduction but global mortality, leading to variable island size and hence variable numbers of individual interactions. We find that the analysis of this example significantly sharpens our understanding of relatedness. As an application, we obtain a version of Hamilton's rule for a tag-based model of altruism in a randomly mixed population. For large populations, the selective advantage of altruism is enhanced by low (but not too low) tag mutation rates and large numbers of tags. For moderate population sizes and moderate numbers of tags, we find a window of tag mutation rates with critical benefit/cost ratios of between 1 and 3.     

Empty sites can promote altruistic behavior

Spatial structure has been shown to promote altruistic behavior, however, it also increases the intensity of competition among relatives. Our purpose here is to develop a model in which this competition is minimized, more precisely a local increase in fecundity has a minimal competitive effect on the fitness of nearby individuals. We work with an island model in which sites are allowed to be empty, choosing our demographic rules so that in patches with higher fecundity, empty sites are filled at a higher rate. We also allow dispersal rates to evolve in response to the proportion of empty sites in the patch. Patches with different numbers of empty sites differ in frequency, in within-patch consanguinity, and in reproductive value. Using an inclusive fitness argument, we show that our model does promote altruism; indeed Hamilton's Rule is shown to hold. The only negative effect on an actor of a gift of fecundity to a patchmate turns out to be a slight decrease in reproductive value due to an increased probability of an empty site being occupied. We show that altruists are most favored in islands with an intermediate number of empty sites.     

Altruism via kin-selection strategies that rely on arbitrary tags with which they coevolve

Hamilton's rule explains when natural selection will favor altruism between conspecifics, given their degree of relatedness. In practice, indicators of relatedness (such as scent) coevolve with strategies based on these indicators, a fact not included in previous theories of kin recognition. Using a combination of simulation modeling and mathematical extension of Hamilton's rule, we demonstrate how altruism can emerge and be sustained in a coevolutionary setting where relatedness depends on an individual's social environment and varies from one locus to another. The results support a very general expectation of widespread, and not necessarily weak, conditional altruism in nature.     

Kin selection in human populations: theory reconsidered

Past considerations of kin selection have assumed a dyadic fitness exchange relationship between altruist and recipient. This approach does not account for all alleles affected by altruistic behavior. This can be corrected by focusing on matings rather than on individuals. I present a model that tries to account for fitness changes resulting from altruistic acts, not only for the altruist and recipient but also for their spouses, in an evolving population. Results from this model indicate that Hamilton's rule fails to predict when the altruism allele will increase in frequency and, more important, suggest that kin selection can, at most, account for low levels of a gene for altruism but only if fairly extreme conditions are met.     

Detecting kin selection at work using inclusive fitness

A recent model shows that altruism can evolve with limited migration and variable group sizes, and the authors claim that kin selection cannot provide a sufficient explanation of their results. It is demonstrated, using a recent reformulation of Hamilton's original arguments, that the model falls squarely within the scope of inclusive fitness theory, which furthermore shows how to calculate inclusive fitness and the relevant relatedness. A distinction is drawn between inclusive fitness, which is a method of analysing social behaviour; and kin selection, a process that operates through genetic similarity brought about by common ancestry, but not by assortation by genotype or by direct assessment of genetic similarity. The recent model is analysed, and it turns out that kin selection provides a sufficient explanation to considerable quantitative accuracy, contrary to the authors' claims. A parallel analysis is possible and would be illuminating for all models of social behaviour in which individuals' effects on each other's offspring numbers combine additively.     

Comparative statics of games between relatives

According to Hamilton's theory of kin selection, species tend to evolve behavior such that each organism appears to be attempting to maximize its inclusive fitness. In particular, two neighbors are likely to help each other if the cost of doing so is less than the benefit multiplied by r, their coefficient of relatedness. Since the latter is less than unity, mutual altruism benefits both neighbors. However, is it theoretically possible that acting so as to maximize the inclusive, rather than personal, fitness may harm both parties. This may occur in strategic symmetric pairwise interactions (more specifically, nxn games), in which the outcome depends on both sides' actions. In this case, the equilibrium outcome may be less favorable to the interactants' personal fitness than if each of them acted so as to maximize the latter. This paper shows, however, that such negative effect of relatedness on fitness is incompatible with evolutionary stability. If the symmetric equilibrium strategies are evolutionarily stable, a higher coefficient of relatedness can only entail higher personal fitness for the two neighbors. This suggests that negative comparative statics as above are not likely to occur in nature.     

Hamilton's missing link

Hamilton's famous rule was presented in 1964 in a paper called "The genetical theory of social behaviour (I and II)", Journal of Theoretical Biology 7, 1-16, 17-32. The paper contains a mathematical genetical model from which the rule supposedly follows, but it does not provide a link between the paper's central result, which states that selection dynamics take the population to a state where mean inclusive fitness is maximized, and the rule, which states that selection will lead to maximization of individual inclusive fitness. This note provides a condition under which Hamilton's rule does follow from his central result.     

Transactional skew and assured fitness return models fail to predict patterns of cooperation in wasps

Cooperative breeders often exhibit reproductive skew, where dominant individuals reproduce more than subordinates. Two approaches derived from Hamilton's inclusive fitness model predict when subordinate behavior is favored over living solitarily. The assured fitness return (AFR) model predicts that subordinates help when they are highly likely to gain immediate indirect fitness. Transactional skew models predict dominants and subordinates "agree" on a level of reproductive skew that induces subordinates to join groups. We show the AFR model to be a special case of transactional skew models that assumes no direct reproduction by subordinates. We use data from 11 populations of four wasp species (Polistes, Liostenogaster) as a test of whether transactional frameworks suffice to predict when subordinate behavior should be observed in general and the specific level of skew observed in cooperative groups. The general prediction is supported; in 10 of 11 cases, transactional models correctly predict presence or absence of cooperation. In contrast, the specific prediction is not consistent with the data. Where cooperation occurs, the model accurately predicts highly biased reproductive skew between full sisters. However, the model also predicts that distantly related or unrelated females should cooperate with low skew. This prediction fails: cooperation with high skew is the observed norm. Neither the generalized transactional model nor the special-case AFR model can explain this significant feature of wasp sociobiology. Alternative, nontransactional hypotheses such as parental manipulation and kin recognition errors are discussed.     

Reciprocal altruism in bats and other mammals

In this paper five conditions are specified which must be met before reciprocal altruism, rather than kin selection, should be invoked. Four purported mammalian examples— social grooming in coati, cluster position in roosting pallid bats, information exchange among greater spear-nosed bats, and blood regurgitation among vampire bats—are examined to determine if reciprocal altruism is necessary to plausibly explain each situation. Results from a computer simulation which apportions the relative selective advantage of vampire bat food sharing to kin selection and reciprocal altruism are then presented. The results demonstrate that the increase in individual survivorship due to reciprocal food sharing events in this species provides a greater increase in inclusive fitness than can be attributed to aiding relatives. This analysis suggests that reciprocal altruism can be selectively more important than kin selection when altruistic behaviors in a relatively large social group occur frequently and provide a major fitness benefit to the recipient even when that recipient is related to the donor.     

Hamilton goes empirical: estimation of inclusive fitness from life-history data

Hamilton's theory of kin selection is one of the most important advances in evolutionary biology since Darwin. Central to the kin-selection theory is the concept of inclusive fitness. However, despite the importance of inclusive fitness in evolutionary theory, empirical estimation of inclusive fitness has remained an elusive task. Using the concept of individual fitness, I present a method for estimating inclusive fitness and its components for diploid organisms with age-structured life histories. The method presented here: (i) allows empirical estimation of inclusive fitness from life-history data; (ii) simultaneously considers all components of fitness, including timing and magnitude of reproduction; (iii) is consistent with Hamilton's definition of inclusive fitness; and (iv) adequately addresses shortcomings of existing methods of estimating inclusive fitness. I also demonstrate the application of this new method for testing Hamilton's rule.     

Altruism,tit for tat and ‘outlaw’ genes

Summary In a prior study we combined game theory and inclusive fitness models to examine whether the guarded altruism that can evolve among non-relatives (tit for tat, TFT) might also evolve among close relatives, supplanting unconditional altruism. In most cases, TFT replaced unconditional altruism in family-structured models. Even when TFT is selected at a single locus, however, by withholding altruism from non-reciprocating relatives it may qualify as an outlaw from the standpoint of modifier genes at other loci. Here we examine this possibility with a series of haploid, two-locus models in which a modifier gene transforms TFT into unconditional altruism. The modifier allele spreads to fixation whenever Hamilton's Rule is satisfied, resulting in an unconditional altruist replacing the TFT strategy. As such, TFT may be regarded as an outlaw vulnerable to suppression by alleles at other loci.     

How to measure inclusive fitness

Although inclusive fitness (Hamilton 1964) is regarded as the basic currency of natural selection, difficulty in applying inclusive fitness theory to field studies persists, a quarter-century after its introduction (Grafen 1982, 1984; Brown 1987). For instance, strict application of the original (and currently accepted) definition of inclusive fitness predicts that no one should ever attempt to breed among obligately cooperative breeders. Much of this confusion may have arisen because Hamilton's (1964) original verbal definition of inclusive fitness was not in complete accord with his justifying model. By re-examining Hamilton's original model, a modified verbal definition of inclusive fitness can be justified.     

Group selection and kin selection: formally equivalent approaches

Inclusive fitness theory, summarised in Hamilton's rule, is a dominant explanation for the evolution of social behaviour. A parallel thread of evolutionary theory holds that selection between groups is also a candidate explanation for social evolution. The mathematical equivalence of these two approaches has long been known. Several recent papers, however, have objected that inclusive fitness theory is unable to deal with strong selection or with non-additive fitness effects, and concluded that the group selection framework is more general, or even that the two are not equivalent after all. Yet, these same problems have already been identified and resolved in the literature. Here, I survey these contemporary objections, and examine them in the light of current understanding of inclusive fitness theory.