Is there a role for culture in human behavioral ecology?

Most research in human behavioral ecology has been acultural, which raises the question of how best to incorporate the concept of culture into this approach. A necessary step in this direction is to pare the culture concept down to its ideational elements, excluding behavior and its material products (Durham 1991; Geertz 1973; Keesing 1974). The cultural and reproductive success hypothesis, though empirically successful (Irons 1993), is not a model for all of culture because of widespread discrepancies between behavior and culture to which it does not call attention. Cultural transmission models are also weakened by such discrepancies, but, more importantly, such models are most relevant to phenomena different from those central to human behavioral ecology. A better way to incorporate culture into human behavioral ecology is to see it as the context of human action and as a tool people use in social manipulation. The study of signal systems is a key to an understanding of social manipulation and to the incorporation of culture into human behavioral ecology. Examples of the manipulation of culture for reproductive benefit include Yanomamö kin term manipulation (Chagnon 1988), incest rules (Thornhill 1990, 1991), and the derogation of sexual competitors (Buss and Dedden 1990). The human behavioral ecological study of social manipulation in cultural contexts needs to be expanded. Two phenomena that might shed light on such manipulation are the Rashomon effect and the audience effect.     

PROBLEMS WITH TESTING INBREEDING AVOIDANCE: THE CASE OF THE COLLARED FLYCATCHER

Four year's data on collared flycatchers, Ficedula albicollis, breeding in a nestbox plot on the island of Gotland, Sweden, was used to investigate whether individuals avoid mating with close kin (i.e., parents or sibs). Only one case of close inbreeding (0.5% of all pairs) was observed during the years of study. The observed frequency of close inbreeding was compared to expected frequencies based on two different null models. Assuming no inbreeding avoidance behaviors (e.g., dispersal or kin recognition), but taking into account the fact that mortality, and different arrival and pairing times of individuals reduce the probability of mating with close kin, the expected frequency of close inbreeding is 10% and 15% for female and male recruits (i.e., born in the study plot), respectively. However, assuming mating to be random within the study plot reduced the expected frequency of close inbreeding to 1% or less for both males and females. Consequently, conclusions drawn concerning inbreeding avoidance depend on the null model used. Contrasting estimated costs of tolerating close inbreeding with those of avoiding it (by dispersal to other plots), however, suggests that the costs of avoiding close inbreeding are substantially greater than those of tolerating it. Therefore, although inbreeding avoidance cannot be rejected as a cause of dispersal of this species, it is not the primary cause, and particularly not for sex-biased dispersal. The general problems of investigating inbreeding avoidance are discussed. It is argued that all previous null models based on random mating in finite populations produce expected frequencies of close inbreeding that in fact include inbreeding avoidance, since they implicitly assume random dispersal within a finite population. Thus, comparisons between observed and expected frequencies of close inbreeding based on random mating are inadequate. The most promising method of investigating inbreeding avoidance is to experimentally study individual movements and mating preferences in the presence and absence of close kin.     

Dynamics of alliance formation and the egalitarian revolution

Background

Arguably the most influential force in human history is the formation of social coalitions and alliances (i.e., long-lasting coalitions) and their impact on individual power. Understanding the dynamics of alliance formation and its consequences for biological, social, and cultural evolution is a formidable theoretical challenge. In most great ape species, coalitions occur at individual and group levels and among both kin and non-kin. Nonetheless, ape societies remain essentially hierarchical, and coalitions rarely weaken social inequality. In contrast, human hunter-gatherers show a remarkable tendency to egalitarianism, and human coalitions and alliances occur not only among individuals and groups, but also among groups of groups. These observations suggest that the evolutionary dynamics of human coalitions can only be understood in the context of social networks and cognitive evolution.

Methodology/Principal Findings

Here, we develop a stochastic model describing the emergence of networks of allies resulting from within-group competition for status or mates between individuals utilizing dyadic information. The model shows that alliances often emerge in a phase transition-like fashion if the group size, awareness, aggressiveness, and persuasiveness of individuals are large and the decay rate of individual affinities is small. With cultural inheritance of social networks, a single leveling alliance including all group members can emerge in several generations.

Conclusions/Significance

We propose a simple and flexible theoretical approach for studying the dynamics of alliance emergence applicable where game-theoretic methods are not practical. Our approach is both scalable and expandable. It is scalable in that it can be generalized to larger groups, or groups of groups. It is expandable in that it allows for inclusion of additional factors such as behavioral, genetic, social, and cultural features. Our results suggest that a rapid transition from a hierarchical society of great apes to an egalitarian society of hunter-gatherers (often referred to as “egalitarian revolution”) could indeed follow an increase in human cognitive abilities. The establishment of stable group-wide egalitarian alliances creates conditions promoting the origin of cultural norms favoring the group interests over those of individuals.     

Genetic relatedness and group size in an aggregation economy

Summary We use Hamilton's Rule to investigate effects of genetic relatedness on the predicted size of social groups. We assume an aggregation economy; individual fitness initially increases with group size, but in sufficiently large groups each member's individual fitness declines with further increments in the size of the group. We model two processes of group formation, designated free entry and group-controlled entry. The first model assumes that solitary individuals decide to join groups or remain alone; group size equilibrates when solitaries no longer choose to join. The second model allows group members to regulate the size of the group, so that the predicted group size results from members' decisions to repel or accept intruding solitaries. Both the Nash equilibrium group size and any change in the equilibrium caused by varying the level of relatedness depend on the particular entry rule assumed. The largest equilibrium group size occurs when solitaries choose between joining or not joining and individuals are unrelated. Increasing genetic relatedness may reduce and can never increase, equilibrium group size when this entry rule applies. The smallest equilibrium group size occurs when group members choose between repelling or accepting intruders and individuals are unrelated. Under this entry rule, increasing genetic relatedness can increase and can never decrease, equilibrium group size. We extend the models' predictions to suggest when individuals should prefer kin vs non-kin as members of the same group.     

Logistic regression methods for retrospective case-control studies using complex sampling procedures

There are a number of possible designs for case-control studies. The simplest uses two separate simple random samples, but an actual study may use more complex sampling procedures. Typically, stratification is used to control for the effects of one or more risk factors in which we are interested. It has been shown (Anderson, 1972, Biometrika 59, 19-35; Prentice and Pyke, 1979, Biometrika 66, 403-411) that the unconditional logistic regression estimators apply under stratified sampling, so long as the logistic model includes a term for each stratum. We consider the case-control problem with stratified samples and assume a logistic model that does not include terms for strata, i.e., for fixed covariates the (prospective) probability of disease does not depend on stratum. We assume knowledge of the proportion sampled in each stratum as well as the total number in the stratum. We use this knowledge to obtain the maximum likelihood estimators for all parameters in the logistic model including those for variables completely associated with strata. The approach may also be applied to obtain estimators under probability sampling.     

"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.     

Indirect genetic effects and kin recognition: estimating IGEs when interactions differ between kin and strangers

Social interactions among individuals are widespread, both in natural and domestic populations. As a result, trait values of individuals may be affected by genes in other individuals, a phenomenon known as indirect genetic effects (IGEs). IGEs can be estimated using linear mixed models. The traditional IGE model assumes that an individual interacts equally with all its partners, whether kin or strangers. There is abundant evidence, however, that individuals behave differently towards kin as compared with strangers, which agrees with predictions from kin-selection theory. With a mix of kin and strangers, therefore, IGEs estimated from a traditional model may be incorrect, and selection based on those estimates will be suboptimal. Here we investigate whether genetic parameters for IGEs are statistically identifiable in group-structured populations when IGEs differ between kin and strangers, and develop models to estimate such parameters. First, we extend the definition of total breeding value and total heritable variance to cases where IGEs depend on relatedness. Next, we show that the full set of genetic parameters is not identifiable when IGEs differ between kin and strangers. Subsequently, we present a reduced model that yields estimates of the total heritable effects on kin, on non-kin and on all social partners of an individual, as well as the total heritable variance for response to selection. Finally we discuss the consequences of analysing data in which IGEs depend on relatedness using a traditional IGE model, and investigate group structures that may allow estimation of the full set of genetic parameters when IGEs depend on kin.     

Family counts: deciding when to murder among the Icelandic Vikings

In small scale societies, lethal attacks on another individual usually invite revenge by the victim's family. We might expect those who perpetrate such attacks to do so only when their own support network (mainly family) is larger than that of the potential victim so as to minimise the risk of retaliation. Using data from Icelandic family sagas, we show that this prediction holds whether we consider biological kin or affinal kin (in-laws): on average, killers had twice as many relatives as their victims. These findings reinforce the importance of kin as a source of implicit protection even when they are not physically present. The results also support Hughes' (1988) claim that affines are biological kin because of the shared genetic interests they have in the offspring generation.     

THE EVOLUTIONARILY STABLE PHENOTYPE DISTRIBUTION IN A RANDOM ENVIRONMENT

In an unpredictably changing environment, phenotypic variability may evolve as a “bet-hedging” strategy. We examine here two models for evolutionarily stable phenotype distributions resulting from stabilizing selection with a randomly fluctuating optimum. Both models include overlapping generations, either survival of adults or a dormant propagule pool. In the first model (mixed-strategies model) we assume that individuals can produce offspring with a distribution of phenotypes, in which case, the evolutionarily stable population always consists of a single genotype. We show that there is a unique evolutionarily stable strategy (ESS) distribution that does not depend on the amount of generational overlap, and that the ESS distribution generically is discrete rather than continuous; that is, there are distinct classes of offspring rather than a continuous distribution of offspring phenotypes. If the probability of extreme fluctuations in the optimum is sufficiently small, then the ESS distribution is monomorphic: a single type fitted to the mean environment. At higher levels of variability, the ESS distribution is polymorphic, and we find stability conditions for dimorphic distributions. For an exponential or similarly broad-tailed distribution of the optimum phenotype, the ESS consists of an infinite number of distinct phenotypes. In the second model we assume that an individual produces offspring with a single, genetically determined phenotype (pure-strategies model). The ESS population then contains multiple genotypes when the environmental variance is sufficiently high. However the phenotype distributions are similar to those in the mixed-strategies model: discrete, with an increasing number of distinct phenotypes as the environmental variance increases.     

Chemosignals of fear enhance cognitive performance in humans

It is well documented across phyla that animals experiencing stress and fear produce chemical warning signals that can lead to behavioral, endocrinological, and immunological changes in the recipient animals of the same species. Humans distinguish between fear and other emotional chemosignals based on olfactory cues. Here, we study the effect of human fear chemosignals on the speed and accuracy of cognitive performance. In a double-blind experiment, female participants performed a word-association task while smelling one of the three types of olfactory stimuli: fear sweat, neutral sweat, and control odor carrier. We found that the participants exposed to the fear condition performed more accurately and yet with no sacrifice for speed on meaningful word conditions than those under either the neutral or the control condition. At the same time, they performed slower on tasks that contained ambiguous content. Possible factors that could introduce bias, such as individual differences due to anxiety, verbal skills, and perceived qualities of the smells, were ruled out. Our results demonstrate that human fear chemosignals enhance cognitive performances in the recipient. We suggest that this effect originates from learned associations, including greater cautiousness and concomitant changes in cognitive strategies.     

Density and genetic relatedness increase dispersal distance in a subsocial organism

Although dispersal distance plays a major role in determining whether organisms will reach new habitats, empirical data on the environmental factors that affect dispersal distance are lacking. Population density and kin competition are two factors theorised to increase dispersal distance. Using the two‐spotted spider mite as a model species, we altered these two environmental conditions and measured the mean dispersal distance of individuals, as well as other attributes of the dispersal kernel. We find that both density and relatedness in the release patch increase dispersal distance. Relatedness, but not density, changes the shape of the dispersal kernel towards a more skewed and leptokurtic shape including a longer ‘fat‐tail’. This is the first experimental demonstration that kin competition can shape the whole distribution of dispersal distances in a population, and thus affect the geographical spread of dispersal phenotypes.     

Strong reciprocity, human cooperation, and the enforcement of social norms

This paper provides strong evidence challenging the self-interest assumption that dominates the behavioral sciences and much evolutionary thinking. The evidence indicates that many people have a tendency to voluntarily cooperate, if treated fairly, and to punish noncooperators. We call this behavioral propensity “strong reciprocity” and show empirically that it can lead to almost universal cooperation in circumstances in which purely self-interested behavior would cause a complete breakdown of cooperation. In addition, we show that people are willing to punish those who behaved unfairly towards a third person or who defected in a Prisoner’s Dilemma game with a third person. This suggests that strong reciprocity is a powerful device for the enforcement of social norms involving, for example, food sharing or collective action. Strong reciprocity cannot be rationalized as an adaptive trait by the leading evolutionary theories of human cooperation (in other words, kin selection, reciprocal altruism, indirect reciprocity, and costly signaling theory). However, multilevel selection theories of cultural evolution are consistent with strong reciprocity.     

Constraints on the origin and maintenance of genetic kin recognition

Kin-recognition mechanisms allow helping behaviors to be directed preferentially toward related individuals, and could be expected to evolve in many cases. However, genetic kin recognition requires a genetic polymorphism on which recognition is based, and kin discriminating behaviors will affect the evolution of such polymorphism. It is unclear whether genetic polymorphisms used in kin recognition should be maintained by extrinsic selection pressures or not, as opposite conclusions have been reached by analytical one-locus models and simulations exploring different population structures. We analyze a two-locus model in a spatially subdivided population following the island model of dispersal between demes of finite size. We find that in the absence of mutation, selection eliminates polymorphism in most cases, except with extreme spatial structure and low recombination. With mutation, the population may reach a stable limit cycle over which both loci are polymorphic; however, the average frequency of conditional helping can be high only under strong structure and low recombination. Finally, we review evidence for extrinsic selection maintaining polymorphism on which kin recognition is based.     

Growing with siblings: a common ground for cooperation or for fiercer competition among plants?

Recent work has shown that certain plants can identify their kin in competitive settings through root recognition, and react by decreasing root growth when competing with relatives. Although this may be a necessary step in kin selection, no clear associated improvement in individual or group fitness has been reported to qualify as such. We designed an experiment to address whether genetic relatedness between neighbouring plants affects individual or group fitness in artificial populations. Seeds of Lupinus angustifolius were sown in groups of siblings, groups of different genotypes from the same population and groups of genotypes from different populations. Both plants surrounded by siblings and by genotypes from the same population had lower individual fitness and produced fewer flowers and less vegetative biomass as a group. We conclude that genetic relatedness entails decreased individual and group fitness in L. angustifolius. This, together with earlier work, precludes the generalization that kin recognition may act as a widespread, major microevolutionary mechanism in plants.     

The evolution of trans-generational altruism: kin selection meets niche construction

A cornerstone result of sociobiology states that limited dispersal can induce kin competition to offset the kin selected benefits of altruism. Several mechanisms have been proposed to circumvent this dilemma but all assume that actors and recipients of altruism interact during the same time period. Here, this assumption is relaxed and a model is developed where individuals express an altruistic act, which results in posthumously helping relatives living in the future. The analysis of this model suggests that kin selected benefits can then feedback on the evolution of the trait in a way that promotes altruistic helping at high rates under limited dispersal. The decoupling of kin competition and kin selected benefits results from the fact that by helping relatives living in the future, an actor is helping individuals that are not in direct competition with itself. A direct consequence is that behaviours which actors gain by reducing the common good of present and future generations can be opposed by kin selection. The present model integrates niche-constructing traits with kin selection theory and delineates demographic and ecological conditions under which altruism can be selected for; and conditions where the 'tragedy of the commons' can be reduced.     

Dissecting High-Dimensional Phenotypes with Bayesian Sparse Factor Analysis of Genetic Covariance Matrices

Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection. For example, changes in gene expression can provide insight into developmental and physiological mechanisms that link genotype and phenotype. However, classical analytical techniques are poorly suited to quantitative genetic studies of gene expression where the number of traits assayed per individual can reach many thousand. Here, we derive a Bayesian genetic sparse factor model for estimating the genetic covariance matrix (G-matrix) of high-dimensional traits, such as gene expression, in a mixed-effects model. The key idea of our model is that we need consider only G-matrices that are biologically plausible. An organism’s entire phenotype is the result of processes that are modular and have limited complexity. This implies that the G-matrix will be highly structured. In particular, we assume that a limited number of intermediate traits (or factors, e.g., variations in development or physiology) control the variation in the high-dimensional phenotype, and that each of these intermediate traits is sparse – affecting only a few observed traits. The advantages of this approach are twofold. First, sparse factors are interpretable and provide biological insight into mechanisms underlying the genetic architecture. Second, enforcing sparsity helps prevent sampling errors from swamping out the true signal in high-dimensional data. We demonstrate the advantages of our model on simulated data and in an analysis of a published Drosophila melanogaster gene expression data set.     

Low relationship quality predicts scratch contagion during tense situations in orangutans (Pongo pygmaeus)

Primates show various forms of behavioral contagion that are stronger between kin and friends. As a result, behavioral contagion is thought to promote group coordination, social cohesion, and possibly state matching. Aside from contagious yawning, little is known about the contagious effect of other behaviors. Scratching is commonly observed during arousal and as such may play a role within group dynamics. While the Bornean orangutan (Pongo pygmaeus) is commonly considered the least social great ape, orangutans do engage in social interactions. Therefore, their social organization makes them a suitable case for studying the social function of behavioral contagion. Through behavioral observations of captive orangutans, we recorded all yawn and scratch events together with the corresponding behavior of all bystander group-members. As yawning was rarely observed, no conclusions could be drawn regarding this behavior. Scratching was contagious and occurred within 90 s after the triggering scratch. Specifically, orangutans showed increased scratch contagion when they had seen a weakly bonded individual scratch during tense contexts. When the orangutan had not seen the triggering scratch, the contagiousness of scratching was not affected by context or relationship quality. Our results indicate that behavioral contagion is not simply higher between individuals with stronger social relationships, but that the contagiousness of behaviors may vary based on the context and on social factors. We discuss these findings in light of an adaptive function that may reduce aggression.     

Sex‐biased dispersal: a review of the theory

Dispersal is ubiquitous throughout the tree of life: factors selecting for dispersal include kin competition, inbreeding avoidance and spatiotemporal variation in resources or habitat suitability. These factors differ in whether they promote male and female dispersal equally strongly, and often selection on dispersal of one sex depends on how much the other disperses. For example, for inbreeding avoidance it can be sufficient that one sex disperses away from the natal site. Attempts to understand sex‐specific dispersal evolution have created a rich body of theoretical literature, which we review here. We highlight an interesting gap between empirical and theoretical literature. The former associates different patterns of sex‐biased dispersal with mating systems, such as female‐biased dispersal in monogamous birds and male‐biased dispersal in polygynous mammals. The predominant explanation is traceable back to Greenwood's ( 1980 ) ideas of how successful philopatric or dispersing individuals are at gaining mates or the resources required to attract them. Theory, however, has developed surprisingly independently of these ideas: models typically track how immigration and emigration change relatedness patterns and alter competition for limiting resources. The limiting resources are often considered sexually distinct, with breeding sites and fertilizable females limiting reproductive success for females and males, respectively. We show that the link between mating system and sex‐biased dispersal is far from resolved: there are studies showing that mating systems matter, but the oft‐stated association between polygyny and male‐biased dispersal is not a straightforward theoretical expectation. Here, an important understudied factor is the extent to which movement is interpretable as an extension of mate‐searching (e.g. are matings possible en route or do they only happen after settling in new habitat – or can females perhaps move with stored sperm). We also point out other new directions for bridging the gap between empirical and theoretical studies: there is a need to build Greenwood's influential yet verbal explanation into formal models, which also includes the possibility that an individual benefits from mobility as it leads to fitness gains in more than one final breeding location (a possibility not present in models with a very rigid deme structure). The order of life‐cycle events is likewise important, as this impacts whether a departing individual leaves behind important resources for its female or male kin, or perhaps both, in the case of partially overlapping resource use.     

Predictors of reproductive success in female white-faced capuchins (Cebus capucinus)

Early investigations into variable reproductive success in nonhuman primates tended to focus on the benefits conferred by high dominance rank. However, the effect of high rank on individual reproductive success has been found to vary both intra- and interspecifically, requiring researchers to expand their investigations to include additional factors. Here we examine the age and rank of the mother, sex of the infant, group size, number of close kin, replacement of group males, and resource availability as possible predictors of female reproductive success in white-faced capuchins (Cebus capucinus) in the Santa Rosa sector of the Area de Conservación Guanacaste, Costa Rica. We examine the length of interbirth intervals (IBI) and infant survivorship as measures of individual reproductive success for the 31 adult females that resided in our three study groups between 1986 and 2007. The greatest predictor of IBI length was whether or not the first infant in the interval survived (number of matrilineal kin and resource availability were also significant predictors); while infant survivorship was most significantly predicted by the occurrence of a turnover in group males in the year following the birth of an infant (infant sex was also a significant factor). Based on these findings, we conclude that male and female reproductive strategies are at odds in this species, with male strategies strongly influencing female reproductive success.