Upstream reciprocity and the evolution of gratitude

If someone is nice to you, you feel good and may be inclined to be nice to somebody else. This every day experience is borne out by experimental games: the recipients of an act of kindness are more likely to help in turn, even if the person who benefits from their generosity is somebody else. This behaviour, which has been called ‘upstream reciprocity’, appears to be a misdirected act of gratitude: you help somebody because somebody else has helped you. Does this make any sense from an evolutionary or a game theoretic perspective? In this paper, we show that upstream reciprocity alone does not lead to the evolution of cooperation, but it can evolve and increase the level of cooperation if it is linked to either direct or spatial reciprocity. We calculate the random walks of altruistic acts that are induced by upstream reciprocity. Our analysis shows that gratitude and other positive emotions, which increase the willingness to help others, can evolve in the competitive world of natural selection.     

Participation costs can suppress the evolution of upstream reciprocity

Indirect reciprocity, one of the many mechanisms proposed to explain the evolution of cooperation, is the idea that altruistic actions can be rewarded by third parties. Upstream or generalized reciprocity is one type of indirect reciprocity in which individuals help someone if they have been helped by somebody else in the past. Although empirically found to be at work in humans, the evolution of upstream reciprocity is difficult to explain from a theoretical point of view. A recent model of upstream reciprocity, first proposed by Nowak and Roch (2007) and further analyzed by Iwagami and Masuda (2010), shows that while upstream reciprocity alone does not lead to the evolution of cooperation, it can act in tandem with mechanisms such as network reciprocity and increase the total level of cooperativity in the population. We argue, however, that Nowak and Roch's model systematically leads to non-uniform interaction rates, where more cooperative individuals take part in more games than less cooperative ones. As a result, the critical benefit-to-cost ratios derived under this model in previous studies are not invariant with respect to the addition of participation costs. We show that accounting for these costs can hinder and even suppress the evolution of upstream reciprocity, both for populations with non-random encounters and graph-structured populations.     

Social structure of primate interaction networks facilitates the emergence of cooperation

Animal cooperation has puzzled biologists for a long time as its existence seems to contravene the basic notion of evolutionary biology that natural selection favours ‘selfish’ genes that promote only their own well-being. Evolutionary game theory has shown that cooperators can prosper in populations of selfish individuals if they occur in clusters, interacting more frequently with each other than with the selfish. Here we show that social networks of primates possess the necessary social structure to promote the emergence of cooperation. By simulating evolutionary dynamics of cooperative behaviour on interaction networks of 70 primate groups, we found that for most groups network reciprocity augmented the fixation probability for cooperation. The variation in the strength of this effect can be partly explained by the groups’ community modularity—a network measure for the groups’ heterogeneity. Thus, given selective update and partner choice mechanisms, network reciprocity has the potential to explain socially learned forms of cooperation in primate societies.     

The dissimilarity of species interaction networks

In a context of global changes, and amidst the perpetual modification of community structure undergone by most natural ecosystems, it is more important than ever to understand how species interactions vary through space and time. The integration of biogeography and network theory will yield important results and further our understanding of species interactions. It has, however, been hampered so far by the difficulty to quantify variation among interaction networks. Here, we propose a general framework to study the dissimilarity of species interaction networks over time, space or environments, allowing both the use of quantitative and qualitative data. We decompose network dissimilarity into interactions and species turnover components, so that it is immediately comparable to common measures of β‐diversity. We emphasise that scaling up β‐diversity of community composition to the β‐diversity of interactions requires only a small methodological step, which we foresee will help empiricists adopt this method. We illustrate the framework with a large dataset of hosts and parasites interactions and highlight other possible usages. We discuss a research agenda towards a biogeographical theory of species interactions.     

Effects of social group size on information transfer and task allocation

Summary Social animals exchange information during social interaction. The rate of interaction and, hence, the rate of information exchange, typically changes with density and density may be affected by the size of the social group. We investigate models in which each individual may be engaged in one of several tasks. For example, the different tasks could represent alternative foraging locations exploited by an ant colony. An individual's decision about which task to pursue depends both on environmental stimuli and on interactions among individuals. We examine how group size affects the allocation of individuals among the various tasks. Analysis of the models shows the following. (1) Simple interactions among individuals with limited ability to process information can lead to group behaviour that closely approximates the predictions of evolutionary optimality models, (2) Because per capita rates of social interaction may increase with group size, larger groups may be more efficient than smaller ones at tracking a changing environment, (3) Group behaviour is determined both by each individual's interaction with environmental stimuli and by social exchange of information. To keep these processes in balance across a range of group sizes, organisms are predicted to regulate per capita rates of social interaction and (4) Stochastic models show, at least in some cases, that the results described here occur even in small groups of approximately ten individuals.     

The geographic structure of selection on a coevolving interaction between social parasitic wasps and their hosts hampers social evolution

Social parasites exploit societies, rather than organisms, and rear their brood in social insect colonies at the expense of their hosts, triggering a coevolutionary process that may affect host social structure. The resulting coevolutionary trajectories may be further altered by selection imposed by predators, which exploit the abundant resources concentrated in these nests. Here, we show that geographic differences in selection imposed by predators affects the structure of selection on coevolving hosts and their social parasites. In a multiyear study, we monitored the fate of the annual breeding attempts of the solitary nesting foundresses of Polistes biglumis wasps in four geographically distinct populations that varied in levels of attack by the congeneric social parasite, P. atrimandibularis. Foundress fitness depended mostly on whether, during the long founding phase, a colony was invaded by social parasites or attacked by predators. Foundresses from each population differed in morphological traits and reproductive tactics that were consistent with selection imposed by their natural enemies and in ways that may affect host sociality. In turn, parasite traits were consistent with selection imposed locally by hosts, implying a geographic mosaic of coevolution in this brood parasitic interaction.     

The effects of data collection and observation methods on uncertainty of social networks in wild primates

In social species, network centralities of group members shape social transmission and other social phenomena. Different factors have been found to influence the measurement of social networks, such as data collection and observation methods. In this study, we collected data on adults and juveniles and examined the effect of data collection method (ad libitum sampling vs. focal animal sampling) and observation method (interaction—grooming; play—vs. association—arm-length; 2 m; 5 m proximities—) on social networks in wild vervet monkeys. First, we showed using a bootstrapping method, that uncertainty of ad libitum grooming and play matrices were lesser than uncertainty of focal matrices. Nevertheless, grooming and play networks constructed from ad libitum and focal animal sampling were very similar and highly correlated. We improved the certainty of both grooming and play networks by pooling focal and ad libitum matrices. Second, we reported a high correlation between the proximity arm-length network and the focal grooming one making an arm-length proximity network a reasonable proxy for a grooming one in vervet monkeys. However, we did not find such a correlation between proximity networks and the play one. Studying the effects of methodological issues as data collection and observation methods can help improve understanding of what shapes social networks and which data collection method to choose to study sociality.     

The influence of social interaction on the acclimation of rainbow trout, Oncorhynchus mykiss (Walbaum) to chronic stress

To establish the time required for fish to acclimate to experimental conditions, comprising holding within a spatially restrictive environment, rainbow trout were transferred from rearing tanks (1500 1) to smaller volume holding tanks (50 1). The fish were maintained singly, in pairs, in groups of five fish, and in groups of 10 fish, and selected indices of physiological stress were monitored at intervals following the onset of confinement. In all cases transfer and confinement provoked a stress response in the fish, indicated by significantly elevated plasma cortisol levels, and significantly reduced numbers of circulating lymphocytes. Recovery of these parameters to levels similar to unstressed control fish, was most rapid among the fish confined singly, requiring 2 to 4 weeks, although weight gain, indicative of feeding, was apparent within 1 to 2 weeks. Acclimation of the fish confined as pairs was severely confounded by the development of hierarchical relationships between the fish. This resulted in some individuals displaying rapid acclimation and growth, in contrast to other fish within the groups which failed to acclimate, exhibited signs of chronic stress, and ultimately succumbed to bacterial infections. Similar, though less severe, evidence of social stress was observed among the fish confined as groups of five. A decline in the coefficient of variance for weight within the fish confined as groups of 10 suggested an absence of growth inhibition due to social interaction among these fish. The implications of these results for experimental design are discussed.     

The influence of grafted polymer architecture and fluid hydrodynamics on protein separation by entropic interaction chromatography

Entropic interaction chromatography (EIC) provides efficient size-based separation of protein mixtures through the entropy change associated with solute partitioning into a layer of hydrophilic homopolymer that has been end-grafted within the pores of a macroporous chromatography support. In this work, surface-initiated atom-transfer radical polymerization (ATRP) is used to prepare a library of EIC stationary phases covering a wide range of grafted-chain densities and molecular weights. Exhaustive chain cleavage and analysis by saponification and GPC-MALLS, respectively, show that the new ATRP synthesis procedure allows for excellent control over graft molecular weight and polydispersity. The method is used to prepare high-density grafts (up to 0.164 +/- 0.005 chains/nm(2)) that extend the range of EIC applications to include efficient buffer-exchange and desalting of protein preparations. Reducing the graft density allows for greater partitioning of high molecular weight solutes, extending the linear range of the selectivity curve. Increasing graft molecular weight also alters selectivity, but more directly affects column capacity by increasing the volume of the grafted layer. Protein partitioning in high-density EIC columns is found to decrease with mobile-phase velocity (u). Although solute mass transfer resistances leading to an increase in plate height can explain this effect, pressure drop data across the column are indicative of weak convective flow through at least a fraction of the grafted architecture. Modeling of the grafted brush properties in the presence of solvent flow by subjecting a self-consistent-field theory representation of the brush to a viscous shear force predicts that the grafted chains will tilt and elongate in the direction of flow. The shear force may therefore act to reduce the number of conformations available to chains, increasing their rigidity without significantly altering the thickness of the grafted layer. A reduction in protein partitioning is then predicted when the dependence on u of the solute entropy loss is stronger than that of the grafted polymer, a condition met at high graft densities.