Individual costs and societal benefits of interventions during the COVID-19 pandemic.

Individual and societal reactions to an ongoing pandemic can lead to social dilemmas: In some cases, each individual is tempted to not follow an intervention, but for the whole society, it would be best if they did. Now that in most countries, the extent of regulations to reduce SARS-CoV-2 transmission is very small, interventions are driven by individual decision-making. Assuming that individuals act in their best own interest, we propose a framework in which this situation can be quantified, depending on the protection the intervention provides to a user and to others, the risk of getting infected, and the costs of the intervention. We discuss when a tension between individual and societal benefits arises and which parameter comparisons are important to distinguish between different regimes of intervention use.

Sex or cannibalism: Polyphenism and kin recognition control social action strategies in nematodes.

Resource polyphenisms, where single genotypes produce alternative feeding strategies in response to changing environments, are thought to be facilitators of evolutionary novelty. However, understanding the interplay between environment, morphology, and behavior and its significance is complex. We explore a radiation of Pristionchus nematodes with discrete polyphenic mouth forms and associated microbivorous versus cannibalistic traits. Notably, comparing 29 Pristionchus species reveals that reproductive mode strongly correlates with mouth-form plasticity. Male-female species exhibit the microbivorous morph and avoid parent-offspring conflict as indicated by genetic hybrids. In contrast, hermaphroditic species display cannibalistic morphs encouraging competition. Testing predation between 36 co-occurring strains of the hermaphrodite P. pacificus showed that killing inversely correlates with genomic relatedness. These empirical data together with theory reveal that polyphenism (plasticity), kin recognition, and relatedness are three major factors that shape cannibalistic behaviors. Thus, developmental plasticity influences cooperative versus competitive social action strategies in diverse animals.

Evolution of multicellular life cycles under costly fragmentation.

A fascinating wealth of life cycles is observed in biology, from unicellularity to the concerted fragmentation of multicellular units. However, the understanding of factors driving their evolution is still limited. We show that costs of fragmentation have a major impact on the evolution of life cycles due to their influence on the growth rates of the associated populations. We model a group structured population of undifferentiated cells, where cell clusters reproduce by fragmentation. Fragmentation events are associated with a cost expressed by either a fragmentation delay, an additional risk, or a cell loss. The introduction of such fragmentation costs vastly increases the set of possible life cycles. Based on these findings, we suggest that the evolution of life cycles involving splitting into multiple offspring can be directly associated with the fragmentation cost. Moreover, the impact of this cost alone is strong enough to drive the emergence of multicellular units that eventually split into many single cells, even under scenarios that strongly disfavour collectives compared to solitary individuals.

Which risk scenarios can drive the emergence of costly cooperation?

In collective risk dilemmas, cooperation prevents collective loss only when players contribute sufficiently. In these more complex variants of a social dilemma, the form of the risk curve is crucial and can strongly affect the feasibility of a cooperative outcome. The risk typically depends on the sum of all individual contributions. Here, we introduce a general approach to analyze the stabilization of cooperation under any decreasing risk curve and discuss how different risk curves affect cooperative outcomes. We show that the corresponding solutions can be reached by social learning or evolutionary dynamics. Furthermore, we extend our analysis to cases where individuals do not only care about their expected payoff, but also about the associated distribution of payoffs. This approach is an essential step to understand the effects of risk decay on cooperation.

Evolutionary performance of zero-determinant strategies in multiplayer games.

Repetition is one of the key mechanisms to maintain cooperation. In long-term relationships, in which individuals can react to their peers׳ past actions, evolution can promote cooperative strategies that would not be stable in one-shot encounters. The iterated prisoner׳s dilemma illustrates the power of repetition. Many of the key strategies for this game, such as ALLD, ALLC, Tit-for-Tat, or generous Tit-for-Tat, share a common property: players using these strategies enforce a linear relationship between their own payoff and their co-player׳s payoff. Such strategies have been termed zero-determinant (ZD). Recently, it was shown that ZD strategies also exist for multiplayer social dilemmas, and here we explore their evolutionary performance. For small group sizes, ZD strategies play a similar role as for the repeated prisoner׳s dilemma: extortionate ZD strategies are critical for the emergence of cooperation, whereas generous ZD strategies are important to maintain cooperation. In large groups, however, generous strategies tend to become unstable and selfish behaviors gain the upper hand. Our results suggest that repeated interactions alone are not sufficient to maintain large-scale cooperation. Instead, large groups require further mechanisms to sustain cooperation, such as the formation of alliances or institutions, or additional pairwise interactions between group members.

Under high stakes and uncertainty the rich should lend the poor a helping hand.

In social dilemmas, there is tension between individual incentives to optimize personal gain versus social benefits. An additional cause of conflict in such social dilemmas is heterogeneity. Cultural differences or financial inequity often interfere with decision making when a diverse group of individuals interact. We address these issues in situations where individuals are either rich or poor. Often, it is unclear how rich and poor individuals should interact - should the poor invest the same as the rich, or should the rich assist the poor? Which distribution of efforts can be considered as fair? To address the effects of heterogeneity on decisions, we model a collective-risk dilemma where players collectively have to invest more than a certain threshold, with heterogeneity and multiple rounds. We aim to understand the natural behavior and to infer which strategies are particularly stable in such asymmetric collective-risk games. Large scale individual based simulations show that when the poor players have half of the wealth the rich players posses, the poor contribute only when early contributions are made by the rich players. The rich contribute on behalf of the poor only when their own external assets are worth protecting. Under a certain degree of uncertainty we observe the rich maintain cooperation by assisting the poor.

An economic experiment reveals that humans prefer pool punishment to maintain the commons.

Punishment can stabilize costly cooperation and ensure the success of a common project that is threatened by free-riders. Punishment mechanisms can be classified into pool punishment, where the punishment act is carried out by a paid third party, (e.g. a police system or a sheriff), and peer punishment, where the punishment act is carried out by peers. Which punishment mechanism is preferred when both are concurrently available within a society? In an economic experiment, we show that the majority of subjects choose pool punishment, despite being costly even in the absence of defectors, when second-order free-riders, cooperators that do not punish, are also punished. Pool punishers are mutually enforcing their support for the punishment organization, stably trapping each other. Our experimental results show how organized punishment could have displaced individual punishment in human societies.

How small are small mutation rates?

We consider evolutionary game dynamics in a finite population of size N. When mutations are rare, the population is monomorphic most of the time. Occasionally a mutation arises. It can either reach fixation or go extinct. The evolutionary dynamics of the process under small mutation rates can be approximated by an embedded Markov chain on the pure states. Here we analyze how small the mutation rate should be to make the embedded Markov chain a good approximation by calculating the difference between the real stationary distribution and the approximated one. While for a coexistence game, where the best reply to any strategy is the opposite strategy, it is necessary that the mutation rate µ is less than N (-1/2)exp[-N] to ensure that the approximation is good, for all other games, it is sufficient if the mutation rate is smaller than (N ln N)(-1). Our results also hold for a wide class of imitation processes under arbitrary selection intensity.

Exploring the Link between Genetic Relatedness r and Social Contact Structure k in Animal Social Networks.

Our understanding of how cooperation can arise in a population of selfish individuals has been greatly advanced by theory. More than one approach has been used to explore the effect of population structure. Inclusive fitness theory uses genetic relatedness r to express the role of population structure. Evolutionary graph theory models the evolution of cooperation on network structures and focuses on the number of interacting partners k as a quantity of interest. Here we use empirical data from a hierarchically structured animal contact network to examine the interplay between independent, measurable proxies for these key parameters. We find strong inverse correlations between estimates of r and k over three levels of social organization, suggesting that genetic relatedness and social contact structure capture similar structural information in a real population.

Evolution of cooperation on stochastic dynamical networks.

Cooperative behavior that increases the fitness of others at a cost to oneself can be promoted by natural selection only in the presence of an additional mechanism. One such mechanism is based on population structure, which can lead to clustering of cooperating agents. Recently, the focus has turned to complex dynamical population structures such as social networks, where the nodes represent individuals and links represent social relationships. We investigate how the dynamics of a social network can change the level of cooperation in the network. Individuals either update their strategies by imitating their partners or adjust their social ties. For the dynamics of the network structure, a random link is selected and breaks with a probability determined by the adjacent individuals. Once it is broken, a new one is established. This linking dynamics can be conveniently characterized by a Markov chain in the configuration space of an ever-changing network of interacting agents. Our model can be analytically solved provided the dynamics of links proceeds much faster than the dynamics of strategies. This leads to a simple rule for the evolution of cooperation: The more fragile links between cooperating players and non-cooperating players are (or the more robust links between cooperators are), the more likely cooperation prevails. Our approach may pave the way for analytically investigating coevolution of strategy and structure.

Social learning promotes institutions for governing the commons.

Theoretical and empirical research highlights the role of punishment in promoting collaborative efforts. However, both the emergence and the stability of costly punishment are problematic issues. It is not clear how punishers can invade a society of defectors by social learning or natural selection, or how second-order free-riders (who contribute to the joint effort but not to the sanctions) can be prevented from drifting into a coercion-based regime and subverting cooperation. Here we compare the prevailing model of peer-punishment with pool-punishment, which consists in committing resources, before the collaborative effort, to prepare sanctions against free-riders. Pool-punishment facilitates the sanctioning of second-order free-riders, because these are exposed even if everyone contributes to the common good. In the absence of such second-order punishment, peer-punishers do better than pool-punishers; but with second-order punishment, the situation is reversed. Efficiency is traded for stability. Neither other-regarding tendencies or preferences for reciprocity and equity, nor group selection or prescriptions from higher authorities, are necessary for the emergence and stability of rudimentary forms of sanctioning institutions regulating common pool resources and enforcing collaborative efforts.

Via freedom to coercion: the emergence of costly punishment.

In human societies, cooperative behavior in joint enterprises is often enforced through institutions that impose sanctions on defectors. Many experiments on so-called public goods games have shown that in the absence of such institutions, individuals are willing to punish defectors, even at a cost to themselves. Theoretical models confirm that social norms prescribing the punishment of uncooperative behavior are stable-once established, they prevent dissident minorities from spreading. But how can such costly punishing behavior gain a foothold in the population? A surprisingly simple model shows that if individuals have the option to stand aside and abstain from the joint endeavor, this paves the way for the emergence and establishment of cooperative behavior based on the punishment of defectors. Paradoxically, the freedom to withdraw from the common enterprise leads to enforcement of social norms. Joint enterprises that are compulsory rather than voluntary are less likely to lead to cooperation.