Movement patterns, social dynamics, and the evolution of cooperation

Diffusion and pattern formation in spatial games

Diffusion plays an important role in a wide variety of phenomena, from bacterial quorum sensing to the dynamics of traffic flow. While it generally tends to level out gradients and inhomogeneities, diffusion has nonetheless been shown to promote pattern formation in certain classes of systems. Formation of stable structures often serves as a key factor in promoting the emergence and persistence of cooperative behavior in otherwise competitive environments, however, an in-depth analysis on the impact of diffusion on such systems is lacking. We therefore investigate the effects of diffusion on cooperative behavior using a cellular automaton (CA) model of the noisy spatial iterated prisoner's dilemma (IPD), physical extension, and stochasticity being unavoidable characteristics of several natural phenomena. We further derive a mean-field (MF) model that captures the three-species predation dynamics from the CA model and highlight how pattern formation arises in this new model, then characterize how including diffusion by interchange similarly enables the emergence of large scale structures in the CA model as well. We investigate how these emerging patterns favors cooperative behavior for parameter space regions where IPD error rates classically forbid such dynamics. We thus demonstrate how the coupling of diffusion with nonlinear dynamics can, counterintuitively, promote large-scale structure formation and in return establish new grounds for cooperation to take hold in stochastic spatial systems.

Empirically testing a relationship between cooperation and the prime numbers

Theoretical models suggest a relationship between cooperation and the prime numbers. In environments where agents play multiple one-shot prisoner's dilemma games per generation, cooperators evolve to fixation more frequently when cooperating on a cyclical schedule with a prime-number period length. This finding parrots classic predator-prey models showing selection for prime-number prey life cycles. Here, I report an empirical test of the former models using previously published data concerning humans playing one-shot public goods games across multiple time points-i.e. an analogue to multiple one-shot prisoner's dilemma games. I find very modest evidence of cyclicality at prime-numbered time intervals, though results indicate rough agreement between theoretical predictions and observed rates of full cooperation across time points. Analyses of individual decisions find increased contributions to the public good at prime-number time points and separate placebo tests indicate a 4-in-1000 chance of spuriously estimating this effect. However, when exploratory analyses exclude low-value prime-numbered time points, the magnitude of the estimated effect decreases and the hypothesis of no effect cannot be rejected, implying that low-value, prime-number time points drive estimates, contrary to theoretical model predictions. These findings cast doubt on the hypothesis of increased cooperation at prime-number time points-at least among humans playing public goods games.

Cooperation in public goods game does not require assortment and depends on population density

The threshold public goods game is one of the best-known models of non-linear public goods dilemmas. Cooperators and defectors typically coexist in this game when the population is assumed to follow the so-called structured deme model. In this article, we develop a dynamical model of a general N-player game in which there is no deme structure: Individuals interact with randomly chosen neighbours and selection occurs between randomly chosen pairs of individuals. We show that in the deterministic limit, the dynamics in this model leads to the same replicator dynamics as in the structured deme model, i.e., coexistence of cooperators and defectors is typical in threshold public goods game even when the population is completely well mixed. We extend the model to study the effect of density dependence and density fluctuation on the dynamics. We show analytically and numerically that decreasing population density increases the equilibrium frequency of cooperators till the fixation of this strategy, but below a critical density cooperators abruptly disappear from the population. Our numerical investigations show that weak density fluctuations enhance cooperation, while strong fluctuations suppress it.

Time delays shape the eco-evolutionary dynamics of cooperation

We study the intricate interplay between ecological and evolutionary processes through the lens of the prisoner's dilemma game. But while previous studies on cooperation amongst selfish individuals often assume instantaneous interactions, we take into consideration delays to investigate how these might affect the causes underlying prosocial behavior. Through analytical calculations and numerical simulations, we demonstrate that delays can lead to oscillations, and by incorporating also the ecological variable of altruistic free space and the evolutionary strategy of punishment, we explore how these factors impact population and community dynamics. Depending on the parameter values and the initial fraction of each strategy, the studied eco-evolutionary model can mimic a cyclic dominance system and even exhibit chaotic behavior, thereby highlighting the importance of complex dynamics for the effective management and conservation of ecological communities. Our research thus contributes to the broader understanding of group decision-making and the emergence of moral behavior in multidimensional social systems.

Eco-evolutionary cyclic dominance among predators, prey, and parasites

Predator-prey interactions are one of ecology's central research themes, but with many interdisciplinary implications across the social and natural sciences. Here we consider an often-overlooked species in these interactions, namely parasites. We first show that a simple predator-prey-parasite model, inspired by the classical Lotka-Volterra equations, fails to produce a stable coexistence of all three species, thus failing to provide a biologically realistic outcome. To improve this, we introduce free space as a relevant eco-evolutionary component in a new mathematical model that uses a game-theoretical payoff matrix to describe a more realistic setup. We then show that the consideration of free space stabilizes the dynamics by means of cyclic dominance that emerges between the three species. We determine the parameter regions of coexistence as well as the types of bifurcations leading to it by means of analytical derivations as well as by means of numerical simulations. We conclude that the consideration of free space as a finite resource reveals the limits of biodiversity in predator-prey-parasite interactions, and it may also help us in the determination of factors that promote a healthy biota.

Cell aggregation is associated with enzyme secretion strategies in marine polysaccharide-degrading bacteria

Polysaccharide breakdown by bacteria requires the activity of enzymes that degrade polymers either intra- or extra-cellularly. The latter mechanism generates a localized pool of breakdown products that are accessible to the enzyme producers themselves as well as to other organisms. Marine bacterial taxa often show marked differences in the production and secretion of degradative enzymes that break down polysaccharides. These differences can have profound effects on the pool of diffusible breakdown products and hence on the ecological dynamics. However, the consequences of differences in enzymatic secretions on cellular growth dynamics and interactions are unclear. Here we study growth dynamics of single cells within populations of marine Vibrionaceae strains that grow on the abundant marine polymer alginate, using microfluidics coupled to quantitative single-cell analysis and mathematical modelling. We find that strains that have low extracellular secretions of alginate lyases aggregate more strongly than strains that secrete high levels of enzymes. One plausible reason for this observation is that low secretors require a higher cellular density to achieve maximal growth rates in comparison with high secretors. Our findings indicate that increased aggregation increases intercellular synergy amongst cells of low-secreting strains. By mathematically modelling the impact of the level of degradative enzyme secretion on the rate of diffusive oligomer loss, we find that enzymatic secretion capability modulates the propensity of cells within clonal populations to cooperate or compete with each other. Our experiments and models demonstrate that enzymatic secretion capabilities can be linked with the propensity of cell aggregation in marine bacteria that extracellularly catabolize polysaccharides.

Weak selection helps cheap but harms expensive cooperation in spatial threshold dilemmas

Public Goods Games (PGGs) are n-person games with dependence of individual fitness benefits on the collective investment by the players. We have studied a simple PGG scenario played out by cooperating (C) and defecting (D) agents, applying the highly nonlinear threshold benefit function in an individual-based lattice model. A semi-analytical approximation of the lattice model has been developed and shown to describe the dynamics fairly well in the vicinity of the steady state. Besides the expected outcomes (i.e., the negative effect on cooperator persistence of higher cooperation costs and/or more intensive mixing of the population) we have found a surprising, counter-intuitive effect of the strength of selection on the steady state of the model. The effect is different at low and high cooperation costs, and it shows up only in the lattice model, suggesting that stochastic effects and higher order spatial correlations due to the emergent spatial clustering of cooperators (not taken into account in the semi-analytical approximation) must be responsible for the unexpected results for which we propose an intuitive explanation, present a tentative demonstration, and shortly discuss their biological relevance.

Hunter-gatherer foraging networks promote information transmission

Central-place foraging (CPF), where foragers return to a central location (or home), is a key feature of hunter-gatherer social organization. CPF could have significantly changed hunter-gatherers' spatial use and mobility, altered social networks and increased opportunities for information-exchange. We evaluated whether CPF patterns facilitate information-transmission and considered the potential roles of environmental conditions, mobility strategies and population sizes. We built an agent-based model of CPF where agents moved according to a simple optimal foraging rule, and could encounter other agents as they moved across the environment. They either foraged close to their home within a given radius or moved the location of their home to new areas. We analysed the interaction networks arising under different conditions and found that, at intermediate levels of environmental heterogeneity and mobility, CPF increased global and local network efficiencies as well as the rate of contagion-based information-transmission. We also found that central-place mobility strategies can further improve information transmission in larger populations. Our findings suggest that the combination of foraging and movement strategies, as well as the environmental conditions that characterized early human societies, may have been a crucial precursor in our species' unique capacity to innovate, accumulate and rely on complex culture.

Temporal assortment of cooperators in the spatial prisoner's dilemma

We study a spatial, one-shot prisoner's dilemma (PD) model in which selection operates on both an organism's behavioral strategy (cooperate or defect) and its decision of when to implement that strategy, which we depict as an organism's choice of one point in time, out of a set of discrete time slots, at which to carry out its PD strategy. Results indicate selection for cooperators across various time slots and parameter settings, including parameter settings in which cooperation would not evolve in an exclusively spatial model-as in work investigating exogenously imposed temporal networks. Moreover, in the presence of time slots, cooperators' portion of the population grows even under different combinations of spatial structure, transition rules, and update dynamics, though rates of cooperator fixation decline under pairwise comparison and synchronous updating. These findings indicate that, under certain evolutionary processes, merely existing in time and space promotes the evolution of cooperation.

Network Connectivity Dynamics, Cognitive Biases, and the Evolution of Cultural Diversity in Round-Robin Interactive Micro-Societies

The distribution of cultural variants in a population is shaped by both neutral evolutionary dynamics and by selection pressures. The temporal dynamics of social network connectivity, that is, the order in which individuals in a population interact with each other, has been largely unexplored. In this paper, we investigate how, in a fully connected social network, connectivity dynamics, alone and in interaction with different cognitive biases, affect the evolution of cultural variants. Using agent-based computer simulations, we manipulate population connectivity dynamics (early, mid, and late full-population connectivity); content bias, or a preference for high-quality variants; coordination bias, or whether agents tend to use self-produced variants (egocentric bias), or to switch to variants observed in others (allocentric bias); and memory size, or the number of items that agents can store in their memory. We show that connectivity dynamics affect the time-course of variant spread, with lower connectivity slowing down convergence of the population onto a single cultural variant. We also show that, compared to a neutral evolutionary model, content bias accelerates convergence and amplifies the effects of connectivity dynamics, while larger memory size and coordination bias, especially egocentric bias, slow down convergence. Furthermore, connectivity dynamics affect the frequency of high-quality variants (adaptiveness), with late connectivity populations showing bursts of rapid change in adaptiveness followed by periods of relatively slower change, and early connectivity populations following a single-peak evolutionary dynamic. We evaluate our simulations against existing data collected from previous experiments and show how our model reproduces the empirical patterns of convergence.

Eco-evolutionary dynamics of cooperation in the presence of policing

Ecology and evolution are inherently linked, and studying a mathematical model that considers both holds promise of insightful discoveries related to the dynamics of cooperation. In the present article, we use the prisoner's dilemma (PD) game as a basis for long-term apprehension of the essential social dilemma related to cooperation among unrelated individuals. We upgrade the contemporary PD game with an inclusion of evolution-induced act of punishment as a third competing strategy in addition to the traditional cooperators and defectors. In a population structure, the abundance of ecologically-viable free space often regulates the reproductive opportunities of the constituents. Hence, additionally, we consider the availability of free space as an ecological footprint, thus arriving at a simple eco-evolutionary model, which displays fascinating complex dynamics. As possible outcomes, we report the individual dominance of cooperators and defectors as well as a plethora of mixed states, where different strategies coexist followed by maintaining the diversity in a socio-ecological framework. These states can either be steady or oscillating, whereby oscillations are sustained by cyclic dominance among different combinations of cooperators, defectors, and punishers. We also observe a novel route to cyclic dominance where cooperators, punishers, and defectors enter a coexistence via an inverse Hopf bifurcation that is followed by an inverse period doubling route.

Aggregative cycles evolve as a solution to conflicts in social investment

Multicellular organization is particularly vulnerable to conflicts between different cell types when the body forms from initially isolated cells, as in aggregative multicellular microbes. Like other functions of the multicellular phase, coordinated collective movement can be undermined by conflicts between cells that spend energy in fuelling motion and ‘cheaters’ that get carried along. The evolutionary stability of collective behaviours against such conflicts is typically addressed in populations that undergo extrinsically imposed phases of aggregation and dispersal. Here, via a shift in perspective, we propose that aggregative multicellular cycles may have emerged as a way to temporally compartmentalize social conflicts. Through an eco-evolutionary mathematical model that accounts for individual and collective strategies of resource acquisition, we address regimes where different motility types coexist. Particularly interesting is the oscillatory regime that, similarly to life cycles of aggregative multicellular organisms, alternates on the timescale of several cell generations phases of prevalent solitary living and starvation-triggered aggregation. Crucially, such self-organized oscillations emerge as a result of evolution of cell traits associated to conflict escalation within multicellular aggregates.

In aggregative multicellular life cycles, cells come together in heterogenous aggregates, whose collective function benefits all the constituent cells. Current explanations for the evolutionary stability of such organization presume that alternating phases of aggregation and dispersal are already in place. Here we propose that, instead of being externally driven, the temporal arrangement of aggregative life cycles may emerge from the interplay between ecology and evolution in populations with differential motility. In our model, cell motility underpins group formation and allows cells to forage individually and collectively. Notably, slower cells can exploit the propulsion by faster cells within multicellular groups. When the level of such exploitation is let evolve, increasing social conflicts are associated to the evolutionary emergence of self-sustained oscillations. Akin to aggregative life cycles, resource exhaustion triggers group formation, whereas conflicts within multicellular groups restrain resource consumption, thus paving the way for the subsequent unicellular phase. The evolutionary transition from equilibrium coexistence to life cycles solves conflicts among heterogenous cell types by integrating them on a timescale longer than cell division, that comes to be associated to multicellular organization.

The Ecology of Individual Differences Empirically Applied to Space-Use and Movement Tactics

Movement provides a link between individual behavioral ecology and the spatial and temporal variation in an individual's landscape. Individual variation in movement traits is an important axis of animal personality, particularly in the context of foraging ecology. We tested whether individual caribou (Rangifer tarandus) displayed plasticity in movement and space-use behavior across a gradient of resource aggregation. We quantified first-passage time and range-use ratio as proxies for movement-related foraging behavior and examined how these traits varied at the individual level across a foraging resource gradient. Our results suggest that individuals adjusted first-passage time but not range-use ratio to maximize access to high-quality foraging resources. First-passage time was repeatable, and intercepts for first-passage time and range-use ratio were negatively correlated. Individuals matched first-passage time but not range-use ratio to the expectations of our patch-use model that maximized access to foraging resources, a result that suggests that individuals acclimated their movement patterns to accommodate both intra- and interannual variation in foraging resources on the landscape. Collectively, we highlight repeatable movement and space-use tactics and provide insight into how individual plasticity in movement interacts with landscape processes to affect the distribution of behavioral phenotypes and potentially fitness and population dynamics.

Cooperation on Interdependent Networks by Means of Migration and Stochastic Imitation

Evolutionary game theory in the realm of network science appeals to a lot of research communities, as it constitutes a popular theoretical framework for studying the evolution of cooperation in social dilemmas. Recent research has shown that cooperation is markedly more resistant in interdependent networks, where traditional network reciprocity can be further enhanced due to various forms of interdependence between different network layers. However, the role of mobility in interdependent networks is yet to gain its well-deserved attention. Here we consider an interdependent network model, where individuals in each layer follow different evolutionary games, and where each player is considered as a mobile agent that can move locally inside its own layer to improve its fitness. Probabilistically, we also consider an imitation possibility from a neighbor on the other layer. We show that, by considering migration and stochastic imitation, further fascinating gateways to cooperation on interdependent networks can be observed. Notably, cooperation can be promoted on both layers, even if cooperation without interdependence would be improbable on one of the layers due to adverse conditions. Our results provide a rationale for engineering better social systems at the interface of networks and human decision making under testing dilemmas.

The opportunity cost of walking away in the spatial iterated prisoner's dilemma

Previous work with the spatial iterated prisoner's dilemma has shown that the ability to respond to a partner's defection by simply "walking away" allows so-called walk away cooperators to outcompete defectors as well as cooperators that do not respond to defection. These findings are important because they suggest a relatively simple route by which cooperation can evolve. But it remains to be seen just how robust the walk away strategy is to ecologically important variables such as population density, strategic error, and offspring dispersal. The results of our simulation experiments show that the evolutionary success of walk away cooperators decreases with decreasing population density and/or with increasing error. This relationship is best explained by the ways in which population density and error jointly affect the opportunity cost of walking away. This opportunity cost also explains why naive cooperators regularly outcompete walk away cooperators in pair-wise competition, something not observed in previous studies. Our results further show that local offspring dispersal can inhibit the evolution of cooperation by negating the protection low population density affords the most vulnerable cooperators. Our research identifies socio-ecological conditions in which forgiveness trumps flight in the spatial iterated prisoner's dilemma.

Collapse and rescue of cooperation in evolving dynamic networks

The evolutionary dynamics of social traits depend crucially on the social structure of a population. The effects of social structure on social behaviors are well-studied, but relatively little is known about how social structure itself coevolves with social traits. Here, I study such coevolution with a simple yet realistic model of within-group social structure where social connections are either inherited from a parent or made randomly. I show that cooperation evolves when individuals make few random connections, but the presence of cooperation selects for increased rates of random connections, which leads to its collapse. Inherent costs of social connections can prevent this negative feedback, but these costs can negate some or all of the aggregate benefits of cooperation. Exogenously maintained social inheritance can mitigate the latter problem and allow cooperation to increase the average fitness of a population. These results illustrate how coevolutionary dynamics can constrain the long-term persistence of cooperation.

How ecology shapes exploitation: a framework to predict the behavioural response of human and animal foragers along exploration-exploitation trade-offs

Understanding how humans and other animals behave in response to changes in their environments is vital for predicting population dynamics and the trajectory of coupled social-ecological systems. Here, we present a novel framework for identifying emergent social behaviours in foragers (including humans engaged in fishing or hunting) in predator-prey contexts based on the exploration difficulty and exploitation potential of a renewable natural resource. A qualitative framework is introduced that predicts when foragers should behave territorially, search collectively, act independently or switch among these states. To validate it, we derived quantitative predictions from two models of different structure: a generic mathematical model, and a lattice-based evolutionary model emphasising exploitation and exclusion costs. These models independently identified that the exploration difficulty and exploitation potential of the natural resource controls the social behaviour of resource exploiters. Our theoretical predictions were finally compared to a diverse set of empirical cases focusing on fisheries and aquatic organisms across a range of taxa, substantiating the framework's predictions. Understanding social behaviour for given social-ecological characteristics has important implications, particularly for the design of governance structures and regulations to move exploited systems, such as fisheries, towards sustainability. Our framework provides concrete steps in this direction.

Social identity and cooperation in cultural evolution

I discuss the function of social identity signaling in facilitating cooperative group formation, and how the nature of that function changes with the structure of social organization. I propose that signals of social identity facilitate assortment for successful coordination in large-scale societies, and that the multidimensional, context-dependent nature of social identity is crucial for successful coordination when individuals have to cooperate in different contexts. Furthermore, the structure of social identity is tied to the structure of society, so that as societies grow larger and more interconnected, the landscape of social identities grows more heterogeneous. This discussion bears directly on the need to articulate the dynamics of emergent, ephemeral groups as a major factor in human cultural evolution.

Effects of motion in structured populations

In evolutionary processes, population structure has a substantial effect on natural selection. Here, we analyse how motion of individuals affects constant selection in structured populations. Motion is relevant because it leads to changes in the distribution of types as mutations march towards fixation or extinction. We describe motion as the swapping of individuals on graphs, and more generally as the shuffling of individuals between reproductive updates. Beginning with a one-dimensional graph, the cycle, we prove that motion suppresses natural selection for death-birth (DB) updating or for any process that combines birth-death (BD) and DB updating. If the rule is purely BD updating, no change in fixation probability appears in the presence of motion. We further investigate how motion affects evolution on the square lattice and weighted graphs. In the case of weighted graphs, we find that motion can be either an amplifier or a suppressor of natural selection. In some cases, whether it is one or the other can be a function of the relative reproductive rate, indicating that motion is a subtle and complex attribute of evolving populations. As a first step towards understanding less restricted types of motion in evolutionary graph theory, we consider a similar rule on dynamic graphs induced by a spatial flow and find qualitatively similar results, indicating that continuous motion also suppresses natural selection.

Mobility can promote the evolution of cooperation via emergent self-assortment dynamics

The evolution of costly cooperation, where cooperators pay a personal cost to benefit others, requires that cooperators interact more frequently with other cooperators. This condition, called positive assortment, is known to occur in spatially-structured viscous populations, where individuals typically have low mobility and limited dispersal. However many social organisms across taxa, from cells and bacteria, to birds, fish and ungulates, are mobile, and live in populations with considerable inter-group mixing. In the absence of information regarding others' traits or conditional strategies, such mixing may inhibit assortment and limit the potential for cooperation to evolve. Here we employ spatially-explicit individual-based evolutionary simulations to incorporate costs and benefits of two coevolving costly traits: cooperative and local cohesive tendencies. We demonstrate that, despite possessing no information about others' traits or payoffs, mobility (via self-propulsion or environmental forcing) facilitates assortment of cooperators via a dynamically evolving difference in the cohesive tendencies of cooperators and defectors. We show analytically that this assortment can also be viewed in a multilevel selection framework, where selection for cooperation among emergent groups can overcome selection against cooperators within the groups. As a result of these dynamics, we find an oscillatory pattern of cooperation and defection that maintains cooperation even in the absence of well known mechanisms such as kin interactions, reciprocity, local dispersal or conditional strategies that require information on others' strategies or payoffs. Our results offer insights into differential adhesion based mechanisms for positive assortment and reveal the possibility of cooperative aggregations in dynamic fission-fusion populations.

The Spatial Dynamics of Predators and the Benefits and Costs of Sharing Information

Predators of all kinds, be they lions hunting in the Serengeti or fishermen searching for their catch, display various collective strategies. A common strategy is to share information about the location of prey. However, depending on the spatial characteristics and mobility of predators and prey, information sharing can either improve or hinder individual success. Here, our goal is to investigate the interacting effects of space and information sharing on predation efficiency, represented by the expected rate at which prey are found and consumed. We derive a feeding functional response that accounts for both spatio-temporal heterogeneity and communication, and validate this mathematical analysis with a computational agent-based model. This agent-based model has an explicit yet minimal representation of space, as well as information sharing about the location of prey. The analytical model simplifies predator behavior into a few discrete states and one essential trade-off, between the individual benefit of acquiring information and the cost of creating spatial and temporal correlation between predators. Despite the absence of an explicit spatial dimension in these equations, they quantitatively predict the predator consumption rates measured in the agent-based simulations across the explored parameter space. Together, the mathematical analysis and agent-based simulations identify the conditions for when there is a benefit to sharing information, and also when there is a cost.

When should we work together and when should we work alone? This question is central to our efforts to understand social and ecological systems alike, from lions hunting in the Serengeti to fishermen searching for their catch. Here, we develop a mathematical modeling framework to identify the essential spatial factors controlling the benefits and costs of sharing information. Our approach marries computation with mathematical analysis, and our results highlight that it is only under certain spatial conditions that information sharing is a useful cooperative strategy. Notably, we find conditions for which fully collective and fully individual search are both attractive.

Lizard movement tracks: variation in path re-use behaviour is consistent with a scent-marking function

Individual movement influences the spatial and social structuring of a population. Animals regularly use the same paths to move efficiently to familiar places, or to patrol and mark home ranges. We found that Australian sleepy lizards (Tiliqua rugosa), a monogamous species with stable pair-bonds, repeatedly used the same paths within their home ranges and investigated whether path re-use functions as a scent-marking behaviour, or whether it is influenced by site familiarity. Lizards can leave scent trails on the substrate when moving through the environment and have a well-developed vomeronasal system to detect and respond to those scents. Path re-use would allow sleepy lizards to concentrate scent marks along these well-used trails, advertising their presence. Hypotheses of mate attraction and mating competition predict that sleepy lizard males, which experience greater intra-sexual competition, mark more strongly. Consistent with those hypotheses, males re-used their paths more than females, and lizards that showed pairing behaviour with individuals of the opposite sex re-used paths more than unpaired lizards, particularly among females. Hinterland marking is most economic when home ranges are large and mobility is low, as is the case in the sleepy lizard. Consistent with this strategy, re-used paths were predominantly located in the inner 50% home range areas. Together, our detailed movement analyses suggest that path re-use is a scent marking behaviour in the sleepy lizard. We also investigated but found less support for alternative explanations of path re-use behaviour, such as site familiarity and spatial knowledge. Lizards established the same number of paths, and used them as often, whether they had occupied their home ranges for one or for more years. We discuss our findings in relation to maintenance of the monogamous mating system of this species, and the spatial and social structuring of the population.

Evolution of fairness in the dictator game by multilevel selection

The most perplexing experimental results on fairness come from the dictator game where one of two players, the dictator, decides how to divide a resource with an anonymous player. The dictator, acting self-interestedly, should offer nothing to the anonymous second player, but in experimental studies, dictators offer much more than nothing. We developed a multilevel selection model to explain why people offer more than nothing in the dictator game. We show that fairness can evolve when population structure emerges from the aggregation and limited dispersal of offspring. We begin with an analytical model that shows how fair behavior can benefit groups by minimizing within-group variance in resources and thereby increasing group fitness. To investigate the generality of this result, we developed an agent-based model with agents that have no information about other agents. We allowed agents to aggregate into groups and evolve different levels of fairness by playing the dictator game for resources to reproduce. This allowed multilevel selection to emerge from the spatiotemporal properties of individual agents. We found that the population structure that emerged under low population densities was most conducive to the evolution of fairness, which is consistent with group selection as a major evolutionary force. We also found that fairness only evolves if resources are not too scarce relative to the lifespan of agents. We conclude that the evolution of fairness could evolve under multilevel selection. Thus, our model provides a novel explanation for the results of dictator game experiments, in which participants often fairly split a resource rather than keeping it all for themselves.

The cultural evolution of emergent group-level traits

Many of the most important properties of human groups - including properties that may give one group an evolutionary advantage over another - are properly defined only at the level of group organization. Yet at present, most work on the evolution of culture has focused solely on the transmission of individual-level traits. I propose a conceptual extension of the theory of cultural evolution, particularly related to the evolutionary competition between cultural groups. The key concept in this extension is the emergent group-level trait. This type of trait is characterized by the structured organization of differentiated individuals and constitutes a unit of selection that is qualitatively different from selection on groups as defined by traditional multilevel selection (MLS) theory. As a corollary, I argue that the traditional focus on cooperation as the defining feature of human societies has missed an essential feature of cooperative groups. Traditional models of cooperation assume that interacting with one cooperator is equivalent to interacting with any other. However, human groups involve differential roles, meaning that receiving aid from one individual is often preferred to receiving aid from another. In this target article, I discuss the emergence and evolution of group-level traits and the implications for the theory of cultural evolution, including ramifications for the evolution of human cooperation, technology, and cultural institutions, and for the equivalency of multilevel selection and inclusive fitness approaches.

Percolation and cooperation with mobile agents: geometric and strategy clusters

We study the conditions for persistent cooperation in an off-lattice model of mobile agents playing the Prisoner's Dilemma game with pure, unconditional strategies. Each agent has an exclusion radius r(P), which accounts for the population viscosity, and an interaction radius r(int), which defines the instantaneous contact network for the game dynamics. We show that, differently from the r(P)=0 case, the model with finite-sized agents presents a coexistence phase with both cooperators and defectors, besides the two absorbing phases, in which either cooperators or defectors dominate. We provide, in addition, a geometric interpretation of the transitions between phases. In analogy with lattice models, the geometric percolation of the contact network (i.e., irrespective of the strategy) enhances cooperation. More importantly, we show that the percolation of defectors is an essential condition for their survival. Differently from compact clusters of cooperators, isolated groups of defectors will eventually become extinct if not percolating, independently of their size.

Institutions and cooperation in an ecology of games

Social dilemmas have long been studied formally as cooperation games that pit individual gains against those of the group. In the real world, individuals face an ecology of games where they play many such games simultaneously, often with overlapping co-players. Here, we study an agent-based model of an ecology of public goods games and compare the effectiveness of two institutional mechanisms for promoting cooperation: a simple institution of limited group size (capacity constraints) and a reputational institution based on observed behavior. Reputation is shown to allow much higher relative payoffs for cooperators than do capacity constraints, but only if (1) the rate of reputational information flow is fast enough relative to the rate of social mobility, and (2) cooperators are relatively common in the population. When these conditions are not met, capacity constraints are more effective at protecting the interests of cooperators. Because of the simplicity of the limited-group-size rule, capacity constraints can also generate social organization, which promotes cooperation much more quickly than can reputation. Our results are discussed in terms of both normative prescriptions and evolutionary theory regarding institutions that regulate cooperation. More broadly, the ecology-of-games approach developed here provides an adaptable modeling framework for studying a wide variety of problems in the social sciences.

Cooperation in Harsh Environments and the Emergence of Spatial Patterns

This paper concerns the confluence of two important areas of research in mathematical biology: spatial pattern formation and cooperative dilemmas. Mechanisms through which social organisms form spatial patterns are not fully understood. Prior work connecting cooperation and pattern formation has often included unrealistic assumptions that shed doubt on the applicability of those models toward understanding real biological patterns. I investigated a more biologically realistic model of cooperation among social actors. The environment is harsh, so that interactions with cooperators are strictly needed to survive. Harshness is implemented via a constant energy deduction. I show that this model can generate spatial patterns similar to those seen in many naturally-occuring systems. Moreover, for each payoff matrix there is an associated critical value of the energy deduction that separates two distinct dynamical processes. In low-harshness environments, the growth of cooperator clusters is impeded by defectors, but these clusters gradually expand to form dense dendritic patterns. In very harsh environments, cooperators expand rapidly but defectors can subsequently make inroads to form reticulated patterns. The resulting web-like patterns are reminiscent of transportation networks observed in slime mold colonies and other biological systems.