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

Spatial structure could explain the maintenance of alternative reproductive tactics in tree cricket males

Trait polymorphisms are widespread in nature, and explaining their stable co-existence is a central problem in ecology and evolution. Alternative reproductive tactics, in which individuals of one or more sex exhibit discrete, discontinuous traits in response to reproductive competition, represent a special case of trait polymorphism in which the traits are often complex, behavioural, and dynamic. Thus, studying how alternative reproductive tactics are maintained may provide general insights into how complex trait polymorphisms are maintained in populations. We construct a spatially explicit individual-based model inspired from extensively collected empirical data to address the mechanisms behind the co-existence of three behavioural alternative reproductive tactics in males of a tree cricket (Oecanthus henryi). Our results show that the co-existence of these tactics over ecological time scales is facilitated by the spatial structure of the landscape they inhabit, which serves to equalise the otherwise unequal mating benefits of the three tactics. We also show that this co-existence is unlikely if spatial aspects of the system are not considered. Our findings highlight the importance of spatial dynamics in understanding ecological and evolutionary processes and underscore the power of integrative approaches that combine models with empirical data.

Evolution as a result of resource flow in ecosystems: Ecological dynamics can drive evolution

To see how the flow of energy across ecosystems can derive evolution, I introduce a framework in which individuals interact with their peers and environment to accumulate resources, and use the resources to pay for their metabolic costs, grow and reproduce. I show that two conservation principles determine the system's equilibrium state: conservation of resources- a physical principle stating that in the equilibrium, resource production and consumption should balance, and payoff equality- an economic principle, stating that the payoffs of different types in equilibrium should equal. Besides the equilibrium state, the system shows non-equilibrium fluctuations derived by the exponential growth of the individuals in which the payoff equality principle does not hold. A simple gradient-ascend dynamical mean-field equation predicts the onset of non-equilibrium fluctuations. As an example, I study the evolution of cooperation in public goods games. In both mixed and structured populations, cooperation evolves naturally in resource-poor environments but not in resource-rich environments. Population viscosity facilitates cooperation in poor environments but can be detrimental to cooperation in rich environments. In addition, cooperators and defectors show different life-history strategies: Cooperators live shorter lives and reproduce more than defectors. Both population structure and, more significantly, population viscosity reduce lifespan and life history differences between cooperators and defectors.

Evolution of selfish multicellularity: collective organisation of individual spatio-temporal regulatory strategies

BACKGROUND

The unicellular ancestors of modern-day multicellular organisms were remarkably complex. They had an extensive set of regulatory and signalling genes, an intricate life cycle and could change their behaviour in response to environmental changes. At the transition to multicellularity, some of these behaviours were co-opted to organise the development of the nascent multicellular organism. Here, we focus on the transition to multicellularity before the evolution of stable cell differentiation, to reveal how the emergence of clusters affects the evolution of cell behaviour.

RESULTS

We construct a computational model of a population of cells that can evolve the regulation of their behavioural state - either division or migration - and study both a unicellular and a multicellular context. Cells compete for reproduction and for resources to survive in a seasonally changing environment. We find that the evolution of multicellularity strongly determines the co-evolution of cell behaviour, by altering the competition dynamics between cells. When adhesion cannot evolve, cells compete for survival by rapidly migrating towards resources before dividing. When adhesion evolves, emergent collective migration alleviates the pressure on individual cells to reach resources. This allows individual cells to maximise their own replication. Migrating adhesive clusters display striking patterns of spatio-temporal cell state changes that visually resemble animal development.

CONCLUSIONS

Our model demonstrates how emergent selection pressures at the onset of multicellularity can drive the evolution of cellular behaviour to give rise to developmental patterns.

Data-driven discovery of stochastic dynamical equations of collective motion

Coarse-grained descriptions of collective motion of flocking systems are often derived for the macroscopic or the thermodynamic limit. However, the size of many real flocks falls within 'mesoscopic' scales (10 to 100 individuals), where stochasticity arising from the finite flock sizes is important. Previous studies on mesoscopic models have typically focused on non-spatial models. Developing mesoscopic scale equations, typically in the form of stochastic differential equations, can be challenging even for the simplest of the collective motion models that explicitly account for space. To address this gap, here, we take a novel data-driven equation learning approach to construct the stochastic mesoscopic descriptions of a simple, spatial, self-propelled particle (SPP) model of collective motion. In the spatial model, a focal individual can interact withkrandomly chosen neighbours within an interaction radius. We considerk = 1 (called stochastic pairwise interactions),k = 2 (stochastic ternary interactions), andkequalling all available neighbours within the interaction radius (equivalent to Vicsek-like local averaging). For the stochastic pairwise interaction model, the data-driven mesoscopic equations reveal that the collective order is driven by a multiplicative noise term (hence termed, noise-induced flocking). In contrast, for higher order interactions (k > 1), including Vicsek-like averaging interactions, models yield collective order driven by a combination of deterministic and stochastic forces. We find that the relation between the parameters of the mesoscopic equations describing the dynamics and the population size are sensitive to the density and to the interaction radius, exhibiting deviations from mean-field theoretical expectations. We provide semi-analytic arguments potentially explaining these observed deviations. In summary, our study emphasises the importance of mesoscopic descriptions of flocking systems and demonstrates the potential of the data-driven equation discovery methods for complex systems studies.

Single-cell phenotypic plasticity modulates social behavior in Dictyostelium discoideum

In Dictyostelium chimeras, "cheaters" are strains that positively bias their contribution to the pool of spores, i.e., the reproductive cells resulting from development. On evolutionary time scales, the selective advantage; thus, gained by cheaters is predicted to undermine collective functions whenever social behaviors are genetically determined. Genotypes; however, are not the sole determinant of spore bias, but the relative role of genetic and plastic differences in evolutionary success is unclear. Here, we study chimeras composed of cells harvested in different phases of population growth. We show that such heterogeneity induces frequency-dependent, plastic variation in spore bias. In genetic chimeras, the magnitude of such variation is not negligible and can even reverse the classification of a strain's social behavior. Our results suggest that differential cell mechanical properties can underpin, through biases emerging during aggregation, a "lottery" in strains' reproductive success that may counter the evolution of cheating.

Conformity effect on the evolution of cooperation in signed networks

Human behaviors are often subject to conformity, but little research attention has been paid to social dilemmas in which players are assumed to only pursue the maximization of their payoffs. The present study proposed a generalized prisoner dilemma model in a signed network considering conformity. Simulation shows that conformity helps promote the imitation of cooperative behavior when positive edges dominate the network, while negative edges may impede conformity from fostering cooperation. The logic of homophily and xenophobia allows for the coexistence of cooperators and defectors and guides the evolution toward the equality of the two strategies. We also find that cooperation prevails when individuals have a higher probability of adjusting their relation signs, but conformity may mediate the effect of network adaptation. From a population-wide view, network adaptation and conformity are capable of forming the structures of attractors or repellers.

Quantal response equilibrium for the Prisoner's Dilemma game in Markov strategies

Within the studies of human cooperation, there are gaps that require further investigation. One possible area for growth is developing theoretical concepts which describe high levels of cooperation. In this paper, we present a symmetrical quantal response equilibrium (QRE) in Prisoner’s Dilemma game (PD) constructed in Markov strategies (tolerance to defection and mutual cooperation). To prove the adequacy of the resulting equilibrium, we compare it with the previously found Nash equilibrium in PD in Markov strategies: the QRE converges with the Nash equilibrium that corresponds with the theory. Next, we investigate the properties of QRE in PD in Markov strategies by testing it against experimental data. For low levels of rationality, the found equilibrium manages to describe high cooperation. We derive the levels of rationality under which the intersection between Nash and QRE occurs. Lastly, our experimental data suggest that QRE serves as a dividing line between behavior with low and high cooperation.

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.

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.

Evolution of multicellularity by collective integration of spatial information

At the origin of multicellularity, cells may have evolved aggregation in response to predation, for functional specialisation or to allow large-scale integration of environmental cues. These group-level properties emerged from the interactions between cells in a group, and determined the selection pressures experienced by these cells. We investigate the evolution of multicellularity with an evolutionary model where cells search for resources by chemotaxis in a shallow, noisy gradient. Cells can evolve their adhesion to others in a periodically changing environment, where a cell's fitness solely depends on its distance from the gradient source. We show that multicellular aggregates evolve because they perform chemotaxis more efficiently than single cells. Only when the environment changes too frequently, a unicellular state evolves which relies on cell dispersal. Both strategies prevent the invasion of the other through interference competition, creating evolutionary bi-stability. Therefore, collective behaviour can be an emergent selective driver for undifferentiated multicellularity.

Emergence of diverse life cycles and life histories at the origin of multicellularity

The evolution of multicellularity has given rise to a remarkable diversity of multicellular life cycles and life histories. Whereas some multicellular organisms are long-lived, grow through cell division, and repeatedly release single-celled propagules (for example, animals), others are short-lived, form by aggregation, and propagate only once, by generating large numbers of solitary cells (for example, cellular slime moulds). There are no systematic studies that explore how diverse multicellular life cycles can come about. Here, we focus on the origin of multicellularity and develop a mechanistic model to examine the primitive life cycles that emerge from a unicellular ancestor when an ancestral gene is co-opted for cell adhesion. Diverse life cycles readily emerge, depending on ecological conditions, group-forming mechanism, and ancestral constraints. Among these life cycles, we recapitulate both extremes of long-lived groups that propagate continuously and short-lived groups that propagate only once, with the latter type of life cycle being particularly favoured when groups can form by aggregation. Our results show how diverse life cycles and life histories can easily emerge at the origin of multicellularity, shaped by ancestral constraints and ecological conditions. Beyond multicellularity, this finding has similar implications for other major transitions, such as the evolution of sociality.

Fission-fusion dynamics and group-size-dependent composition in heterogeneous populations

Many animal groups are heterogeneous and may even consist of individuals of different species, called mixed-species flocks. Mathematical and computational models of collective animal movement behavior, however, typically assume that groups and populations consist of identical individuals. In this paper, using the mathematical framework of the coagulation-fragmentation process, we develop and analyze a model of merge and split group dynamics, also called fission-fusion dynamics, for heterogeneous populations that contain two types (or species) of individuals. We assume that more heterogeneous groups experience higher split rates than homogeneous groups, forming two daughter groups whose compositions are drawn uniformly from all possible partitions. We analytically derive a master equation for group size and compositions and find mean-field steady-state solutions. We predict that there is a critical group size below which groups are more likely to be homogeneous and contain the abundant type or species. Despite the propensity of heterogeneous groups to split at higher rates, we find that groups are more likely to be heterogeneous but only above the critical group size. Monte Carlo simulation of the model show excellent agreement with these analytical model results. Thus, our model makes a testable prediction that composition of flocks are group-size-dependent and do not merely reflect the population level heterogeneity. We discuss the implications of our results to empirical studies on flocking systems.

Ecological feedback on diffusion dynamics

Spatial patterns are ubiquitous across different scales of organization in ecological systems. Animal coat pattern, spatial organization of insect colonies and vegetation in arid areas are prominent examples from such diverse ecologies. Typically, pattern formation has been described by reaction-diffusion equations, which consider individuals dispersing between subpopulations of a global pool. This framework applied to public goods game nicely showed the endurance of populations via diffusion and generation of spatial patterns. However, how the spatial characteristics, such as diffusion, are related to the eco-evolutionary process as well as the nature of the feedback from evolution to ecology and vice versa, has been so far neglected. We present a thorough analysis of the ecologically driven evolutionary dynamics in a spatially extended version of ecological public goods games. Furthermore, we show how these evolutionary dynamics feed back into shaping the ecology, thus together determining the fate of the system.

Demographic noise and cost of greenbeard can facilitate greenbeard cooperation

Cooperation among organisms, where cooperators suffer a personal cost to benefit others, is ubiquitous in nature. Greenbeard is a key mechanism for the evolution of cooperation, where a single gene or a set of linked genes codes for both cooperation and a phenotypic tag (metaphorically called "green beard"). Greenbeard cooperation is typically thought to decline over time since defectors can also evolve the tag. However, models of tag-based cooperation typically ignore two key realistic features: populations are finite, and that phenotypic tags can be costly. We develop an analytical model for coevolutionary dynamics of two evolvable traits in finite populations with mutations: costly cooperation and a costly tag. We show that an interplay of demographic noise and cost of the tag can induce coevolutionary cycling, where the evolving population does not reach a steady state but spontaneously switches between cooperative tag-carrying and noncooperative tagless states. Such dynamics allows the tag to repeatedly reappear even after it is invaded by defectors. Thus, we highlight the surprising possibility that the cost of the tag, together with demographic noise, can facilitate the evolution of greenbeard cooperation. We discuss implications of these findings in the context of the evolution of quorum sensing and multicellularity.