Self-structuring in spatial evolutionary ecology

Pattern transitions in spatial epidemics: Mechanisms and emergent properties

Infectious diseases are a threat to human health and a hindrance to societal development. Consequently, the spread of diseases in both time and space has been widely studied, revealing the different types of spatial patterns. Transitions between patterns are an emergent property in spatial epidemics that can serve as a potential trend indicator of disease spread. Despite the usefulness of such an indicator, attempts to systematize the topic of pattern transitions have been few and far between. We present a mini-review on pattern transitions in spatial epidemics, describing the types of transitions and their underlying mechanisms. We show that pattern transitions relate to the complexity of spatial epidemics by, for example, being accompanied with phenomena such as coherence resonance and cyclic evolution. The results presented herein provide valuable insights into disease prevention and control, and may even be applicable outside epidemiology, including other branches of medical science, ecology, quantitative finance, and elsewhere.

Limited gene dispersal and spatial genetic structure as stabilizing factors in an ant-plant mutualism

Comparative studies of the population genetics of closely associated species are necessary to properly understand the evolution of these relationships because gene flow between populations affects the partners' evolutionary potential at the local scale. As a consequence (at least for antagonistic interactions), asymmetries in the strength of the genetic structures of the partner populations can result in one partner having a co-evolutionary advantage. Here, we assess the population genetic structure of partners engaged in a species-specific and obligatory mutualism: the Neotropical ant-plant, Hirtella physophora, and its ant associate, Allomerus decemarticulatus. Although the ant cannot complete its life cycle elsewhere than on H. physophora and the plant cannot live for long without the protection provided by A. decemarticulatus, these species also have antagonistic interactions: the ants have been shown to benefit from castrating their host plant and the plant is able to retaliate against too virulent ant colonies. We found similar short dispersal distances for both partners, resulting in the local transmission of the association and, thus, inbred populations in which too virulent castrating ants face the risk of local extinction due to the absence of H. physophora offspring. On the other hand, we show that the plant populations probably experienced greater gene flow than did the ant populations, thus enhancing the evolutionary potential of the plants. We conclude that such levels of spatial structure in the partners' populations can increase the stability of the mutualistic relationship. Indeed, the local transmission of the association enables partial alignments of the partners' interests, and population connectivity allows the plant retaliation mechanisms to be locally adapted to the castration behaviour of their symbionts.

Social carry-over effects underpin trans-seasonally linked structure in a wild bird population

Spatial structure underpins numerous population processes by determining the environment individuals' experience and which other individuals they encounter. Yet, how the social landscape influences individuals' spatial decisions remains largely unexplored. Wild great tits (Parus major) form freely moving winter flocks, but choose a single location to establish a breeding territory over the spring. We demonstrate that individuals' winter social associations carry‐over into their subsequent spatial decisions, as individuals breed nearer to those they were most associated with during winter. Further, they also form territory boundaries with their closest winter associates, irrespective of breeding distance. These findings were consistent across years, and among all demographic classes, suggesting that such social carry‐over effects may be general. Thus, prior social structure can shape the spatial proximity, and fine‐scale arrangement, of breeding individuals. In this way, social networks can influence a wide range of processes linked to individuals' breeding locations, including other social interactions themselves.

Invasion fitness, inclusive fitness, and reproductive numbers in heterogeneous populations

How should fitness be measured to determine which phenotype or "strategy" is uninvadable when evolution occurs in a group-structured population subject to local demographic and environmental heterogeneity? Several fitness measures, such as basic reproductive number, lifetime dispersal success of a local lineage, or inclusive fitness have been proposed to address this question, but the relationships between them and their generality remains unclear. Here, we ascertain uninvadability (all mutant strategies always go extinct) in terms of the asymptotic per capita number of mutant copies produced by a mutant lineage arising as a single copy in a resident population ("invasion fitness"). We show that from invasion fitness uninvadability is equivalently characterized by at least three conceptually distinct fitness measures: (i) lineage fitness, giving the average individual fitness of a randomly sampled mutant lineage member; (ii) inclusive fitness, giving a reproductive value weighted average of the direct fitness costs and relatedness weighted indirect fitness benefits accruing to a randomly sampled mutant lineage member; and (iii) basic reproductive number (and variations thereof) giving lifetime success of a lineage in a single group, and which is an invasion fitness proxy. Our analysis connects approaches that have been deemed different, generalizes the exact version of inclusive fitness to class-structured populations, and provides a biological interpretation of natural selection on a mutant allele under arbitrary strength of selection.

Wherever I may roam: social viscosity and kin affiliation in a wild population despite natal dispersal

When it is time to leave home and disperse from the natal area, you might expect siblings to scatter far and wide. But in the great tit, siblings associate more than unrelated birds at feeders, and not only because they start off their journey from the same nest. Complex social behaviors can evolve when relatives cluster, and knowing how those clusters persist despite dispersal is important for understanding the evolution of sociality.

Dispersal affects the social contexts individuals experience by redistributing individuals in space, and the nature of social interactions can have important fitness consequences. During the vagrancy stage of natal dispersal, after an individual has left its natal site and before it has settled to breed, social affiliations might be predicted by opportunities to associate (e.g., distance in space and time between natal points of origin) or kin preferences. We investigated the social structure of a population of juvenile great tits (Parus major) and asked whether social affiliations during vagrancy were predicted by 1) the distance between natal nest-boxes, 2) synchrony in fledge dates, and 3) accounting for spatial and temporal predictors, whether siblings tended to stay together. We show that association strength was affected predominantly by spatial proximity at fledging and, to a lesser extent, temporal proximity in birth dates. Independently of spatial and temporal effects, sibling pairs associated more often than expected by chance. Our results suggest that the structure of the winter population is shaped primarily by limits to dispersal through incomplete population mixing. In addition, our results reveal kin structure, and hence the scope for fitness-related interactions between particular classes of kin. Both spatial-mediated and socially mediated population structuring can have implications for our understanding of the evolution of sociality.

When is bigger better? The effects of group size on the evolution of helping behaviours

Understanding the evolution of sociality in humans and other species requires understanding how selection on social behaviour varies with group size. However, the effects of group size are frequently obscured in the theoretical literature, which often makes assumptions that are at odds with empirical findings. In particular, mechanisms are suggested as supporting large-scale cooperation when they would in fact rapidly become ineffective with increasing group size. Here we review the literature on the evolution of helping behaviours (cooperation and altruism), and frame it using a simple synthetic model that allows us to delineate how the three main components of the selection pressure on helping must vary with increasing group size. The first component is the marginal benefit of helping to group members, which determines both direct fitness benefits to the actor and indirect fitness benefits to recipients. While this is often assumed to be independent of group size, marginal benefits are in practice likely to be maximal at intermediate group sizes for many types of collective action problems, and will eventually become very small in large groups due to the law of decreasing marginal returns. The second component is the response of social partners on the past play of an actor, which underlies conditional behaviour under repeated social interactions. We argue that under realistic conditions on the transmission of information in a population, this response on past play decreases rapidly with increasing group size so that reciprocity alone (whether direct, indirect, or generalised) cannot sustain cooperation in very large groups. The final component is the relatedness between actor and recipient, which, according to the rules of inheritance, again decreases rapidly with increasing group size. These results explain why helping behaviours in very large social groups are limited to cases where the number of reproducing individuals is small, as in social insects, or where there are social institutions that can promote (possibly through sanctioning) large-scale cooperation, as in human societies. Finally, we discuss how individually devised institutions can foster the transition from small-scale to large-scale cooperative groups in human evolution.

Sharing the sandbox: Evolutionary mechanisms that maintain bacterial cooperation

Microbes are now known to participate in an extensive repertoire of cooperative behaviors such as biofilm formation, production of extracellular public-goods, group motility, and higher-ordered multicellular structures. A fundamental question is how these cooperative tasks are maintained in the face of non-cooperating defector cells. Recently, a number of molecular mechanisms including facultative participation, spatial sorting, and policing have been discovered to stabilize cooperation. Often these different mechanisms work in concert to reinforce cooperation. In this review, we describe bacterial cooperation and the current understanding of the molecular mechanisms that maintain it.

Siderophore production and the evolution of investment in a public good: An adaptive dynamics approach to kin selection

Like many other bacteria, Pseudomonas aeruginosa sequesters iron from the environment through the secretion, and subsequent uptake, of iron-binding molecules. As these molecules can be taken up by other bacteria in the population than those who secreted them, this is a form of cooperation through a public good. Traditionally, this problem has been studied by comparing the relative fitnesses of siderophore-producing and non-producing strains, but this gives no information about the fate of strains that do produce intermediate amounts of siderophores. Here, we investigate theoretically how the amount invested in this form of cooperation evolves. We use a mechanistic description of the laboratory protocols used in experimental evolution studies to describe the competition and cooperation of the bacteria. From this dynamical model we derive the fitness following the adaptive dynamics method. The results show how selection is driven by local siderophore production and local competition. Because siderophore production reduces the growth rate, local competition decreases with the degree of relatedness (which is a dynamical variable in our model). Our model is not restricted to the analysis of small phenotypic differences and allows for theoretical exploration of the effects of large phenotypic differences between cooperators and cheats. We predict that an intermediate ESS level of cooperation (molecule production) should exist. The adaptive dynamics approach allows us to assess evolutionary stability, which is often not possible in other kin-selection models. We found that selection can lead to an intermediate strategy which in our model is always evolutionarily stable, yet can allow invasion of strategies that are much more cooperative. Our model describes the evolution of a public good in the context of the ecology of the microorganism, which allows us to relate the extent of production of the public good to the details of the interactions.

Topological effects of network structure on long-term social network dynamics in a wild mammal

Social structure influences ecological processes such as dispersal and invasion, and affects survival and reproductive success. Recent studies have used static snapshots of social networks, thus neglecting their temporal dynamics, and focused primarily on a limited number of variables that might be affecting social structure. Here, instead we modelled effects of multiple predictors of social network dynamics in the spotted hyena, using observational data collected during 20 years of continuous field research in Kenya. We tested the hypothesis that the current state of the social network affects its long-term dynamics. We employed stochastic agent-based models that allowed us to estimate the contribution of multiple factors to network changes. After controlling for environmental and individual effects, we found that network density and individual centrality affected network dynamics, but that social bond transitivity consistently had the strongest effects. Our results emphasise the significance of structural properties of networks in shaping social dynamics.

Local densities connect spatial ecology to game, multilevel selection and inclusive fitness theories of cooperation

Cooperation plays a crucial role in many aspects of biology. We use the spatial ecological metrics of local densities to measure and model cooperative interactions. While local densities can be found as technical details in current theories, we aim to establish them as central to an approach that describes spatial effects in the evolution of cooperation. A resulting local interaction model neatly partitions various spatial and non-spatial selection mechanisms. Furthermore, local densities are shown to be fundamental for important metrics of game theory, multilevel selection theory and inclusive fitness theory. The corresponding metrics include structure coefficients, spatial variance, contextual covariance, relatedness, and inbreeding coefficient or F-statistics. Local densities serve as the basis of an emergent spatial theory that draws from and brings unity to multiple theories of cooperation.

The idiosyncrasy of spatial structure in bacterial competition

Background

The spatial structure of a habitat can have a strong impact on community dynamics. Different experimental approaches exist to explore the effect of spatial structure on bacterial communities. To investigate the effect of ‘space’, a single implementation of spatial structure is often contrasted to bacterial community dynamics in well-mixed cultures. While such comparisons are useful, it is likely that the observed dynamics will be particular to the specific experimental implementation of spatial structure. In order to address this question, we track the community dynamics of a two-strain Escherichia coli community in various spatial habitats and relate the observed dynamics to the structure of a habitat.

Results

By tracking the community dynamics of rpoS wild-type and mutant E. coli in radially expanding colonies on solid and semi-solid agar plates, we find that the mutant strain outcompetes the wild-type on semi-solid agar plates, whereas the two strains coexist on solid agar. We compare these results to previous studies in which the same two strains were shown to coexist in habitats spatially structured by microfabrication, while the mutant outcompeted the wild-type in well-mixed batch cultures. Together, these observations show that different implementations of space may result in qualitatively different community dynamics. Furthermore, we argue that the same competitive outcome (e.g. coexistence) may arise from distinct underlying dynamics in different experimental implementations of spatial structure.

Conclusions

Our observations demonstrate that different experimental implementations of spatial structure may not only lead to quantitatively different communities (changes in the relative abundance of types) but can also lead to qualitatively different outcomes of long-term community dynamics (coexistence versus extinction and loss of biodiversity).

Games among relatives revisited

We present a simple model for the evolution of social behavior in family-structured, finite sized populations. Interactions are represented as evolutionary games describing frequency-dependent selection. Individuals interact more frequently with siblings than with members of the general population, as quantified by an assortment parameter r, which can be interpreted as "relatedness". Other models, mostly of spatially structured populations, have shown that assortment can promote the evolution of cooperation by facilitating interaction between cooperators, but this effect depends on the details of the evolutionary process. For our model, we find that sibling assortment promotes cooperation in stringent social dilemmas such as the Prisoner's Dilemma, but not necessarily in other situations. These results are obtained through straightforward calculations of changes in gene frequency. We also analyze our model using inclusive fitness. We find that the quantity of inclusive fitness does not exist for general games. For special games, where inclusive fitness exists, it provides less information than the straightforward analysis.

Spatial structure, transmission modes and the evolution of viral exploitation strategies

Spatial structure and local migration are predicted to promote the evolution of less aggressive host exploitation strategies in horizontally transmitted pathogens. Here we explore the effect of spatial structure on the evolution of pathogens that can use both horizontal and vertical routes of transmission. First, we analyse theoretically how vertical transmission can alter evolutionary trajectories and confirm that space can impede the spread of virulent pathogens. Second, we test this prediction using the latent phage λ which transmits horizontally and vertically in Escherichia coli populations. We show that the latent phage λ wins competition against the virulent mutant λcI857 in spatially structured epidemics, but loses when spatial structure is eroded. The vertical transmission of phage λ immunizes its local host pool against superinfection and prevents the spread of the virulent λcI857. This effect breaks down when mixing facilitates horizontal transmission to uninfected hosts. We thus confirm the importance of spatial structure for the evolutionary maintenance of prudent infection strategies in latent viruses.

Immunity, suicide or both? Ecological determinants for the combined evolution of anti-pathogen defense systems

Background

Parasite-host arms race is one of the key factors in the evolution of life. Most cellular life forms, in particular prokaryotes, possess diverse forms of defense against pathogens including innate immunity, adaptive immunity and programmed cell death (altruistic suicide). Coevolution of these different but interacting defense strategies yields complex evolutionary regimes.

Results

We develop and extensively analyze a computational model of coevolution of different defense strategies to show that suicide as a defense mechanism can evolve only in structured populations and when the attainable degree of immunity against pathogens is limited. The general principle of defense evolution seems to be that hosts do not evolve two costly defense mechanisms when one is sufficient. Thus, the evolutionary interplay of innate immunity, adaptive immunity and suicide, leads to an equilibrium state where the combination of all three defense strategies is limited to a distinct, small region of the parameter space. The three strategies can stably coexist only if none of them are highly effective. Coupled adaptive immunity-suicide systems, the existence of which is implied by the colocalization of genes for the two types of defense in prokaryotic genomes, can evolve either when immunity-associated suicide is more efficacious than other suicide systems or when adaptive immunity functionally depends on the associated suicide system.

Conclusions

Computational modeling reveals a broad range of outcomes of coevolution of anti-pathogen defense strategies depending on the relative efficacy of different mechanisms and population structure. Some of the predictions of the model appear compatible with recent experimental evolution results and call for additional experiments.

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.

Oh sister, where art thou? Spatial population structure and the evolution of an altruistic defence trait

The evolution of parasite virulence and host defences is affected by population structure. This effect has been confirmed in studies focusing on large spatial scales, whereas the importance of local structure is not well understood. Slavemaking ants are social parasites that exploit workers of another species to rear their offspring. Enslaved workers of the host species Temnothorax longispinosus have been found to exhibit an effective post-enslavement defence behaviour: enslaved workers were observed killing a large proportion of the parasites' offspring. As enslaved workers do not reproduce, they gain no direct fitness benefit from this 'rebellion' behaviour. However, there may be an indirect benefit: neighbouring host nests that are related to 'rebel' nests can benefit from a reduced raiding pressure, as a result of the reduction in parasite nest size due to the enslaved workers' killing behaviour. We use a simple mathematical model to examine whether the small-scale population structure of the host species could explain the evolution of this potentially altruistic defence trait against slavemaking ants. We find that this is the case if enslaved host workers are related to nearby host nests. In a population genetic study, we confirm that enslaved workers are, indeed, more closely related to host nests within the raiding range of their resident slavemaker nest, than to host nests outside the raiding range. This small-scale population structure seems to be a result of polydomy (e.g. the occupation of several nests in close proximity by a single colony) and could have enabled the evolution of 'rebellion' by kin selection.

Cooperative investment in public goods is kin directed in communal nests of social birds

The tragedy of the commons predicts social collapse when public goods are jointly exploited by individuals attempting to maximize their fitness at the expense of other social group members. However, animal societies have evolved many times despite this vulnerability to exploitation by selfish individuals. Kin selection offers a solution to this social dilemma, but in large social groups mean relatedness is often low. Sociable weavers (Philetairus socius) live in large colonies that share the benefits of a massive communal nest, which requires individual investment for construction and maintenance. Here, we show that despite low mean kinship within colonies, relatives are spatially and socially clustered and that nest-building males have higher local relatedness to other colony members than do non-building males. Alternative hypotheses received little support, so we conclude that the benefits of the public good are shared with kin and that cooperative investment is, despite the large size and low relatedness of these communities, kin directed.

Modeling the potential impact of host population survival on the evolution of M. tuberculosis latency

Tuberculosis (TB) is an infectious disease with a peculiar feature: Upon infection with the causative agent, Mycobacterium Tuberculosis (MTB), most hosts enter a latent state during which no transmission of MTB to new hosts occurs. Only a fraction of latently infected hosts develop TB disease and can potentially infect new hosts. At first glance, this seems like a waste of transmission potential and therefore an evolutionary suboptimal strategy for MTB. It might be that the human immune response keeps MTB in check in most hosts, thereby preventing it from achieving its evolutionary optimum. Another possible explanation is that long latency and progression to disease in only a fraction of hosts are evolutionary beneficial to MTB by allowing it to persist better in small host populations. Given that MTB has co-evolved with human hosts for millenia or longer, it likely encountered small host populations for a large share of its evolutionary history and had to evolve strategies of persistence. Here, we use a mathematical model to show that indeed, MTB persistence is optimal for an intermediate duration of latency and level of activation. The predicted optimal level of activation is above the observed value, suggesting that human co-evolution has lead to host immunity, which keeps MTB below its evolutionary optimum.

Evolution of microbial markets

Biological market theory has been used successfully to explain cooperative behavior in many animal species. Microbes also engage in cooperative behaviors, both with hosts and other microbes, that can be described in economic terms. However, a market approach is not traditionally used to analyze these interactions. Here, we extend the biological market framework to ask whether this theory is of use to evolutionary biologists studying microbes. We consider six economic strategies used by microbes to optimize their success in markets. We argue that an economic market framework is a useful tool to generate specific and interesting predictions about microbial interactions, including the evolution of partner discrimination, hoarding strategies, specialized versus diversified mutualistic services, and the role of spatial structures, such as flocks and consortia. There is untapped potential for studying the evolutionary dynamics of microbial systems. Market theory can help structure this potential by characterizing strategic investment of microbes across a diversity of conditions.

Metabolic and demographic feedbacks shape the emergent spatial structure and function of microbial communities

Microbes are predominantly found in surface-attached and spatially structured polymicrobial communities. Within these communities, microbial cells excrete a wide range of metabolites, setting the stage for interspecific metabolic interactions. The links, however, between metabolic and ecological interactions (functional relationships), and species spatial organization (structural relationships) are still poorly understood. Here, we use an individual-based modelling framework to simulate the growth of a two-species surface-attached community where food (resource) is traded for detoxification (service) and investigate how metabolic constraints of individual species shape the emergent structural and functional relationships of the community. We show that strong metabolic interdependence drives the emergence of mutualism, robust interspecific mixing, and increased community productivity. Specifically, we observed a striking and highly stable emergent lineage branching pattern, generating a persistent lineage mixing that was absent when the metabolic exchange was removed. These emergent community properties are driven by demographic feedbacks, such that aid from neighbouring cells directly enhances focal cell growth, which in turn feeds back to neighbour fecundity. In contrast, weak metabolic interdependence drives conflict (exploitation or competition), and in turn greater interspecific segregation. Together, these results support the idea that species structural and functional relationships represent the net balance of metabolic interdependencies.

Understanding the structure and functioning of polymicrobial communities is a major challenge in biology, as witnessed by the dramatic yet mysterious roles played by the human microbiome in human health. Microbial multispecies communities often show complex spatial structures and patterns of metabolic exchange, yet our understanding of how species spatial and ecological relationships emerge from the metabolic rules of species interactions is still limited. What mechanisms underlie multispecies community self-organization? In this study, we simulate the growth of a minimal—two species— community and show how the emergent properties of community spatial structure and function depend on the nature of metabolic interactions between the two species. We found that strong mutual need for help (strong metabolic interdependence) favours the emergence of mutualism, increased productivity and lineage mixing via striking and highly stable branching patterns. In contrast, when the mutual need for help is low, conflict dominates and the two species tend to segregate. Finally, we show how the emergent species mixing follows from a positive feedback of providing aid to neighbouring helpers.

Biological information: why we need a good measure and the challenges ahead

Evolution can be characterized as a process that shapes and maintains information across generations. It is also widely acknowledged that information may play a pivotal role in many other ecological processes. Most of the ecologically relevant information (and some important evolutionary information too) is of a very subjective and analogue kind: individuals use cues that may carry information useful only to them but not to others. This is a problem because most information theory has been developed for objective and discrete information. Can information theory be extended to this theory to incorporate multiple forms of information, each with its own (physical) carriers and dynamics? Here, I will not review all the possible roles that information can play, but rather what conditions an appropriate theory should satisfy. The most promising starting point is provided by entropy measures of conditional probabilities (using the so-called Kullback-Leibler divergence), allowing an assessment of how acquiring information can lead to an increase in fitness. It is irrelevant (to a certain extent) where the information comes from-genes, experience or culture-but it is important to realize that information is not merely subjective but its value should be evaluated in fitness terms, and it is here that evolutionary theory has an enormous potential. A number of important stumbling points remain, however; namely, the identification of whose fitness it concerns and what role the spatio-temporal dynamics plays (which is tightly linked to the nature of the physical carriers of the information and the processes that impact on it).

Spatial self-organization favors heterotypic cooperation over cheating

Heterotypic cooperation—two populations exchanging distinct benefits that are costly to produce—is widespread. Cheaters, exploiting benefits while evading contribution, can undermine cooperation. Two mechanisms can stabilize heterotypic cooperation. In ‘partner choice’, cooperators recognize and choose cooperating over cheating partners; in ‘partner fidelity feedback’, fitness-feedback from repeated interactions ensures that aiding your partner helps yourself. How might a spatial environment, which facilitates repeated interactions, promote fitness-feedback? We examined this process through mathematical models and engineered Saccharomyces cerevisiae strains incapable of recognition. Here, cooperators and their heterotypic cooperative partners (partners) exchanged distinct essential metabolites. Cheaters exploited partner-produced metabolites without reciprocating, and were competitively superior to cooperators. Despite initially random spatial distributions, cooperators gained more partner neighbors than cheaters did. The less a cheater contributed, the more it was excluded and disfavored. This self-organization, driven by asymmetric fitness effects of cooperators and cheaters on partners during cell growth into open space, achieves assortment.

DOI:http://dx.doi.org/10.7554/eLife.00960.001

Cooperation between individuals of the same species, and also between different species, is known to be important in evolution. Large fish, for example, rely on small cleaner fish to remove parasites, while the small fish benefit from the nutrients in these parasites. However, cooperation can be undermined by other individuals or species who “cheat” by taking advantage of those who cooperate, without providing any benefits in return. For example, some cleaner fish cheat by biting off healthy tissue from their host, in addition to parasites.

Genetically-related individuals who cooperate by sharing identical benefits can combat cheaters by giving preferential treatment to their relatives (a process known as kin discrimination) or by staying close to the relatives to form clusters (kin fidelity). However, two genetically-unrelated populations that mutually cooperate by sharing different benefits cannot employ these methods to overcome cheaters. Instead they rely on either partner choice or partner fidelity feedback.

Partner choice – the approach adopted by cleaner fish and their hosts – relies on one population recognizing a signal from the other population and responding accordingly: for example, large fish observe cleaner fish and approach those that cooperate with their current host and avoid those that cheat. Partner fidelity feedback, on the other hand, relies on repeated interactions between the two populations providing an advantage in terms of evolutionary fitness to both: for example, organelles called mitochondria and chloroplasts live inside cells, helping the cells to harvest energy and providing energy for themselves and the host cells in the process. In some cases – such as the cooperation between figs and fig wasps, or between certain plants and the bacteria that fix nitrogen in their roots – researchers cannot agree if the populations are relying on partner choice or partner fidelity feedback.

Now Momeni et al. have used a combination of experiments on yeast and mathematical modeling to explore partner fidelity feedback in greater detail. They started by using genetic engineering techniques to produce two species of yeast that mutually cooperate, each providing a metabolite that is essential to the other, but are not able to recognize each other: this means that these populations cannot rely on partner choice to combat cheaters. Momeni et al. then observed how these two species interacted with each other and a third species of yeast that cheated by consuming one of the metabolites without releasing any metabolite of its own.

Momeni et al. found that as long as there was space for the yeast cells to grow into, the two species that cooperated self-organized into mixed clusters, with the cheating species being excluded from these clusters. The self-organization was driven by a positive feedback loop involving the two species that cooperated, with each species helping to increase the fitness of the other. The results of Momeni et al. demonstrate that it is possible for two genetically unrelated populations to cooperate and combat cheaters without the use of partner choice.

DOI:http://dx.doi.org/10.7554/eLife.00960.002

Spatial structure facilitates cooperation in a social dilemma: empirical evidence from a bacterial community

Cooperative organisms are ubiquitous in nature, despite their vulnerability to exploitation by cheaters. Although numerous theoretical studies suggest that spatial structure is critical for cooperation to persist, the spatial ecology of microbial cooperation remains largely unexplored experimentally. By tracking the community dynamics of cooperating (rpoS wild-type) and cheating (rpoS mutant) Escherichia coli in well-mixed flasks and microfabricated habitats, we demonstrate that spatial structure stabilizes coexistence between wild-type and mutant and thus facilitates cooperator maintenance. We develop a method to interpret our experimental results in the context of game theory, and show that the game wild-type and mutant bacteria play in an unstructured environment changes markedly over time, and eventually obeys a prisoner's dilemma leading to cheater dominance. In contrast, when wild-type and mutant E. coli co-inhabit a spatially-structured habitat, cooperators and cheaters coexist at intermediate frequencies. Our findings show that even in microhabitats lacking patchiness or spatial heterogeneities in resource availability, surface growth allows cells to form multi-cellular aggregates, yielding a self-structured community in which cooperators persist.

Fitness consequences of outcrossing in a social spider with an inbreeding mating system

Inbreeding mating systems are uncommon because of inbreeding depression. Mating among close relatives can evolve, however, when outcrossing is constrained. Social spiders show obligatory mating among siblings. In combination with a female-biased sex ratio, sib-mating results in small effective populations. In such a system, high genetic homozygosity is expected, and drift may cause population divergence. We tested the effect of outcrossing in the social spider Stegodyphus dumicola. Females were mated to sib-males, to a non-nestmate within the population, or to a male from a distant population, and fitness traits of F1s were compared. We found reduced hatching success of broods from between-population crosses, suggesting the presence of population divergence at a large geographical scale that may result in population incompatibility. However, a lack of a difference in offspring performance between inbred and outbred crosses indicates little genetic variation between populations, and could suggest recent colonization by a common ancestor. This is consistent with population dynamics of frequent colonizations by single sib-mated females of common origin, and extinctions of populations after few generations. Although drift or single mutations can lead to population divergence at a relatively short time scale, it is possible that dynamic population processes homogenize these effects at longer time scales.

The impact of spatial scale and habitat configuration on patterns of trait variation and local adaptation in a wild plant parasite

Theory indicates that spatial scale and habitat configuration are fundamental for coevolutionary dynamics and how diversity is maintained in host-pathogen interactions. Yet, we lack empirical data to translate the theory to natural host-parasite systems. In this study, we conduct a multiscale cross-inoculation study using the specialist wild plant pathogen Podosphaera plantaginis on its host plant Plantago lanceolata. We apply the same sampling scheme to a region with highly fragmented (Åland) and continuous (Saaremaa) host populations. Although theory predicts higher parasite virulence in continuous regions, we did not detect differences in traits conferring virulence among the regions. Patterns of adaptation were highly scale dependent. We detected parasite maladaptation among regions, and among populations separated by intermediate distances (6.0-40.0 km) within the fragmented region. In contrast, parasite performance did not vary significantly according to host origin in the continuous landscape. For both regions, differentiation among populations was much larger for genetic variation than for phenotypic variation, indicating balancing selection maintaining phenotypic variation within populations. Our findings illustrate the critical role of spatial scale and habitat configuration in driving host-parasite coevolution. The absence of more aggressive strains in the continuous landscape, in contrast to theoretical predictions, has major implications for long-term decision making in conservation, agriculture, and public health.

Predator attack rate evolution in space: the role of ecology mediated by complex emergent spatial structure and self-shading

Predation interactions are an important element of ecological communities. Population spatial structure has been shown to influence predator evolution, resulting in the evolution of a reduced predator attack rate; however, the evolutionary role of traits governing predator and prey ecology is unknown. The evolutionary effect of spatial structure on a predator's attack rate has primarily been explored assuming a fixed metapopulation spatial structure, and understood in terms of group selection. But endogenously generated, emergent spatial structure is common in nature. Furthermore, the evolutionary influence of ecological traits may be mediated through the spatial self-structuring process. Drawing from theory on pathogens, the evolutionary effect of emergent spatial structure can be understood in terms of self-shading, where a voracious predator limits its long-term invasion potential by reducing local prey availability. Here we formalize the effects of self-shading for predators using spatial moment equations. Then, through simulations, we show that in a spatial context self-shading leads to relationships between predator-prey ecology and the predator's attack rate that are not expected in a non-spatial context. Some relationships are analogous to relationships already shown for host-pathogen interactions, but others represent new trait dimensions. Finally, since understanding the effects of ecology using existing self-shading theory requires simplifications of the emergent spatial structure that do not apply well here, we also develop metrics describing the complex spatial structure of the predator and prey populations to help us explain the evolutionary effect of predator and prey ecology in the context of self-shading. The identification of these metrics may provide a step towards expansion of the predictive domain of self-shading theory to more complex spatial dynamics.

Adaptive dynamics with interaction structure

Evolutionary dynamics depend critically on a population's interaction structure-the pattern of which individuals interact with which others, depending on the state of the population and the environment. Previous research has shown, for example, that cooperative behaviors disfavored in well-mixed populations can be favored when interactions occur only between spatial neighbors or group members. Combining the adaptive dynamics approach with recent advances in evolutionary game theory, we here introduce a general mathematical framework for analyzing the long-term evolution of continuous game strategies for a broad class of evolutionary models, encompassing many varieties of interaction structure. Our main result, the canonical equation of adaptive dynamics with interaction structure, characterizes expected evolutionary trajectories resulting from any such model, thereby generalizing a central tool of adaptive dynamics theory. Interestingly, the effects of different interaction structures and update rules on evolutionary trajectories are fully captured by just two real numbers associated with each model, which are independent of the considered game. The first, a structure coefficient, quantifies the effects on selection pressures and thus on the shapes of expected evolutionary trajectories. The second, an effective population size, quantifies the effects on selection responses and thus on the expected rates of adaptation. Applying our results to two social dilemmas, we show how the range of evolutionarily stable cooperative behaviors systematically varies with a model's structure coefficient.

Evolutionary suicide as a consequence of runaway selection for greater aggregation tendency

Aggregation of individuals is a common phenomenon in nature. By aggregating, individuals can reap benefits but may also be subject to associated costs from increased competition. The benefits of aggregation can depend on population density, which in turn can be affected by aggregation when it determines reproductive success of individuals. The Allee effect is often considered to be one of the factors that can explain the evolution of aggregation behavior. We investigated this hypothesis with a mathematical model which integrates population dynamics and evolution. Individuals gain synergistically from aggregation but suffer from scramble competition with aggregation tendency as an evolving trait. We found that aggregation behavior can stabilize the population dynamics and reduce population growth. The results show that the Allee effect alone is not sufficient for aggregative behavior to evolve as an evolutionarily stable strategy. We also found that weak local competition does not promote aggregation due to feedback from the population level: under low competition, the population can achieve high density such that aggregation becomes costly rather than beneficial. Our model instead exhibits an escalation of aggregation tendency, leading to the extinction of the population in a process known as evolutionary suicide. We conclude that for aggregation to evolve as an evolutionarily stable strategy we need to consider other factors such as inter-patch dispersal to new patches and avoidance of excessively large groups.

Modelling the course of an HIV infection: insights from ecology and evolution

The Human Immunodeficiency Virus (HIV) is one of the most threatening viral agents. This virus infects approximately 33 million people, many of whom are unaware of their status because, except for flu-like symptoms right at the beginning of the infection during the acute phase, the disease progresses more or less symptom-free for 5 to 10 years. During this asymptomatic phase, the virus slowly destroys the immune system until the onset of AIDS when opportunistic infections like pneumonia or Kaposi’s sarcoma can overcome immune defenses. Mathematical models have played a decisive role in estimating important parameters (e.g., virion clearance rate or life-span of infected cells). However, most models only account for the acute and asymptomatic latency phase and cannot explain the progression to AIDS. Models that account for the whole course of the infection rely on different hypotheses to explain the progression to AIDS. The aim of this study is to review these models, present their technical approaches and discuss the robustness of their biological hypotheses. Among the few models capturing all three phases of an HIV infection, we can distinguish between those that mainly rely on population dynamics and those that involve virus evolution. Overall, the modeling quest to capture the dynamics of an HIV infection has improved our understanding of the progression to AIDS but, more generally, it has also led to the insight that population dynamics and evolutionary processes can be necessary to explain the course of an infection.