Coevolution in multidimensional trait space favours escape from parasites and pathogens

Challenges for the human immune system after leaving Earth

From the start of life on Earth, several immune defense mechanisms have evolved to guarantee cellular integrity, homeostasis, and host survival. All these sophisticated balances as shaped by and towards the environmental needs have occurred over hundreds of millions of years. Human spaceflight involves various health hazards, such as higher levels of radiation, altered gravity, isolation and confinement, living in tight quarters, and stress associated with being away from home. A growing body of evidence points towards immunological changes in astronauts, including heightened pro-inflammatory responses, reactivation of latent viruses, and cell-mediated alterations, reflecting a dysbalanced state in astronauts. Simultaneously, enhanced pathogenicity, virulence, and drug resistance properties of microorganisms tip the scale out of favor for prolonged stay in space. As we have learned from the past, we see potential for the human immune system, forged and maintained throughout evolutionary history, to adapt to the space exposome. It is unlikely that this will happen in the short time frames set for current space exploration missions. Instead, major risks to astronaut health need to be addressed first, before humans can safely evolve into the space environment.

The evolution of chemodiversity in plants-From verbal to quantitative models

Plants harbour a great chemodiversity, that is diversity of specialised metabolites (SMs), at different scales. For instance, individuals can produce a large number of SMs, and populations can differ in their metabolite composition. Given the ecological and economic importance of plant chemodiversity, it is important to understand how it arises and is maintained over evolutionary time. For other dimensions of biodiversity, that is species diversity and genetic diversity, quantitative models play an important role in addressing such questions. Here, we provide a synthesis of existing hypotheses and quantitative models, that is mathematical models and computer simulations, for the evolution of plant chemodiversity. We describe each model's ingredients, that is the biological processes that shape chemodiversity, the scales it considers and whether it has been formalized as a quantitative model. Although we identify several quantitative models, not all are dynamic and many influential models have remained verbal. To fill these gaps, we outline our vision for the future of chemodiversity modelling. We identify quantitative models used for genetic variation that may be adapted for chemodiversity, and we present a flexible framework for the creation of individual-based models that address different scales of chemodiversity and combine different ingredients that bring this chemodiversity about.

Complex eco-evolutionary dynamics induced by the coevolution of predator–prey movement strategies

The coevolution of predators and prey has been the subject of much empirical and theoretical research that produced intriguing insights into the interplay of ecology and evolution. To allow for mathematical analysis, models of predator–prey coevolution are often coarse-grained, focussing on population-level processes and largely neglecting individual-level behaviour. As selection is acting on individual-level properties, we here present a more mechanistic approach: an individual-based simulation model for the coevolution of predators and prey on a fine-grained resource landscape, where features relevant for ecology (like changes in local densities) and evolution (like differences in survival and reproduction) emerge naturally from interactions between individuals. Our focus is on predator–prey movement behaviour, and we present a new method for implementing evolving movement strategies in an efficient and intuitively appealing manner. Throughout their lifetime, predators and prey make repeated movement decisions on the basis of their movement strategies. Over the generations, the movement strategies evolve, as individuals that successfully survive and reproduce leave their strategy to more descendants. We show that the movement strategies in our model evolve rapidly, thereby inducing characteristic spatial patterns like spiral waves and static spots. Transitions between these patterns occur frequently, induced by antagonistic coevolution rather than by external events. Regularly, evolution leads to the emergence and stable coexistence of qualitatively different movement strategies within the same population. Although the strategy space of our model is continuous, we often observe the evolution of discrete movement types. We argue that rapid evolution, coexistent movement types, and phase shifts between different ecological regimes are not a peculiarity of our model but a result of more realistic assumptions on eco-evolutionary feedbacks and the number of evolutionary degrees of freedom.

Multidimensional divergent selection, local adaptation, and speciation

Divergent selection applied to one or more traits drives local adaptation and may lead to ecological speciation. Divergent selection on many traits might be termed "multidimensional" divergent selection. There is a commonly held view that multidimensional divergent selection is likely to promote local adaptation and speciation to a greater extent than unidimensional divergent selection. We disentangle the core concepts underlying dimensionality as a property of the environment, phenotypes, and genome. In particular, we identify a need to separate the overall strength of selection and the number of loci affected from dimensionality per se, and to distinguish divergence dimensionality from dimensionality of stabilizing selection. We then critically scrutinize this commonly held view that multidimensional selection promotes speciation, re-examining the evidence base from theory, experiments, and nature. We conclude that the evidence base is currently weak and generally suffers from confounding of possible causal effects. Finally, we propose several mechanisms by which multidimensional divergent selection and related processes might influence divergence, both as a driver and as a barrier.

Microbial Pathogenicity in Space

After a less dynamic period, space exploration is now booming. There has been a sharp increase in the number of current missions and also of those being planned for the near future. Microorganisms will be an inevitable component of these missions, mostly because they hitchhike, either attached to space technology, like spaceships or spacesuits, to organic matter and even to us (human microbiome), or to other life forms we carry on our missions. Basically, we never travel alone. Therefore, we need to have a clear understanding of how dangerous our "travel buddies" can be; given that, during space missions, our access to medical assistance and medical drugs will be very limited. Do we explore space together with pathogenic microorganisms? Do our hitchhikers adapt to the space conditions, as well as we do? Do they become pathogenic during that adaptation process? The current review intends to better clarify these questions in order to facilitate future activities in space. More technological advances are needed to guarantee the success of all missions and assure the reduction of any possible health and environmental risks for the astronauts and for the locations being explored.

Scale-dependent effects of host patch traits on species composition in a stickleback parasite metacommunity

A core goal of ecology is to understand the abiotic and biotic variables that regulate species distributions and community composition. A major obstacle is that the rules governing species distributions can change with spatial scale. Here, we illustrate this point using data from a spatially nested metacommunity of parasites infecting a metapopulation of threespine stickleback fish from 34 lakes on Vancouver Island, British Columbia. Like most parasite metacommunities, the composition of stickleback parasites differs among host individuals within each host population, and differs between host populations. The distribution of each parasite taxon depends, to varying degrees, on individual host traits (e.g., mass, diet) and on host-population characteristics (e.g., lake size, mean host mass, mean diet). However, in most cases in this data set, a given parasite was regulated by different factors at the host-individual and host-population scales, leading to scale-dependent patterns of parasite-species co-occurrence.

Physiological Stress Integrates Resistance to Rattlesnake Venom and the Onset of Risky Foraging in California Ground Squirrels

Using venom for predation often leads to the evolution of resistance in prey. Understanding individual variation in venom resistance is key to unlocking basic mechanisms by which antagonistic coevolution can sustain variation in traits under selection. For prey, the opposing challenges of predator avoidance and resource acquisition often lead to correlated levels of risk and reward, which in turn can favor suites of integrated morphological, physiological and behavioral traits. We investigate the relationship between risk-sensitive behaviors, physiological resistance to rattlesnake venom, and stress in a population of California ground squirrels. For the same individuals, we quantified foraging decisions in the presence of snake predators, fecal corticosterone metabolites (a measure of “stress”), and blood serum inhibition of venom enzymatic activity (a measure of venom resistance). Individual responses to snakes were repeatable for three measures of risk-sensitive behavior, indicating that some individuals were consistently risk-averse whereas others were risk tolerant. Venom resistance was lower in squirrels with higher glucocorticoid levels and poorer body condition. Whereas resistance failed to predict proximity to and interactions with snake predators, individuals with higher glucocorticoid levels and in lower body condition waited the longest to feed when near a snake. We compared alternative structural equation models to evaluate alternative hypotheses for the relationships among stress, venom resistance, and behavior. We found support for stress as a shared physiological correlate that independently lowers venom resistance and leads to squirrels that wait longer to feed in the presence of a snake, whereas we did not find evidence that resistance directly facilitates latency to forage. Our findings suggest that stress may help less-resistant squirrels avoid a deadly snakebite, but also reduces feeding opportunities. The combined lethal and non-lethal effects of stressors in predator–prey interactions simultaneously impact multiple key traits in this system, making environmental stress a potential contributor to geographic variation in trait expression of toxic predators and resistant prey.

An individual-based model for the eco-evolutionary emergence of bipartite interaction networks

How ecological interaction networks emerge on evolutionary time scales remains unclear. Here we build an individual-based eco-evolutionary model for the emergence of mutualistic, antagonistic and neutral bipartite interaction networks. Exploring networks evolved under these scenarios, we find three main results. First, antagonistic interactions tend to foster species and trait diversity, while mutualistic interactions reduce diversity. Second, antagonistic interactors evolve higher specialisation, which results in networks that are often more modular than neutral ones; resource species in these networks often display phylogenetic conservatism in interaction partners. Third, mutualistic interactions lead to networks that are more nested than neutral ones, with low phylogenetic conservatism in interaction partners. These results tend to match overall empirical trends, demonstrating that structures of empirical networks that have most often been explained by ecological processes can result from an evolutionary emergence. Our model contributes to the ongoing effort of better integrating ecological interactions and macroevolution.

How long do Red Queen dynamics survive under genetic drift? A comparative analysis of evolutionary and eco-evolutionary models

Background

Red Queen dynamics are defined as long term co-evolutionary dynamics, often with oscillations of genotype abundances driven by fluctuating selection in host-parasite systems. Much of our current understanding of these dynamics is based on theoretical concepts explored in mathematical models that are mostly (i) deterministic, inferring an infinite population size and (ii) evolutionary, thus ecological interactions that change population sizes are excluded. Here, we recall the different mathematical approaches used in the current literature on Red Queen dynamics. We then compare models from game theory (evo) and classical theoretical ecology models (eco-evo), that are all derived from individual interactions and are thus intrinsically stochastic. We assess the influence of this stochasticity through the time to the first loss of a genotype within a host or parasite population.

Results

The time until the first genotype is lost (“extinction time”), is shorter when ecological dynamics, in the form of a changing population size, is considered. Furthermore, when individuals compete only locally with other individuals extinction is even faster. On the other hand, evolutionary models with a fixed population size and competition on the scale of the whole population prolong extinction and therefore stabilise the oscillations. The stabilising properties of intra-specific competitions become stronger when population size is increased and the deterministic part of the dynamics gain influence. In general, the loss of genotype diversity can be counteracted with mutations (or recombination), which then allow the populations to recurrently undergo negative frequency-dependent selection dynamics and selective sweeps.

Conclusion

Although the models we investigated are equal in their biological motivation and interpretation, they have diverging mathematical properties both in the derived deterministic dynamics and the derived stochastic dynamics. We find that models that do not consider intraspecific competition and that include ecological dynamics by letting the population size vary, lose genotypes – and thus Red Queen oscillations – faster than models with competition and a fixed population size.

Long-term evolutionary conflict, Sisyphean arms races, and power in Fisher's geometric model

Evolutionary conflict and arms races are important drivers of evolution in nature. During arms races, new abilities in one party select for counterabilities in the second party. This process can repeat and lead to successive fixations of novel mutations, without a long-term increase in fitness. Models of co-evolution rarely address successive fixations, and one of the main models that use successive fixations-Fisher's geometric model-does not address co-evolution. We address this gap by expanding Fisher's geometric model to the evolution of joint phenotypes that are affected by two parties, such as probability of infection of a host by a pathogen. The model confirms important intuitions and offers some new insights. Conflict can lead to long-term Sisyphean arms races, where parties continue to climb toward their fitness peaks, but are dragged back down by their opponents. This results in far more adaptive evolution compared to the standard geometric model. It also results in fixation of mutations of larger effect, with the important implication that the common modeling assumption of small mutations will apply less often under conflict. Even in comparison with random abiotic change of the same magnitude, evolution under conflict results in greater distances from the optimum, lower fitness, and more fixations, but surprisingly, not larger fixed mutations. We also show how asymmetries in selection strength, mutation size, and mutation input allow one party to win over another. However, winning abilities come with diminishing returns, helping to keep weaker parties in the game.

Surfing on the seascape: Adaptation in a changing environment

The environment changes constantly at various time scales and, in order to survive, species need to keep adapting. Whether these species succeed in avoiding extinction is a major evolutionary question. Using a multilocus evolutionary model of a mutation-limited population adapting under strong selection, we investigate the effects of the frequency of environmental fluctuations on adaptation. Our results rely on an "adaptive-walk" approximation and use mathematical methods from evolutionary computation theory to investigate the interplay between fluctuation frequency, the similarity of environments, and the number of loci contributing to adaptation. First, we assume a linear additive fitness function, but later generalize our results to include several types of epistasis. We show that frequent environmental changes prevent populations from reaching a fitness peak, but they may also prevent the large fitness loss that occurs after a single environmental change. Thus, the population can survive, although not thrive, in a wide range of conditions. Furthermore, we show that in a frequently changing environment, the similarity of threats that a population faces affects the level of adaptation that it is able to achieve. We check and supplement our analytical results with simulations.

The evolution of variance in sequential defences

The defences used by organisms against predators display a great degree of variability. Defence phenotypes can differ substantially among individuals of the same species, and a single individual can itself deploy a variety of defences. Here, we use a mathematical model that includes mutation and selection to understand the evolutionary origin of this variability in a population of a species that deploys defences sequentially ("first" and "second" defences). Typically, the first defence evolves to have lower variance, i.e. appears more closely accumulated around the ideal phenotype, than the second defence (even when the breaching the first defence incurs more fitness loss than breaching the second defence with the other parameters the same for both defences). However, if the first defence is much less effective in repelling predators, or is much less tolerant of deviation from the ideal phenotype, then the first defence can evolve to have higher variance than the second. Other factors like mutation strength and the losses in the fitness when each defence fails also influence the defence variance. Larger mutation rate incurs larger equilibrium variances, and when the comparative importance in fitness of one defence increases, then the ratio between the variances of this defence and the other defence decreases. Sequentially acting defences are found in many organisms, so we encourage empirical research to test our theoretical predictions.

Evolutionary Conflict

Evolutionary conflict occurs when two parties can each affect a joint phenotype, but they gain from pushing it in opposite directions. Conflicts occur across many biological levels and domains but share many features. They are a major source of biological maladaptation. They affect biological diversity, often increasing it, at almost every level. Because opponents create selection that can be strong, persistent, and malevolent, conflict often leads to accelerated evolution and arms races. Conflicts might even drive the majority of adaptation, with pathogens leading the way as selective forces. The evolution of conflicts is complex, with outcomes determined partly by the relative evolvability of each party and partly by the kinds of power that each evolves. Power is a central issue in biology. In addition to physical strength and weapons, it includes strength from numbers and complexity; abilities to bind and block; advantageous timing; and abilities to acquire, use, and distort information.

Trade-off shapes diversity in eco-evolutionary dynamics

We introduce an Interaction- and Trade-off-based Eco-Evolutionary Model (ITEEM), in which species are competing in a well-mixed system, and their evolution in interaction trait space is subject to a life-history trade-off between replication rate and competitive ability. We demonstrate that the shape of the trade-off has a fundamental impact on eco-evolutionary dynamics, as it imposes four phases of diversity, including a sharp phase transition. Despite its minimalism, ITEEM produces a remarkable range of patterns of eco-evolutionary dynamics that are observed in experimental and natural systems. Most notably we find self-organization towards structured communities with high and sustained diversity, in which competing species form interaction cycles similar to rock-paper-scissors games.

Insect societies fight back: the evolution of defensive traits against social parasites

Insect societies face many social parasites that exploit their altruistic behaviours or their resources. Due to the fitness costs these social parasites incur, hosts have evolved various behavioural, chemical, architectural and morphological defence traits. Similar to bacteria infecting multicellular hosts, social parasites have to successfully go through several steps to exploit their hosts. Here, we review how social insects try to interrupt this sequence of events. They can avoid parasite contact by choosing to nest in parasite-free locales or evade attacks by adapting their colony structure. Once social parasites attack, hosts attempt to detect them, which can be facilitated by adjustments in colony odour. If social parasites enter the nest, hosts can either aggressively defend their colony or take their young and flee. Nest structures are often shaped to prevent social parasite invasion or to safeguard host resources. Finally, if social parasites successfully establish themselves in host nests, hosts can rebel by killing the parasite brood or by reproducing in the parasites' presence. Hosts of social parasites can therefore develop multiple traits, leading to the evolution of complex defence portfolios of co-dependent traits. Social parasites can respond to these multi-level defences with counter-adaptations, potentially leading to geographical mosaics of coevolution.This article is part of the Theo Murphy meeting issue 'Evolution of pathogen and parasite avoidance behaviours'.

Does coevolution with a shared parasite drive hosts to partition their defences among species?

When mimicry imposes costs on models, selection may drive the model's phenotype to evolve away from its mimic. For example, brood parasitism often drives hosts to diversify in egg appearance among females within a species, making mimetic parasitic eggs easier to detect. However, when a single parasite species exploits multiple host species, parasitism could also drive host egg evolution away from other co-occurring hosts, to escape susceptibility to their respective mimics. This hypothesis predicts that sympatric hosts of the same parasite should partition egg phenotypic space (defined by egg colour, luminance and pattern) among species to avoid one another. We show that eggs of warbler species parasitized by the cuckoo finch Anomalospiza imberbis in Zambia partition phenotypic space much more distinctly than do eggs of sympatric but unparasitized warblers. Correspondingly, cuckoo finch host-races better match their own specialist host than other local host species. In the weaver family, parasitized by the diederik cuckoo Chrysococcyx caprius, by contrast, parasitized species were more closely related and overlapped extensively in phenotypic space; correspondingly, cuckoos did not match their own host better than others. These results suggest that coevolutionary arms races between hosts and parasites may be shaped by the wider community context in which they unfold.

Rethinking Conventional Wisdom: Are Locally Adapted Parasites Ahead in the Coevolutionary Race?

The metaphors of the Red Queen and the arms race have inspired a large amount of research aimed at understanding the process of antagonistic coevolution between hosts and parasites. One approach that has been heavily used is to estimate the strength of parasite local adaptation using a reciprocal cross infection or transplant study. These studies frequently conclude that the locally adapted species is ahead in the coevolutionary race. Here, I use mathematical models to decompose parasite infectivity into components attributable to local versus global adaptation and to develop a robust index of which species is ahead in the coevolutionary race, which I term coevolutionary advantage. Computer simulations of coevolving host-parasite interactions demonstrate that because the magnitudes of local and global adaptation are largely independent, the link between the sign of local adaptation and coevolutionary advantage is tenuous. A consequence of the weak coupling between local adaptation and coevolutionary advantage is that the bulk of existing empirical studies do not sample enough populations for any reliable conclusions to be drawn. Together, these results suggest that the long-standing conventional wisdom holding that locally adapted parasites are ahead in the coevolutionary race should be reconsidered.

A spatial theory for emergent multiple predator-prey interactions in food webs

Predator–prey interaction is inherently spatial because animals move through landscapes to search for and consume food resources and to avoid being consumed by other species. The spatial nature of species interactions necessitates integrating spatial processes into food web theory and evaluating how predators combine to impact their prey. Here, we present a spatial modeling approach that examines emergent multiple predator effects on prey within landscapes. The modeling is inspired by the habitat domain concept derived from empirical synthesis of spatial movement and interactions studies. Because these principles are motivated by synthesis of short‐term experiments, it remains uncertain whether spatial contingency principles hold in dynamical systems. We address this uncertainty by formulating dynamical systems models, guided by core habitat domain principles, to examine long‐term multiple predator–prey spatial dynamics. To describe habitat domains, we use classical niche concepts describing resource utilization distributions, and assume species interactions emerge from the degree of overlap between species. The analytical results generally align with those from empirical synthesis and present a theoretical framework capable of demonstrating multiple predator effects that does not depend on the small spatial or temporal scales typical of mesocosm experiments, and help bridge between empirical experiments and long‐term dynamics in natural systems.

Genetics of host-parasite interactions: towards a comprehensive dissection of Drosophila resistance to viral infection

One of the major challenges in evolutionary biology is to unravel the genetic basis of adaptation. This issue has been gaining momentum in recent years with the accelerated development of novel genetic and genomic techniques and resources. In this issue of Molecular Ecology, Cogni et al. (2016) address the genetic basis of resistance to two viruses in Drosophila melanogaster using a panel of recombinant inbred lines with unprecedented resolution allowing detection of rare alleles and/or alleles of small effect. The study confirms the role of previously identified genes of major effect and adds novel regions with minor effect to the genetic basis of Drosophila resistance to the Drosophila C virus or the sigma virus. Additional analyses reveal the absence of cross-resistance and of epistasis between the various genomic regions. This detailed information on the genetic architecture of host resistance constitutes an important step towards the understanding of both the physiology of antiviral immunity and the evolution of host-parasite interactions.

The Evolutionary Consequences of Stepwise Infection Processes

Molecular and cellular studies reveal that the resistance of hosts to parasites and pathogens is a cascade-like process with multiple steps required to be passed for successful infection. By contrast, much of evolutionary reasoning is based on strongly simplified, one- or two-step infection processes with simple genetics or on resistance being a quantitative trait. Here we attempt a conceptual unification of these two perspectives with the aim of cross-fostering research and filling some of the gaps in our concepts of the ecology and evolution of disease. This conceptual unification has a profound impact on the way we understand the genetics and evolution of host resistance, ecological immunity, evolution of virulence, defence portfolios, and host-pathogen coevolution.

A genomic perspective on the generation and maintenance of genetic diversity in herbivorous insects

Understanding the processes that generate and maintain genetic variation within populations is a central goal in evolutionary biology. Theory predicts that some of this variation is maintained as a consequence of adapting to variable habitats. Studies in herbivorous insects have played a key role in confirming this prediction. Here, we highlight theoretical and conceptual models for the maintenance of genetic diversity in herbivorous insects, empirical genomic studies testing these models, and pressing questions within the realm of evolutionary and functional genomic studies. To address key gaps, we propose an integrative approach combining population genomic scans for adaptation, genome-wide characterization of targets of selection through experimental manipulations, mapping the genetic architecture of traits influencing fitness, and functional studies. We also stress the importance of studying the maintenance of genetic variation across biological scales-from variation within populations to divergence among populations-to form a comprehensive view of adaptation in herbivorous insects.

Coevolution can explain defensive secondary metabolite diversity in plants

Many plant species produce defensive compounds that are often highly diverse within and between populations. The genetic and cellular mechanisms by which metabolite diversity is produced are increasingly understood, but the evolutionary explanations for persistent diversification in plant secondary metabolites have received less attention. Here we consider the role of plant-herbivore coevolution in the maintenance and characteristics of diversity in plant secondary metabolites. We present a simple model in which plants can evolve to invest in a range of defensive toxins, and herbivores can evolve resistance to these toxins. We allow either single-species evolution or reciprocal coevolution. Our model shows that coevolution maintains toxin diversity within populations. Furthermore, there is a fundamental coevolutionary asymmetry between plants and their herbivores, because herbivores must resist all plant toxins, whereas plants need to challenge and nullify only one resistance trait. As a consequence, average plant fitness increases and insect fitness decreases as number of toxins increases. When costs apply, the model showed both arms race escalation and strong coevolutionary fluctuation in toxin concentrations across time. We discuss the results in the context of other evolutionary explanations for secondary metabolite diversification.

Individual-based models for adaptive diversification in high-dimensional phenotype spaces

Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient.

Collective defence portfolios of ant hosts shift with social parasite pressure

Host defences become increasingly costly as parasites breach successive lines of defence. Because selection favours hosts that successfully resist parasitism at the lowest possible cost, escalating coevolutionary arms races are likely to drive host defence portfolios towards ever more expensive strategies. We investigated the interplay between host defence portfolios and social parasite pressure by comparing 17 populations of two Temnothorax ant species. When successful, collective aggression not only prevents parasitation but also spares host colonies the cost of searching for and moving to a new nest site. However, once parasites breach the host's nest defence, host colonies should resort to flight as the more beneficial resistance strategy. We show that under low parasite pressure, host colonies more likely responded to an intruding Protomognathus americanus slavemaker with collective aggression, which prevented the slavemaker from escaping and potentially recruiting nest-mates. However, as parasite pressure increased, ant colonies of both host species became more likely to flee rather than to fight. We conclude that host defence portfolios shift consistently with social parasite pressure, which is in accordance with the degeneration of frontline defences and the evolution of subsequent anti-parasite strategies often invoked in hosts of brood parasites.

Coevolution drives the emergence of complex traits and promotes evolvability

The evolution of complex organismal traits is obvious as a historical fact, but the underlying causes--including the role of natural selection--are contested. Gould argued that a random walk from a necessarily simple beginning would produce the appearance of increasing complexity over time. Others contend that selection, including coevolutionary arms races, can systematically push organisms toward more complex traits. Methodological challenges have largely precluded experimental tests of these hypotheses. Using the Avida platform for digital evolution, we show that coevolution of hosts and parasites greatly increases organismal complexity relative to that otherwise achieved. As parasites evolve to counter the rise of resistant hosts, parasite populations retain a genetic record of past coevolutionary states. As a consequence, hosts differentially escape by performing progressively more complex functions. We show that coevolution's unique feedback between host and parasite frequencies is a key process in the evolution of complexity. Strikingly, the hosts evolve genomes that are also more phenotypically evolvable, similar to the phenomenon of contingency loci observed in bacterial pathogens. Because coevolution is ubiquitous in nature, our results support a general model whereby antagonistic interactions and natural selection together favor both increased complexity and evolvability.

Environmental bacteriophages: viruses of microbes in aquatic ecosystems

Since the discovery 2–3 decades ago that viruses of microbes are abundant in marine ecosystems, viral ecology has grown increasingly to reach the status of a full scientific discipline in environmental sciences. A dedicated ISVM society, the International Society for Viruses of Microorganisms, (http://www.isvm.org/) was recently launched. Increasing studies in viral ecology are sources of novel knowledge related to the biodiversity of living things, the functioning of ecosystems, and the evolution of the cellular world. This is because viruses are perhaps the most diverse, abundant, and ubiquitous biological entities in the biosphere, although local environmental conditions enrich for certain viral types through selective pressure. They exhibit various lifestyles that intimately depend on the deep-cellular mechanisms, and are ultimately replicated by members of all three domains of cellular life (Bacteria, Eukarya, Archaea), as well as by giant viruses of some eukaryotic cells. This establishes viral parasites as microbial killers but also as cell partners or metabolic manipulators in microbial ecology. The present chapter sought to review the literature on the diversity and functional roles of viruses of microbes in environmental microbiology, focusing primarily on prokaryotic viruses (i.e., phages) in aquatic ecosystems, which form the bulk of our knowledge in modern environmental viral ecology.

Multidimensional (co)evolutionary stability

The complexity of biotic and abiotic environmental conditions is such that the fitness of individuals is likely to depend on multiple traits. Using a synthetic framework of phenotypic evolution that draws from adaptive dynamics and quantitative genetics approaches, we explore how the number of traits under selection influences convergence stability and evolutionary stability in models for coevolution in multidimensional phenotype spaces. Our results allow us to identify three different effects of trait dimensionality on stability. First are (i) a "combinatorial effect": without epistasis and genetic correlations, a higher number of trait dimensions offers more opportunities for equilibria to be unstable; and (ii) epistatic interactions, that is, fitness interactions between traits, which tend to destabilize evolutionary equilibria; this effect increases with the dimension of phenotype space. These first two effects influence both convergence stability and evolutionary stability, while (iii) genetic correlations (due, e.g., to pleiotropy or linkage disequilibrium) can affect only convergence stability. We illustrate the general prediction that increased dimensionality destabilizes evolutionary equilibria using examples drawn from well-studied classical models of frequency-dependent competition for resources, adaptation to a spatially heterogeneous environment, and antagonistic coevolution. In addition, our analyses show that increased dimensionality can favor diversification, for example, in the form of local adaptation, as well as evolutionary escape.

Chaos and unpredictability in evolution

The possibility of complicated dynamic behavior driven by nonlinear feedbacks in dynamical systems has revolutionized science in the latter part of the last century. Yet despite examples of complicated frequency dynamics, the possibility of long-term evolutionary chaos is rarely considered. The concept of "survival of the fittest" is central to much evolutionary thinking and embodies a perspective of evolution as a directional optimization process exhibiting simple, predictable dynamics. This perspective is adequate for simple scenarios, when frequency-independent selection acts on scalar phenotypes. However, in most organisms many phenotypic properties combine in complicated ways to determine ecological interactions, and hence frequency-dependent selection. Therefore, it is natural to consider models for evolutionary dynamics generated by frequency-dependent selection acting simultaneously on many different phenotypes. Here we show that complicated, chaotic dynamics of long-term evolutionary trajectories in phenotype space is very common in a large class of such models when the dimension of phenotype space is large, and when there are selective interactions between the phenotypic components. Our results suggest that the perspective of evolution as a process with simple, predictable dynamics covers only a small fragment of long-term evolution.

Rethinking mutualism stability: cheaters and the evolution of sanctions

How cooperation originates and persists in diverse species, from bacteria to multicellular organisms to human societies, is a major question in evolutionary biology. A large literature asks: what prevents selection for cheating within cooperative lineages? In mutualisms, or cooperative interactions between species, feedback between partners often aligns their fitness interests, such that cooperative symbionts receive more benefits from their hosts than uncooperative symbionts. But how do these feedbacks evolve? Cheaters might invade symbiont populations and select for hosts that preferentially reward or associate with cooperators (often termed sanctions or partner choice); hosts might adapt to variation in symbiont quality that does not amount to cheating (e.g., environmental variation); or conditional host responses might exist before cheaters do, making mutualisms stable from the outset. I review evidence from yucca-yucca moth, fig-fig wasp, and legume-rhizobium mutualisms, which are commonly cited as mutualisms stabilized by sanctions. Based on the empirical evidence, it is doubtful that cheaters select for host sanctions in these systems; cheaters are too uncommon. Recognizing that sanctions likely evolved for functions other than retaliation against cheaters offers many insights about mutualism coevolution, and about why mutualism evolves in only some lineages of potential hosts.

Do-or-die life cycles and diverse post-infection resistance mechanisms limit the evolution of parasite host ranges

In light of the dynamic nature of parasite host ranges and documented potential for rapid host shifts, the observed high host specificity of most parasites remains an ecological paradox. Different variants of host-use trade-offs have become a mainstay of theoretical explanations of the prevalence of host specialism, but empirical evidence for such trade-offs is rare. We propose an alternative theory based on basic features of the parasite life cycle: host selection and subsequent intrahost replication. We introduce a new concept of effective burst size that accounts for the fact that successful host selection does not guarantee intrahost replication. Our theory makes a general prediction that a parasite will expand its host range if its effective burst size is positive. An in silico model of bacteria-phage coevolution verifies our predictions and demonstrates that the tendency for relatively narrow host ranges in parasites can be explained even in the absence of trade-offs.

Abrupt community transitions and cyclic evolutionary dynamics in complex food webs

Understanding the emergence and maintenance of biodiversity ranks among the most fundamental challenges in evolutionary ecology. While processes of community assembly have frequently been analyzed from an ecological perspective, their evolutionary dimensions have so far received less attention. To elucidate the eco-evolutionary processes underlying the long-term build-up and potential collapse of community diversity, here we develop and examine an individual-based model describing coevolutionary dynamics driven by trophic interactions and interference competition, of a pair of quantitative traits determining predator and prey niches. Our results demonstrate the (1) emergence of communities with multiple trophic levels, shown here for the first time for stochastic models with linear functional responses, and (2) intermittent and cyclic evolutionary transitions between two alternative community states. In particular, our results indicate that the interplay of ecological and evolutionary dynamics often results in extinction cascades that remove the entire trophic level of consumers from a community. Finally, we show the (3) robustness of our results under variations of model assumptions, underscoring that processes of consumer collapse and subsequent rebound could be important elements of understanding biodiversity dynamics in natural communities.

Evolving digital ecological networks

"It is hard to realize that the living world as we know it is just one among many possibilities" [1]. Evolving digital ecological networks are webs of interacting, self-replicating, and evolving computer programs (i.e., digital organisms) that experience the same major ecological interactions as biological organisms (e.g., competition, predation, parasitism, and mutualism). Despite being computational, these programs evolve quickly in an open-ended way, and starting from only one or two ancestral organisms, the formation of ecological networks can be observed in real-time by tracking interactions between the constantly evolving organism phenotypes. These phenotypes may be defined by combinations of logical computations (hereafter tasks) that digital organisms perform and by expressed behaviors that have evolved. The types and outcomes of interactions between phenotypes are determined by task overlap for logic-defined phenotypes and by responses to encounters in the case of behavioral phenotypes. Biologists use these evolving networks to study active and fundamental topics within evolutionary ecology (e.g., the extent to which the architecture of multispecies networks shape coevolutionary outcomes, and the processes involved).

Evolution in a changing environment

We propose a simple model for genetic adaptation to a changing environment, describing a fitness landscape characterized by two maxima. One is associated with "specialist" individuals that are adapted to the environment; this maximum moves over time as the environment changes. The other maximum is static, and represents "generalist" individuals not affected by environmental changes. The rest of the landscape is occupied by "maladapted" individuals. Our analysis considers the evolution of these three subpopulations. Our main result is that, in presence of a sufficiently stable environmental feature, as in the case of an unchanging aspect of a physical habitat, specialists can dominate the population. By contrast, rapidly changing environmental features, such as language or cultural habits, are a moving target for the genes; here, generalists dominate, because the best evolutionary strategy is to adopt neutral alleles not specialized for any specific environment. The model we propose is based on simple assumptions about evolutionary dynamics and describes all possible scenarios in a non-trivial phase diagram. The approach provides a general framework to address such fundamental issues as the Baldwin effect, the biological basis for language, or the ecological consequences of a rapid climate change.

The evolution of mutualism in gut microbiota via host epithelial selection

A computer model of the gut shows how a host can readily select friendly bacteria over harmful bacteria through a process called “selectivity amplification.”

The human gut harbours a large and genetically diverse population of symbiotic microbes that both feed and protect the host. Evolutionary theory, however, predicts that such genetic diversity can destabilise mutualistic partnerships. How then can the mutualism of the human microbiota be explained? Here we develop an individual-based model of host-associated microbial communities. We first demonstrate the fundamental problem faced by a host: The presence of a genetically diverse microbiota leads to the dominance of the fastest growing microbes instead of the microbes that are most beneficial to the host. We next investigate the potential for host secretions to influence the microbiota. This reveals that the epithelium–microbiota interface acts as a selectivity amplifier: Modest amounts of moderately selective epithelial secretions cause a complete shift in the strains growing at the epithelial surface. This occurs because of the physical structure of the epithelium–microbiota interface: Epithelial secretions have effects that permeate upwards through the whole microbial community, while lumen compounds preferentially affect cells that are soon to slough off. Finally, our model predicts that while antimicrobial secretion can promote host epithelial selection, epithelial nutrient secretion will often be key to host selection. Our findings are consistent with a growing number of empirical papers that indicate an influence of host factors upon microbiota, including growth-promoting glycoconjugates. We argue that host selection is likely to be a key mechanism in the stabilisation of the mutualism between a host and its microbiota.

The cells of our bodies are greatly outnumbered by the bacteria that live on us and, in particular, in our gut. It is now clear that many gut bacteria are highly beneficial, protecting us from pathogens and helping us with digestion. But what prevents beneficial bacteria from going bad? Why don't bacteria evolve to shirk on the help that they provide and simply use us as a food source? Here we explore this problem using a computer model that reduces the problem to its key elements. We first illustrate the basic problem faced by a host: Whenever beneficial bacteria grow slowly, the host will lose them to fast-growing species that provide no benefit. We then propose a solution to the host's problem: The host can use secretions—nutrients and toxins—to control the bacteria that grow on the epithelial cell layer of the gut. In particular, our model predicts that the epithelial surface acts as a “selectivity amplifier”. The host can thereby maintain beneficial bacteria with only small amounts of weakly selective secretions. Our model fits with a growing body of experimental data showing that hosts have diverse and important influences on their gut bacteria.

Paleovirology and virally derived immunity

Paleovirology, the study of viruses on evolutionary timescales, can exploit information from endogenous viral elements (EVEs), which are the result of heritable horizontal gene transfer (HGT) from viruses to hosts. The availability of genomic data has increased opportunities to study EVEs, and bioinformatics techniques have been crucial in cataloguing EVE diversity and taxonomic coverage. Recent advances show that some EVEs have been co-opted as cellular genes, often as inhibitors of viral infection. These genes are an intriguing strategy in virus-host evolutionary battles in that genetic material is transferred from virus to host, and then used by the host against the virus. In this review, we consider the genes and processes involved in EVE-derived immunity (EDI), assess factors leading to its emergence, and outline how future work will benefit from incorporating evolutionary approaches.