COEVOLUTION AND THE ARCHITECTURE OF MUTUALISTIC NETWORKS

Although coevolution is widely recognized as an important evolutionary process for pairs of reciprocally specialized species, its importance within species‐rich communities of generalized species has been questioned. Here we develop and analyze mathematical models of mutualistic communities, such as those between plants and pollinators or plants and seed‐dispersers to evaluate the importance of coevolutionary selection within complex communities. Our analyses reveal that coevolutionary selection can drive significant changes in trait distributions with important consequences for the network structure of mutualistic communities. One such consequence is greater connectance caused by an almost invariable increase in the rate of mutualistic interaction within the community. Another important consequence is altered patterns of nestedness. Specifically, interactions mediated by a mechanism of phenotype matching tend to be antinested when coevolutionary selection is weak and even more strongly antinested as increasing coevolutionary selection favors the emergence of reciprocal specialization. In contrast, interactions mediated by a mechanism of phenotype differences tend to be nested when coevolutionary selection is weak, but less nested as increasing coevolutionary selection favors greater levels of generalization in both plants and animals. Taken together, our results show that coevolutionary selection can be an important force within mutualistic communities, driving changes in trait distributions, interaction rates, and even network structure.     

The coevolutionary dynamics of antagonistic interactions mediated by quantitative traits with evolving variances

Quantitative traits frequently mediate coevolutionary interactions between predator and prey or parasite and host. Previous efforts to understand and predict the coevolutionary dynamics of these interactions have generally assumed that standing genetic variation is fixed or absent altogether. We develop a genetically explicit model of coevolution that bridges the gap between these approaches by allowing genetic variation itself to evolve. Analysis of this model shows that the evolution of genetic variance has important consequences for the dynamics and outcome of coevolution. Of particular importance is our demonstration that coevolutionary cycles can emerge in the absence of stabilizing selection, an outcome not possible in previous models of coevolution mediated by quantitative traits. Whether coevolutionary cycles evolve depends upon the strength of selection, the number of loci, and the rate of mutation in each of the interacting species. Our results also generate novel predictions for the expected sign and magnitude of linkage disequilibria in each species.     

ADAPTIVE DIVERGENCE IN DARWIN'S RACE: HOW COEVOLUTION CAN GENERATE TRAIT DIVERSITY IN A POLLINATION SYSTEM

Understanding how reciprocal selection shapes interacting species in Darwin's coevolutionary race is a captivating pursuit in evolutionary ecology. Coevolving traits can potentially display following three patterns: (1) geographical variation in matched traits, (2) bias in trait matching, and (3) bimodal distribution of a trait in certain populations. Based on the framework of adaptive dynamics, we present an evolutionary model for a coevolving pollination system involving the long‐proboscid fly (Moegistorhynchus longirostris) and the long‐tubed iris (Lapeirousia anceps). The model successfully demonstrates that Darwin's hypothesis can lead to all three patterns if costs are involved. Geographical variation in matched traits could be driven by geographical variation in environmental factors that affect the cost rate of trait escalation. Unequal benefits derived from the interaction by the fly and the flower could potentially cause the bias in trait matching of the system. Different cost rates to trait elongation incurred by the two species and weak assortative interactions in the coevolutionary race can drive divergent selection (i.e., an evolutionary branching) that leads to the bimodal distribution of traits. Overall, the model highlights the importance of assortative interactions and the balance of costs incurred by coevolving species as factors determining the eventual phenotypic outcome of coevolutionary interactions.     

The impact of environmental change on host-parasite coevolutionary dynamics

Environmental factors are known to affect the strength and the specificity of interactions between hosts and parasites. However, how this shapes patterns of coevolutionary dynamics is not clear. Here, we construct a simple mathematical model to study the effect of environmental change on host-parasite coevolutionary outcome when interactions are of the matching-alleles or the gene-for-gene type. Environmental changes may effectively alter the selective pressure and the level of specialism in the population. Our results suggest that environmental change altering the specificity of selection in antagonistic interactions can produce alternating time windows of cyclical allele-frequency dynamics and cessation thereof. This type of environmental impact can also explain the maintenance of polymorphism in gene-for-gene interactions without costs. Overall, our study points to the potential consequences of environmental variation in coevolution, and thus the importance of characterizing genotype-by-genotype-by-environment interactions in natural host-parasite systems, especially those that change the direction of selection acting between the two species.     

Coevolution by different functional mechanisms modulates the structure and dynamics of antagonistic and mutualistic networks

A central problem in the study of species interactions is to understand the underlying ecological and evolutionary mechanisms that shape and are shaped by trait evolution in interacting assemblages. The patterns of interaction among species (i.e. network structure) provide the pathways for evolution and coevolution, which are modulated by how traits affect individual fitness (i.e. functional mechanisms). Functional mechanisms, in turn, also affect the likelihood of an ecological interaction, shaping the structure of interaction networks. Here, we build adaptive network models to explore the potential role of coevolution by two functional mechanisms, trait matching and exploitation barrier, in driving trait evolution and the structure of interaction networks. We use these models to explore how different scenarios of coevolution and functional mechanisms reproduce the empirical network patterns observed in antagonistic and mutualistic interactions and affect trait evolution. Scenarios assuming coevolutionary feedback with a strong effect of functional mechanism better reproduce the empirical structure of networks. Antagonistic and mutualistic networks, however, are better explained by different functional mechanisms and the structure of antagonisms is better reproduced than that of mutualisms. Scenarios assuming coevolution by strong trait matching between interacting partners better explain the structure of antagonistic networks, whereas those assuming strong barrier effects better reproduce the structure of mutualistic networks. The dynamics resulting from the feedback between strong functional mechanisms and coevolution favor the stability of antagonisms and mutualisms. Selection favoring trait matching reduces temporal trait fluctuation and the magnitude of arms races in antagonisms, whereas selection due to exploitation barriers reduces temporal trait fluctuations in mutualisms. Our results indicate that coevolutionary models better reproduce the network structure of antagonisms than those of mutualisms and that different functional mechanisms may favor the persistence of antagonistic and mutualistic interacting assemblages.     

Coinfecting parasites can modify fluctuating selection dynamics in host–parasite coevolution

Genetically specific interactions between hosts and parasites can lead to coevolutionary fluctuations in their genotype frequencies over time. Such fluctuating selection dynamics are, however, expected to occur only under specific circumstances (e.g., high fitness costs of infection to the hosts). The outcomes of host–parasite interactions are typically affected by environmental/ecological factors, which could modify coevolutionary dynamics. For instance, individual hosts are often infected with more than one parasite species and interactions between them can alter host and parasite performance. We examined the potential effects of coinfections by genetically specific (i.e., coevolving) and nonspecific (i.e., generalist) parasite species on fluctuating selection dynamics using numerical simulations. We modeled coevolution (a) when hosts are exposed to a single parasite species that must genetically match the host to infect, (b) when hosts are also exposed to a generalist parasite that increases fitness costs to the hosts, and (c) when coinfecting parasites compete for the shared host resources. Our results show that coinfections can enhance fluctuating selection dynamics when they increase fitness costs to the hosts. Under resource competition, coinfections can either enhance or suppress fluctuating selection dynamics, depending on the characteristics (i.e., fecundity, fitness costs induced to the hosts) of the interacting parasites.     

Antagonistic coevolution between multiple quantitative traits: Matching dynamics can arise from difference interactions

Coevolution is one of the major drivers of complex dynamics in population ecology. Historically, antagonistic coevolution in victim-exploiter systems has been a topic of special interest, and involves traits with various genetic architectures (e.g., the number of genes involved) and effects on interactions. For example, exploiters may need to have traits that “match” those of victims for successful exploitation (i.e., a matching interaction), or traits that exceed those of victims (i.e., a difference interaction). Different models exist which are appropriate for different types of traits, including Mendelian (discrete) and quantitative (continuous) traits. For models with multiple Mendelian traits, recent studies have shown that antagonistic coevolutionary patterns that appear as matching interactions can arise due to multiple difference interactions with costs of having large trait values. Here we generalize their findings to quantitative traits and show, analogously, that the multidimensional difference interactions with costs sometimes behave qualitatively the same as matching interactions. While previous studies in quantitative genetics have used the dichotomy between matching and difference frameworks to explore coevolutionary dynamics, we suggest that exploring multidimensional trait space is important to examine the generality of results obtained from one-dimensional traits.     

Genetic correlations and the coevolutionary dynamics of three-species systems

The majority of species interact with at least several others. We develop simple genetic models of coevolution between three species where interactions are mediated by quantitative traits. We assume that one of the species has two quantitative traits, each of which governs its interaction with one of the other two species. We use this model to explore how genetic correlations between the two traits in the multivariate species shape the evolutionary dynamics and outcomes of three species interactions. Our results suggest that genetic correlations are most important when at least one of the interactions is between a predator and prey or parasite and host. In these cases, genetic correlations between traits lead to a wide variety of novel coevolutionary outcomes and dynamics. In particular, genetic correlations can affect the existence and stability of coevolutionary equilibrium points, and they can lead to recurrent or permanent maladaptation. When the three species interact only as competitors or mutualists, however, genetic correlations have no effect on the outcome of coevolution. In all cases, our results reveal the surprising conclusion that both positive and negative genetic correlations between traits have qualitatively identical effects on coevolutionary dynamics.     

Coevolutionary alternation in antagonistic interactions

Coevolution between parasites and hosts or predators and prey often involves multiple species with similar kinds of defenses and counter-defenses. Classic examples include the interactions between phytophagous insects and their host plants, thick-shelled invertebrates and their shell-crushing predators, and ungulates and their predators. There are three major hypotheses for the nonequilibrium coevolutionary dynamics of these multispecific trophic interactions: escalation in traits, cycles in traits leading to fluctuating polymorphisms, and coevolutionary alternation. The conditions under which cycles and escalation are likely to occur have been well developed theoretically. In contrast, the conditions favoring coevolutionary alternation-evolutionary fluctuations in predator or prey preference driven by evolutionary shifts in relative levels of prey defense and vice versa-have yet to be identified. Using a set of quantitative coevolutionary models, we demonstrate that coevolutionary alternation can occur across a wide range of biologically plausible conditions. The result is often repeated, and potentially rapid, evolutionary shifts in patterns of specialization within networks of interacting species.     

Coevolution in temporally variable environments

Many potentially mutualistic interactions are conditional, with selection that varies between mutualism and antagonism over space and time. We develop a genetic model of temporally variable coevolution that incorporates stochastic fluctuations between mutualism and antagonism. We use this model to determine conditions necessary for the coevolution of matching traits between a host and a conditional mutualist. Using an analytical approximation, we show that matching traits will coevolve when the geometric mean interaction is mutualistic. When this condition does not hold, polymorphism and trait mismatching are maintained, and coevolutionary cycles may result. Numerical simulations verify this prediction and suggest that it remains robust in the presence of temporal autocorrelation. These results are compared with those from spatial models with unrestricted movement. The comparisons demonstrate that gene flow is unnecessary for generating empirical patterns predicted by the geographic mosaic theory of coevolution.     

Predicting rates of interspecific interaction from phylogenetic trees

Integrating phylogenetic information can potentially improve our ability to explain species' traits, patterns of community assembly, the network structure of communities, and ecosystem function. In this study, we use mathematical models to explore the ecological and evolutionary factors that modulate the explanatory power of phylogenetic information for communities of species that interact within a single trophic level. We find that phylogenetic relationships among species can influence trait evolution and rates of interaction among species, but only under particular models of species interaction. For example, when interactions within communities are mediated by a mechanism of phenotype matching, phylogenetic trees make specific predictions about trait evolution and rates of interaction. In contrast, if interactions within a community depend on a mechanism of phenotype differences, phylogenetic information has little, if any, predictive power for trait evolution and interaction rate. Together, these results make clear and testable predictions for when and how evolutionary history is expected to influence contemporary rates of species interaction.     

Non-genetic inheritance and the patterns of antagonistic coevolution

ABSTRACT: BACKGROUND: Antagonistic species interactions can lead to coevolutionary genotype or phenotype frequency oscillations, with important implications for ecological and evolutionary processes. However, direct empirical evidence of such oscillations is rare. The rarity of observations is generally attributed to inherent difficulties of ecological and evolutionary long-term studies, to weak or absent interaction between species, or to the absence of negative frequency-dependence. RESULTS: Here, we show that another factor - non-genetic inheritance, mediated for example by epigenetic mechanisms - can completely eliminate oscillations even if only a small fraction of offspring are affected. We analytically derive the threshold value of this fraction at which the dynamics change from oscillatory to stable, and investigate how selection, mutation and generation times differences between the two species affect the threshold value. These results strongly suggest that the lack of phenotype frequency oscillations should not be attributed to the lack of strong interactions between antagonistic species. CONCLUSIONS: Given increasing evidence of non-genetic effects on the outcomes of antagonistic species interactions, we suggest that these effects should be incorporated into ecological and evolutionary models of interacting species.     

Ecological interactions drive evolutionary loss of traits

Loss of traits can dramatically alter the fate of species. Evidence is rapidly accumulating that the prevalence of trait loss is grossly underestimated. New findings demonstrate that traits can be lost without affecting the external phenotype, provided the lost function is compensated for by species interactions. This is important because trait loss can tighten the ecological relationship between partners, affecting the maintenance of species interactions. Here, we develop a new perspective on so-called `compensated trait loss' and how this type of trait loss may affect the evolutionary dynamics between interacting organisms. We argue that: (1) the frequency of compensated trait loss is currently underestimated because it can go unnoticed as long as ecological interactions are maintained; (2) by analysing known cases of trait loss, specific factors promoting compensated trait loss can be identified and (3) genomic sequencing is a key way forwards in detecting compensated trait loss. We present a comprehensive literature survey showing that compensated trait loss is taxonomically widespread, can involve essential traits, and often occurs as replicated evolutionary events. Despite its hidden nature, compensated trait loss is important in directing evolutionary dynamics of ecological relationships and has the potential to change facultative ecological interactions into obligatory ones.     

Phenotypic mismatches reveal escape from arms-race coevolution

Because coevolution takes place across a broad scale of time and space, it is virtually impossible to understand its dynamics and trajectories by studying a single pair of interacting populations at one time. Comparing populations across a range of an interaction, especially for long-lived species, can provide insight into these features of coevolution by sampling across a diverse set of conditions and histories. We used measures of prey traits (tetrodotoxin toxicity in newts) and predator traits (tetrodotoxin resistance of snakes) to assess the degree of phenotypic mismatch across the range of their coevolutionary interaction. Geographic patterns of phenotypic exaggeration were similar in prey and predators, with most phenotypically elevated localities occurring along the central Oregon coast and central California. Contrary to expectations, however, these areas of elevated traits did not coincide with the most intense coevolutionary selection. Measures of functional trait mismatch revealed that over one-third of sampled localities were so mismatched that reciprocal selection could not occur given current trait distributions. Estimates of current locality-specific interaction selection gradients confirmed this interpretation. In every case of mismatch, predators were “ahead” of prey in the arms race; the converse escape of prey was never observed. The emergent pattern suggests a dynamic in which interacting species experience reciprocal selection that drives arms-race escalation of both prey and predator phenotypes at a subset of localities across the interaction. This coadaptation proceeds until the evolution of extreme phenotypes by predators, through genes of large effect, allows snakes to, at least temporarily, escape the arms race.     

Nonrandom mating preserves intrasexual polymorphism and stops population differentiation in sexual conflict

Evolutionary conflict between the sexes is predicted to lead to sexual arms races in which male adaptations for acquiring mates ("offense" traits) are met by female counteradaptations--for example, to reduce mating rate ("defense" traits). Such coevolutionary chases may be perpetual. However, we show here that the coevolutionary process may also lead to a stable state in which multiple offense-defense trait pairs are maintained. This type of polymorphism below the species level is a result of sexual conflict in combination with nonrandom mating. Our results show that if nonrandom mating occurs with respect to male and female conflict traits, genetic correlations will act to stabilize the trait frequencies so that all morphs are maintained. We discuss the results in special relation to the evolution of female polymorphism in diving beetles and argue that the process we describe may be a general force that maintains polymorphism in other taxa as well.     

Dos and don'ts of testing the geographic mosaic theory of coevolution

The geographic mosaic theory of coevolution is stimulating much new research on interspecific interactions. We provide a guide to the fundamental components of the theory, its processes and main predictions. Our primary objectives are to clarify misconceptions regarding the geographic mosaic theory of coevolution and to describe how empiricists can test the theory rigorously. In particular, we explain why confirming the three main predicted empirical patterns (spatial variation in traits mediating interactions among species, trait mismatching among interacting species and few species-level coevolved traits) does not provide unequivocal support for the theory. We suggest that strong empirical tests of the geographic mosaic theory of coevolution should focus on its underlying processes: coevolutionary hot and cold spots, selection mosaics and trait remixing. We describe these processes and discuss potential ways each can be tested.     

Evolution and coevolution in mutualistic networks

A major current challenge in evolutionary biology is to understand how networks of interacting species shape the coevolutionary process. We combined a model for trait evolution with data for twenty plant-animal assemblages to explore coevolution in mutualistic networks. The results revealed three fundamental aspects of coevolution in species-rich mutualisms. First, coevolution shapes species traits throughout mutualistic networks by speeding up the overall rate of evolution. Second, coevolution results in higher trait complementarity in interacting partners and trait convergence in species in the same trophic level. Third, convergence is higher in the presence of super-generalists, which are species that interact with multiple groups of species. We predict that worldwide shifts in the occurrence of super-generalists will alter how coevolution shapes webs of interacting species. Introduced species such as honeybees will favour trait convergence in invaded communities, whereas the loss of large frugivores will lead to increased trait dissimilarity in tropical ecosystems.     

The evolutionary response of predators to dangerous prey: hotspots and coldspots in the geographic mosaic of coevolution between garter snakes and newts

The "geographic mosaic" approach to understanding coevolution is predicated on the existence of variable selection across the landscape of an interaction between species. A range of ecological factors, from differences in resource availability to differences in community composition, can generate such a mosaic of selection among populations, and thereby differences in the strength of coevolution. The result is a mixture of hotspots, where reciprocal selection is strong, and coldspots, where reciprocal selection is weak or absent, throughout the ranges of species. Population subdivision further provides the opportunity for nonadaptive forces, including gene flow, drift, and metapopulation dynamics, to influence the coevolutionary interaction between species. Some predicted results of this geographic mosaic of coevolution include maladapted or mismatched phenotypes, maintenance of high levels of polymorphism, and prevention of stable equilibrium trait combinations. To evaluate the potential for the geographic mosaic to influence predator-prey coevolution, we investigated the geographic pattern of genetically determined TTX resistance in the garter snake Thamnophis sirtalis over much of the range of its ecological interaction with toxic newts of genus Taricha. We assayed TTX resistance in over 2900 garter snakes representing 333 families from 40 populations throughout western North America. Our results provide dramatic evidence that geographic structure is an important component in coevolutionary interactions between predators and prey. Resistance levels vary substantially (over three orders of magnitude) among populations and over short distances. The spatial array of variation is consistent with two areas of intense evolutionary response by predators ("hotspots") surrounded by clines of decreasing resistance. Some general predictions of the geographic mosaic process are supported, including clinal variation in phenotypes, polymorphism in some populations, and divergent outcomes of the interaction between predator and prey. Conversely, our data provide little support for one of the major predictions, mismatched values of interacting traits. Two lines of evidence suggest selection is paramount in determining population variation in resistance. First, phylogenetic information indicates that two hotspots of TTX resistance have evolved independently. Second, in the one region that TTX levels in prey have been quantified, resistance and toxicity levels match almost perfectly over a wide phenotypic and geographic range. However, these results do not preclude the role the nonadaptive forces in generating the overall geographic mosaic of TTX resistance. Much work remains to fill in the geographic pattern of variation among prey populations and, just as importantly, to explore the variation in the ecology of the interaction that occurs within populations.     

Linking the coevolutionary and population dynamics of host–parasitoid interactions

The interplay between coevolutionary and population or community dynamics is currently the focus of much empirical and theoretical consideration. Here, we develop a simulation model to study the coevolutionary and population dynamics of a hypothetical host–parasitoid interaction. In the model, host resistance and parasitoid virulence are allowed to coevolve. We investigate how trade-offs associated with these traits modify the system's coevolutionary and population dynamics. The most important influence on these dynamics comes from the incorporation of density-dependent costs of resistance ability. We find three main outcomes. First, if the costs of resistance are high, then one or both of the players go extinct. Second, when the costs of resistance are intermediate to low, cycling population and coevolutionary dynamics are found, with slower evolutionary changes observed when the costs of virulence are also low. Third, when the costs associated with resistance and virulence are both high, the hosts trade-off resistance against fecundity and invest little in resistance. However, the parasitoids continue to invest in virulence, leading to stable host and parasitoid population sizes. These results support the hypothesis that costs associated with resistance and virulence will maintain the heritable variation in these traits found in natural populations and that the nature of these trade-offs will greatly influence the population dynamics of the interacting species. Received: December 20, 1999 / Accepted: July 17, 2000     

The ecological consequences of environmentally induced phenotypic changes

Population dynamics and species persistence are often mediated by species traits. Yet many important traits, like body size, can be set by resource availability and predation risk. Environmentally induced changes in resource levels or predation risk may thus have downstream ecological consequences. Here, we assess whether quantity and type of resources affect the phenotype, the population dynamics, and the susceptibility to predation of a mixotrophic protist through experiments and a model. We show that cell shape, but not size, changes with resource levels and type, and is linked to carrying capacity, thus affecting population dynamics. Also, these changes lead to differential susceptibility to predation, with direct consequences for predator‐prey dynamics. We describe important links between environmental changes, traits, population dynamics and ecological interactions, that underscore the need to further understand how trait‐mediated interactions may respond to environmental shifts in resource levels in an increasingly changing world.