The Role of Indirect Effects in Coevolution along the Mutualism-Antagonism Continuum

AbstractThe web of interactions in a community drives the coevolution of species. Yet it is unclear how the outcome of species interactions influences the coevolutionary dynamics of communities. This is a pressing matter, as changes to the outcome of interactions may become more common with human-induced global change. Here, we combine network and evolutionary theory to explore coevolutionary outcomes in communities harboring mutualistic and antagonistic interactions. We show that as the ratio of mutualistic to antagonistic interactions decreases, selection imposed by direct partners outweighs that imposed by indirect partners. This weakening of indirect effects results in communities composed of species with dissimilar traits and fast rates of adaptation. These changes are more pronounced when specialist consumers are the first species to engage in antagonistic interactions. Hence, a shift in the outcome of species interactions may reverberate across communities and alter the direction and speed of coevolution.

Conspicuous coloration of toxin-resistant predators implicates additional trophic interactions in a predator-prey arms race

Antagonistic coevolution between natural enemies can produce highly exaggerated traits, such as prey toxins and predator resistance. This reciprocal process of adaptation and counter-adaptation may also open doors to other evolutionary novelties not directly involved in the phenotypic interface of coevolution. We tested the hypothesis that predator-prey coevolution coincided with the evolution of conspicuous coloration on resistant predators that retain prey toxins. In western North America, common garter snakes (Thamnophis sirtalis) have evolved extreme resistance to tetrodotoxin (TTX) in the coevolutionary arms race with their deadly prey, Pacific newts (Taricha spp.). TTX-resistant snakes can retain large amounts of ingested TTX, which could serve as a deterrent against the snakes' own predators if TTX toxicity and resistance are coupled with a conspicuous warning signal. We evaluated whether arms race escalation covaries with bright red coloration in snake populations across the geographic mosaic of coevolution. Snake colour variation departs from the neutral expectations of population genetic structure and covaries with escalating clines of newt TTX and snake resistance at two coevolutionary hotspots. In the Pacific Northwest, bright red coloration fits an expected pattern of an aposematic warning to avian predators: TTX-resistant snakes that consume highly toxic newts also have relatively large, reddish-orange dorsal blotches. Snake coloration also seems to have evolved with the arms race in California, but overall patterns are less intuitively consistent with aposematism. These results suggest that interactions with additional trophic levels can generate novel traits as a cascading consequence of arms race coevolution across the geographic mosaic.

Blue and green food webs respond differently to elevation and land use

While aquatic (blue) and terrestrial (green) food webs are parts of the same landscape, it remains unclear whether they respond similarly to shared environmental gradients. We use empirical community data from hundreds of sites across Switzerland and a synthesis of interaction information in the form of a metaweb to show that inferred blue and green food webs have different structural and ecological properties along elevation and among various land-use types. Specifically, in green food webs, their modular structure increases with elevation and the overlap of consumers' diet niche decreases, while the opposite pattern is observed in blue food webs. Such differences between blue and green food webs are particularly pronounced in farmland-dominated habitats, indicating that anthropogenic habitat modification modulates the climatic effects on food webs but differently in blue versus green systems. These findings indicate general structural differences between blue and green food webs and suggest their potential divergent future alterations through land-use or climatic changes.

Effects of habitat destruction on coevolving metacommunities

Habitat destruction is a growing threat to biodiversity and ecosystem services. The ecological consequences of habitat loss and fragmentation involve reductions in species abundance and even the extinction of species and their interactions. However, we do not yet understand how habitat loss alters the coevolutionary trajectories of the remaining species or how coevolution, in turn, affects their response to habitat loss. To investigate this, we develop a spatially explicit model which couples metacommunity and coevolutionary dynamics. We show that, by changing the size, composition and structure of local networks, habitat destruction increases the diversity of coevolutionary trajectories of mutualists across the landscape. Conversely, in antagonistic communities, some species increase while others reduce their spatial trait heterogeneity. Furthermore, we show that while coevolution dampens the negative effects of habitat destruction in mutualistic networks, its effects on the persistence of antagonistic communities tend to be smaller and less predictable.

A network perspective for sustainable agroecosystems

Nature-based management aims to improve sustainable agroecosystem production, but its efficacy has been variable. We argue that nature-based agroecosystem management could be significantly improved by explicitly considering and manipulating the underlying networks of species interactions. A network perspective can link species interactions to ecosystem functioning and stability, identify influential species and interactions, and suggest optimal management approaches. Recent advances in predicting the network roles of species from their functional traits could allow direct manipulation of network architecture through additions or removals of species with targeted traits. Combined with improved understanding of the structure and dynamics of networks across spatial and temporal scales and interaction types, including social-ecological, applying these tools to nature-based management can contribute to sustainable agroecosystems.

Ehrlich and Raven escape and radiate coevolution hypothesis at different levels of organization: Past and future perspectives

The classic paper by Ehrlich and Raven on coevolution will soon be 60 years old. Although they were not the first to develop the idea of coevolution, their thought-provoking paper certainly popularized this idea and inspired several generations of scientists interested in coevolution. Here, we describe some of their main contributions, quantitatively measure the impact of their seminal paper on different fields of research, and discuss how ideas related to their original paper might push the study of coevolution forward. To guide our discussion, we explore their original hypothesis into three research fields that are associated with distinct scales/levels of organization: (1) the genetic mechanisms underlying coevolutionary interactions; (2) the potential association between coevolutionary diversification and the organization of ecological networks; and (3) the micro- and macroevolutionary mechanisms and expected patterns under their hypothesis. By doing so, we discuss potentially overlooked aspects and future directions for the study of coevolutionary dynamics and diversification.

Sex-biased parasitism, host mass and mutualistic bat flies: an antagonistic individual-based network of bat-bat fly interactions

Individual-based networks provide the building blocks for community-level networks. However, network studies of bats and their parasites have focused only on the species level. Intrapopulation variation may allow certain host individuals to play important roles in the dynamics of the parasites. Therefore, we evaluated how the variation in host sex, body size, ectoparasite abundance and co-occurrence configure individual-based networks of the lesser bulldog bat Noctilio albiventris and bat flies. We expected bat individuals with greater body mass and forearms acting as the core in the network. We also expected males to play a more important role in the network. We sampled a network of N. albiventris bat individuals and their bat flies to describe the structure of an antagonistic individual-based network. We aimed to identify the most relevant bat individuals in the network, focusing on the implications inherent to each of the following approaches: (i) core-periphery organization; (ii) modularity; (iii) species level metrics; and (iv) the main ecological driver of bat individual roles in the network, using niche-based predictors (body mass, forearm and sex). We showed that a network of N. albiventris individuals and their bat flies had low modularity containing a persistent nucleus of individuals and bat flies with well-established interactions. Male individuals with greater body mass played an important role in the network, while for females neither mass nor forearm length were important predictors of their role in the network. Finally, individuals with a high abundance of Paradyschiria parvula played a core role. These results provide an alternative perspective to understand the patterns and mechanisms of interspecific interactions between parasites on the host, as well as sex-biased parasitism.

Consumers' active choice behaviour promotes coevolutionary units in antagonistic networks

Individual behaviour and local context can influence the evolution of ecological interactions and how they structure into networks. In trophic interactions, consumers can increase their fitness by actively choosing resources that they are more likely to explore successfully. Mathematical modelling is often employed in theoretical studies to understand the coevolutionary dynamics between consumers and resources. However, they often disregard the individual consumer behaviour since the complexity of these systems usually requires simplifying assumptions about interaction details. Using an individual-based model, we model a community of several species that interact antagonistically. Each individual has a trait (attack or defence) that is explicitly modelled and the probability of the interaction to occur successfully increases with increased trait-matching. In addition, consumers can actively choose resources that guarantee greater fitness. We show that active consumer choice can generate coevolutionary units over time. It means that the traits of both consumers and resources converge into multiple groups with similar traits and the species interactions stay restricted to these groups over time. We also observed that network structure is more dependent on the parameter that delimits active consumer choice than on the intensity of selective pressure. Thus, our results support the idea that consumer active choice behaviour plays an important role in the ecological and evolutionary processes that structure interacting communities.

Phenotypic and functional variation in venom and venom resistance of two sympatric rattlesnakes and their prey

Predator-prey interactions often lead to the coevolution of adaptations associated with avoiding predation and, for predators, overcoming those defences. Antagonistic coevolutionary relationships are often not simple interactions between a single predator and prey but rather a complex web of interactions between multiple coexisting species. Coevolution between venomous rattlesnakes and small mammals has led to physiological venom resistance in several mammalian taxa. In general, viperid venoms contain large quantities of snake venom metalloproteinase toxins (SVMPs), which are inactivated by SVMP inhibitors expressed in resistant mammals. We explored variation in venom chemistry, SVMP expression, and SVMP resistance across four co-distributed species (California Ground Squirrels, Bryant's Woodrats, Southern Pacific Rattlesnakes, and Red Diamond Rattlesnakes) collected from four different populations in Southern California. Our aim was to understand phenotypic and functional variation in venom and venom resistance in order to compare coevolutionary dynamics of a system involving two sympatric predator-prey pairs to past studies that have focused on single pairs. Proteomic analysis of venoms indicated that these rattlesnakes express different phenotypes when in sympatry, with Red Diamonds expressing more typical viperid venom (with a diversity of SVMPs) and Southern Pacifics expressing a more atypical venom with a broader range of non-enzymatic toxins. We also found that although blood sera from both mammals were generally able to inhibit SVMPs from both rattlesnake species, inhibition depended strongly on the snake population, with snakes from one geographic site expressing SVMPs to which few mammals were resistant. Additionally, we found that Red Diamond venom, rather than woodrat resistance, was locally adapted. Our findings highlight the complexity of coevolutionary relationships between multiple predators and prey that exhibit similar offensive and defensive strategies in sympatry.

Next-generation cophylogeny: unravelling eco-evolutionary processes

A fundamental question in evolutionary biology is how microevolutionary processes translate into species diversification. Cophylogeny provides an appropriate framework to address this for symbiotic associations, but historically has been primarily limited to unveiling patterns. We argue that it is essential to integrate advances from ecology and evolutionary biology into cophylogeny, to gain greater mechanistic insights and transform cophylogeny into a platform to advance understanding of interspecific interactions and diversification more widely. We discuss key directions, such as incorporating trait reconstruction and considering multiple scales of network organization, and highlight recent developments for implementation. A new quantitative framework is proposed to allow integration of relevant information, such as quantitative traits and assessment of the contribution of individual mechanisms to cophylogenetic patterns.

Habitat generalist species constrain the diversity of mimicry rings in heterogeneous habitats

How evolution creates and maintains trait patterns in species-rich communities is still an unsolved topic in evolutionary ecology. One classical example of community-level pattern is the unexpected coexistence of different mimicry rings, each of which is a group of mimetic species with the same warning signal. The coexistence of different mimicry rings in a community seems paradoxical because selection among unpalatable species should favor convergence to a single warning pattern. We combined mathematical modeling based on network theory and numerical simulations to explore how different types of selection, such as mimetic and environmental selections, and habitat use by mimetic species influence the formation of coexisting rings. We show that when habitat and mimicry are strong sources of selection, the formation of multiple rings takes longer due to conflicting selective pressures. Moreover, habitat generalist species decrease the distinctiveness of different mimicry rings’ patterns and a few habitat generalist species can generate a “small-world effect”, preventing the formation of multiple mimicry rings. These results may explain why the coexistence of mimicry rings is more common in groups of animals that tend towards habitat specialism, such as butterflies.

Coevolutionary patterns caused by prey selection

Many theoretical models have been formulated to better understand the coevolutionary patterns that emerge from antagonistic interactions. These models usually assume that the attacks by the exploiters are random, so the effect of victim selection by exploiters on coevolutionary patterns remains unexplored. Here we analytically studied the payoff for predators and prey under coevolution assuming that every individual predator can attack only a small number of prey any given time, considering two scenarios: (i) predation occurs at random; (ii) predators select prey according to phenotype matching. We also develop an individual based model to verify the robustness of our analytical prediction. We show that both scenarios result in well known similar coevolutionary patterns if population sizes are sufficiently high: symmetrical coevolutionary branching and symmetrical coevolutionary cycling (Red Queen dynamics). However, for small population sizes, prey selection can cause unexpected coevolutionary patterns. One is the breaking of symmetry of the coevolutionary pattern, where the phenotypes evolve towards one of two evolutionarily stable patterns. As population size increases, the phenotypes oscillate between these two values in a novel form of Red Queen dynamics, the episodic reversal between the two stable patterns. Thus, prey selection causes prey phenotypes to evolve towards more extreme values, which reduces the fitness of both predators and prey, increasing the likelihood of extinction.

The Role of Evolution in Shaping Ecological Networks

The structure of ecological networks reflects the evolutionary history of their biotic components, and their dynamics are strongly driven by ecoevolutionary processes. Here, we present an appraisal of recent relevant research, in which the pervasive role of evolution within ecological networks is manifest. Although evolutionary processes are most evident at macroevolutionary scales, they are also important drivers of local network structure and dynamics. We propose components of a blueprint for further research, emphasising process-based models, experimental evolution, and phenotypic variation, across a range of distinct spatial and temporal scales. Evolutionary dimensions are required to advance our understanding of foundational properties of community assembly and to enhance our capability of predicting how networks will respond to impending changes.

Tri-trophic interactions: bridging species, communities and ecosystems

A vast body of research demonstrates that many ecological and evolutionary processes can only be understood from a tri-trophic viewpoint, that is, one that moves beyond the pairwise interactions of neighbouring trophic levels to consider the emergent features of interactions among multiple trophic levels. Despite its unifying potential, tri-trophic research has been fragmented, following two distinct paths. One has focused on the population biology and evolutionary ecology of simple food chains of interacting species. The other has focused on bottom-up and top-down controls over the distribution of biomass across trophic levels and other ecosystem-level variables. Here, we propose pathways to bridge these two long-standing perspectives. We argue that an expanded theory of tri-trophic interactions (TTIs) can unify our understanding of biological processes across scales and levels of organisation, ranging from species evolution and pairwise interactions to community structure and ecosystem function. To do so requires addressing how community structure and ecosystem function arise as emergent properties of component TTIs, and, in turn, how species traits and TTIs are shaped by the ecosystem processes and the abiotic environment in which they are embedded. We conclude that novel insights will come from applying tri-trophic theory systematically across all levels of biological organisation.

Revealing biases in the sampling of ecological interaction networks

The structure of ecological interactions is commonly understood through analyses of interaction networks. However, these analyses may be sensitive to sampling biases with respect to both the interactors (the nodes of the network) and interactions (the links between nodes), because the detectability of species and their interactions is highly heterogeneous. These ecological and statistical issues directly affect ecologists’ abilities to accurately construct ecological networks. However, statistical biases introduced by sampling are difficult to quantify in the absence of full knowledge of the underlying ecological network’s structure. To explore properties of large-scale ecological networks, we developed the software EcoNetGen, which constructs and samples networks with predetermined topologies. These networks may represent a wide variety of communities that vary in size and types of ecological interactions. We sampled these networks with different mathematical sampling designs that correspond to methods used in field observations. The observed networks generated by each sampling process were then analyzed with respect to the number of components, size of components and other network metrics. We show that the sampling effort needed to estimate underlying network properties depends strongly both on the sampling design and on the underlying network topology. In particular, networks with random or scale-free modules require more complete sampling to reveal their structure, compared to networks whose modules are nested or bipartite. Overall, modules with nested structure were the easiest to detect, regardless of the sampling design used. Sampling a network starting with any species that had a high degree (e.g., abundant generalist species) was consistently found to be the most accurate strategy to estimate network structure. Because high-degree species tend to be generalists, abundant in natural communities relative to specialists, and connected to each other, sampling by degree may therefore be common but unintentional in empirical sampling of networks. Conversely, sampling according to module (representing different interaction types or taxa) results in a rather complete view of certain modules, but fails to provide a complete picture of the underlying network. To reduce biases introduced by sampling methods, we recommend that these findings be incorporated into field design considerations for projects aiming to characterize large species interaction networks.

Recent advances in understanding the role of secondary metabolites in species-rich multitrophic networks

Understanding coexistence in species-rich communities remains a primary challenge of ecology. Interactions mediated through multitrophic networks are thought to play an important role in sustaining species coexistence in the face of competition for resources. The identity of trophic partners and the intensity with which they interact are often mediated by diverse secondary metabolites. Recent innovations in organic-molecule bioinformatics and multivariate statistical analysis are rapidly advancing our understanding of metabolites and the multitrophic interactions they mediate. Here, I examine recent advances in the study of chemical ecology in species-rich multitrophic communities, with an emphasis on plant-herbivore networks, and explore the potential for chemically mediated interactions to shape community composition and sustain species diversity in ecological communities.

Eco-evolutionary feedbacks promote fluctuating selection and long-term stability of antagonistic networks

Studies have shown the potential for rapid adaptation in coevolving populations and that the structure of species interaction networks can modulate the vulnerability of ecological systems to perturbations. Although the feedback loop between population dynamics and coevolution of traits is crucial for understanding long-term stability in ecological assemblages, modelling eco-evolutionary dynamics in species-rich assemblages is still a challenge. We explore how eco-evolutionary feedbacks influence trait evolution and species abundances in 23 empirical antagonistic networks. We show that, if selection due to antagonistic interactions is stronger than other selective pressures, eco-evolutionary feedbacks lead to higher mean species abundances and lower temporal variation in abundances. By contrast, strong selection of antagonistic interactions leads to higher temporal variation of traits and on interaction strengths. Our results present a theoretical link between the study of the species persistence and coevolution in networks of interacting species, pointing out the ways by which coevolution may decrease the vulnerability of species within antagonistic networks to demographic fluctuation.

The geographic mosaic of coevolution in mutualistic networks

Ecological interactions shape adaptations through coevolution not only between pairs of species but also through entire multispecies assemblages. Local coevolution can then be further altered through spatial processes that have been formally partitioned in the geographic mosaic theory of coevolution. A major current challenge is to understand the spatial patterns of coadaptation that emerge across ecosystems through the interplay between gene flow and selection in networks of interacting species. Here, we combine a coevolutionary model, network theory, and empirical information on species interactions to investigate how gene flow and geographical variation in selection affect trait patterns in mutualistic networks. We show that gene flow has the surprising effect of favoring trait matching, especially among generalist species in species-rich networks typical of pollination and seed dispersal interactions. Using an analytical approximation of our model, we demonstrate that gene flow promotes trait matching by making the adaptive landscapes of different species more similar to each other. We use this result to show that the progressive loss of gene flow associated with habitat fragmentation may undermine coadaptation in mutualisms. Our results therefore provide predictions of how spatial processes shape the evolution of species-rich interactions and how the widespread fragmentation of natural landscapes may modify the coevolutionary process.

Adaptive Networks for Restoration Ecology

The urgent need to restore biodiversity and ecosystem functioning challenges ecology as a predictive science. Restoration ecology would benefit from evolutionary principles embedded within a framework that combines adaptive network models and the phylogenetic structure of ecological interactions. Adaptive network models capture feedbacks between trait evolution, species abundances, and interactions to explain resilience and functional diversity within communities. Phylogenetically-structured network data, increasingly available via next-generation sequencing, inform constraints affecting interaction rewiring. Combined, these approaches can predict eco-evolutionary changes triggered by community manipulation practices, such as translocations and eradications of invasive species. We discuss theoretical and methodological opportunities to bridge network models and data from restoration projects and propose how this can be applied to the functional restoration of ecological interactions.

Non-adaptive origins of evolutionary innovations increase network complexity in interacting digital organisms

The origin of evolutionary innovations is a central problem in evolutionary biology. To what extent such innovations have adaptive or non-adaptive origins is hard to assess in real organisms. This limitation, however, can be overcome using digital organisms, i.e. self-replicating computer programs that mutate, evolve and coevolve within a user-defined computational environment. Here, we quantify the role of the non-adaptive origins of host resistance traits in determining the evolution of ecological interactions among host and parasite digital organisms. We find that host resistance traits arising spontaneously as exaptations increase the complexity of antagonistic host-parasite networks. Specifically, they lead to higher host phenotypic diversification, a larger number of ecological interactions and higher heterogeneity in interaction strengths. Given the potential of network architecture to affect network dynamics, such exaptations may increase the persistence of entire communities. Our in silico approach, therefore, may complement current theoretical advances aimed at disentangling the ecological and evolutionary mechanisms shaping species interaction networks.This article is part of the themed issue 'Process and pattern in innovations from cells to societies'.

Ecological Complexity in Plant Virus Host Range Evolution

The host range of a plant virus is the number of species in which it can reproduce. Most studies of plant virus host range evolution have focused on the genetics of host-pathogen interactions. However, the distribution and abundance of plant viruses and their hosts do not always overlap, and these spatial and temporal discontinuities in plant virus-host interactions can result in various ecological processes that shape host range evolution. Recent work shows that the distributions of pathogenic and resistant genotypes, vectors, and other resources supporting transmission vary widely in the environment, producing both expected and unanticipated patterns. The distributions of all of these factors are influenced further by competitive effects, natural enemies, anthropogenic disturbance, the abiotic environment, and herbivory to mention some. We suggest the need for further development of approaches that (i) explicitly consider resource use and the abiotic and biotic factors that affect the strategies by which viruses exploit resources; and (ii) are sensitive across scales. Host range and habitat specificity will largely determine which phyla are most likely to be new hosts, but predicting which host and when it is likely to be infected is enormously challenging because it is unclear how environmental heterogeneity affects the interactions of viruses and hosts.