Indirect effects shape species fitness in coevolved mutualistic networks.

Ecological interactions are one of the main forces that sustain Earth's biodiversity. A major challenge for studies of ecology and evolution is to determine how these interactions affect the fitness of species when we expand from studying isolated, pairwise interactions to include networks of interacting species1-4. In networks, chains of effects caused by a range of species have an indirect effect on other species they do not interact with directly, potentially affecting the fitness outcomes of a variety of ecological interactions (such as mutualism)5-7. Here we apply analytical techniques and numerical simulations to 186 empirical mutualistic networks and show how both direct and indirect effects alter the fitness of species coevolving in these networks. Although the fitness of species usually increased with the number of mutualistic partners, most of the fitness variation across species was driven by indirect effects. We found that these indirect effects prevent coevolving species from adapting to their mutualistic partners and to other sources of selection pressure in the environment, thereby decreasing their fitness. Such decreases are distributed in a predictable way within networks: peripheral species receive more indirect effects and experience higher reductions in fitness than central species. This topological effect was also evident when we analysed an empirical study of an invasion of pollination networks by honeybees. As honeybees became integrated as a central species within networks, they increased the contribution of indirect effects on several other species, reducing their fitness. Our study shows how and why indirect effects can govern the adaptive landscape of species-rich mutualistic assemblages.

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.

Mechanistic interactions as the origin of modularity in biological networks.

Biological networks are often modular. Explanations for this peculiarity either assume an adaptive advantage of a modular design such as higher robustness, or attribute it to neutral factors such as constraints underlying network assembly. Interestingly, most insights on the origin of modularity stem from models in which interactions are either determined by highly simplistic mechanisms, or have no mechanistic basis at all. Yet, empirical knowledge suggests that biological interactions are often mediated by complex structural or behavioural traits. Here, we investigate the origins of modularity using a model in which interactions are determined by potentially complex traits. Specifically, we model system elements-such as the species in an ecosystem-as finite-state machines (FSMs), and determine their interactions by means of communication between the corresponding FSMs. Using this model, we show that modularity probably emerges for free. We further find that the more modular an interaction network is, the less complex are the traits that mediate the interactions. Altogether, our results suggest that the conditions for modularity to evolve may be much broader than previously thought.

Language extinction triggers the loss of unique medicinal knowledge.

Over 30% of the 7,400 languages in the world will no longer be spoken by the end of the century. So far, however, our understanding of whether language extinction may result in the loss of linguistically unique knowledge remains limited. Here, we ask to what degree indigenous knowledge of medicinal plants is associated with individual languages and quantify how much indigenous knowledge may vanish as languages and plants go extinct. Focusing on three regions that have a high biocultural diversity, we show that over 75% of all 12,495 medicinal plant services are linguistically unique-i.e., only known to one language. Whereas most plant species associated with linguistically unique knowledge are not threatened, most languages that report linguistically unique knowledge are. Our finding of high uniqueness in indigenous knowledge and strong coupling with threatened languages suggests that language loss will be even more critical to the extinction of medicinal knowledge than biodiversity loss.

Network motifs involving both competition and facilitation predict biodiversity in alpine plant communities.

Biological diversity depends on multiple, cooccurring ecological interactions. However, most studies focus on one interaction type at a time, leaving community ecologists unsure of how positive and negative associations among species combine to influence biodiversity patterns. Using surveys of plant populations in alpine communities worldwide, we explore patterns of positive and negative associations among triads of species (modules) and their relationship to local biodiversity. Three modules, each incorporating both positive and negative associations, were overrepresented, thus acting as "network motifs." Furthermore, the overrepresentation of these network motifs is positively linked to species diversity globally. A theoretical model illustrates that these network motifs, based on competition between facilitated species or facilitation between inferior competitors, increase local persistence. Our findings suggest that the interplay of competition and facilitation is crucial for maintaining biodiversity.

The Resilience of Plant-Pollinator Networks.

There is growing awareness of pollinator declines worldwide. Conservation efforts have mainly focused on finding the direct causes, while paying less attention to building a systemic understanding of the fragility of these communities of pollinators. To fill this gap, we need operational measures of network resilience that integrate two different approaches in theoretical ecology. First, we should consider the range of conditions compatible with the stable coexistence of all of the species in a community. Second, we should address the rate and shape of network collapse once this safe operational space is exited. In this review, we describe this integrative approach and consider several mechanisms that may enhance the resilience of pollinator communities, chiefly rewiring the network of interactions, increasing heterogeneity, allowing variance, and enhancing coevolution. The most pressing need is to develop ways to reduce the gap between these theoretical recommendations and practical applications. This perspective shifts the emphasis from traditional approaches focusing on the equilibrium states to strategies that allow pollination networks to cope with global environmental change.

Five fundamental ways in which complex food webs may spiral out of control.

Theory suggests that increasingly long, negative feedback loops of many interacting species may destabilize food webs as complexity increases. Less attention has, however, been paid to the specific ways in which these 'delayed negative feedbacks' may affect the response of complex ecosystems to global environmental change. Here, we describe five fundamental ways in which these feedbacks might pave the way for abrupt, large-scale transitions and species losses. By combining topological and bioenergetic models, we then proceed by showing that the likelihood of such transitions increases with the number of interacting species and/or when the combined effects of stabilizing network patterns approach the minimum required for stable coexistence. Our findings thus shift the question from the classical question of what makes complex, unaltered ecosystems stable to whether the effects of, known and unknown, stabilizing food-web patterns are sufficient to prevent abrupt, large-scale transitions under global environmental change.

Rigorous Criteria for the Collapse of Nonlinear Cooperative Networks.

Many real-world complex systems, when hitting a tipping point, undergo irreversible sudden shifts that can eventually take a great toll on humanity and the natural world, such as ecosystem collapses, disease outbreaks, etc. Previous work has adopted approximations to predict the tipping points, but due to the nature of nonlinearity, this may lead to unexpected errors in predicting real-world systems. Here we obtain the rigorous bounds of the tipping points for general nonlinear cooperative networks. Our results offer two rigorous criteria that determine the collapse and survival of such a system. These two criteria are decided by the combined effect of dynamical parameters and interaction topology.

Indirect effects drive coevolution in mutualistic networks.

Ecological interactions have been acknowledged to play a key role in shaping biodiversity. Yet a major challenge for evolutionary biology is to understand the role of ecological interactions in shaping trait evolution when progressing from pairs of interacting species to multispecies interaction networks. Here we introduce an approach that integrates coevolutionary dynamics and network structure. Our results show that non-interacting species can be as important as directly interacting species in shaping coevolution within mutualistic assemblages. The contribution of indirect effects differs among types of mutualism. Indirect effects are more likely to predominate in nested, species-rich networks formed by multiple-partner mutualisms, such as pollination or seed dispersal by animals, than in small and modular networks formed by intimate mutualisms, such as those between host plants and their protective ants. Coevolutionary pathways of indirect effects favour ongoing trait evolution by promoting slow but continuous reorganization of the adaptive landscape of mutualistic partners under changing environments. Our results show that coevolution can be a major process shaping species traits throughout ecological networks. These findings expand our understanding of how evolution driven by interactions occurs through the interplay of selection pressures moving along multiple direct and indirect pathways.

Beyond pairwise mechanisms of species coexistence in complex communities.

The tremendous diversity of species in ecological communities has motivated a century of research into the mechanisms that maintain biodiversity. However, much of this work examines the coexistence of just pairs of competitors. This approach ignores those mechanisms of coexistence that emerge only in diverse competitive networks. Despite the potential for these mechanisms to create conditions under which the loss of one competitor triggers the loss of others, we lack the knowledge needed to judge their importance for coexistence in nature. Progress requires borrowing insight from the study of multitrophic interaction networks, and coupling empirical data to models of competition.

Hidden effects of habitat restoration on the persistence of pollination networks.

Past and recent studies have focused on the effects of global change drivers such as species invasions on species extinction. However, as we enter the United Nations Decade of Ecosystem Restoration the aim must switch to understanding how invasive-species management affects the persistence of the remaining species in a community. Focusing on plant-pollinator interactions, we test how species persistence is affected by restoration via the removal of invasive plant species. Restoration had a clear positive effect on plant persistence, whereas there was no difference between across treatments for pollinator persistence in the early season, but a clear effect in late season, with higher persistence in unrestored sites. Network structure affected only pollinator persistence, while centrality had a strong positive effect on both plants and pollinators. Our results suggest a hidden effect of invasive plants-although they may compete with native plant species, invasive plants may provide important resources for pollinators, at least in the short term.

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.

Cheating in Mutualisms Promotes Diversity and Complexity.

AbstractMutualisms such as those between flowering plants and their pollinators are common in nature. Yet understanding their persistence in the face of cheaters and identifying the mechanisms behind their stunning diversity provide formidable challenges for evolutionary biologists. To shed light onto these questions, we introduce an individual-based model of two coevolving species in which individuals of one species use a Boolean circuit to discriminate between cooperators and cheaters in the other species. This conveys the idea that interactions are often mediated by complex biological processes rather than the matching of a single trait, as often assumed in models of coevolution. Our results show that cheating promotes diversification and complex discrimination mechanisms at the cost of a higher risk for mutualism to collapse. This result is mediated by an inverse relationship between mutational robustness and organismal complexity.

Mycoheterotrophic plants preferentially target arbuscular mycorrhizal fungi that are highly connected to autotrophic plants.

How mycoheterotrophic plants that obtain carbon and soil nutrients from fungi are integrated in the usually mutualistic arbuscular mycorrhizal networks is unknown. Here, we compare autotrophic and mycoheterotrophic plant associations with arbuscular mycorrhizal fungi and use network analysis to investigate interaction preferences in the tripartite network. We sequenced root tips from autotrophic and mycoheterotrophic plants to assemble the combined tripartite network between autotrophic plants, mycorrhizal fungi and mycoheterotrophic plants. We compared plant-fungi interactions between mutualistic and antagonist networks, and searched for a diamond-like module defined by a mycoheterotrophic and an autotrophic plant interacting with the same pair of fungi to investigate whether pairs of fungi simultaneously linked to plant species from each interaction type were overrepresented throughout the network. Mycoheterotrophic plants as a group interacted with a subset of the fungi detected in autotrophs but are indirectly linked to all autotrophic plants, and fungi with a high overlap in autotrophic partners tended to interact with a similar set of mycoheterotrophs. Moreover, pairs of fungi sharing the same mycoheterotrophic and autotrophic plant species are overrepresented in the network. We hypothesise that the maintenance of antagonistic interactions is maximised by targeting well linked mutualistic fungi, thereby minimising the risk of carbon supply shortages.

Indigenous knowledge networks in the face of global change.

Indigenous communities rely extensively on plants for food, shelter, and medicine. It is still unknown, however, to what degree their survival is jeopardized by the loss of either plant species or knowledge about their services. To fill this gap, here we introduce indigenous knowledge networks describing the wisdom of indigenous people on plant species and the services they provide. Our results across 57 Neotropical communities show that cultural heritage is as important as plants for preserving indigenous knowledge both locally and regionally. Indeed, knowledge networks collapse as fast when plant species are driven extinct as when cultural diffusion, either within or among communities, is lost. But it is the joint loss of plant species and knowledge that erodes these networks at a much higher rate. Our findings pave the road toward integrative policies that recognize more explicitly the inseparable links between cultural and biological heritage.

The joint role of coevolutionary selection and network structure in shaping trait matching in mutualisms.

Coevolution can sculpt remarkable trait similarity between mutualistic partners. Yet, it remains unclear which network topologies and selection regimes enhance trait matching. To address this, we simulate coevolution in topologically distinct networks under a gradient of mutualistic selection strength. We describe three main insights. First, trait matching is jointly influenced by the strength of mutualistic selection and the structural properties of the network where coevolution is unfolding. Second, the strength of mutualistic selection determines the network descriptors better correlated with higher trait matching. While network modularity enhances trait matching when coevolution is weak, network connectance does so when coevolution is strong. Third, the structural properties of networks outrank those of modules or species in determining the degree of trait matching. Our findings suggest networks can both enhance or constrain trait matching, depending on the strength of mutualistic selection.

Habitat restoration in spatially explicit metacommunity models.

In a time of rapid habitat destruction threatening the existence of many species, restoration of degraded habitats plays a crucial role in hampering biodiversity decline and recovering ecosystem services. The goal of this study is to advance the understanding of the consequences of habitat restoration on metacommunities, which is of upmost importance for designing successful restoration projects. We approach habitat restoration from a theoretical perspective by analysing spatially explicit metacommunity models which have previously been essential to understanding the effects of habitat loss and fragmentation. We investigate the efficiency of various restoration strategies on metacommunities involving interactions ranging from pairwise competition, predation and mutualism to more complex three-trophic modules. Our novel approach for measuring the restoration efficiency enables direct comparison of the responses of species in different metacommunities. We show that species recovery is affected by the amount of habitat destroyed, and the restoration strategy. When habitat is restored by randomly selecting destroyed sites, species recovery becomes less efficient and more uncertain with increasing amount of previously destroyed habitat. However, when the destroyed sites are restored in clusters, minimising the effects of fragmentation, species recovery and the certainty of success are substantially improved. Furthermore, we demonstrate that the community structure and the types of interactions involved determine the most efficient restoration approach. Our findings highlight the importance of carefully planning the restoration process, especially in landscapes where a large proportion of habitat has been destroyed, and with species at the brink of extinction. Our results may be used as guidelines for designing habitat restoration projects.

Genetic correlations and ecological networks shape coevolving mutualisms.

Ecological interactions shape the evolution of multiple species traits in populations. These traits are often linked to each other through genetic correlations, affecting how each trait evolves through selection imposed by interacting partners. Here, we integrate quantitative genetics, coevolutionary theory and network science to explore how trait correlations affect the coevolution of mutualistic species not only in pairs of species but also in species-rich networks across space. We show that genetic correlations may determine the pace of coevolutionary change, affect species abundances and fuel divergence among populations of the same species. However, this trait divergence promoted by genetic correlations is partially buffered by the nested structure of species-rich mutualisms. Our study, therefore, highlights how coevolution and its ecological consequences may result from conflicting processes at different levels of organisation, ranging from genes to communities.

Foreseeing the future of mutualistic communities beyond collapse.

Changing conditions may lead to sudden shifts in the state of ecosystems when critical thresholds are passed. Some well-studied drivers of such transitions lead to predictable outcomes such as a turbid lake or a degraded landscape. Many ecosystems are, however, complex systems of many interacting species. While detecting upcoming transitions in such systems is challenging, predicting what comes after a critical transition is terra incognita altogether. The problem is that complex ecosystems may shift to many different, alternative states. Whether an impending transition has minor, positive or catastrophic effects is thus unclear. Some systems may, however, behave more predictably than others. The dynamics of mutualistic communities can be expected to be relatively simple, because delayed negative feedbacks leading to oscillatory or other complex dynamics are weak. Here, we address the question of whether this relative simplicity allows us to foresee a community's future state. As a case study, we use a model of a bipartite mutualistic network and show that a network's post-transition state is indicated by the way in which a system recovers from minor disturbances. Similar results obtained with a unipartite model of facilitation suggest that our results are of relevance to a wide range of mutualistic systems.

Partner Fidelity and Asymmetric Specialization in Ecological Networks.

AbstractSpecies are embedded in complex networks of interdependencies that may change across geographic locations. Yet most approaches to investigate the architecture of this entangled web of life have considered exclusively local communities. To quantify to what extent species interactions change at a biogeographic scale, we need to shed light on how among-community variation affects the occurrence of species interactions. Here we quantify the probability for two partners to interact wherever they co-occur (i.e., partner fidelity) by analyzing the most extensive database on species interaction networks worldwide. We found that mutualistic species show more fidelity in their interactions than antagonistic ones when there is asymmetric specialization (i.e., when specialist species interact with generalist partners). Moreover, resources (e.g., plants in plant-pollinator mutualisms or hosts in host-parasite interactions) show a higher partner fidelity in mutualistic interactions than in antagonistic interactions, which can be explained neither by sampling effort nor by phylogenetic constraints developed during their evolutionary histories. In spite of the general belief that mutualistic interactions among free-living species are labile, asymmetric specialization is very much conserved across large geographic areas.