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.

Mutualistic coevolution and community diversity favour persistence in metacommunities under environmental changes.

Linking local to regional ecological and evolutionary processes is key to understand the response of Earth's biodiversity to environmental changes. Here we integrate evolution and mutualistic coevolution in a model of metacommunity dynamics and use numerical simulations to understand how coevolution can shape species distribution and persistence in landscapes varying in space and time. Our simulations show that coevolution and species richness can synergistically shape distribution patterns by increasing colonization and reducing extinction of populations in metacommunities. Although conflicting selective pressures emerging from mutualisms may increase mismatches with the local environment and the rate of local extinctions, coevolution increases trait matching among mutualists at the landscape scale, counteracting local maladaptation and favouring colonization and range expansions. Our results show that by facilitating colonization, coevolution can also buffer the effects of environmental changes, preventing species extinctions and the collapse of metacommunities. Our findings reveal the mechanisms whereby coevolution can favour persistence under environmental changes and highlight that these positive effects are greater in more diverse systems that retain landscape connectivity.

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.

Annual precipitation predicts the phylogenetic signal in bat-fruit interaction networks across the Neotropics.

Closely related species tend to be more similar than randomly selected species from the same phylogenetic tree. This pattern, known as a phylogenetic signal, has been extensively studied for intrinsic (e.g. morphology), as well as extrinsic (e.g. climatic preferences), properties but less so for ecological interactions. Phylogenetic signals of species interactions (i.e. resource use) can vary across time and space, but the causes behind such variations across broader spatial extents remain elusive. Here, we evaluated how current and historical climates influence phylogenetic signals of bat-fruit interaction networks across the Neotropics. We performed a model selection relating the phylogenetic signals of each trophic level (bats and plants) with a set of current and historical climatic factors deemed ecologically important in shaping biotic interactions. Bat and plant phylogenetic signals in bat-fruit interaction networks varied little with climatic factors, although bat phylogenetic signals positively covaried with annual precipitation. These findings indicated that water availability could increase resource availability, favouring higher niche partitioning of trophic resources among bat species and hence bat phylogenetic signals across bat-fruit interaction networks. Overall, our study advances our understanding of the spatial dynamics of bat-fruit interactions by highlighting the association of current climatic factors with phylogenetic patterns of biotic interactions.

Temporal organization among pollination systems in a tropical seasonal forest.

Temporal constancy of pollination systems is essential for the maintenance of pollinators through time. Community-level assessment of flowering phenology allows understanding variations across seasons and years and the risks of decoupling flowering and pollinators' activity. We evaluated flowering patterns and temporal diversity of pollination systems in a tropical seasonal forest. We asked whether the temporal organization of flowering times differs among pollination systems; if there is a constancy of pollination systems through the year, since climate and phylogenies constraint flowering time; if there is a prevalent flowering pattern by pollination system, and if the temporal organization of pollination systems by modularity analyses is coherent with grouping by pre-defined seasons. We characterized 10 pollination systems, examined flowering strategies, climate cues and phylogenetic constraints. Pollination by large-to-medium bees dominated (49.2%), followed by diverse insects (22.1%) and flies (14.7%). The remaining systems represented 14% of species. Flowering occurred year-round for most pollination systems, predominating the seasonal flowering strategy. Flowering patterns ranged from aggregated to nested, and random. Climate affected the flowering of most pollination systems, but there was no phylogeny constraint. Modularity grouped pollination systems differently than rainfall seasonality. Contrasting the expectations of reduced temporal constancy, most systems were present year-round, facilitating the exploitation of floral resources by pollinators. Diversity of pollination systems remained constant despite climate seasonality, indicating that several factors influence the optimum flowering time for pollination in seasonally dry vegetations. Global warming may disrupt phenological patterns and the temporal organization of plant communities, a matter for future studies.

Macroevolutionary stability predicts interaction patterns of species in seed dispersal networks.

Assessing deep-time mechanisms affecting the assembly of ecological networks is key to understanding biodiversity changes on broader time scales. We combined analyses of diversification rates with interaction network descriptors from 468 bird species belonging to 29 seed dispersal networks to show that bird species that contribute most to the network structure of plant-frugivore interactions belong to lineages that show higher macroevolutionary stability. This association is stronger in warmer, wetter, less seasonal environments. We infer that the macroevolutionary sorting mechanism acts through the regional pool of species by sorting species on the basis of the available relative differences in diversification rates, rather than absolute rates. Our results illustrate how the interplay between interaction patterns and diversification dynamics may shape the organization and long-term dynamics of ecological networks.

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.

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.

Diverse interactions and ecosystem engineering can stabilize community assembly.

The complexity of an ecological community can be distilled into a network, where diverse interactions connect species in a web of dependencies. Species interact directly with each other and indirectly through environmental effects, however to our knowledge the role of these ecosystem engineers has not been considered in ecological network models. Here we explore the dynamics of ecosystem assembly, where species colonization and extinction depends on the constraints imposed by trophic, service, and engineering dependencies. We show that our assembly model reproduces many key features of ecological systems, such as the role of generalists during assembly, realistic maximum trophic levels, and increased nestedness with mutualistic interactions. We find that ecosystem engineering has large and nonlinear effects on extinction rates. While small numbers of engineers reduce stability by increasing primary extinctions, larger numbers of engineers increase stability by reducing primary extinctions and extinction cascade magnitude. Our results suggest that ecological engineers may enhance community diversity while increasing persistence by facilitating colonization and limiting competitive exclusion.

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 indirect paths to cascading effects of extinctions in mutualistic networks.

Biodiversity loss is a hallmark of our times, but predicting its consequences is challenging. Ecological interactions form complex networks with multiple direct and indirect paths through which the impacts of an extinction may propagate. Here we show that accounting for these multiple paths connecting species is necessary to predict how extinctions affect the integrity of ecological networks. Using an approach initially developed for the study of information flow, we estimate indirect effects in plant-pollinator networks and find that even those species with several direct interactions may have much of their influence over others through long indirect paths. Next, we perform extinction simulations in those networks and show that although traditional connectivity metrics fail in the prediction of coextinction patterns, accounting for indirect interaction paths allows predicting species' vulnerability to the cascading effects of an extinction event. Embracing the structural complexity of ecological systems contributes towards a more predictive ecology, which is of paramount importance amid the current biodiversity crisis.

Associated evolution of fruit size, fruit colour and spines in Neotropical palms.

Understanding how ecological interactions have shaped the evolutionary dynamics of species traits remains a challenge in evolutionary ecology. Combining trait evolution models and phylogenies, we analysed the evolution of characters associated with seed dispersal (fruit size and colour) and herbivory (spines) in Neotropical palms to infer the role of these opposing animal-plant interactions in driving evolutionary patterns. We found that the evolution of fruit colour and fruit size was associated in Neotropical palms, supporting the adaptive interpretation of seed-dispersal syndromes and highlighting the role of frugivores in shaping plant evolution. Furthermore, we revealed a positive association between fruit size and the presence of spines on palm leaves, bracteas and stems. We hypothesize that interactions between palms and large-bodied frugivores/herbivores may explain the evolutionary relationship between fruit size and spines. Large-bodied frugivores, such as extinct megafauna, besides consuming the fruits and dispersing large seeds, may also have consumed the leaves or damaged the plants, thus simultaneously favouring the evolution of large fruits and defensive structures. Our findings show how current trait patterns can be understood as the result of the interplay between antagonistic and mutualistic interactions that have happened throughout the evolutionary history of a clade.

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.

Low-load pathogen spillover predicts shifts in skin microbiome and survival of a terrestrial-breeding amphibian.

Wildlife disease dynamics are strongly influenced by the structure of host communities and their symbiotic microbiota. Conspicuous amphibian declines associated with the waterborne fungal pathogen Batrachochytrium dendrobatidis (Bd) have been observed in aquatic-breeding frogs globally. However, less attention has been given to cryptic terrestrial-breeding amphibians that have also been declining in tropical regions. By experimentally manipulating multiple tropical amphibian assemblages harbouring natural microbial communities, we tested whether Bd spillover from naturally infected aquatic-breeding frogs could lead to Bd amplification and mortality in our focal terrestrial-breeding host: the pumpkin toadlet Brachycephalus pitanga. We also tested whether the strength of spillover could vary depending on skin bacterial transmission within host assemblages. Terrestrial-breeding toadlets acquired lethal spillover infections from neighbouring aquatic hosts and experienced dramatic but generally non-protective shifts in skin bacterial composition primarily attributable to their Bd infections. By contrast, aquatic-breeding amphibians maintained mild Bd infections and higher survival, with shifts in bacterial microbiomes that were unrelated to Bd infections. Our results indicate that Bd spillover from even mildly infected aquatic-breeding hosts may lead to dysbiosis and mortality in terrestrial-breeding species, underscoring the need to further investigate recent population declines of terrestrial-breeding amphibians in the tropics.

Coevolution Creates Complex Mosaics across Large Landscapes.

The spatial distribution of populations can influence the evolutionary outcome of species interactions. The variation in direction and strength of selection across local communities creates geographic selection mosaics that, when combined with gene flow and genomic processes such as genome duplication or hybridization, can fuel ongoing coevolution. A fundamental problem to solve is how coevolution proceeds when many populations that vary in their ecological outcomes are connected across large landscapes. Here we use a lattice model to explore this problem. Our results show that the complex interrelationships among the elements of the geographic mosaic of coevolution can lead to the formation of clusters of populations with similar phenotypes that are larger than expected by local selection. Our results indicate that neither the spatial distribution of phenotypes nor the spatial differences in magnitude and direction of selection alone dictate coevolutionary dynamics: the geographic mosaic of coevolution affects formation of phenotypic clusters, which in turn affect the spatial and temporal dynamics of coevolution. Because the formation of large phenotypic clusters depends on gene flow, we predict that current habitat fragmentation will change the outcomes of geographic mosaics, coupling spatial patterns in selection and phenotypes.

Extreme diversification of floral volatiles within and among species of Lithophragma (Saxifragaceae).

A major challenge in evolutionary biology is to understand how complex traits of multiple functions have diversified and codiversified across interacting lineages and geographic ranges. We evaluate intra- and interspecific variation in floral scent, which is a complex trait of documented importance for mutualistic and antagonistic interactions between plants, pollinators, and herbivores. We performed a large-scale, phylogenetically structured study of an entire plant genus (Lithophragma, Saxifragaceae), of which several species are coevolving with specialized pollinating floral parasites of the moth genus Greya (Prodoxidae). We sampled 94 Lithophragma populations distributed across all 12 recognized Lithophragma species and subspecies, and four populations of related saxifragaceous species. Our results reveal an unusually high diversity of floral volatiles among populations, species, and clades within the genus. Moreover, we found unexpectedly major changes at each of these levels in the biosynthetic pathways used by local populations in their floral scents. Finally, we detected significant, but variable, genus- and species-level patterns of ecological convergence in the floral scent signal, including an impact of the presence and absence of two pollinating Greya moth species. We propose that one potential key to understanding floral scent variation in this hypervariable genus is its geographically diverse interactions with the obligate specialized Greya moths and, in some species and sites, more generalized copollinators.

Interaction strength promotes robustness against cascading effects in mutualistic networks.

Perturbations, such as fluctuations in abundance, can ripple across species assemblages through ecological interactions. Furthermore, the way in which ecological interactions are organized into a network and the interaction strengths connecting species may be important for cascading effects. Previous work revealed that network structure determines how cascading effects spread across species assemblages. A next step is to understand how interaction strengths influence cascading effects. Here, we assume that perturbations have negative effects, and we evaluate whether interaction strength affects network robustness to cascading effects in mutualistic interactions, and examine the role of network structure in mediating perturbation cascades when interaction strength is incorporated. We combine empirical data on 18 mutualistic networks, two simulations scenarios, and network theory, to investigate how network structure affects perturbation spreading time, a proxy of network robustness to cascading effects. Simulations in which we included interaction strength presented higher mean spreading time, indicating that interaction strength increases network robustness. Richness, modularity, and nestedness had a strong, positive effect, on mean perturbation spreading time regardless of the interaction strengths. We found that network structure and the distribution of interaction strengths affected communities' robustness to perturbation spreading. Our results contribute to the discussion on the danger that ecosystems face when species, and interactions alike, become extinct.

Analysing ecological networks of species interactions.

Network approaches to ecological questions have been increasingly used, particularly in recent decades. The abstraction of ecological systems - such as communities - through networks of interactions between their components indeed provides a way to summarize this information with single objects. The methodological framework derived from graph theory also provides numerous approaches and measures to analyze these objects and can offer new perspectives on established ecological theories as well as tools to address new challenges. However, prior to using these methods to test ecological hypotheses, it is necessary that we understand, adapt, and use them in ways that both allow us to deliver their full potential and account for their limitations. Here, we attempt to increase the accessibility of network approaches by providing a review of the tools that have been developed so far, with - what we believe to be - their appropriate uses and potential limitations. This is not an exhaustive review of all methods and metrics, but rather, an overview of tools that are robust, informative, and ecologically sound. After providing a brief presentation of species interaction networks and how to build them in order to summarize ecological information of different types, we then classify methods and metrics by the types of ecological questions that they can be used to answer from global to local scales, including methods for hypothesis testing and future perspectives. Specifically, we show how the organization of species interactions in a community yields different network structures (e.g., more or less dense, modular or nested), how different measures can be used to describe and quantify these emerging structures, and how to compare communities based on these differences in structures. Within networks, we illustrate metrics that can be used to describe and compare the functional and dynamic roles of species based on their position in the network and the organization of their interactions as well as associated new methods to test the significance of these results. Lastly, we describe potential fruitful avenues for new methodological developments to address novel ecological questions.

Integrating Computational Methods to Investigate the Macroecology of Microbiomes.

Studies in microbiology have long been mostly restricted to small spatial scales. However, recent technological advances, such as new sequencing methodologies, have ushered an era of large-scale sequencing of environmental DNA data from multiple biomes worldwide. These global datasets can now be used to explore long standing questions of microbial ecology. New methodological approaches and concepts are being developed to study such large-scale patterns in microbial communities, resulting in new perspectives that represent a significant advances for both microbiology and macroecology. Here, we identify and review important conceptual, computational, and methodological challenges and opportunities in microbial macroecology. Specifically, we discuss the challenges of handling and analyzing large amounts of microbiome data to understand taxa distribution and co-occurrence patterns. We also discuss approaches for modeling microbial communities based on environmental data, including information on biological interactions to make full use of available Big Data. Finally, we summarize the methods presented in a general approach aimed to aid microbiologists in addressing fundamental questions in microbial macroecology, including classical propositions (such as "everything is everywhere, but the environment selects") as well as applied ecological problems, such as those posed by human induced global environmental changes.

Unifying host-associated diversification processes using butterfly-plant networks.

Explaining the exceptional diversity of herbivorous insects is an old problem in evolutionary ecology. Here we focus on the two prominent hypothesised drivers of their diversification, radiations after major host switch or variability in host use due to continuous probing of new hosts. Unfortunately, current methods cannot distinguish between these hypotheses, causing controversy in the literature. Here we present an approach combining network and phylogenetic analyses, which directly quantifies support for these opposing hypotheses. After demonstrating that each hypothesis produces divergent network structures, we then investigate the contribution of each to diversification in two butterfly families: Pieridae and Nymphalidae. Overall, we find that variability in host use is essential for butterfly diversification, while radiations following colonisation of a new host are rare but can produce high diversity. Beyond providing an important reconciliation of alternative hypotheses for butterfly diversification, our approach has potential to test many other hypotheses in evolutionary biology.