Multiple interactions networks: towards more realistic descriptions of the web of life

Adaptive rewiring shapes structure and stability in a three-guild herbivore-plant-pollinator network

Animal species, encompassing both pollinators and herbivores, exhibit a preference for plants based on optimal foraging theory. Understanding the intricacies of these adaptive plant-animal interactions in the context of community assembly poses a main challenge in ecology. This study delves into the impact of adaptive interaction rewiring between species belonging to different guilds on the structure and stability of a 3-guild ecological network, incorporating both mutualistic and antagonistic interactions. Our findings reveal that adaptive rewiring results in sub-networks becoming more nested and compartmentalized. Furthermore, the rewiring of interactions uncovers a positive correlation between a plant's generalism concerning both pollinators and herbivores. Additionally, there is a positive correlation between a plant's degree centrality and its energy budget. Although network stability does not exhibit a clear relationship with non-random structures, it is primarily influenced by the balance of multiple interaction strengths. In summary, our results underscore the significance of adaptive interaction rewiring in shaping the structure of 3-guild networks. They emphasize the importance of considering the balance of multiple interactions for the stability of adaptive networks, providing valuable insights into the complex dynamics of ecological communities.

The structure and robustness of ecological networks with two interaction types

Until recently, most ecological network analyses investigating the effects of species' declines and extinctions have focused on a single type of interaction (e.g. feeding). In nature, however, diverse interactions co-occur, each of them forming a layer of a 'multilayer' network. Data including information on multiple interaction types has recently started to emerge, giving us the opportunity to have a first glance at possible commonalities in the structure of these networks. We studied the structural features of 44 tripartite ecological networks from the literature, each composed of two layers of interactions (e.g. herbivory and pollination), and investigated their robustness to species losses. Considering two interactions simultaneously, we found that the robustness of the whole community is a combination of the robustness of the two ecological networks composing it. The way in which the layers of interactions are connected to each other affects the interdependence of their robustness. In many networks, this interdependence is low, suggesting that restoration efforts would not automatically propagate through the whole community. Our results highlight the importance of considering multiple interactions simultaneously to better gauge the robustness of ecological communities to species loss and to more reliably identify key species that are important for the persistence of ecological communities.

Estimating co-extinction threats in terrestrial ecosystems

The biosphere is changing rapidly due to human endeavour. Because ecological communities underlie networks of interacting species, changes that directly affect some species can have indirect effects on others. Accurate tools to predict these direct and indirect effects are therefore required to guide conservation strategies. However, most extinction-risk studies only consider the direct effects of global change-such as predicting which species will breach their thermal limits under different warming scenarios-with predictions of trophic cascades and co-extinction risks remaining mostly speculative. To predict the potential indirect effects of primary extinctions, data describing community interactions and network modelling can estimate how extinctions cascade through communities. While theoretical studies have demonstrated the usefulness of models in predicting how communities react to threats like climate change, few have applied such methods to real-world communities. This gap partly reflects challenges in constructing trophic network models of real-world food webs, highlighting the need to develop approaches for quantifying co-extinction risk more accurately. We propose a framework for constructing ecological network models representing real-world food webs in terrestrial ecosystems and subjecting these models to co-extinction scenarios triggered by probable future environmental perturbations. Adopting our framework will improve estimates of how environmental perturbations affect whole ecological communities. Identifying species at risk of co-extinction (or those that might trigger co-extinctions) will also guide conservation interventions aiming to reduce the probability of co-extinction cascades and additional species losses.

Herbivore-induced pollinator limitation increases community stability of mutualism-antagonism continuum

Plants connect both pollinators and herbivores, and motivate the exploration of community structure in ecological networks merging antagonistic and mutualistic interactions. Evidence has shown that the two opposite plant-animal interactions are not independent from each other, in particular, herbivores can affect plant-pollinator pairwise interactions. Here, we explored effects of herbivore-induced pollinator limitation on community stability (including temporal stability and composition stability) of the mutualism-antagonism continuum. Our model demonstrated that pollinator limitation can boost up both temporal stability (i.e., the proportion of stable communities) and composition stability (i.e., species persistence), while the positive effects also depend on the strength of antagonistic and mutualistic interactions. Specifically, a community with higher temporal stability has a higher composition stability. Meanwhile, the correlations between network architecture and composition stability are also affected by pollinator limitation. Therefore, our results highlight that pollinator limitation can enhance community stability and may alter network architecture-composition stability relationship, and further advance the interplay between multiple types of species interactions within ecological networks.

Non-random interactions within and across guilds shape the potential to coexist in multi-trophic ecological communities

Theory posits that the persistence of species in ecological communities is shaped by their interactions within and across trophic guilds. However, we lack empirical evaluations of how the structure, strength and sign of biotic interactions drive the potential to coexist in diverse multi-trophic communities. Here, we model community feasibility domains, a theoretically informed measure of multi-species coexistence probability, from grassland communities comprising more than 45 species on average from three trophic guilds (plants, pollinators and herbivores). Contrary to our hypothesis, increasing community complexity, measured either as the number of guilds or community richness, did not decrease community feasibility. Rather, we observed that high degrees of species self-regulation and niche partitioning allow for maintaining larger levels of community feasibility and higher species persistence in more diverse communities. Our results show that biotic interactions within and across guilds are not random in nature and both structures significantly contribute to maintaining multi-trophic diversity.

Stability-instability transition in tripartite merged ecological networks

Although ecological networks are typically constructed based on a single type of interaction, e.g. trophic interactions in a food web, a more complete picture of ecosystem composition and functioning arises from merging networks of multiple interaction types. In this work, we consider tripartite networks constructed by merging two bipartite networks, one mutualistic and one antagonistic. Taking the interactions within each sub-network to be distributed randomly, we consider the stability of the dynamics of the network based on the spectrum of its community matrix. In the asymptotic limit of a large number of species, we show that the spectrum undergoes an eigenvalue phase transition, which leads to an abrupt destabilisation of the network as the ratio of mutualists to antagonists is increased. We also derive results that show how this transition is manifest in networks of finite size, as well as when disorder is introduced in the segregation of the two interaction types. Our random-matrix results will serve as a baseline for understanding the behaviour of merged networks with more realistic structures and/or more detailed dynamics.

Biological Microbial Interactions from Cooccurrence Networks in a High Mountain Lacustrine District

A fundamental question in biology is why some species tend to occur together in the same locations, while others are never observed coexisting. This question becomes particularly relevant for microorganisms thriving in the highly diluted waters of high mountain lakes, where biotic interactions might be required to make the most of an extreme environment. We studied a high-throughput gene data set of alpine lakes (>220 Pyrenean lakes) with cooccurrence network analysis to infer potential biotic interactions, using the combination of a probabilistic method for determining significant cooccurrences and coexclusions between pairs of species and a conceptual framework for classifying the nature of the observed cooccurrences and coexclusions. This computational approach (i) determined and quantified the importance of environmental variables and spatial distribution and (ii) defined potential interacting microbial assemblages. We determined the properties and relationships between these assemblages by examining node properties at the taxonomic level, indicating associations with their potential habitat sources (i.e., aquatic versus terrestrial) and their functional strategies (i.e., parasitic versus mixotrophic). Environmental variables explained fewer pairs in bacteria than in microbial eukaryotes for the alpine data set, with pH alone explaining the highest proportion of bacterial pairs. Nutrient composition was also relevant for explaining association pairs, particularly in microeukaryotes. We identified a reduced subset of pairs with the highest probability of species interactions (“interacting guilds”) that significantly reached higher occupancies and lower mean relative abundances in agreement with the carrying capacity hypothesis. The interacting bacterial guilds could be more related to habitat and microdispersal processes (i.e., aquatic versus soil microbes), whereas for microeukaryotes trophic roles (osmotrophs, mixotrophs, and parasitics) could potentially play a major role. Overall, our approach may add helpful information to guide further efforts for a mechanistic understanding of microbial interactions in situ.

IMPORTANCE A fundamental question in biology is why some species tend to occur together in the same locations, while others are never observed to coexist. This question becomes particularly relevant for microorganisms thriving in the highly diluted waters of high mountain lakes, in which biotic interactions might be required to make the most of an extreme environment. Microbial metacommunities are too often only studied in terms of their environmental niches and geographic barriers since they show inherent difficulties to quantify biological interactions and their role as drivers of ecosystem functioning. Our study highlights that telling apart potential interactions from both environmental and geographic niches may help for the initial characterization of organisms with similar ecologies in a large scope of ecosystems, even when information about actual interactions is partial and limited. The multilayered statistical approach carried out here offers the possibility of going beyond taxonomy to understand microbiological behavior in situ.

How Multiple Interaction Types Affect Disease Spread and Dilution in Ecological Networks

Ecological communities are composed of different functional guilds that are engaging in multiple types of biotic interactions. We explore how ecological networks fare when confronting infectious diseases according to density-dependent (DD) and frequency-dependent (FD) transmission modes. Our model shows that network compositions can dictate both disease spreading and the relationship between disease and community diversity (including species richness and Shannon’s diversity) as depicted in the dilution effect. The disease becomes more prevalent within communities harboring more mutualistic interactions, generating a positive relationship between disease prevalence and community diversity (i.e., an amplification effect). By contrast, in communities with a fixed proportion of mutualistic interactions, higher diversity from the balance of competition and predation can impede disease prevalence (i.e., the dilution effect). Within-species disease prevalence increases linearly with a species’ degree centrality. These patterns of disease transmission and the diversity-disease relationship hold for both transmission modes. Our analyses highlight the complex effects of interaction compositions in ecological networks on infectious disease dynamics and further advance the debate on the dilution effect of host diversity on disease prevalence.

Unveiling the complexity and ecological function of aquatic macrophyte-animal networks in coastal ecosystems

Network theory offers innovative tools to explore the complex ecological mechanisms regulating species associations and interactions. Although interest in ecological networks has grown steadily during the last two decades, the application of network approaches has been unequally distributed across different study systems: while some kinds of interactions (e.g. plant-pollinator and host-parasite) have been extensively investigated, others remain relatively unexplored. Among the latter, aquatic macrophyte-animal associations in coastal environments have been largely neglected, despite their major role in littoral ecosystems. The ubiquity of macrophyte systems, their accessibility and multi-faceted ecological, economical and societal importance make macrophyte-animal systems an ideal subject for ecological network science. In fact, macrophyte-animal networks offer an aquatic counterpart to terrestrial plant-animal networks. In this review, we show how the application of network analysis to aquatic macrophyte-animal associations has the potential to broaden our understanding of how coastal ecosystems function. Network analysis can also provide a key to understanding how such ecosystems will respond to on-going and future threats from anthropogenic disturbance and environmental change. For this, we: (i) identify key issues that have limited the application of network theory and modelling to aquatic animal-macrophyte associations; (ii) illustrate through examples based on empirical data how network analysis can offer new insights on the complexity and functioning of coastal ecosystems; and (iii) provide suggestions for how to design future studies and establish this new research line into network ecology.

Species richness increases fitness differences, but does not affect niche differences

A key question in ecology is what limits species richness. Modern coexistence theory presents the persistence of species as a balance between niche differences and fitness differences that favour and hamper coexistence, respectively. With most applications focusing on species pairs, however, we know little about if and how this balance changes with species richness. Here, we apply recently developed definitions of niche and fitness differences, based on invasion analysis, to multispecies communities. We present the first mathematical proof that, for invariant average interaction strengths, the average fitness difference among species increases with richness, while the average niche difference stays constant. Extensive simulations with more complex models and analyses of empirical data confirmed these mathematical results. Combined, our work suggests that, as species accumulate in ecosystems, ever-increasing fitness differences will at some point exceed constant niche differences, limiting species richness. Our results contribute to a better understanding of coexistence multispecies communities.

Analysis of complex trophic networks reveals the signature of land-use intensification on soil communities in agroecosystems

Increasing evidence suggests that agricultural intensification is a threat to many groups of soil biota, but how the impacts of land-use intensity on soil organisms translate into changes in comprehensive soil interaction networks remains unclear. Here for the first time, we use environmental DNA to examine total soil multi-trophic diversity and food web structure for temperate agroecosystems along a gradient of land-use intensity. We tested for response patterns in key properties of the soil food webs in sixteen fields ranging from arable crops to grazed permanent grasslands as part of a long-term management experiment. We found that agricultural intensification drives reductions in trophic group diversity, although taxa richness remained unchanged. Intensification generally reduced the complexity and connectance of soil interaction networks and induced consistent changes in energy pathways, but the magnitude of management-induced changes depended on the variable considered. Average path length (an indicator of food web redundancy and resilience) did not respond to our management intensity gradient. Moreover, turnover of network structure showed little response to increasing management intensity. Our data demonstrates the importance of considering different facets of trophic networks for a clearer understanding of agriculture-biodiversity relationships, with implications for nature-based solutions and sustainable agriculture.

Perception-driven dynamics of mimicry based on attractor field model

We provide a formal account of an interface that bridges two different levels of dynamic processes manifested by mimicry: prey-prey interactions and predators' perception. Mimicry is a coevolutionary process between an animate selective agent and at least two similar organisms selected by agent's perception-driven actions. Attractor field model explains perceived similarity of forms by noting that in both human and animal cognition, morphologically intermediate forms are more likely to be perceived as belonging to rare rather than abundant forms. We formalize this model in terms of predators' perception space deformation using numerical simulations and argue that the probability of confusion between similar species creates pressure on the perception space, which in turn leads to inflation of regions of perception space with high density of species representations. Such inflation causes increased discrimination between species by a predator, which implies that adaptive mimicry could initially emerge more easily among atypical species because they do not need the same level of similarity to the model. We provide a theoretical instrument to conceptualize interdependence between objective measurable matrices and perceived matrices of the same external reality. We believe that our framework leads to a more precise understanding of the evolution of mimicry.

Network Properties of Local Fungal Communities Reveal the Anthropogenic Disturbance Consequences of Farming Practices in Vineyard Soils

Agroecosystems are human-managed ecosystems subject to generalized ecological rules. Understanding the ecology behind the assembly and dynamics of soil fungal communities is a fruitful way to improve management practices and plant productivity. Thus, monitoring soil health would benefit from the use of metrics that arise from ecological explanations that can also be informative for agricultural management. Beyond traditional biodiversity descriptors, community-level properties have the potential of informing about particular ecological situations. Here we assess the impact of different farming practices in a survey of 350 vineyard soils from the United States and Spain by estimating network properties based on spatial associations. Our observations using traditional approaches show results concurring with previous literature: the influence of geographic and climatic factors on sample distributions, or different operational taxonomic unit (OTU) compositions depending on agricultural managements. Furthermore, using network properties, we observe that fungal communities ranged from dense arrangements of associations to a sparser structure of associations, indicating differential levels of niche specialization. We detect fungal arrangements capable of thriving in wider or smaller ranges of temperature, revealing that niche specialization may be a critical soil process impacting soil health. Low-intervention practices (organic and biodynamic managements) promoted densely clustered networks, describing an equilibrium state based on mixed collaborative communities. In contrast, conventionally managed vineyards had highly modular sparser communities, supported by a higher coexclusion proportion. Thus, we hypothesize that network properties at the community level may help to understand how the environment and land use can affect community structure and ecological processes in agroecosystems.

IMPORTANCE Soil fungal communities play a key role in agroecosystem sustainability. The complexity of fungal communities, at both taxonomic and functional levels, makes it difficult to find clear patterns connecting community composition with ecosystem function and to understand the impact of biotic (interspecies interactions) and abiotic (e.g., climate or anthropogenic disturbances) factors on it. Here we combine network analysis methods and properties, proposing a novel analytical approach: to infer ecological properties from local networks, which we apply to the study of fungal communities in vineyard soils. We conclude that different levels of farming intensification may lead to different ecological strategies in soil fungal communities settled by particular association arrangements.

Author Video: An author video summary of this article is available.

Rare plant species are at a disadvantage when both herbivory and pollination interactions are considered in an alpine meadow

Rare plant species often suffer less damage than common species because of positive density-dependent herbivory, and it has been suggested that this 'rare species advantage' fosters plant species coexistence. However, it is unknown whether rare species have an advantage when pollination interactions are also considered. We hypothesized that a 'positive density-dependent pollination success' across plant species would result in common plants experiencing higher seed set rates compared to rare species, and that positive density-dependent effects would negate or even override the positive density-dependent damage due to herbivory resulting in higher seed loss rates in common plant species. We tested this hypothesis by concurrently examining a plant-predispersal seed predator system and a plant-pollinator system for 24 Asteraceae species growing in an alpine meadow community (Sichuan Province, China). Having previously reported a positive density-dependent effect on seed loss rates due to seed predators, we here focus on the density-dependent effects on pollination success by investigating pollinator species richness, visitation frequencies and seed set rates for each plant species. We also estimated the seed output rate of each plant species as the product of seed set rate and the rate of surviving seeds (i.e. 1 - the seed loss rate). Consistent with our hypothesis, a positive density-dependent effect was observed for pollinator species richness, visitation frequencies and seed set rates across plant species. Moreover, the positive effect overrode the negative density-dependent effect of herbivores on seed production, such that common species tended to have a higher seed output rate than rare species (i.e. we observed a 'rare species disadvantage'). These results indicate that the low seed output rate of rare species might result from a pollination limitation, and that both mutualistic and antagonistic interactions should be examined simultaneously to fully understand plant species coexistence in local communities.

Species functional traits and abundance as drivers of multiplex ecological networks: first empirical quantification of inter-layer edge weights

Many vertebrate species act as both plant pollinators and seed-dispersers, thus interconnecting these processes, particularly on islands. Ecological multilayer networks are a powerful tool to explore interdependencies between processes; however, quantifying the links between species engaging in different types of interactions (i.e. inter-layer edges) remains a great challenge. Here, we empirically measured inter-layer edge weights by quantifying the role of individually marked birds as both pollinators and seed-dispersers of Galápagos plant species over an entire year. Although most species (80%) engaged in both functions, we show that only a small proportion of individuals actually linked the two processes, highlighting the need to further consider intra-specific variability in individuals' functional roles. Furthermore, we found a high variation among species in linking both processes, i.e. some species contribute more than others to the modular organization of the multilayer network. Small and abundant species are particularly important for the cohesion of pollinator seed-dispersal networks, demonstrating the interplay between species traits and neutral processes structuring natural communities.

The Structure of Ecological Networks Across Levels of Organization

Interactions connect the units of ecological systems, forming networks. Individual-based networks characterize variation in niches among individuals within populations. These individual-based networks merge with each other, forming species-based networks and food webs that describe the architecture of ecological communities. Networks at broader spatiotemporal scales portray the structure of ecological interactions across landscapes and over macroevolutionary time. Here, I review the patterns observed in ecological networks across multiple levels of biological organization. A fundamental challenge is to understand the amount of interdependence as we move from individual-based networks to species-based networks and beyond. Despite the uneven distribution of studies, regularities in network structure emerge across scales due to the fundamental architectural patterns shared by complex networks and the interplay between traits and numerical effects. I illustrate the integration of these organizational scales by exploring the consequences of the emergence of highly connected species for network structures across scales.

Interactions among interactions: The dynamical consequences of antagonism between mutualists

Species often interact with multiple mutualistic partners that provide functionally different benefits and/or that interact with different life-history stages. These functionally different partners, however, may also interact directly with one another in other ways, indirectly altering net outcomes and persistence of the mutualistic system as a whole. We present a population dynamical model of a three-species system involving antagonism between species sharing a mutualist partner species with two explicit life stages. We find that, regardless of whether the antagonism is predatory or non-consumptive, persistence of the shared mutualist is possible only under a restrictive set of conditions. As the rate of antagonism between the species sharing the mutualist increases, indirect rather than direct interactions increasingly determine species' densities and sometimes result in complex, oscillatory dynamics for all species. Surprisingly, persistence of the mutualistic system is particularly dependent upon the degree to which each of the two mutualistic interactions is specialized. Our work investigates a novel mechanism by which changing ecological conditions can lead to extinction of mutualist partners and provides testable predictions regarding the interactive roles of mutualism and antagonism in net outcomes for species' densities.

Geographical variation of multiplex ecological networks in marine intertidal communities

Understanding the drivers of geographical variation in species distributions, and the resulting community structure, constitutes one of the grandest challenges in ecology. Geographical patterns of species richness and composition have been relatively well studied. Less is known about how the entire set of trophic and non-trophic ecological interactions, and the complex networks that they create by gluing species together in complex communities, change across geographical extents. Here, we compiled data of species composition and three types of ecological interactions occurring between species in rocky intertidal communities across a large spatial extent (~970 km of shoreline) of central Chile, and analyzed the geographical variability in these multiplex networks (i.e., comprising several interaction types) of ecological interactions. We calculated nine network summary statistics common across interaction types, and additional network attributes specific to each of the different types of interactions. We then investigated potential environmental drivers of this multivariate network organization. These included variation in sea surface temperature and coastal upwelling, the main drivers of productivity in nearshore waters. Our results suggest that structural properties of multiplex ecological networks are affected by local species richness and modulated by factors influencing productivity and environmental predictability. Our results show that non-trophic negative interactions are more sensitive to spatially structured temporal environmental variation than feeding relationships, with non-trophic positive interactions being the least labile to it. We also show that environmental effects are partly mediated through changes in species richness and partly through direct influences on species interactions, probably associated to changes in environmental predictability and to bottom-up nutrient availability. Our findings highlight the need for a comprehensive picture of ecological interactions and their geographical variability if we are to predict potential effects of environmental changes on ecological communities.

A methodological framework to analyse determinants of host-microbiota networks, with an application to the relationships between Daphnia magna's gut microbiota and bacterioplankton

The past 30 years have seen both a surge of interest in assessing ecological interactions using tools borrowed from network theory and an explosion of data on the occurrence of microbial symbionts thanks to next-generation sequencing. Given that classic network methods cannot currently measure the respective effects of different environmental and biological drivers on network structure, we here present two methods to elucidate the determinants of bipartite interaction networks. The first method is based on classifications and compares communities within networks to the grouping of nodes by treatment or similar controlling groups. The second method assesses the link between multivariate explanatory variables and network structure using redundancy analyses after singular value decomposition. In both methods, the significance of effects can be gauged through two randomizations. Our methods were applied to experimental data on Daphnia magna and its interactions with gut microbiota and bacterioplankton. The whole network was affected by Daphnia's diet (algae and/or cyanobacteria) and sample type, but not by Daphnia genotype. At coarse grains, bacterioplankton and gut microbiota communities were different. At this scale, the structure of the gut microbiota-based network was not linked to any explanatory factors, while the bacterioplankton-based network was related to both Daphnia's diet and genotype. At finer grains, Daphnia's diet and genotype affected both microbial networks, but the effect of diet on gut microbiota network structure was mediated solely by differences in microbial richness. While no reciprocal effect between the microbial communities could be found, fine-grained analyses presented a more nuanced picture, with bacterioplankton likely affecting the composition of the gut microbiota. Our methods are widely applicable to bipartite networks, can elucidate both controlled and environmental effects in experimental setting using a large amount of sequencing data and can tease apart reciprocal effects of networks on one another. The twofold approach we propose has the advantage of being able to tease apart effects at different scales of network structure, thus allowing for detailed assessment of reciprocal effects of linked networks on one another. As such, our network methods can help ecologists understand huge datasets reporting microbial co-occurrences within different hosts.

Mutualism increases diversity, stability, and function of multiplex networks that integrate pollinators into food webs

Ecosystems are composed of complex networks of many species interacting in different ways. While ecologists have long studied food webs of feeding interactions, recent studies increasingly focus on mutualistic networks including plants that exchange food for reproductive services provided by animals such as pollinators. Here, we synthesize both types of consumer-resource interactions to better understand the controversial effects of mutualism on ecosystems at the species, guild, and whole-community levels. We find that consumer-resource mechanisms underlying plant-pollinator mutualisms can increase persistence, productivity, abundance, and temporal stability of both mutualists and non-mutualists in food webs. These effects strongly increase with floral reward productivity and are qualitatively robust to variation in the prevalence of mutualism and pollinators feeding upon resources in addition to rewards. This work advances the ability of mechanistic network theory to synthesize different types of interactions and illustrates how mutualism can enhance the diversity, stability, and function of complex ecosystems.

Aside from their pollination function, pollinators consume and are consumed by other members of ecological communities; these relationships could explain the controversial effects of pollinators on ecological networks. Here the authors show that when mutualists such as pollinators are introduced into food webs, they increase ecosystem biodiversity, stability, and function.

Hierarchically embedded interaction networks represent a missing link in the study of behavioral and community ecology

Because genes and phenotypes are embedded within individuals, and individuals within populations, interactions within one level of biological organization are inherently linked to interactors at others. Here, we expand the network paradigm to consider that nodes can be embedded within other nodes, and connections (edges) between nodes at one level of organization form "bridges" for connections between nodes embedded within them. Such hierarchically embedded networks highlight two central properties of biological systems: 1) processes occurring across multiple levels of organization shape connections among biological units at any given level of organization and 2) ecological effects occurring at a given level of organization can propagate up or down to additional levels. Explicitly considering the embedded structure of evolutionary and ecological networks can capture otherwise hidden feedbacks and generate new insights into key biological phenomena, ultimately promoting a broader understanding of interactions in evolutionary theory.

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.

Modular structure in fish co-occurrence networks: A comparison across spatial scales and grouping methodologies

Network modules are used for diverse purposes, ranging from delineation of biogeographical provinces to the study of biotic interactions. We assess spatial scaling effects on modular structure, using a multi-step process to compare fish co-occurrence networks at three nested scales. We first detect modules with simulated annealing and use spatial clustering tests (interspecific distances among species' range centroids) to determine if modules consist of species with broadly overlapping ranges; strong spatial clustering may reflect environmental filtering, while absence of spatial clustering may reflect positive interspecific relationships (commensalism or mutualism). We then use non-hierarchical, multivariate cluster analysis as an alternative method to identify fish subgroups, we repeat spatial clustering tests for the multivariate clusters, then compare spatial clustering results among modules and clusters. Next, we compare species lists within modules and clusters, and estimate congruence as the proportion of species assigned to the same groups by the two methods. Finally, we use a well-documented nest associate complex (fishes that deposit eggs in the gravel nests of a common host) to assess whether strong within-group associations may, in fact, reflect positive interspecific relationships. At each scale, 2-4 network modules were detected but a consistent relationship between scale and the number of modules was not observed. Significant spatial clustering was detected at all scales for network modules and multivariate clusters but was less prevalent at smaller scales. Congruence between modules and clusters was always < 90% and generally decreased as the number of groups increased. At all scales, the complete nest associate complex was completely preserved within a single network module, but not within a single multivariate cluster. Collectively, our results suggest that network modules are promising tools for studying positive interactions and that smaller scales may be preferable in this research.

Consequences of multiple flower-insect interactions for subsequent plant-insect interactions and plant reproduction

PREMISE OF THE STUDY

Plants often interact simultaneously with multiple antagonists and mutualists that can alter plant traits at the phenotypic or genetic level, subsequent plant-insect interactions, and reproduction. Although many studies have examined the effects of single floral antagonisms on subsequent pollination and plant reproduction, we know very little about the combined, potentially non-additive effects of multiple flower-insect interactions.

METHODS

We simulated increased florivory, nectar robbing, and pollination on field-grown Impatiens capensis, which allowed us to determine interactive effects on five subsequent plant-insect interactions and 16 plant traits, including traits related to plant growth, floral attractiveness, floral defenses, and plant reproduction.

KEY RESULTS

All three manipulative treatments had significant non-additive effects on the behavior of subsequent floral visitors, indicating that the effect of floral visitors generally depended on the presence or behavior of others. Pollination increased visitation by both pollinators and nectar larcenists (robbers and thieves), while florivory reduced pollinator and larcenist visits. Surprisingly, supplemental pollination also increased leaf herbivory. Florivores often responded to manipulations in opposite ways than did nectar larcenists and pollinators, suggesting different mechanisms influencing visitors that consume nectar compared to floral tissue. While our treatments did not affect any floral trait measured, they non-additively impacted plant reproduction, with florivory having a larger overall impact than either nectar robbing or pollination.

CONCLUSIONS

These results emphasize the importance of understanding the context in which flower-insect interactions occur because the composition of the interacting community can have large and non-additive impacts on subsequent insect behavior and plant reproduction.

The effect of multiple biotic interaction types on species persistence

No species can persist in isolation from other species, but how biotic interactions affect species persistence is still a matter of inquiry. Is persistence more likely in communities with higher proportion of competing species, or in communities with more positive interactions? How do different components of community structure mediate this relationship? We address these questions using a novel simulation framework that generates realistic communities with varying numbers of species and different proportions of biotic interaction types within and across trophic levels. We show that when communities have fewer species, persistence is more likely if positive interactions-such as mutualism and commensalism-are prevalent. In species-rich communities, the disproportionate effect of positive interactions on persistence is diluted and different combinations of biotic interaction types can coexist without affecting persistence significantly. We present the first theoretical examination of how multiple-interaction networks with varying architectures relate to local species persistence, and provide insight about the underlying causes of stability in communities.