A simple stochastic model for complex coextinctions in mutualistic networks: robustness decreases with connectance

Understanding and predicting species extinctions and coextinctions is a major goal of ecological research in the face of a biodiversity crisis. Typically, models based on network topology are used to simulate coextinctions in mutualistic networks. However, such topological models neglect two key biological features of species interactions: variation in the intrinsic dependence of species on the mutualism, and variation in the relative importance of each interacting partner. By incorporating both types of variation, we developed a stochastic coextinction model capable of simulating extinction cascades far more complex than those observed in previous topological models. Using a set of empirical mutualistic networks, we show that the traditional topological model may either underestimate or overestimate the number and likelihood of coextinctions, depending on the intrinsic dependence of species on the mutualism. More importantly, contrary to topological models, our stochastic model predicts extinction cascades to be more likely in highly connected mutualistic communities.     

The nested assembly of plant facilitation networks prevents species extinctions

Facilitation is a positive interaction assembling ecological communities and preserving global biodiversity. Although communities acquire emerging properties when many species interact, most of our knowledge about facilitation is based on studies between pairs of species. To understand how plant facilitation preserves biodiversity in complex ecological communities, we propose to move from the study of pairwise interactions to the network approach. We show that facilitation networks behave as mutualistic networks do, characterized by a nonrandom, nested structure of plant-plant interactions in which a few generalist nurses facilitate a large number of species while the rest of the nurses facilitate only a subset of them. Consequently, generalist nurses shape a dense and highly connected network. Interestingly, such generalist nurses are the most abundant species in the community, making facilitation-shaped communities strongly resistant to extinction, as revealed by coextinction simulations. The nested structure of facilitative networks explains why facilitation, by preventing extinction, preserves biodiversity.     

Rewiring and indirect effects underpin modularity reshuffling in a marine food web under environmental shifts

Species are characterized by physiological and behavioral plasticity, which is part of their response to environmental shifts. Nonetheless, the collective response of ecological communities to environmental shifts cannot be predicted from the simple sum of individual species responses, since co‐existing species are deeply entangled in interaction networks, such as food webs. For these reasons, the relation between environmental forcing and the structure of food webs is an open problem in ecology. To this respect, one of the main problems in community ecology is defining the role each species plays in shaping community structure, such as by promoting the subdivision of food webs in modules—that is, aggregates composed of species that more frequently interact—which are reported as community stabilizers. In this study, we investigated the relationship between species roles and network modularity under environmental shifts in a highly resolved food web, that is, a “weighted” ecological network reproducing carbon flows among marine planktonic species. Measuring network properties and estimating weighted modularity, we show that species have distinct roles, which differentially affect modularity and mediate structural modifications, such as modules reconfiguration, induced by environmental shifts. Specifically, short‐term environmental changes impact the abundance of planktonic primary producers; this affects their consumers’ behavior and cascades into the overall rearrangement of trophic links. Food web re‐adjustments are both direct, through the rewiring of trophic‐interaction networks, and indirect, with the reconfiguration of trophic cascades. Through such “systemic behavior,” that is, the way the food web acts as a whole, defined by the interactions among its parts, the planktonic food web undergoes a substantial rewiring while keeping almost the same global flow to upper trophic levels, and energetic hierarchy is maintained despite environmental shifts. This behavior suggests the potentially high resilience of plankton networks, such as food webs, to dramatic environmental changes, such as those provoked by global change.     

Unifying facilitation and recruitment networks

Ecological network studies are providing important advances about the organization, stability and dynamics of ecological systems. However, the ecological networks approach is being integrated very slowly in plant community ecology, even though the first studies on plant facilitation networks (FNs) were published more than a decade ago. The study of interaction networks between established plants and plants recruiting beneath them, which we call Recruitment Networks (RNs), can provide new insights on mechanisms driving plant community structure and dynamics. RNs basically describe which plants recruit under which others, so they can be seen as a generalisation of the classic FNs since they do not imply any particular effect (positive, negative or neutral) of the established plants on recruiting ones. RNs summarise information on the structure of sapling banks. More importantly, the information included in RNs can be incorporated into models of replacement dynamics to evaluate how different aspects of network structure, or different mechanisms of network assembly, may affect plant community stability and species coexistence. To allow an efficient development of the study of FNs and RNs, here we unify concepts, synthesise current knowledge, clarify some conceptual issues, and propose basic methodological guidelines to standardise sampling methods that could make future studies of these networks directly comparable.     

Motifs in bipartite ecological networks: uncovering indirect interactions

Indirect interactions play an essential role in governing population, community and coevolutionary dynamics across a diverse range of ecological communities. Such communities are widely represented as bipartite networks: graphs depicting interactions between two groups of species, such as plants and pollinators or hosts and parasites. For over thirty years, studies have used indices, such as connectance and species degree, to characterise the structure of these networks and the roles of their constituent species. However, compressing a complex network into a single metric necessarily discards large amounts of information about indirect interactions. Given the large literature demonstrating the importance and ubiquity of indirect effects, many studies of network structure are likely missing a substantial piece of the ecological puzzle. Here we use the emerging concept of bipartite motifs to outline a new framework for bipartite networks that incorporates indirect interactions. While this framework is a significant departure from the current way of thinking about bipartite ecological networks, we show that this shift is supported by analyses of simulated and empirical data. We use simulations to show how consideration of indirect interactions can highlight differences missed by the current index paradigm that may be ecologically important. We extend this finding to empirical plant–pollinator communities, showing how two bee species, with similar direct interactions, differ in how specialised their competitors are. These examples underscore the need to not rely solely on network‐ and species‐level indices for characterising the structure of bipartite ecological networks.     

Do bipartite binary antagonistic and mutualistic networks have different responses to the taxonomic resolution of nodes?

1. Bipartite network analyses are increasingly being used to better understand mutualistic and antagonistic plant–insect interactions at the community level. As a result of taxonomic limitations, it is usually very difficult to identify all nodes of a network down to the species level and many studies leave some specimens identified as lower resolution taxa. Accordingly, we do not know how much a lower resolution taxonomic representation changes the network structure compared with a representation with all nodes at species level. 2. The present study aimed to test whether insect–plant networks built using different combinations of taxonomic levels can still preserve the same basic structure of networks built only with species. 3. In total, 73 bipartite published interaction networks (mutualistic and antagonistic) were selected, which were turned into binary networks and reconstructed using the nodes classified as species, genus, family or order (representing different levels of classification difficulty). The network structures were compared using their binary representations mainly using connectance, NODF (Nestedness metric based on Overlap and Decreasing Fill) and modularity. 4. The mutualistic network structure was strongly linearly related to the original network structures if all nodes were grouped up to genus level. In antagonistic networks, the structure was related to the original network only if nodes were only grouped at the species level. 5. The findings of the present study are especially helpful for comparative network studies, such as those assessing the effects of environmental gradients. For mutualistic networks, Citizen Science programmes can provide useful ecological indicators, even with its taxonomic limitations.     

Predicting the non‐linear collapse of plant–frugivore networks due to habitat loss

Habitat loss can trigger cascades of secondary extinctions, changing the organization of interacting assemblages. Until recently, most extinction models in interaction systems had limited ecological realism. Here, we estimate a realistic sequence of species extinctions resulting from habitat loss to assess its impacts on the structure of frugivory networks from the Brazilian Atlantic Forest. We show that realistic and random extinctions led to similar patterns. We also identified a threshold in the response of network structure to habitat loss. When forest cover was reduced to less than 40% of the landscape, network organization changed dramatically. Hence, the number of species being lost, rather than the order of species extinctions, is the key determinant of its impacts on the organization of frugivory networks. We highlight the need to conserve around 40% of forest cover to keep the basic organization of frugivory networks, a threshold already reached at the best‐preserved Brazilian Atlantic Forest bioregion.     

Evolution of competitive ability: an adaptation speed vs. accuracy tradeoff rooted in gene network size

Ecologists have increasingly come to understand that evolutionary change on short time-scales can alter ecological dynamics (and vice-versa), and this idea is being incorporated into community ecology research programs. Previous research has suggested that the size and topology of the gene network underlying a quantitative trait should constrain or facilitate adaptation and thereby alter population dynamics. Here, I consider a scenario in which two species with different genetic architectures compete and evolve in fluctuating environments. An important trade-off emerges between adaptive accuracy and adaptive speed, driven by the size of the gene network underlying the ecologically-critical trait and the rate of environmental change. Smaller, scale-free networks confer a competitive advantage in rapidly-changing environments, but larger networks permit increased adaptive accuracy when environmental change is sufficiently slow to allow a species time to adapt. As the differences in network characteristics increase, the time-to-resolution of competition decreases. These results augment and refine previous conclusions about the ecological implications of the genetic architecture of quantitative traits, emphasizing a role of adaptive accuracy. Along with previous work, in particular that considering the role of gene network connectivity, these results provide a set of expectations for what we may observe as the field of ecological genomics develops.     

Effect of livestock grazing in the partitions of a semiarid plant–plant spatial signed network

In recent times, network theory has become a useful tool to study the structure of the interactions in ecological communities. However, typically, these approaches focus on a particular kind of interaction while neglecting other possible interactions present in the ecosystem. Here, we present an ecological network for plant communities that consider simultaneously positive and negative interactions, which were derived from the spatial association and segregation between plant species. We employed this network to study the structure and the association strategies in a semiarid plant community of Cabo de Gata-Níjar Natural Park, SE Spain, and how they changed in 4 sites that differed in stocking rate. Association strategies were obtained from the partitions of the network, built based on a relaxed structural balance criterion. We found that grazing simplified the structure of the plant community. With increasing stocking rate species with no significant associations became dominant and the number of partitions decreased in the plant community. Independently of stocking rate, many species presented an associative strategy in the plant community because they benefit from the association to certain ‘nurse’ plants. These ‘nurses’ together with species that developed a segregating strategy, intervened in most of the interactions in the community. Ecological networks that combine links with different signs provide a new insight to analyze the structure of natural communities and identify the species which play a central role in them.     

Symmetric assembly and disassembly processes in an ecological network

The processes whereby ecological networks emerge, persist and decay throughout ecosystem development are largely unknown. Here we study networks of plant and arbuscular mycorrhizal fungal (AMF) communities along a 120 000 year soil chronosequence, as they undergo assembly (progression) and then disassembly (retrogression). We found that network assembly and disassembly were symmetrical, self‐reinforcing processes that together were capable of generating key attributes of network architecture. Plant and AMF species that had short indirect paths to others in the community (i.e. high centrality), rather than many direct interaction partners (i.e. high degree), were best able to attract new interaction partners and, in the case of AMF species, also to retain existing interactions with plants during retrogression. We then show using simulations that these non‐random patterns of attachment and detachment promote nestedness of the network. These results have implications for predicting extinction sequences, identifying focal points for invasions and suggesting trajectories for restoration.     

Can network metrics predict vulnerability and species roles in bird‐dispersed plant communities? Not without behaviour

Network metrics are widely used to infer the roles of mutualistic animals in plant communities and to predict the effect of species' loss. However, their empirical validation is scarce. Here we parameterized a joint species model of frugivory and seed dispersal with bird movement and foraging data from tropical and temperate communities. With this model, we investigate the effect of frugivore loss on seed rain, and compare our predictions to those of standard coextinction models and network metrics. Topological coextinction models underestimated species loss after the removal of highly linked frugivores with unique foraging behaviours. Network metrics informed about changes in seed rain quantity after frugivore loss. However, changes in seed rain composition were only predicted by partner diversity. Nestedness, closeness, and d’ specialisation could not anticipate the effects of rearrangements in plant–frugivore communities following species loss. Accounting for behavioural differences among mutualists is critical to improve predictions from network models.     

Spatial resolution and location impact group structure in a marine food web

Ecological processes in food webs depend on species interactions. By identifying broad‐scaled interaction patterns, important information on species' ecological roles may be revealed. Here, we use the group model to examine how spatial resolution and proximity influence group structure. We examine a data set from the Barents Sea, with food webs described for both the whole region and 25 subregions. We test how the group structure in the networks differ comparing (1) the regional metaweb to subregions and (2) subregion to subregion. We find that more than half the species in the metaweb change groups when compared to subregions. Between subregions, networks with similar group structure are spatially related. Interestingly, although species overlap is important for similarity in group structure, there are notable exceptions. Our results highlight that species ecological roles vary depending on fine‐scaled differences in the patterns of interactions, and that local network characteristics are important to consider.     

Reshaping our understanding of species’ roles in landscape‐scale networks

In network ecology, landscape‐scale processes are often overlooked, yet there is increasing evidence that species and interactions spill over between habitats, calling for further study of interhabitat dependencies. Here, we investigate how species connect a mosaic of habitats based on the spatial variation of their mutualistic and antagonistic interactions using two multilayer networks, combining pollination, herbivory and parasitism in the UK and New Zealand. Developing novel methods of network analysis for landscape‐scale ecological networks, we discovered that few plant and pollinator species acted as connectors or hubs, both within and among habitats, whereas herbivores and parasitoids typically have more peripheral network roles. Insect species’ roles depend on factors other than just the abundance of taxa in the lower trophic level, exemplified by larger Hymenoptera connecting networks of different habitats and insects relying on different resources across different habitats. Our findings provide a broader perspective for landscape‐scale management and ecological community conservation.     

Can plant-pollinator network metrics indicate environmental quality?

Plant-pollinator interaction networks may be more informative than the diversity of species in the evaluation of the effects of environmental change. Considering that networks vary with the integrity of ecosystems, their changes may help to predict the consequences of anthropogenic impacts on biodiversity and ecological processes. This characteristic highlights its use as environmental quality indicator. However, to employ interaction networks as ecological indicators it is necessary to identify the most sensitive metrics and understand how and why they vary with environmental changes. This review aimed to identify, in empirical studies, which network metrics have been evidenced as being more sensitive to changes in environmental quality. We analyzed published empirical studies, that applied the network approach on environmental quality gradients. In addition to the network metric behavior, we studied the interactions between them and possible causes of their variation. The available empirical data indicated that degree, nestedness and connectance did not have a simple, linear or unidirectional response to habitat degradation. Conversely, the metrics interaction asymmetry, d' (reciprocal specialization index of the species) showed the most consistent responses to environmental change. The role of the species changed, ranging between generalists and specialists under different conditions. In addition, specialist species with morphological and behavioral constraints were lost in worse environmental quality situations. The identity of interacting species and their role in the network, with a further specification of groups and interactions most affected, are the properties with greater potential to indicate changes in environmental quality. Most of the available studies focused on metrics at the network level, but several studies and this review indicate that the patterns at the network level can be better understood in the light of metrics analyzed at the species level. Our results provide information that enrich the network analysis, highlighting the need to consider important features that are often neglected. Discussions and information compiled here are important for deciding how to look at empirical data and what to look for, as well as to indicate some caveats when interpreting data on plant-pollinator interactions with a complex network approach. Network metrics can be good indicators of environmental quality if the underlying ecological causes of the numerical changes are carefully analyzed.     

Comparing species interaction networks along environmental gradients

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co‐variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant–hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis‐based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients.     

Modelling dendritic ecological networks in space: an integrated network perspective

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2‐D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2‐D space can be used to explore the influence of multi‐scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).     

Compensation masks trophic cascades in complex food webs

Ecological networks, or food webs, describe the feeding relationships between interacting species within an ecosystem. Understanding how the complexity of these networks influences their response to changing top-down control is a central challenge in ecology. Here, we provide a model-based investigation of trophic cascades — an oft-studied ecological phenomenon that occurs when changes in the biomass of top predators indirectly effect changes in the biomass of primary producers — in complex food webs that are representative of the structure of real ecosystems. Our results reveal that strong cascades occur primarily in low richness and weakly connected food webs, a result in agreement with some prior predictions. The primary mechanism underlying weak or absent cascades was a strong compensatory response; in most webs, predators induced large population level cascades that were masked by changes in the opposite direction by other species in the same trophic guild. Thus, the search for a general theory of trophic cascades in food webs should focus on uncovering features of real ecosystems that promote biomass compensation within functional guilds or trophic levels.     

Coevolutionary dynamics shape the structure of bacteria‐phage infection networks

Coevolution—reciprocal evolutionary change among interacting species driven by natural selection—is thought to be an important force in shaping biodiversity. This ongoing process takes place within tangled networks of species interactions. In microbial communities, evolutionary change between hosts and parasites occurs at the same time scale as ecological change. Yet, we still lack experimental evidence of the role of coevolution in driving changes in the structure of such species interaction networks. Filling this gap is important because network structure influences community persistence through indirect effects. Here, we quantified experimentally to what extent coevolutionary dynamics lead to contrasting patterns in the architecture of bacteria–phage infection networks. Specifically, we look at the tendency of these networks to be organized in a nested pattern by which the more specialist phages tend to infect only a proper subset of those bacteria infected by the most generalist phages. We found that interactions between coevolving bacteria and phages become less nested over time under fluctuating dynamics, and more nested under arms race dynamics. Moreover, when coevolution results in high average infectivity, phages and bacteria differ more from each other over time under arms race dynamics than under fluctuating dynamics. The tradeoff between the fitness benefits of evolving resistance/infectivity traits and the costs of maintaining them might explain these differences in network structure. Our study shows that the interaction pattern between bacteria and phages at the community level depends on the way coevolution unfolds.     

The dimensionality of ecological networks

How many dimensions (trait‐axes) are required to predict whether two species interact? This unanswered question originated with the idea of ecological niches, and yet bears relevance today for understanding what determines network structure. Here, we analyse a set of 200 ecological networks, including food webs, antagonistic and mutualistic networks, and find that the number of dimensions needed to completely explain all interactions is small ( < 10), with model selection favouring less than five. Using 18 high‐quality webs including several species traits, we identify which traits contribute the most to explaining network structure. We show that accounting for a few traits dramatically improves our understanding of the structure of ecological networks. Matching traits for resources and consumers, for example, fruit size and bill gape, are the most successful combinations. These results link ecologically important species attributes to large‐scale community structure.     

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.