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Species interactions are key drivers of biodiversity and ecosystem stability. Current theoretical frameworks for understanding the role of interactions make many assumptions which unfortunately, do not always hold in natural, diverse communities. This mismatch extends to annual plants, a common model system for studying coexistence, where interactions are typically averaged across environmental conditions and transitive competitive hierarchies are assumed to dominate. We quantify interaction networks for a community of annual wildflowers in Western Australia across a natural shade gradient at local scales. Whilst competition dominated, intraspecific and interspecific facilitation were widespread in all shade categories. Interaction strengths and directions varied substantially despite close spatial proximity and similar levels of local species richness, with most species interacting in different ways under different environmental conditions. Contrary to expectations, all networks were predominantly intransitive. These findings encourage us to rethink how we conceive of and categorize the mechanisms driving biodiversity in plant systems. [ABSTRACT FROM AUTHOR]

Network theory allows us to understand complex systems by evaluating how their constituent elements interact with one another. Such networks are built from matrices which describe the effect of each element on all others. Quantifying the strength of these interactions from empirical data can be difficult, however, because the number of potential interactions increases nonlinearly as more elements are included in the system, and not all interactions may be empirically observable when some elements are rare.We present a novel modelling framework which uses measures of species performance in the presence of varying densities of their potential interaction partners to estimate the strength of pairwise interactions in diverse horizontal systems.Our method allows us to directly estimate pairwise effects when they are statistically identifiable and to approximate pairwise effects when they would otherwise be statistically unidentifiable. The resulting interaction matrices can include positive and negative effects, the effect of a species on itself, and allows for non‐symmetrical interactions.We show how to link the parameters inferred by our framework to a population dynamics model to make inferences about the effect of interactions on community dynamics and diversity.The advantages of these features are illustrated with a case study on an annual wildflower community of 22 focal and 52 neighbouring species, and a discussion of potential applications of this framework extending well beyond plant community ecology. [ABSTRACT FROM AUTHOR]

Extinctions stemming from environmental change often trigger trophic cascades and coextinctions. Bottom–up cascades occur when changes in the primary producers in a network elicit flow‐on effects to higher trophic levels. However, it remains unclear what determines a species' vulnerability to bottom–up cascades and whether such cascades were a large contributor to the megafauna extinctions that swept across several continents in the Late Pleistocene. The pathways to megafauna extinctions are particularly unclear for Sahul (landmass comprising Australia and New Guinea), where extinctions happened earlier than on other continents. We investigated the potential role of bottom–up trophic cascades in the megafauna extinctions in Late Pleistocene Sahul by first developing synthetic networks that varied in topology to identify how network position (trophic level, diet breadth, basal connections) influences vulnerability to bottom–up cascades. We then constructed pre‐extinction (~80 ka) network models of the ecological community of Naracoorte, south‐eastern Sahul, to assess whether the observed megafauna extinctions could be explained by bottom–up cascades. Synthetic networks showed that node vulnerability to bottom–up cascades decreased with increasing trophic level, diet breadth and basal connections. Extinct species in the Naracoorte community were more vulnerable overall to these cascades than were species that survived. The position of extinct species in the network – tending to be of low trophic level and therefore having relatively narrow diet breadths and fewer connections to plants – made them vulnerable. However, these species also tended to have few or no predators, a network‐position attribute that suggests they might have been particularly vulnerable to new predators. Together, these results suggest that trophic cascades and naivety to predators could have contributed to the megafauna extinction event in Sahul. [ABSTRACT FROM AUTHOR]

It has long been anticipated that relating functional traits to species demography would be a cornerstone for achieving large-scale predictability of ecological systems. If such a relationship existed, species demography could be modeled only by measuring functional traits, transforming our ability to predict states and dynamics of species-rich communities with process-based community models. Here, we introduce a new method that links empirical functional traits with the demographic parameters of a process-based model by calibrating a transfer function through inverse modeling. As a case study, we parameterize a modified Lotka–Volterra model of a high-diversity mountain grassland with static plant community and functional trait data only. The calibrated trait–demography relationships are amenable to ecological interpretation, and lead to species abundances that fit well to the observed community structure. We conclude that our new method offers a general solution to bridge the divide between trait data and process-based models in species-rich ecosystems. Advances in process-based community ecology models are hindered by the challenge of linking functional traits to demography in species-rich systems, where a high number of parameters need to be estimated from limited data. Here the authors propose a new Bayesian framework to calibrate community models via functional traits, and validate it in a species-rich plant community. [ABSTRACT FROM AUTHOR]

Human visitors are associated with the unintended dispersal of weeds, seeds and pathogens across ecological communities. With the increasing popularity of nature‐based tourism, access to protected areas has increased, in turn increasing the risks of unintended dispersal of exotic species to these areas.Here, we assess the potential contribution of both international and domestic visitors travelling within New Zealand to the spread of exotic species. To get an overview of the visitors' travelling patterns across the country, we constructed visitation networks at two spatial scales—a regional scale (which is a coarse scale) and a local territorial scale (which is a finer scale).We then used a Mixed Membership Stochastic Block Model to identify characteristic groups of visitors and places based on the similarities of the visitors' travelling patterns across the country. Overall, we found that there are 10 characteristic groups of visitors travelling to 12 characteristic groups of places at the regional scale and 6 characteristic groups of visitors travelling to 6 characteristic groups of places at the territorial scale.The resulting characteristic travelling patterns of the visitors across New Zealand further allowed us to estimate the different visitor groups' likelihood to travel to protected areas. Overall, we found that some visitor groups are much more likely than others to travel to protected areas of high protection status, at both spatial scales.Synthesis and applications. Our results highlight the importance of accounting for human behaviour—that is, understanding how visitors travel to places—when assessing human‐mediated dispersal. More specifically, we illustrate how to assess the relative contribution of a potential vector dispersing exotic species based on their travelling patterns—especially in cases where the target exotic species are not yet identified or when there is limited information regarding the dispersal routes of exotic species and their potential vectors. As a result, our work offers a holistic perspective on human‐mediated dispersal of exotic species. Moreover, it provides a potential baseline against which both field biologists and practitioners can identify areas that would benefit from further investigation to better understand invasion processes in their focal systems. [ABSTRACT FROM AUTHOR]

Ecological communities often show changes in populations and their interactions over time. To date, however, it has been challenging to effectively untangle the mechanisms shaping such dynamics. One approach that has yet to be fully explored is to treat the varying structure of empirical communities--i.e. their network of interactions--as time series. Here, we follow this approach by applying a network-comparison technique to study the seasonal dynamics of plant-pollinator networks. We find that the structure of these networks is extremely variable, where species constantly change how they interact with each other within seasons. Most importantly, we find the holistic dynamic of plants and pollinators to be remarkably coherent across years, allowing us to reveal general rules by which species first enter, then change their roles, and finally leave the networks. Overall, our results disentangle key aspects of species' interaction turnover, phenology, and seasonal assembly/disassembly processes in empirical plant-pollinator communities. [ABSTRACT FROM AUTHOR]

An important dimension of a species' role is its ability to alter the state and maintain the diversity of its community. Centrality metrics have often been used to identify these species, which are sometimes referred as "keystone" species. However, the relationship between centrality and keystoneness is largely phenomenological and based mostly on our intuition regarding what constitutes an important species. While centrality is useful when predicting which species' extinctions could cause the largest change in a community, it says little about how these species could be used to attain or preserve a particular community state.Here we introduce structural controllability, an approach that allows us to quantify the extent to which network topology can be harnessed to achieve a desired state. It also allows us to quantify a species' control capacity—its relative importance—and identify the set of species that are critical in this context because they have the largest possible control capacity. We illustrate the application of structural controllability with ten pairs of uninvaded and invaded plant‐pollinator communities.We found that the controllability of a community is not dependent on its invasion status, but on the asymmetric nature of its mutual dependences. While central species were also likely to have a large control capacity, centrality fails to identify species that, despite being less connected, were critical in their communities. Interestingly, this set of critical species was mostly composed of plants and included every invasive species in our dataset. We also found that species with high control capacity, and in particular critical species, contribute the most to the stable coexistence of their community. This result was true, even when controlling for the species' degree, abundance/interaction strength, and the relative dependence of their partners.Synthesis. Structural controllability is strongly related to the stability of a network and measures the difficulty of managing an ecological community. It also identifies species that are critical to sustain biodiversity and to change or maintain the state of their community and are therefore likely to be very relevant for management and conservation. [ABSTRACT FROM AUTHOR]

Motivated by both analytical tractability and empirical practicality, community ecologists have long treated the species pair as the fundamental unit of study. This notwithstanding, the challenge of understanding more complex systems has repeatedly generated interest in the role of so‐called higher‐order interactions (HOIs) imposed by species beyond the focal pair. Here we argue that HOIs – defined as non‐additive effects of density on per capita growth – are best interpreted as emergent properties of phenomenological models (e.g. Lotka–Volterra competition) rather than as distinct 'ecological processes' in their own right. Using simulations of consumer‐resource models, we explore the mechanisms and system properties that give rise to HOIs in observational data. We demonstrate that HOIs emerge under all but the most restrictive of assumptions, and that incorporating non‐additivity into phenomenological models improves the quantitative and qualitative accuracy of model predictions. Notably, we also observe that HOIs derive primarily from mechanisms and system properties that apply equally to single‐species or pairwise systems as they do to more diverse communities. Consequently, there exists a strong mandate for further recognition of non‐additive effects in both theoretical and empirical research. [ABSTRACT FROM AUTHOR]

A framework for the description and analysis of multilayer networks is established in statistical physics, and calls are increasing for their adoption by community ecologists. Multilayer networks in community ecology will allow space, time and multiple interaction types to be incorporated into species interaction networks.While the multilayer network framework is applicable to ecological questions, it is one thing to be able to describe ecological communities as multilayer networks and another for multilayer networks to actually prove useful for answering ecological questions. Importantly, documenting multilayer network structure requires substantially greater empirical investment than standard ecological networks. In response, we argue that this additional effort is worthwhile and describe a series of research lines where we expect multilayer networks will generate the greatest impact.Inter‐layer edges are the key component that differentiate multilayer networks from standard ecological networks. Inter‐layer edges join different networks—termed layers—together and represent ecological processes central to the species interactions studied (e.g., inter‐layer edges representing movement for networks separated in space). Inter‐layer edges may take a variety of forms, be species‐ or network‐specific, and be measured with a large suite of empirical techniques. Additionally, the sheer size of ecological multilayer networks also requires some changes to empirical data collection around interaction quantification, collaborative efforts and collation in public databases.Network ecology has already touched on a wide swath of ecology and evolutionary biology. Because network stability and patterns of species linkage are the most developed areas of network ecology, they are a natural starting place for multilayer investigations. However, multilayer networks will also provide novel insights to niche partitioning, the connection between traits and species' interactions, and even the geographic mosaic of co‐evolution.Synthesis. Multilayer networks provide a formal way to bring together the study of species interaction networks and the processes that influence them. However, describing inter‐layer edges and the increasing amounts of data required represent challenges. The pay‐off for added investment will be ecological networks that describe the composition and capture the dynamics of ecological communities more completely and, consequently, have greater power for understanding the patterns and processes that underpin diversity in ecological communities. A plain language summary is available for this article. Plain Language Summary [ABSTRACT FROM AUTHOR]

Both species and their interactions are affected by changes that occur at evolutionary time‐scales, and these changes shape both ecological communities and their phylogenetic structure. That said, extant ecological community structure is contingent upon random chance, environmental filters and local effects. It is therefore unclear how much ecological signal local communities should retain. Here we show that, in a host–parasite system where species interactions vary substantially over a continental gradient, the ecological significance of individual interactions is maintained across different scales. Notably, this occurs despite the fact that observed community variation at the local scale frequently tends to weaken or remove community‐wide phylogenetic signal. When considered in terms of the interplay between community ecology and coevolutionary theory, our results demonstrate that individual interactions are capable and indeed likely to show a consistent signature of past evolutionary history even when woven into communities that do not. [ABSTRACT FROM AUTHOR]

The concordance of evolutionary histories and extant species interactions provides a useful metric for addressing questions of how the structure of ecological communities is influenced by macro-evolutionary processes., We introduce paco (v0.3.1), an R package to perform Procrustean Approach to Cophylogeny. This method assesses the phylogenetic congruence, or evolutionary dependence, of two groups of interacting species using both ecological interaction networks and their phylogenetic history., We demonstrate the functionality of paco through its application to empirical host-parasite and plant-pollinator communities., Although the package is intended to assess the phylogenetic congruence between groups of interacting species, the method is also directly applicable to other scenarios that may show phylogenetic congruence including historical biogeography, molecular systematics, and cultural evolution. [ABSTRACT FROM AUTHOR]

Food webs are the backbone upon which biomass flows through ecosystems. Dynamical models of biomass can reveal how the structure of food webs is involved in many key ecosystem properties, such as persistence, stability, etc., In this contribution, we present BioEnergeticFoodWebs, an implementation of Yodzis & Innes (The American Naturalist 139, 1151?1175, 1992) bio-energetic model, in the high-performance computing language Julia., We illustrate how this package can be used to conduct numerical experiments in a reproducible and standard way., A reference implementation of this widely used model will ease reproducibility and comparison of results across studies. [ABSTRACT FROM AUTHOR]

Previous analyses of empirical food webs (the networks of who eats whom in a community) have revealed that parasites exert a strong influence over observed food web structure and alter many network properties such as connectance and degree distributions. It remains unclear, however, whether these community-level effects are fully explained by differences in the ways that parasites and free-living species interact within a food web., To rigorously quantify the interrelationship between food web structure, the types of species in a web and the distinct types of feeding links between them, we introduce a shared methodology to quantify the structural roles of both species and feeding links. Roles are quantified based on the frequencies with which a species (or link) appears in different food web motifs - the building blocks of networks., We hypothesized that different types of species (e.g. top predators, basal resources, parasites) and different types of links between species (e.g. classic predation, parasitism, concomitant predation on parasites along with their hosts) will show characteristic differences in their food web roles., We found that parasites do indeed have unique structural roles in food webs. Moreover, we demonstrate that different types of feeding links (e.g. parasitism, predation or concomitant predation) are distributed differently in a food web context. More than any other interaction type, concomitant predation appears to constrain the roles of parasites. In contrast, concomitant predation links themselves have more variable roles than any other type of interaction., Together, our results provide a novel perspective on how both species and feeding link composition shape the structure of an ecological community and vice versa. [ABSTRACT FROM AUTHOR]

Ecological communities are composed of many species and an intricate network of interactions between them. Because of their overall complexity, an intriguing approach to understanding network structure is by breaking it down into the structural roles of its constituent species. The structural role of a species can be directly measured based on how it appears in network motifs - the basic building blocks of complex networks. Here, we study the distribution of species' roles at three distinct spatio-temporal scales (i.e. species, network, and temporal) in host-parasitoid networks collected across 22 sites over two years within a fragmented landscape of oaks in southern Finland. We found that species' roles for hosts and parasitoids were heterogeneously distributed across the study system but that roles are strongly conserved over spatial scales. In addition, we found that species' roles were remarkably consistent between years even in the presence of disturbances (e.g. species turnover). Overall, our results suggest that species' roles are an intrinsic property of species that may be predictable over spatial and temporal scales. [ABSTRACT FROM AUTHOR]

Exotic species are thought to alter the structure of natural communities and disrupt ecosystem functioning through invasion. Nevertheless, exotic species may also provide ecological insurance when they contribute to maintain ecosystem functions after the decline of native species following anthropogenic disturbance., Here, this hypothesis is tested with the assemblage of frugivorous birds and fleshy-fruited plants of New Zealand, which has suffered strong historical declines in native birds while simultaneously gaining new frugivores introduced by European settlers., We studied the plant-frugivore assemblage from measures of fruit and bird abundances and fruit consumption in nine forest patches, and tested how this changed across a gradient of relative abundance of exotic birds. We then examined how each bird species' role in the assemblage (the proportion of fruits and the number of plant species consumed) varied with their relative abundance, body size and native/exotic status., The more abundant and, to a lesser extent, larger birds species consumed a higher proportion of fruits from more plant species. Exotic birds consumed fruits less selectively and more proportionate to the local availability than did native species. Interaction networks in which exotic birds had a stronger role as frugivores had higher generalization, higher nestedness and higher redundancy of plants., Exotic birds maintained frugivory when native birds became rarer, and diversified the local spectrum of frugivores for co-occurring native plants. These effects seemed related to the fact that species abundances, rather than trait-matching constraints, ultimately determined the patterns of interactions between birds and plants. By altering the structure of plant-frugivore assemblages, exotic birds likely enhance the stability of the community-wide seed dispersal in the face of continued anthropogenic impact. [ABSTRACT FROM AUTHOR]

Studies of ecological networks (the web of interactions between species in a community) demonstrate an intricate link between a community's structure and its long-term viability. It remains unclear, however, how much a community's persistence depends on the identities of the species present, or how much the role played by each species varies as a function of the community in which it is found. We measured species' roles by studying how species are embedded within the overall network and the subsequent dynamic implications. Using data from 32 empirical food webs, we find that species' roles and dynamic importance are inherent species attributes and can be extrapolated across communities on the basis of taxonomic classification alone. Our results illustrate the variability of roles across species and communities and the relative importance of distinct species groups when attempting to conserve ecological communities. [ABSTRACT FROM AUTHOR]

The idea that species occupy distinct niches is a fundamental concept in ecology. Classically, the niche was described as an n-dimensional hypervolume where each dimension represents a biotic or abiotic characteristic. More recently, it has been hypothesised that a single dimension may be sufficient to explain the system-level organization of trophic interactions observed between species in a community. Here, we test the hypothesis that species body mass is that single dimension. Specifically, we determine how the intervality of food webs ordered by body size compares to that of randomly ordered food webs. We also extend this analysis beyond the community level to the effect of body mass in explaining the diets of individual species. We conclude that body mass significantly explains the ordering of species and the contiguity of diets in empirical communities. At the species-specific level, we find that the degree to which body mass is a significant explanatory variable depends strongly on the phylogenetic history, suggesting that other evolutionarily conserved traits partly account for species' roles in the food web. Our investigation of the role of body mass in food webs thus helps us to better understand the important features of community food-web structure and the evolutionary forces that have led us to the communities we observe. [ABSTRACT FROM AUTHOR]

It has recently been noted that empirical food webs are significantly compartmentalized; that is, subsets of species exist that interact more frequently among themselves than with other species in the community. Although the dynamic implications of compartmentalization have been debated for at least four decades, a general answer has remained elusive. Here, we unambiguously demonstrate that compartmentalization acts to increase the persistence of multitrophic food webs. We then identify the mechanisms behind this result. Compartments in food webs act directly to buffer the propagation of extinctions throughout the community and augment the long-term persistence of its constituent species. This contribution to persistence is greater the more complex the food web, which helps to reconcile the simultaneous complexity and stability of natural communities. [ABSTRACT FROM AUTHOR]

1. Understanding the structure of ecological networks is a crucial task for interpreting community and ecosystem responses to global change. 2. Despite the recent interest in this subject, almost all studies have focused exclusively on one specific network property. The question remains as to what extent different network properties are related and how understanding this relationship can advance our comprehension of the mechanisms behind these patterns. 3. Here, we analysed the relationship between nestedness and modularity, two frequently studied network properties, for a large data set of 95 ecological communities including both plant–animal mutualistic and host–parasite networks. 4. We found that the correlation between nestedness and modularity for a population of random matrices generated from the real communities decreases significantly in magnitude and sign with increasing connectance independent of the network type. At low connectivities, networks that are highly nested also tend to be highly modular; the reverse happens at high connectivities. 5. The above result is qualitatively robust when different null models are used to infer network structure, but, at a finer scale, quantitative differences exist. We observed an important interaction between the network structure pattern and the null model used to detect it. 6. A better understanding of the relationship between nestedness and modularity is important given their potential implications on the dynamics and stability of ecological communities. [ABSTRACT FROM AUTHOR]

1. Food webs, the set of predator–prey interactions in an ecosystem, are a prototypical complex system. Much research to date has concentrated on the use of models to identify and explain the key structural features which characterize food webs. 2. These models often fall into two general categories: (i) phenomenological models which are built upon a set of heuristic rules in order to explain some empirical observation and (ii) population-level models in which interactions between individuals result in emergent properties for the food web. Both types of models have helped to uncover how food-web structure is a product of factors such as foraging behaviour, prey selection and species’ body sizes. 3. Historically, the two types of models have followed rather different approaches to the problem. Despite the apparent differences, the overlap between the two styles of models is substantial. Examples are highlighted here. 4. By paying greater attention to both the similarities and differences between the two, we will be better able to demonstrate the ecological insights offered by phenomenological models. This will help us, for example, design experiments which could validate or refute underlying assumptions of the models. By linking models to data, scaling from individuals to networks, we will be closer to understanding the true origins of food-web structure. [ABSTRACT FROM AUTHOR]

Intervality of a food web is related to the number of trophic dimensions characterizing the niches in a community. We introduce here a mathematically robust measure for food web intervality. It has previously been noted that empirical food webs are not strictly interval; however, upon comparison to suitable null hypotheses, we conclude that empirical food webs actually do exhibit a strong bias toward contiguity of prey, that is, toward intervality. Further, our results strongly suggest that empirically observed species and their diets can be mapped onto a single dimension. This finding validates a critical assumption in the recently proposed static niche model and provides guidance for ongoing efforts to develop dynamic models of ecosystems. [ABSTRACT FROM AUTHOR]

The global biodiversity crisis concerns not only unprecedented loss of species within communities, but also related consequences for ecosystem function. Community ecology focuses on patterns of species richness and community composition, whereas ecosystem ecology focuses on fluxes of energy and materials. Food webs provide a quantitative framework to combine these approaches and unify the study of biodiversity and ecosystem function. We summarise the progression of food-web ecology and the challenges in using the food-web approach. We identify five areas of research where these advances can continue, and be applied to global challenges. Finally, we describe what data are needed in the next generation of food-web studies to reconcile the structure and function of biodiversity. [Copyright &y& Elsevier]