Degree distribution in plant-animal mutualistic networks: forbidden links or random interactions?

Parasite-host network analysis provides insights into the evolution of two mistletoe lineages (Loranthaceae and Santalaceae)

Mistletoes are ecologically important parasitic plants, with > 1600 species from five lineages worldwide. Mistletoe lineages exhibit distinct patterns of species diversification and host specificity, however, the mechanisms underlying these differences are poorly understood. In this study, we analysed a comprehensive parasite-host network, including 280 host species from 60 families and 22 mistletoe species from two lineages (Santalaceae and Loranthaceae) in Xishuangbanna, located in a biodiversity hotspot of tropical Asia. We identified the factors that predict the infection strength of mistletoes. We also detected host specificity and the phylogenetic signal of mistletoes and their hosts. We found that this interaction network could be largely explained by a model based on the relative abundance of species. Host infection was positively correlated with diameter at breast height and tree coverage, but negatively correlated with wood density. Overall, closely related mistletoe species tend to interact more often with similar hosts. However, the two lineages showed a significantly different network pattern. Rates of host generality were higher in Loranthaceae than in Santalaceae, although neither lineage showed phylogenetic signal for host generality. This study demonstrates that the neutral interaction hypothesis provides suitable predictions of the mistletoe-host interaction network, and mistletoe species show significant phylogenetic signals for their hosts. Our findings also indicate that high species diversification in Loranthaceae may be explained by high rates of host generality and the evolutionary history shared by Loranthaceae species with diverse host plants in the tropics.

What constrains food webs? A maximum entropy framework for predicting their structure with minimal biases

Food webs are complex ecological networks whose structure is both ecologically and statistically constrained, with many network properties being correlated with each other. Despite the recognition of these invariable relationships in food webs, the use of the principle of maximum entropy (MaxEnt) in network ecology is still rare. This is surprising considering that MaxEnt is a statistical tool precisely designed for understanding and predicting many types of constrained systems. This principle asserts that the least-biased probability distribution of a system's property, constrained by prior knowledge about that system, is the one with maximum information entropy. MaxEnt has been proven useful in many ecological modeling problems, but its application in food webs and other ecological networks is limited. Here we show how MaxEnt can be used to derive many food-web properties both analytically and heuristically. First, we show how the joint degree distribution (the joint probability distribution of the numbers of prey and predators for each species in the network) can be derived analytically using the number of species and the number of interactions in food webs. Second, we present a heuristic and flexible approach of finding a network's adjacency matrix (the network's representation in matrix format) based on simulated annealing and SVD entropy. We built two heuristic models using the connectance and the joint degree sequence as statistical constraints, respectively. We compared both models' predictions against corresponding null and neutral models commonly used in network ecology using open access data of terrestrial and aquatic food webs sampled globally (N = 257). We found that the heuristic model constrained by the joint degree sequence was a good predictor of many measures of food-web structure, especially the nestedness and motifs distribution. Specifically, our results suggest that the structure of terrestrial and aquatic food webs is mainly driven by their joint degree distribution.

Seasonal and elevational changes of plant-pollinator interaction networks in East African mountains

Across an elevation gradient, several biotic and abiotic factors influence community assemblages of interacting species leading to a shift in species distribution, functioning, and ultimately topologies of species interaction networks. However, empirical studies of climate-driven seasonal and elevational changes in plant-pollinator networks are rare, particularly in tropical ecosystems. Eastern Afromontane Biodiversity Hotspots in Kenya, East Africa. We recorded plant-bee interactions at 50 study sites between 515 and 2600 m asl for a full year, following all four major seasons in this region. We analysed elevational and seasonal network patterns using generalised additive models (GAMs) and quantified the influence of climate, floral resource availability, and bee diversity on network structures using a multimodel inference framework. We recorded 16,741 interactions among 186 bee and 314 plant species of which a majority involved interactions with honeybees. We found that nestedness and bee species specialisation of plant-bee interaction networks increased with elevation and that the relationships were consistent in the cold-dry and warm-wet seasons respectively. Link rewiring increased in the warm-wet season with elevation but remained indifferent in the cold-dry seasons. Conversely, network modularity and plant species were more specialised at lower elevations during both the cold-dry and warm-wet seasons, with higher values observed during the warm-wet seasons. We found flower and bee species diversity and abundance rather than direct effects of climate variables to best predict modularity, specialisation, and link rewiring in plant-bee-interaction networks. This study highlights changes in network architectures with elevation suggesting a potential sensitivity of plant-bee interactions with climate warming and changes in rainfall patterns along the elevation gradients of the Eastern Afromontane Biodiversity Hotspot.

Generalism drives abundance: A computational causal discovery approach

A ubiquitous pattern in ecological systems is that more abundant species tend to be more generalist; that is, they interact with more species or can occur in wider range of habitats. However, there is no consensus on whether generalism drives abundance (a selection process) or abundance drives generalism (a drift process). As it is difficult to conduct direct experiments to solve this chicken-and-egg dilemma, previous studies have used a causal discovery method based on formal logic and have found that abundance drives generalism. Here, we refine this method by correcting its bias regarding skewed distributions, and employ two other independent causal discovery methods based on nonparametric regression and on information theory, respectively. Contrary to previous work, all three independent methods strongly indicate that generalism drives abundance when applied to datasets on plant-hummingbird communities and reef fishes. Furthermore, we find that selection processes are more important than drift processes in structuring multispecies systems when the environment is variable. Our results showcase the power of the computational causal discovery approach to aid ecological research.

Ever since Aristotle, the chicken-or-egg causality dilemma has baffled researchers. Such causality dilemmas are abundant in ecological research, where causal directions are often assumed but not tested. An archetypal example is whether being a generalist causes a species to be more abundant, or whether being more abundant causes a species to be generalists. Without doubt, the gold standard to establish causal directions is controlled experiments. However, controlled experiments that can disentangle the direction of causality in this case are challenging because it involves controlling biotic or abiotic niche breadth. These challenges create an opportunity for computational tools to detect the most likely causal direction. Here, by adapting a set of recently developed computational methods, we provide strong evidence that generalism drives abundance, overturning the previously established direction. We hope our work raises awareness of the potential for computational discovery methods to address long-standing questions in ecology, especially increasingly large datasets become available.

Pollinator richness, pollination networks, and diet adjustment along local and landscape gradients of resource diversity

Loss of habitats and native species, introduction of invasive species, and changing climate regimes lead to the homogenization of landscapes and communities, affecting the availability of habitats and resources for economically important guilds, such as pollinators. Understanding how pollinators and their interactions vary along resource diversity gradients at different scales may help to determine their adaptability to the current diversity loss related to global change. We used data on 20 plant-pollinator communities along gradients of flower richness (local diversity) and landscape heterogeneity (landscape diversity) to understand how the diversity of resources at local and landscape scales affected (1) wild pollinator abundance and richness (accounting also for honey bee abundance), (2) the structure of plant-pollinator networks, (3) the proportion of actively selected interactions (those not occurring by neutral processes), and (4) pollinator diet breadth and species' specialization in networks. Wild pollinator abundance was higher overall in flower-rich and heterogeneous habitats, while wild pollinator richness increased with flower richness (more strongly for beetles and wild bees) and decreased with honeybee abundance. Network specialization (H₂ '), modularity, and functional complementarity were all positively related to floral richness and landscape heterogeneity, indicating niche segregation as the diversity of resources increases at both scales. Flower richness also increased the proportion of actively selected interactions (especially for wild bees and flies), whereas landscape heterogeneity had a weak negative effect on this variable. Overall, network-level metrics responded to larger landscape scales than pollinator-level metrics did. Higher floral richness resulted in a wider taxonomic and functional diet for all the study guilds, while functional diet increased mainly for beetles. Despite this, specialization in networks (d') increased with flower richness for all the study guilds, because pollinator species fed on a narrower subset of plants as communities became richer in species. Our study indicates that pollinators are able to adapt their diet to resource changes at local and landscape scales. However, resource homogenization might lead to poor and generalist pollinator communities, where functionally specialized interactions are lost. This study highlights the importance of including different scales to understand the effects of global change on pollination service through changes in resource diversity.

The Native Bees of Texas: Evaluating the Benefits of a Public Engagement Course

Simple Summary

As concerns over bee population declines have entered the public consciousness worldwide, people are eager to learn about bees, the roles they play in our world, and how to conserve them. However, the public’s growing enthusiasm and efforts to conserve bees in North America are not always matched by their scientific knowledge of native bees. To satisfy a growing regional demand for knowledge about native bees, we have developed a public engagement program that aims to provide basic information about the native bees of Texas and their conservation guidelines based on science. At the University of Texas, Austin, we designed an outreach course with the objectives of teaching basic identification, diversity, ecology, and conservation of native bees and we implemented it on university botanical garden grounds. To gauge the course’s impact and quality, we integrated assessment tools into the course design. Evaluation results indicated that the course had a positive impact on participants who acquired specific topic knowledge and skills. The outreach course helped educate the public on native bees and benefitted participants, such as landowners and citizen scientists, who intended to apply their acquired knowledge and skills to specific conservation projects. It is relevant and timely to offer such courses, especially in regions that represent biodiversity hotspots for native bees and whose habitat is being fragmented and altered by rapid urbanization.

Abstract

Declines in native bee communities due to forces of global change have become an increasing public concern. Despite this heightened interest, there are few publicly available courses on native bees, and little understanding of how participants might benefit from such courses. In October of 2018 and 2019, we taught the ‘Native Bees of Texas’ course to the public at The University of Texas at Austin Lady Bird Johnson Wildflower Center botanical gardens in an active learning environment with slide-based presentations, printed photo-illustrated resources, and direct insect observations. In this study, we evaluated course efficacy and learning outcomes with a pre/post-course test, a survey, and open-ended feedback, focused on quality improvement findings. Overall, participants’ test scores increased significantly, from 60% to 87% correct answers in 2018 and from 64% to 87% in 2019, with greater post-course differences in ecological knowledge than in identification skills. Post-course, the mean of participants’ bee knowledge self-ratings was 4.56 on a five-point scale. The mean of participants’ ratings of the degree to which they attained the course learning objectives was 4.43 on a five-point scale. Assessment results provided evidence that the course enriched participants’ knowledge of native bee ecology and conservation and gave participants a basic foundation in bee identification. This highlights the utility of systematic course evaluations in public engagement efforts related to biodiversity conservation.

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.

Size and isolation of naturally isolated habitats do not affect plant-bee interactions: A case study of ferruginous outcrops within the eastern Amazon forest

Pollination may be severely affected by the decreasing size and increasing isolation of habitat patches. However, most studies that have considered the effects of these two variables on plant-pollinator interactions have been carried out in areas that have undergone anthropogenic fragmentation, and little is known about their effects in natural habitats. The Carajás National Forest and Campos Ferruginosos National Park are two protected areas in the eastern Amazon where one can find isolated ferruginous outcrops characterized by iron-rich soil and herbaceous-shrub vegetation surrounded by Amazon forest. These patches of canga provide an opportunity to analyze plant-pollinator interactions in naturally fragmented areas. Our objective was to test whether the size and isolation of naturally isolated outcrops located in Carajás affect plant-pollinator interactions by using pollination syndromes and interaction networks. We determined the pollination syndromes of 771 plant species that occurred in eleven canga patches and performed field work to analyze plant-pollinator networks in nine canga patches. The structure of the plant-pollinator networks was not affected by the size or isolation of the canga patches. Generalist species were present in all canga areas, indicating that they are important in maintaining the plant communities in isolated canga patches. The lack of significance related to the distance between canga patches suggests that the forest does not prevent pollinator movement between canga patches.

An individual-based model for the eco-evolutionary emergence of bipartite interaction networks

How ecological interaction networks emerge on evolutionary time scales remains unclear. Here we build an individual-based eco-evolutionary model for the emergence of mutualistic, antagonistic and neutral bipartite interaction networks. Exploring networks evolved under these scenarios, we find three main results. First, antagonistic interactions tend to foster species and trait diversity, while mutualistic interactions reduce diversity. Second, antagonistic interactors evolve higher specialisation, which results in networks that are often more modular than neutral ones; resource species in these networks often display phylogenetic conservatism in interaction partners. Third, mutualistic interactions lead to networks that are more nested than neutral ones, with low phylogenetic conservatism in interaction partners. These results tend to match overall empirical trends, demonstrating that structures of empirical networks that have most often been explained by ecological processes can result from an evolutionary emergence. Our model contributes to the ongoing effort of better integrating ecological interactions and macroevolution.

The geographical variation of network structure is scale dependent: understanding the biotic specialization of host-parasitoid networks

Research on the structure of ecological networks suggests that a number of universal patterns exist. Historically, biotic specialization has been thought to increase towards the Equator. Yet, recent studies have challenged this view showing non-conclusive results. Most studies analysing the geographical variation in biotic specialization focus, however, only on the local scale. Little is known about how the geographical variation of network structure depends on the spatial scale of observation (i.e., from local to regional spatial scales). This should be remedied, as network structure changes as the spatial scale of observation changes, and the magnitude and shape of these changes can elucidate the mechanisms behind the geographical variation in biotic specialization. Here we analyse four facets of biotic specialization in host-parasitoid networks along gradients of climatic constancy, classifying the networks according to their spatial extension (local or regional). Namely, we analyse network connectance, consumer diet overlap, consumer diet breadth, and resource vulnerability at both local and regional scales along the gradients of both current climatic constancy and historical climatic change. While at the regional scale none of the climatic variables are associated to biotic specialization, at the local scale, network connectance, consumer diet overlap, and resource vulnerability decrease with current climatic constancy, whereas consumer generalism increases (i.e., broader diet breadths in tropical areas). Similar patterns are observed along the gradient of historical climatic change. We provide an explanation based on different beta-diversity for consumers and resources across the geographical gradients. Our results show that the geographical gradient of biotic specialization is not universal. It depends on both the facet of biotic specialization and the spatial scale of observation.

Bipartite graphs in systems biology and medicine: a survey of methods and applications

The latest advances in high-throughput techniques during the past decade allowed the systems biology field to expand significantly. Today, the focus of biologists has shifted from the study of individual biological components to the study of complex biological systems and their dynamics at a larger scale. Through the discovery of novel bioentity relationships, researchers reveal new information about biological functions and processes. Graphs are widely used to represent bioentities such as proteins, genes, small molecules, ligands, and others such as nodes and their connections as edges within a network. In this review, special focus is given to the usability of bipartite graphs and their impact on the field of network biology and medicine. Furthermore, their topological properties and how these can be applied to certain biological case studies are discussed. Finally, available methodologies and software are presented, and useful insights on how bipartite graphs can shape the path toward the solution of challenging biological problems are provided.

Identifying species at coextinction risk when detection is imperfect: Model evaluation and case study

Losing a species from a community can cause further extinctions, a process also known as coextinction. The risk of being extirpated with an interaction partner is commonly inferred from a species’ host-breadth, derived from observing interactions between species. But observational data suffers from imperfect detection, making coextinction estimates highly unreliable. To address this issue and to account for data uncertainty, we fit a hierarchical N-mixture model to individual-level interaction data from a mutualistic network. We predict (1) with how many interaction partners each species interacts (to indicate their coextinction risk) and (2) how completely the community was sampled. We fit the model to simulated interactions to investigate how variation in sampling effort, interaction probability, and animal abundances influence model accuracy and apply it to an empirical dataset of flowering plants and their insect visitors. The model performed well in predicting the number of interaction partners for scenarios with high abundances, but indicated high parameter uncertainty for networks with many rare species. Yet, model predictions were generally closer to the true value than the observations. Our mutualistic plant-insect community most closely resembled the scenario of high interaction rates with low abundances. Median estimates of interaction partners were frequently much higher than the empirical data indicate, but uncertainty was high. Our analysis suggested that we only detected 14-59% of the flower-visiting insect species, indicating that our study design, which is common for pollinator studies, was inadequate to detect many species. Imperfect detection strongly affects the inferences from observed interaction networks and hence, host specificity, specialisation estimates and network metrics from observational data may be highly misleading for assessing a species’ coextinction risks. Our study shows how models can help to estimate coextinction risk, but also indicates the need for better data (i.e., intensified sampling and individual-level observations) to reduce uncertainty.

Degree heterogeneity and stability of ecological networks

A classic measure of ecological stability describes the tendency of a community to return to equilibrium after small perturbations. While many advances show how the network architecture of these communities severely constrains such tendencies, one of the most fundamental properties of network structure, i.e. degree heterogeneity-the variability of the number of links associated with each species, deserves further study. Here we show that the effects of degree heterogeneity on stability vary with different types of interspecific interactions. Degree heterogeneity consistently destabilizes ecological networks with both competitive and mutualistic interactions, while its effects on networks of predator-prey interactions such as food webs depend on prey contiguity, i.e. the extent to which the species consume an unbroken sequence of prey in community niche space. Increasing degree heterogeneity tends to stabilize food webs except those with the highest prey contiguity. These findings help explain why food webs are highly but not completely interval and, more broadly, deepen our understanding of the stability of complex ecological networks.

Measuring partner choice in plant-pollinator networks: using null models to separate rewiring and fidelity from chance

Recent studies of mutualistic networks show that interactions between partners change across years. Both biological mechanisms and chance could drive these patterns, but the relative importance of these factors has not been separated. We established a field experiment consisting of 102 monospecific plots of 17 native plant species, from which we collected 6713 specimens of 52 bee species over four years. We used these data and a null model to determine whether bee species' foraging choices varied more or less over time beyond the variation expected by chance. Thus we provide the first quantitative definition of rewiring and fidelity as these terms are used in the literature on interaction networks. All 52 bee species varied in plant partner choice across years, but for 27 species this variation was indistinguishable from random partner choice. Another 11 species showed rewiring, varying more across years than expected by chance, while 14 species showed fidelity, indicating that they both prefer certain plant species and are consistent in those preferences across years. Our study shows that rewiring and fidelity both exist in mutualist networks, but that once sampling effects have been accounted for, they are less common than has been reported in the ecological literature.

A Neutral Model for the Evolution of Diet Breadth

Variation in diet breadth among organisms is a pervasive feature of the natural world that has resisted general explanation. In particular, trade-offs in the ability to use one resource at the expense of another have been expected but rarely detected. We explore a spatial model for the evolution of specialization, motivated by studies of plant-feeding insects. The model is neutral with respect to the causes and consequences of diet breadth: the number of hosts utilized is not constrained by trade-offs, and specialization or generalization does not confer a direct advantage with respect to the persistence of populations or the probability of diversification. We find that diet breadth evolves in ways that resemble reports from natural communities. Simulated communities are dominated by specialized species, with a predictable but less species-rich component of generalized taxa. These results raise the possibility that specialization might be a consequence of stochastic diversification dynamics acting on spatially segregated consumer-resource associations rather than a trait either favored or constrained directly by natural selection. Finally, our model generates hypotheses for global patterns of herbivore diet breadth, including a positive effect of host richness and a negative effect of evenness in host plant abundance on the number of specialized taxa.

Influence of plant resistance traits in selectiveness and species strength in a tropical plant-herbivore network

PREMISE OF THE STUDY

Plant-herbivore networks are highly specialized in their interactions, yet they are highly variable with regard to the relative importance of specific host species for herbivores. How host species traits determine specialization and species strength in this antagonistic network is still an unanswered question that we addressed in this study.

METHODS

We assessed plant cover and antiherbivore resistance traits to assess the extent to which they accounted for the variation in specialization and strength of interactions among species in a plant-herbivore network. We studied a tropical antagonistic network including a diverse herbivore-host plant assemblages in different habitat types and climatic seasons, including host plants with different life histories.

KEY RESULTS

Particular combinations of leaf toughness, trichome density, and phenolic compounds influenced herbivore specialization and host species strength, but with a significant spatiotemporal variation among plant life histories. Conversely, plant-herbivore network parameters were not influenced by plant cover.

CONCLUSIONS

Our study highlights the importance of species-specific resistance traits of plants to understand the ecological and evolutionary consequences of plant-herbivore interaction networks. The novelty of our research lies in the use of a trait-based approach to understand the variation observed in diverse plant-herbivore networks.

Plantas, polinizadores e algumas articulações da biologia da polinização com a teoria ecológica

Resumo A consolidação em uma área do conhecimento acontece principalmente quando as informações acerca de um determinado fato ou fenômeno são sistematizadas na forma de uma teoria explicativa, capaz de gerar novas hipóteses testáveis. Na biologia da polinização, o teste de diversas hipóteses ecológicas permitiu ampliar o entendimento sobre os processos que originam, mantêm, alteram ou ainda excluem as interações entre plantas e visitantes florais, gerando os padrões observados na natureza. Visando sintetizar esse panorama teórico e oferecer condições para que novas questões relacionadas ao funcionamento de interações de polinização sejam geradas, compilamos aqui um conjunto de 25 hipóteses, ideias e teorias ecológicas que fornecem aporte conceitual para a área. Essas ideias estão relacionadas a aspectos reprodutivos, morfológicos, cognitivos, macroecológicos e de coexistência, de acordo com a especialização das interações entre as plantas e seus polinizadores. Ao apresentarmos essas ideias principais, esperamos promover a utilização de uma abordagem teórico-conceitual explícita no planejamento e desenvolvimento de estudos em biologia da polinização. Concluímos com a expectativa de que essa contribuição direcione os estudos em biologia da polinização no Brasil e contribua para o avanço e internacionalização das pesquisas desenvolvidas no país.

Geographical variation in the heterogeneity of mutualistic networks

Plant-animal mutualistic networks are characterized by highly heterogeneous degree distributions. The majority of species interact with few partner species, while a small number are highly connected to form network hubs that are proposed to play an important role in community stability. It has not been investigated, however, if or how the degree distributions vary among types of mutualisms or communities, or between plants and animals in the same network. Here, we evaluate the degree distributions of pollination and seed-dispersal networks, which are two major types of mutualistic networks that have often been discussed in parallel, using an index based on Pielou's evenness. Among 56 pollination networks we found strong negative correlation of the heterogeneity between plants and animals, and geographical shifts of network hubs from plants in temperate regions to animals in the tropics. For 28 seed-dispersal networks, by contrast, the correlation was positive, and there is no comparable geographical pattern. These results may be explained by evolution towards specialization in the presence of context-dependent costs that occur if plants share the animal species as interaction partner. How the identity of network hubs affects the stability and resilience of the community is an important question for future studies.

The effects of climatic fluctuations and extreme events on running water ecosystems

Most research on the effects of environmental change in freshwaters has focused on incremental changes in average conditions, rather than fluctuations or extreme events such as heatwaves, cold snaps, droughts, floods or wildfires, which may have even more profound consequences. Such events are commonly predicted to increase in frequency, intensity and duration with global climate change, with many systems being exposed to conditions with no recent historical precedent. We propose a mechanistic framework for predicting potential impacts of environmental fluctuations on running-water ecosystems by scaling up effects of fluctuations from individuals to entire ecosystems. This framework requires integration of four key components: effects of the environment on individual metabolism, metabolic and biomechanical constraints on fluctuating species interactions, assembly dynamics of local food webs, and mapping the dynamics of the meta-community onto ecosystem function. We illustrate the framework by developing a mathematical model of environmental fluctuations on dynamically assembling food webs. We highlight (currently limited) empirical evidence for emerging insights and theoretical predictions. For example, widely supported predictions about the effects of environmental fluctuations are: high vulnerability of species with high per capita metabolic demands such as large-bodied ones at the top of food webs; simplification of food web network structure and impaired energetic transfer efficiency; and reduced resilience and top-down relative to bottom-up regulation of food web and ecosystem processes. We conclude by identifying key questions and challenges that need to be addressed to develop more accurate and predictive bio-assessments of the effects of fluctuations, and implications of fluctuations for management practices in an increasingly uncertain world.

A hybrid behavioural rule of adaptation and drift explains the emergent architecture of antagonistic networks

Ecological processes that can realistically account for network architectures are central to our understanding of how species assemble and function in ecosystems. Consumer species are constantly selecting and adjusting which resource species are to be exploited in an antagonistic network. Here we incorporate a hybrid behavioural rule of adaptive interaction switching and random drift into a bipartite network model. Predictions are insensitive to the model parameters and the initial network structures, and agree extremely well with the observed levels of modularity, nestedness and node-degree distributions for 61 real networks. Evolutionary and community assemblage histories only indirectly affect network structure by defining the size and complexity of ecological networks, whereas adaptive interaction switching and random drift carve out the details of network architecture at the faster ecological time scale. The hybrid behavioural rule of both adaptation and drift could well be the key processes for structure emergence in real ecological networks.

Relative importance of phenotypic trait matching and species' abundances in determining plant-avian seed dispersal interactions in a small insular community

Network theory has provided a general way to understand mutualistic plant-animal interactions at the community level. However, the mechanisms responsible for interaction patterns remain controversial. In this study we use a combination of statistical models and probability matrices to evaluate the relative importance of species morphological and nutritional (phenotypic) traits and species abundance in determining interactions between fleshy-fruited plants and birds that disperse their seeds. The models included variables associated with species abundance, a suite of variables associated with phenotypic traits (fruit diameter, bird bill width, fruit nutrient compounds), and the species identity of the avian disperser. Results show that both phenotypic traits and species abundance are important determinants of pairwise interactions. However, when considered separately, fruit diameter and bill width were more important in determining seed dispersal interactions. The effect of fruit compounds was less substantial and only important when considered together with abundance-related variables and/or the factor 'animal species'.

Heterogeneity in ecological mutualistic networks dominantly determines community stability

Although the hypothesis that nestedness determines mutualistic ecosystem dynamics is accepted in general, results of some recent data analyses and theoretical studies have begun to cast doubt on the impact of nestedness on ecosystem stability. However, definite conclusions have not yet been reached because previous studies are mainly based on numerical simulations. Therefore, we reveal a mathematical architecture in the relationship between ecological mutualistic networks and local stability based on spectral graph analysis. In particular, we propose a theoretical method for estimating the dominant eigenvalue (i.e., spectral radius) of quantitative (or weighted) bipartite networks by extending spectral graph theory, and provide a theoretical prediction that the heterogeneity of node degrees and link weights primarily determines the local stability; on the other hand, nestedness additionally affects it. Numerical simulations demonstrate the validity of our theory and prediction. This study emphasizes the importance of ecological network heterogeneity in ecosystem dynamics, and it enhances our understanding of structure–stability relationships.

Individual-based ant-plant networks: diurnal-nocturnal structure and species-area relationship

Despite the importance and increasing knowledge of ecological networks, sampling effort and intrapopulation variation has been widely overlooked. Using continuous daily sampling of ants visiting three plant species in the Brazilian Neotropical savanna, we evaluated for the first time the topological structure over 24 h and species-area relationships (based on the number of extrafloral nectaries available) in individual-based ant-plant networks. We observed that diurnal and nocturnal ant-plant networks exhibited the same pattern of interactions: a nested and non-modular pattern and an average level of network specialization. Despite the high similarity in the ants’ composition between the two collection periods, ant species found in the central core of highly interacting species totally changed between diurnal and nocturnal sampling for all plant species. In other words, this “night-turnover” suggests that the ecological dynamics of these ant-plant interactions can be temporally partitioned (day and night) at a small spatial scale. Thus, it is possible that in some cases processes shaping mutualistic networks formed by protective ants and plants may be underestimated by diurnal sampling alone. Moreover, we did not observe any effect of the number of extrafloral nectaries on ant richness and their foraging on such plants in any of the studied ant-plant networks. We hypothesize that competitively superior ants could monopolize individual plants and allow the coexistence of only a few other ant species, however, other alternative hypotheses are also discussed. Thus, sampling period and species-area relationship produces basic information that increases our confidence in how individual-based ant-plant networks are structured, and the need to consider nocturnal records in ant-plant network sampling design so as to decrease inappropriate inferences.

Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model

Ecological interaction networks, such as those describing the mutualistic interactions between plants and their pollinators or between plants and their frugivores, exhibit non-random structural properties that cannot be explained by simple models of network formation. One factor affecting the formation and eventual structure of such a network is its evolutionary history. We argue that this, in many cases, is closely linked to the evolutionary histories of the species involved in the interactions. Indeed, empirical studies of interaction networks along with the phylogenies of the interacting species have demonstrated significant associations between phylogeny and network structure. To date, however, no generative model explaining the way in which the evolution of individual species affects the evolution of interaction networks has been proposed. We present a model describing the evolution of pairwise interactions as a branching Markov process, drawing on phylogenetic models of molecular evolution. Using knowledge of the phylogenies of the interacting species, our model yielded a significantly better fit to 21% of a set of plant - pollinator and plant - frugivore mutualistic networks. This highlights the importance, in a substantial minority of cases, of inheritance of interaction patterns without excluding the potential role of ecological novelties in forming the current network architecture. We suggest that our model can be used as a null model for controlling evolutionary signals when evaluating the role of other factors in shaping the emergence of ecological networks.

When is an ecological network complex? Connectance drives degree distribution and emerging network properties

Connectance and degree distributions are important components of the structure of ecological networks. In this contribution, we use a statistical argument and simple network generating models to show that properties of the degree distribution are driven by network connectance. We discuss the consequences of this finding for (1) the generation of random networks in null-model analyses, and (2) the interpretation of network structure and ecosystem properties in relationship with degree distribution.

Plant-pollinator coextinctions and the loss of plant functional and phylogenetic diversity

Plant-pollinator coextinctions are likely to become more frequent as habitat alteration and climate change continue to threaten pollinators. The consequences of the resulting collapse of plant communities will depend partly on how quickly plant functional and phylogenetic diversity decline following pollinator extinctions. We investigated the functional and phylogenetic consequences of pollinator extinctions by simulating coextinctions in seven plant-pollinator networks coupled with independent data on plant phylogeny and functional traits. Declines in plant functional diversity were slower than expected under a scenario of random extinctions, while phylogenetic diversity often decreased faster than expected by chance. Our results show that plant functional diversity was relatively robust to plant-pollinator coextinctions, despite the underlying rapid loss of evolutionary history. Thus, our study suggests the possibility of uncoupled responses of functional and phylogenetic diversity to species coextinctions, highlighting the importance of considering both dimensions of biodiversity explicitly in ecological studies and when planning for the conservation of species and interactions.

Impact of compatibility on the organization of mutualistic networks

Distinct relationships such as activation, inhibition, cooperation, and competition are not established independently but in a correlated manner in complex systems. Thus the patterns of one type of interaction may reflect the impacts of other classes of interactions, but its quantitative understanding remains to be done. Referring to the plant-pollinator mutualistic networks, here we propose and investigate the structural features of a model bipartite network, in which the mutualistic relationship between two different types of nodes is established under the influence of the compatibility among the nodes of the same type. Interestingly, we find that the degree distributions obtained for extremely broad compatibility distributions are similar to those for a constant compatibility, both of which deviate from those for the Gaussian compatibility distributions. We present the analytic arguments to explain this finding. Also the dependence of the topological similarity of two nodes on their compatibility is illustrated. We discuss the application of our findings to complex systems.

The dissimilarity of species interaction networks

In a context of global changes, and amidst the perpetual modification of community structure undergone by most natural ecosystems, it is more important than ever to understand how species interactions vary through space and time. The integration of biogeography and network theory will yield important results and further our understanding of species interactions. It has, however, been hampered so far by the difficulty to quantify variation among interaction networks. Here, we propose a general framework to study the dissimilarity of species interaction networks over time, space or environments, allowing both the use of quantitative and qualitative data. We decompose network dissimilarity into interactions and species turnover components, so that it is immediately comparable to common measures of β-diversity. We emphasise that scaling up β-diversity of community composition to the β-diversity of interactions requires only a small methodological step, which we foresee will help empiricists adopt this method. We illustrate the framework with a large dataset of hosts and parasites interactions and highlight other possible usages. We discuss a research agenda towards a biogeographical theory of species interactions.

The network structure of plant-arbuscular mycorrhizal fungi

Ecological network theory predicts that in mutualistic systems specialists tend to interact with a subset of species with which generalists interact (i.e. nestedness). Approaching plant-arbuscular mycorrhizal fungi (AMF) association using network analyses will allow the generality of this pattern to be expanded to the ubiquitous plant-AMF mutualism. Based on certain plant-AMF specificity recently suggested, networks are expected to be nested as a result of their mutualistic nature, and modular, with certain species interacting more tightly than others. Network analyses were used to test for nestedness and modularity and to compare the different contribution of plant and AMF to the overall nestedness. Plant-AMF networks share general network properties with other mutualisms. Plant species with few AMFs in their roots tend to associate with those AMFs recorded in most plant species. AMFs present in a few plant species occur in plant species sheltering most AMF (i.e. nestedness). This plant-AMF network presents weakly interlinked subsets of species, strongly connected internally (i.e. modularity). Both plants and AMF show a nested structure, although AMFs have lower nestedness than plants. The plant-AMF interaction pattern is interpreted in the context of how plant-AMF associations can be underlying mechanisms shaping plant community assemblages.