Bipartite Interaction Networks Research Articles

Important pollinator species for conserving rare plant species endemic to San Clemente Island, California

Much effort has been spent on the conservation of rare, threatened, and endangered plants in the biodiversity hotspot of the California Floristic Province, however little is known about the identity of their pollinators. In this study we provide the first formal study on the identity of the invertebrate pollinators of five rare endemic island plant species from San Clemente Island, the southernmost of the California Channel Islands: Delphinium variegatum ssp kinkiense, Lithophragma maximum, Malacothamnus clementinus, Malva assurgentiflora ssp glabra, and Sibara filifolia. We surveyed plant-pollinator interactions at populations of each focal plant species using timed sweep-netting. We used pollinator capture data to compile bipartite interaction networks for each plant population, and calculated centrality indices (degree, betweenness centrality, and closeness centrality) of pollinators to identify species important to network stability. We found a significant effect of pollinator taxonomic group (fly, bee, wasp, or Lepidopteran) on some indices of pollinator centrality in interaction networks, and variation in pollinator centrality between different locations. Hoverflies, moths, and butterflies were important generalists with higher network centrality across all plant populations, while bees tended to be more specialists within their networks, except for the Malva assurgentiflora ssp glabra network, where bees were on average of higher centrality than flies. We recommend targeted restoration practices for future study that could support pollination both directly and indirectly to focal rare plant species of conservation interest across plant populations. These practices could augment general pollinator conservation best practices such as reducing pesticide use and planting native plant species to provide increased pollination to endangered plants.

Fossil leaves reveal drivers of herbivore functional diversity during the Cenozoic

Herbivorous arthropods are the most diverse group of multicellular organisms on Earth. The most discussed drivers of their inordinate taxonomic and functional diversity are high niche availability associated with the diversity of host plants and dense niche packing due to host partitioning among herbivores. However, the relative contributions of these two factors to dynamics in the diversity of herbivores throughout Earth's history remain unresolved. Using fossil data on herbivore-induced leaf damage from across the Cenozoic, we infer quantitative bipartite interaction networks between plants and functional feeding types of herbivores. We fit a general model of diversity to these interaction networks and discover that host partitioning among functional groups of herbivores contributed twice as much to herbivore functional diversity as host diversity. These findings indicate that niche packing primarily shaped the dynamics in the functional diversity of herbivores during the past 66 my. Our study highlights how the fossil record can be used to test fundamental theories of biodiversity and represents a benchmark for assessing the drivers of herbivore functional diversity in modern ecosystems.

Do closely related species interact with similar partners? Testing for phylogenetic signal in bipartite interaction networks

Whether interactions between species are conserved on evolutionary time-scales has spurred the development of both correlative and process-based approaches for testing phylogenetic signal in interspecific interactions: do closely related species interact with similar partners? Here we use simulations to test the statistical performances of the two approaches that are the most widely used in the field: Mantel tests and the Phylogenetic Bipartite Linear Model (PBLM). Mantel tests investigate the correlation between phylogenetic distances and dissimilarities in sets of interacting partners, while PBLM is a process-based approach that relies on strong assumptions about how interactions evolve. We find that PBLM often detects a phylogenetic signal when it should not. Simple Mantel tests instead have infrequent false positives and moderate statistical power; however, they often artifactually detect that closely related species interact with dissimilar partners. Partial Mantel tests, which are used to partial out the phylogenetic signal in the number of partners, actually fail at correcting for this confounding effect, and we instead recommend evaluating the significance of Mantel tests with network permutations constraining the number of partners. We also explore the ability of simple Mantel tests to analyze clade- specific phylogenetic signals. We provide general guidelines and an application on an interaction network between orchids and mycorrhizal fungi.

Fish-parasite interaction networks reveal latitudinal and taxonomic trends in the structure of host-parasite associations.

In recent years, treating host–parasite associations as bipartite interaction networks has proven a powerful tool to identify structural patterns and their likely causes in communities of fish and their parasites. Network analysis allows for both community-level properties to be computed and investigated, and species-level roles to be determined. Here, using data from 31 host–parasite interaction networks from local fish communities around the world, we test for latitudinal trends at whole-network level, and taxonomic patterns at individual parasite species level. We found that while controlling for network size (number of species per network), network modularity, or the tendency for the network to be subdivided into groups of species that interact mostly with each other, decreased with increasing latitude. This suggests that tropical fish–parasite networks may be more stable than those from temperate regions in the event of community perturbations, such as species extinction. At the species level, after accounting for the effect of host specificity, we observed no difference in the centrality of parasite species within networks between parasites with different transmission modes. However, species in some taxa, namely branchiurans, acanthocephalans and larval trematodes, generally had higher centrality values than other parasite taxa. Because species with a central position often serve as module connectors, these 3 taxa may play a key role in whole-network cohesion. Our results highlight the usefulness of network analysis to reveal the aspects of fish–parasite community interactions that would otherwise remain hidden and advance our understanding of their evolution.

More than meets the eye: decrypting diversity reveals hidden interaction specificity between frogs and frog‐biting midges

1. Female frog‐biting midges (Diptera: Corethrellidae) eavesdrop on the nocturnal mating calls of their blood hosts – male frogs. Available data suggest variable degrees of specialisation among Corethrella‐host associations, with limited information on the mechanisms involved in host selection and partitioning on a community level.2. Our study provides a first comprehensive analysis of host interactions for a neotropical community of frog‐biting midges, based on both morphological and molecular genetic species delimitation. We used quantitative bipartite interaction networks to investigate host specificity among the midge‐frog community of La Gamba, Pacific lowland Costa Rica.3. Midges that were collected directly from frog hosts (16 frog species) showed more pronounced levels of specificity (network‐wide degree of specialisation: H2′ = 0.3) than those caught with acoustic traps broadcasting their calls (12 frog species; H2′ = 0.08). This indicates that, despite a rather generalist acoustic foraging behaviour, frog‐biting midges discriminate between potential hosts by using additional close‐range recognition cues.4. Based on COI and ITS2 sequencing data, we identified considerable levels of cryptic diversity within our five Corethrella morphotypes, with at least 17 distinct MOTUs of Corethrella in La Gamba. Including these MOTUs in bipartite network analyses produced higher resolution in species interactions, and increased estimators of network specificity (H2′ = 0.42).

LifeWebs: A (global) database of bipartite ecological interaction networks

The structure and dynamics of ecological interactions are nowadays recognized as a crucial challenge to comprehend the assembly, functioning and maintenance of ecological communities, their processes and the services they provide. Nevertheless, while standards and databases for information on species occurrences, traits and phylogenies have been established, interaction networks have lagged behind on the development of these standards. Here, we discuss the challenges and our experiences in developing a global database of bipartite interaction networks. LifeWebs*1 is an effort to compile community-level interaction networks from both published and unpublished sources. We focus on bipartite networks that comprise one specific type of interaction between two groups of species (e.g., plants and herbivores, hosts and parasites, mammals and their microbiota), which are usually presented in a co-occurrence matrix format. However, with LifeWebs, we attempt to go beyond simple matrices by integrating relevant metadata from the studies, especially sampling effort, explicit species information (traits and taxonomy/phylogeny), and environmental/geographic information on the communities. Specifically, we explore 1) the unique aspects of community-level interaction networks when compared to data on single inter-specific interactions, occurrence data, and other biodiversity data and how to integrate these different data types. 2) The trade-off between user friendliness in data input/output vs. machine-readable formats, especially important when data contributors need to provide large amounts of data usually compiled in a non-machine-readable format. 3) How to have a single framework that is general enough to include disparate interaction types while retaining all the meaningful information. We envision LifeWebs to be in a good position to test a general standard for interaction network data, with a large variety of already compiled networks that encompass different types of interactions. We provide a framework for integration with other types of data, and formalization of the data necessary to represent networks into established biodiversity standards.

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

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

Food Web Designer: a flexible tool to visualize interaction networks.

Species are embedded in complex networks of ecological interactions and assessing these networks provides a powerful approach to understand what the consequences of these interactions are for ecosystem functioning and services. This is mandatory to develop and evaluate strategies for the management and control of pests. Graphical representations of networks can help recognize patterns that might be overlooked otherwise. However, there is a lack of software which allows visualizing these complex interaction networks. Food Web Designer is a stand-alone, highly flexible and user friendly software tool to quantitatively visualize trophic and other types of bipartite and tripartite interaction networks. It is offered free of charge for use on Microsoft Windows platforms. Food Web Designer is easy to use without the need to learn a specific syntax due to its graphical user interface. Up to three (trophic) levels can be connected using links cascading from or pointing towards the taxa within each level to illustrate top-down and bottom-up connections. Link width/strength and abundance of taxa can be quantified, allowing generating fully quantitative networks. Network datasets can be imported, saved for later adjustment and the interaction webs can be exported as pictures for graphical display in different file formats. We show how Food Web Designer can be used to draw predator–prey and host-parasitoid food webs, demonstrating that this software is a simple and straightforward tool to graphically display interaction networks for assessing pest control or any other type of interaction in both managed and natural ecosystems from an ecological network perspective.Electronic supplementary materialThe online version of this article (doi:10.1007/s10340-015-0686-7) contains supplementary material, which is available to authorized users.

Comparisons and Contrasts between Asymmetry and Nestedness in Interacting Ecological Networks

We compare and contrast asymmetry and nestedness, two concepts used in the characterisation of the specialist-generalist balance in bipartite ecological interaction networks. Our analysis is relevant to mutualistic networks such as those consisting of flowering plants and pollinators, or fruiting plants and frugivores, or antagonistic networks such as those consisting of plants and herbivores, in an ecological community. We shall refer to the two sets of species in the bipartite network as plants and animals, the usual but not the only ecological situation. By asymmetry we mean either connectivity asymmetry or dependence asymmetry, which are essentially equivalent. Asymmetry expresses two attributes: generalists interact preferentially with specialists, and specialists avoid interacting with each other. Nested patterns, in principle, should express these same two features and one more: the presence of a core of interactions among generalists. We compute the full set of perfectly nested patterns that are possible in an L × L matrix with N interactions representing an ecological network of L plants and L animals, and point out that the number of nested arrangements grows exponentially with N. In addition, we analyse asymmetry for the full set of perfectly nested patterns, and identify extremes of asymmetry inside the universe of nested patterns. The minimal asymmetry is marked by a modular core of interactions between species that are neither specialists nor generalists. On the other hand, the case of maximal asymmetry is formed by a set of few generalists and many specialists with equal connectivity. The stereotypic case of nestedness with a core of interactions among generalists has intermediate asymmetry.

Host–parasite nestedness: A result of co-evolving trait-values

Nestedness is an intriguing feature of ecological networks, where those species found in species-depauperate communities are subsets of those found in communities with greater species richness. For bipartite interaction networks, a “community” of species may be thought of as all those pollinating a particular plant, or infecting a particular host, for example. While there is much clear evidence for nestedness in mutualistic webs, host–parasite webs have proven more contentious. There have been a number of suggested causes for nestedness, including an association between the abundance of individuals and the resulting number of species interactions, and the matching of phenotypic traits between species. Questions remain as to the relative importance of these driving factors, especially as host–parasite and mutualistic webs contain completely different interaction types.We propose a model motivated by both of the above factors, considering a trade-off in resources that a species faces in optimizing its transmission or defense. We construct a multi-species model in which both hosts and parasites have limited resources with which to attack or defend themselves from each other. We analyze the evolution of the manner in which they use these resources using adaptive dynamics, to arrive at a final species interaction matrix, which we then test for nestedness. A general model with m hosts and n microparasite species is described here, but results are given for m=n=5, chosen to be a large enough system for patterns to be identified, but not so large that computational time becomes prohibitive.Our results demonstrate that this co-evolution leads to an unusual amount of nestedness when the trade-offs in transmission for parasites are concave, and an unusual amount of anti-nestedness when they are convex. This enables us to predict the circumstances under which we would expect to observe nestedness in real networks.

Species abundance and asymmetric interaction strength in ecological networks

The strength of interactions among species in a network tends to be highly asymmetric. We evaluate the hypothesis that this asymmetry results from the distribution of abundance among species, so that species interactions occur randomly among individuals. We used a database on mutualistic and antagonistic bipartite quantitative interaction networks. We show that across all types of networks asymmetry was correlated with abundance, so that rare species were asymmetrically affected by their abundant partners, while pairs of interacting abundant species tended to exhibit more symmetric, reciprocally strong effects. A null model shows that abundance provides a sufficient explanation of the asymmetry structure in some networks, but suggests the role of additional factors in others. Although not universal, our hypothesis holds for a substantial fraction of networks analyzed here, and should be considered as a null model in all studies aimed at evaluating the ecological and evolutionary consequences of species interactions.