Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks

The network architecture and phylogeographic drivers of interactions between rodents and seed plants at continental scales

Rodents are known to interact with seed plants in three different ways, including predation in situ, scatter hoarding and larder hoarding of seeds. These behaviours span a spectrum from mutualistic seed dispersal to predation, and they are related to species' and environmental characteristics. We used interaction networks to evaluate the structure and drivers of rodent-seed plant interactions, including geography, phylogeny and traits at continental scales. We constructed five aggregated networks, each representing a continent and containing three subnetworks defined by foraging behaviours, tested questions about their network structures and analysed the driving signals shaping rodent-seed plant interactions at network and species levels. Rodent-seed plant networks varied across continents. We found most rodents exhibited a significant propensity for one foraging behaviour and detected significant modular structures in both aggregated networks and subnetworks. We detected significant co-phylogenetic signals between rodents and seed plants. Distance matrix-based regressions on interaction and module dissimilarity of rodents suggest geographical and phylogenetic forces are important in the assembly of rodent-seed plant networks. In addition, multiple species traits correlated with the roles of rodents within aggregated networks; however, the specific traits associated with these roles varied among interaction types. Our results highlight that geography and phylogenetics are dominant in structuring the architecture of rodent-seed plant networks at continental scales and reveal challenges regarding spatial and taxa coverage in rodent-seed plant interactions.

Global effects of land-use intensity and exotic plants on the structure and phylogenetic signal of plant-herbivore networks

Interactions between plants and herbivorous insects are often phylogenetically structured, with closely related insect species using similar sets of species or lineages of plants, while phylogenetically closer plants tend to share high proportions of their herbivore insect species. Notably, these phylogenetic constraints in plant-herbivore interactions tend to be more pronounced among internal plant-feeding herbivores (i.e., endophages) than among external feeders (i.e., exophages). In the context of growing human-induced habitat conversion and the global proliferation of exotic species, it is crucial to understand how ecological networks respond to land-use intensification and the increasing presence of exotic plants. In this study, we analyzed plant-herbivore network data from various locations of the World to ascertain the degree to which land-use intensity and the prevalence of exotic plants induce predictable changes in their network topology - measured by levels of nestedness and modularity - and phylogenetic structures. Additionally, we investigated whether the intimacy of plant-herbivore interactions, contrasting endophagous with exophagous networks, modulate changes in network structure. Our findings reveal that most plant-herbivore networks are characterized by significant phylogenetic and topological structures. However, neither these structures did not show consistent changes in response to increased levels of land-use intensify. On the other hand, for the networks composed of endophagous herbivores, the level of nestedness was higher in the presence of a high proportion of exotic plants. Additionally, for networks of exophagous herbivores, we observed an increase in the phylogenetic structure of interactions due to exotic host dominance. These results underscore the differential impacts of exotic species and land-use intensity on the phylogenetic and topological structures of plant-herbivore networks.

The structure and robustness of ecological networks with two interaction types

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

Fruit fly phylogeny imprints bacterial gut microbiota

One promising avenue for reconciling the goals of crop production and ecosystem preservation consists in the manipulation of beneficial biotic interactions, such as between insects and microbes. Insect gut microbiota can affect host fitness by contributing to development, host immunity, nutrition, or behavior. However, the determinants of gut microbiota composition and structure, including host phylogeny and host ecology, remain poorly known. Here, we used a well-studied community of eight sympatric fruit fly species to test the contributions of fly phylogeny, fly specialization, and fly sampling environment on the composition and structure of bacterial gut microbiota. Comprising both specialists and generalists, these species belong to five genera from to two tribes of the Tephritidae family. For each fly species, one field and one laboratory samples were studied. Bacterial inventories to the genus level were produced using 16S metabarcoding with the Oxford Nanopore Technology. Sample bacterial compositions were analyzed with recent network-based clustering techniques. Whereas gut microbiota were dominated by the Enterobacteriaceae family in all samples, microbial profiles varied across samples, mainly in relation to fly identity and sampling environment. Alpha diversity varied across samples and was higher in the Dacinae tribe than in the Ceratitinae tribe. Network analyses allowed grouping samples according to their microbial profiles. The resulting groups were very congruent with fly phylogeny, with a significant modulation of sampling environment, and with a very low impact of fly specialization. Such a strong imprint of host phylogeny in sympatric fly species, some of which share much of their host plants, suggests important control of fruit flies on their gut microbiota through vertical transmission and/or intense filtering of environmental bacteria.

From insect-plant interactions to ecological networks

Abstract Since its inception, biodiversity has largely been understood as species diversity and assessed as such. Interactions among species or functional groups are gradually becoming part of an expanded concept of biodiversity. As a case study of the development of a research program in biodiversity, we summarize our multi-decade studies on interactions of Asteraceae and flowerhead-feeding insects in Brazil. Initially, host species were treated as independent replicates in order to assess the local and turnover components of their herbivore diversity. Research then expanded into sampling entire interactive communities of host plants and their associated herbivores in different localities and regions, enabling new research lines to be pursued. Interaction diversity could be assessed and factored into spatial and among-host components, suggesting a new field of interaction geography. Second, host specialization, a key component of interaction diversity, was reframed considering simultaneously relatedness and local availability of plant hosts. Third, with the influence of complex network theory, community-wide species interactions were probed for topological patterns. Having identified the modular structure of these plant-herbivore systems, later we demonstrated that they fit a compound hierarchical topology, in which interactions are nested within large-scale modules. In a brief survey of research funded by Fapesp, especially within the Biota-Fapesp program, we highlight several lines of internationally recognized research on interaction diversity, notably on plant-frugivore and plant-pollinator interactions, together with new theoretical models. The interplay of field studies with new theoretical and analytical approaches has established interaction diversity as an essential component for monitoring, conserving and restoring biodiversity in its broader sense.

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

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

Related plants tend to share pollinators and herbivores, but strength of phylogenetic signal varies among plant families

Related plants are often hypothesized to interact with similar sets of pollinators and herbivores, but this idea has only mixed empirical support. This may be because plant families vary in their tendency to share interaction partners. We quantify overlap of interaction partners for all pairs of plants in 59 pollination and 11 herbivory networks based on the numbers of shared and unshared interaction partners (thereby capturing both proportional and absolute overlap). We test for relationships between phylogenetic distance and partner overlap within each network; whether these relationships varied with the composition of the plant community; and whether well-represented plant families showed different relationships. Across all networks, more closely related plants tended to have greater overlap. The strength of this relationship within a network was unrelated to the composition of the network's plant component, but, when considered separately, different plant families showed different relationships between phylogenetic distance and overlap of interaction partners. The variety of relationships between phylogenetic distance and partner overlap in different plant families probably reflects a comparable variety of ecological and evolutionary processes. Considering factors affecting particular species-rich groups within a community could be the key to understanding the distribution of interactions at the network level.

Adaptive learning in non-social insects: from theory to field work, and back

We review the evidence that learning affects fitness in non-social insects. Early accounts date back from the 1970s and were based on field-based observational and experimental work, yet exploration of the ways in which various forms of learning increase fitness remains limited in non-social insects. We highlight the concerns that arise when artificial laboratory settings, which do not take the ecology of the species into account, are used to estimate fitness benefits of learning. We argue that ecologically-relevant experimental designs are most useful to provide fitness estimates of learning, that is, designs that include: firstly, offspring of wild-caught animals producing newly established stocks under relevant breeding conditions, combined with common-garden and reciprocal transplant experiments; secondly, the spatio-temporal dynamics of key ecological resources; and thirdly, the natural behaviours of the animals while searching for, and probing, resources. Finally, we provide guidelines for the study of fitness-learning relationships in an eco-evolutionary framework.