Motifs in the assembly of food web networks

Trophic tug-of-war: Coexistence mechanisms within and across trophic levels

Ecological communities encompass rich diversity across multiple trophic levels. While modern coexistence theory has been widely applied to understand community assembly, its traditional formalism only allows assembly within a single trophic level. Here, using an expanded definition of niche and fitness differences applicable to multitrophic communities, we study how diversity within and across trophic levels affects species coexistence. If each trophic level is analysed separately, both lower- and higher trophic levels are governed by the same coexistence mechanisms. In contrast, if the multitrophic community is analysed as a whole, different trophic levels are governed by different coexistence mechanisms: coexistence at lower trophic levels is predominantly limited by fitness differences, whereas coexistence at higher trophic levels is predominantly limited by niche differences. This dichotomy in coexistence mechanisms is supported by theoretical derivations, simulations of phenomenological and trait-based models, and a case study of a primeval forest ecosystem. Our work provides a general and testable prediction of coexistence mechanism operating in multitrophic communities.

Imprints of indirect interactions on a resource-mediated ant-plant network across different levels of network organization

Indirect interactions are pivotal in the evolution of interacting species and the assembly of populations and communities. Nevertheless, despite recently being investigated in plant-animal mutualism at the community level, indirect interactions have not been studied in resource-mediated mutualisms involving plant individuals that share different animal species as partners within a population (i.e., individual-based networks). Here, we analyzed an individual-based ant-plant network to evaluate how resource properties affect indirect interaction patterns and how changes in indirect links leave imprints in the network across multiple levels of network organization. Using complementary analytical approaches, we described the patterns of indirect interactions at the micro-, meso-, and macro-scale. We predicted that plants offering intermediate levels of nectar quantity and quality interact with more diverse ant assemblages. The increased number of ant species would cause a higher potential for indirect interactions in all scales evaluated. We found that nectar properties modified patterns of indirect interactions of plant individuals that share mutualistic partners, leaving imprints across different network scales. To our knowledge, this is the first study tracking indirect interactions in multiple scales within an individual-based network. We show that functional traits of interacting species, such as nectar properties, may lead to changes in indirect interactions, which could be tracked across different levels of the network organization evaluated.

Potential extinction cascades in a desert ecosystem: Linking food web interactions to community viability

Desert communities are threatened with species loss due to climate change, and their resistance to such losses is unknown. We constructed a food web of the Mojave Desert terrestrial community (300 nodes, 4080 edges) to empirically examine the potential cascading effects of bird extinctions on this desert network, compared to losses of mammals and lizards. We focused on birds because they are already disappearing from the Mojave, and their relative thermal vulnerabilities are known. We quantified bottom-up secondary extinctions and evaluated the relative resistance of the community to losses of each vertebrate group. The impact of random bird species loss was relatively low compared to the consequences of mammal (causing the greatest number of cascading losses) or reptile loss, and birds were relatively less likely to be in trophic positions that could drive top-down effects in apparent competition and tri-tropic cascade motifs. An avian extinction cascade with year-long resident birds caused more secondary extinctions than the cascade involving all bird species for randomized ordered extinctions. Notably, we also found that relatively high interconnectivity among avian species has formed a subweb, enhancing network resistance to bird losses.

The role of intra-guild indirect interactions in assembling plant-pollinator networks

Understanding the assembly of plant-pollinator communities has become critical to their conservation given the rise of species invasions, extirpations, and species' range shifts. Over the course of assembly, colonizer establishment produces core interaction patterns, called motifs, which shape the trajectory of assembling network structure. Dynamic assembly models can advance our understanding of this process by linking the transient dynamics of colonizer establishment to long-term network development. In this study, we investigate the role of intra-guild indirect interactions and adaptive foraging in shaping the structure of assembling plant-pollinator networks by developing: 1) an assembly model that includes population dynamics and adaptive foraging, and 2) a motif analysis tracking the intra-guild indirect interactions of colonizing species throughout their establishment. We find that while colonizers leverage indirect competition for shared mutualistic resources to establish, adaptive foraging maintains the persistence of inferior competitors. This produces core motifs in which specialist and generalist species coexist on shared mutualistic resources which leads to the emergence of nested networks. Further, the persistence of specialists develops richer and less connected networks which is consistent with empirical data. Our work contributes new understanding and methods to study the effects of species' intra-guild indirect interactions on community assembly.

Ecological network assembly: how the regional metaweb influences local food webs

1. Local food webs result from a sequence of colonisations and extinctions by species from the regional pool or metaweb, i.e., the assembly process. Assembly is theorised to be a selective process: whether or not certain species or network structures can persist is partly determined by local processes including habitat filtering and dynamical constraints. Consequently, local food web structure should reflect these processes. 2. The goal of this study was to test evidence for these selective processes by comparing the structural properties of real food webs to the expected distribution given the metaweb. We were particularly interested in ecological dynamics; if the network properties commonly associated with dynamical stability are indeed the result of stability constraints, then they should deviate from expectation in the direction predicted by theory. 3. To create a null expectation, we used the novel approach of randomly assembling model webs by drawing species and interactions from the empirical metaweb. The assembly model permitted colonisation and extinction, and required a consumer species to have at least one prey, but had no habitat type nor population dynamical constraints. Three data sets were used: (1) the marine Antarctic metaweb, with 2 local food-webs; (2) the 50 lakes of the Adirondacks; and (3) the arthropod community from Florida Keys' classic defaunation experiment. 4. Contrary to our expectations, we found that there were almost no differences between empirical webs and those resulting from the null assembly model. Few empirical food webs showed significant differences with network properties, motif representations and topological roles. Network properties associated with stability did not deviate from expectation in the direction predicted by theory. 5. Our results suggest that - for the commonly used metrics we considered - local food web structure is not strongly influenced by dynamical nor habitat restrictions. Instead, the structure is inherited from the metaweb. This suggests that the network properties typically attributed as causes or consequences of ecological stability are instead a by-product of the assembly process (i.e., spandrels), and may potentially be too coarse to detect the true signal of dynamical constraint.

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.

The multiple meanings of omnivory influence empirical, modular theory and whole food web stability relationships

The persistence of whole communities hinges on the presence of select interactions which act to stabilize communities making the identification of these keystone interactions critical. One potential candidate is omnivory, yet theoretical research on omnivory thus far has been dominated by a modular theory approach whereby an omnivore and consumer compete for a shared resource. Empirical research, however, has highlighted the presence of a broader suite of omnivory modules. Here, we integrate empirical data analysis and mathematical models to explore the influence of both omnivory module (including classic, multi-resource, higher level, mutual predation and cannibalism) and omnivore-resource interaction type on food web stability. We use six classic empirical food webs to examine the prevalence of the different types of omnivory, a multi-species consumer-resource model to determine the stability of these different kinds of omnivory within a module context, and finally extend these models to a 50 species, whole food web model to examine the influence of omnivory on whole food web persistence. Our results challenge the concept that omnivory is broadly stabilizing. In particular, we demonstrate that the impact of omnivory depends on the type of omnivory being examined with multi-resource omnivory having the largest correlation with whole food web persistence. Moreover, our results highlight that we need to exercise caution when scaling modular theory to whole food web theory. Cannibalism, for example, was the most persistent and stable omnivory module in the modular theory analysis, but only demonstrated a weak correlation with whole food web persistence. Lastly, our results demonstrate that the frequency of omnivory modules are more important for whole food web persistence than the frequency of omnivore-resource interactions. Together, these results demonstrate that the role of omnivory often depends both on the type of omnivory being examined and the food web within which it is nested. In whole food web models, omnivory acts less as a keystone interaction, rather, specific types of omnivory, particularly multi-resource omnivory, act as keystone modules. Future work integrating module and whole food web theory is critical for resolving the role of key interactions in food webs.

Replication timing networks reveal a link between transcription regulatory circuits and replication timing control

DNA replication occurs in a defined temporal order known as the replication timing (RT) program and is regulated during development, coordinated with 3D genome organization and transcriptional activity. However, transcription and RT are not sufficiently coordinated to predict each other, suggesting an indirect relationship. Here, we exploit genome-wide RT profiles from 15 human cell types and intermediate differentiation stages derived from human embryonic stem cells to construct different types of RT regulatory networks. First, we constructed networks based on the coordinated RT changes during cell fate commitment to create highly complex RT networks composed of thousands of interactions that form specific functional subnetwork communities. We also constructed directional regulatory networks based on the order of RT changes within cell lineages, and identified master regulators of differentiation pathways. Finally, we explored relationships between RT networks and transcriptional regulatory networks (TRNs) by combining them into more complex circuitries of composite and bipartite networks. Results identified novel trans interactions linking transcription factors that are core to the regulatory circuitry of each cell type to RT changes occurring in those cell types. These core transcription factors were found to bind cooperatively to sites in the affected replication domains, providing provocative evidence that they constitute biologically significant directional interactions. Our findings suggest a regulatory link between the establishment of cell-type-specific TRNs and RT control during lineage specification.

Understanding the Mechanisms Behind the Response to Environmental Perturbation in Microbial Mats: A Metagenomic-Network Based Approach

To date, it remains unclear how anthropogenic perturbations influence the dynamics of microbial communities, what general patterns arise in response to disturbance, and whether it is possible to predict them. Here, we suggest the use of microbial mats as a model of study to reveal patterns that can illuminate the ecological processes underlying microbial dynamics in response to stress. We traced the responses to anthropogenic perturbation caused by water depletion in microbial mats from Cuatro Cienegas Basin (CCB), Mexico, by using a time-series spatially resolved analysis in a novel combination of three computational approaches. First, we implemented MEBS (Multi-genomic Entropy-Based Score) to evaluate the dynamics of major biogeochemical cycles across spatio-temporal scales with a single informative value. Second, we used robust Time Series-Ecological Networks (TS-ENs) to evaluate the total percentage of interactions at different taxonomic levels. Lastly, we utilized network motifs to characterize specific interaction patterns. Our results indicate that microbial mats from CCB contain an enormous taxonomic diversity with at least 100 phyla, mainly represented by members of the rare biosphere (RB). Statistical ecological analyses point out a clear involvement of anaerobic guilds related to sulfur and methane cycles during wet versus dry conditions, where we find an increase in fungi, photosynthetic, and halotolerant taxa. TS-ENs indicate that in wet conditions, there was an equilibrium between cooperation and competition (positive and negative relationships, respectively), while under dry conditions there is an over-representation of negative relationships. Furthermore, most of the keystone taxa of the TS-ENs at family level are members of the RB and the microbial mat core highlighting their crucial role within the community. Our results indicate that microbial mats are more robust to perturbation due to redundant functions that are likely shared among community members in the highly connected TS-ENs with density values close to one (≈0.9). Finally, we provide evidence that suggests that a large taxonomic diversity where all community members interact with each other (low modularity), the presence of permanent of low-abundant taxa, and an increase in competition can be potential buffers against environmental disturbance in microbial mats.

SuperNoder: a tool to discover over-represented modular structures in networks

Background

Networks whose nodes have labels can seem complex. Fortunately, many have substructures that occur often (“motifs”). A societal example of a motif might be a household. Replacing such motifs by named supernodes reduces the complexity of the network and can bring out insightful features. Doing so repeatedly may give hints about higher level structures of the network. We call this recursive process Recursive Supernode Extraction.

Results

This paper describes algorithms and a tool to discover disjoint (i.e. non-overlapping) motifs in a network, replacing those motifs by new nodes, and then recursing. We show applications in food-web and protein-protein interaction (PPI) networks where our methods reduce the complexity of the network and yield insights.

Conclusions

SuperNoder is a web-based and standalone tool which enables the simplification of big graphs based on the reduction of high frequency motifs. It applies various strategies for identifying disjoint motifs with the goal of enhancing the understandability of networks.

Network Analyses Can Advance Above-Belowground Ecology

An understanding of above-belowground (AG-BG) ecology is important for evaluating how plant interactions with enemies, symbionts, and decomposers affect species diversity and will respond to global changes. However, research questions and experiments often focus on only a limited number of interactions, creating an incomplete picture of how entire communities may be involved in AG-BG community ecology. Therefore, a pressing challenge is to formulate hypotheses of AG-BG interactions when considering communities in their full complexity. Here we discuss how network analyses can be a powerful tool to progress AG-BG research, link across scales from individual to community and ecosystem, visualize community interactions between the two (AG and BG) subsystems, and develop testable hypotheses.