Food-web structure and network theory: The role of connectance and size

Food webs for three burn severities after wildfire in the Eldorado National Forest, California

Wildfire dynamics are changing around the world and understanding their effects on ecological communities and landscapes is urgent and important. We report detailed food webs for unburned, low-to-moderate and high severity burned habitats three years post-fire in the Eldorado National Forest, California. The cumulative cross-habitat food web contains 3,084 ontogenetic stages (nodes) or plant parts comprising 849 species (including 107 primary producers, 634 invertebrates, 94 vertebrates). There were 178,655 trophic interactions between these nodes. We provide information on taxonomy, body size, biomass density and trophic interactions under each of the three burn conditions. We detail 19 sampling methods deployed across 27 sites (nine in each burn condition) used to estimate the richness, body size, abundance and biomass density estimates in the node lists. We provide the R code and raw data to estimate summarized node densities and assign trophic links.

Temporal and spatial changes in benthic invertebrate trophic networks along a taxonomic richness gradient

Species interactions underlie most ecosystem functions and are important for understanding ecosystem changes. Representing one type of species interaction, trophic networks were constructed from biodiversity monitoring data and known trophic links to assess how ecosystems have changed over time. The Baltic Sea is subject to many anthropogenic pressures, and low species diversity makes it an ideal candidate for determining how pressures change food webs. In this study, we used benthic monitoring data for 20 years (1980-1989 and 2010-2019) from the Swedish coast of the Baltic Sea and Skagerrak to investigate changes in benthic invertebrate trophic interactions. We constructed food webs and calculated fundamental food web metrics evaluating network horizontal and vertical diversity, as well as stability that were compared over space and time. Our results show that the west coast of Sweden (Skagerrak) suffered a reduction in benthic invertebrate biodiversity by 32% between the 1980s and 2010s, and that the number of links, generality of predators, and vulnerability of prey have been significantly reduced. The other basins (Bothnian Sea, Baltic Proper, and Bornholm Basin) do not show any significant changes in species richness or consistent significant trends in any food web metrics investigated, demonstrating resilience at a lower species diversity. The decreased complexity of the Skagerrak food webs indicates vulnerability to further perturbations and pressures should be limited as much as possible to ensure continued ecosystem functions.

Eigenvalue ratio statistics of complex networks: Disorder versus randomness

The distribution of the ratios of consecutive eigenvalue spacings of random matrices has emerged as an important tool to study spectral properties of many-body systems. This article numerically investigates the eigenvalue ratios distribution of various model networks, namely, small-world, Erdős-Rényi random, and (dis)assortative random having a diagonal disorder in the corresponding adjacency matrices. Without any diagonal disorder, the eigenvalues ratio distribution of these model networks depict Gaussian orthogonal ensemble (GOE) statistics. Upon adding diagonal disorder, there exists a gradual transition from the GOE to Poisson statistics depending upon the strength of the disorder. The critical disorder (w_{c}) required to procure the Poisson statistics increases with the randomness in the network architecture. We relate w_{c} with the time taken by maximum entropy random walker to reach the steady state. These analyses will be helpful to understand the role of eigenvalues other than the principal one for various network dynamics such as transient behavior.

Food web rewiring drives long-term compositional differences and late-disturbance interactions at the community level

Multiple anthropogenic disturbances affect the structure and functioning of communities. Recent evidence highlighted that, after pulse disturbance, the functioning a community performs may be recovered fast due to functional redundancy, whereas community multivariate composition needs a longer time. Yet, the mechanisms that drive the different community recovery times have not been quantified empirically. We use quantitative food-web analysis to assess the influence of species interactions on community recovery. We found species-interactions strength to be the main mechanism driving differences between structural and functional recovery. Additionally, we show that interactions between multiple disturbances appear in the long term only when both species-interaction strength and food-web architecture change significantly.

Ecological communities are constantly exposed to multiple natural and anthropogenic disturbances. Multivariate composition (if recovered) has been found to need significantly more time to be regained after pulsed disturbance compared to univariate diversity metrics and functional endpoints. However, the mechanisms driving the different recovery times of communities to single and multiple disturbances remain unexplored. Here, we apply quantitative ecological network analyses to try to elucidate the mechanisms driving long-term community-composition dissimilarity and late-stage disturbance interactions at the community level. For this, we evaluate the effects of two pesticides, nutrient enrichment, and their interactions in outdoor mesocosms containing a complex freshwater community. We found changes in interactions strength to be strongly related to compositional changes and identified postdisturbance interaction-strength rewiring to be responsible for most of the observed compositional changes. Additionally, we found pesticide interactions to be significant in the long term only when both interaction strength and food-web architecture are reshaped by the disturbances. We suggest that quantitative network analysis has the potential to unveil ecological processes that prevent long-term community recovery.

The Self-Organization of Marine Microbial Networks under Evolutionary and Ecological Processes: Observations and Modeling

Simple Summary

The properties and structure of ecological networks in marine microbial communities determine ecosystem functions and stability; however, the principles of microbial network assemblages are poorly understood. In this study, we revealed the influences of species phylogeny and niches on the self-organization of marine microbial co-occurrence networks and provided a mathematical framework to simulate microbial network assemblages. Our results provide deep insights into network stability from the perspective of network assembly principles and not just network properties, such as complexity and modularity.

Abstract

Evolutionary and ecological processes are primary drivers of ecological network constrictions. However, the ways that these processes underpin self-organization and modularity in networks are poorly understood. Here, we performed network analyses to explore the evolutionary and ecological effects on global marine microbial co-occurrence networks across multiple network levels, including those of nodes, motifs, modules and whole networks. We found that both direct and indirect species interactions were evolutionarily and ecologically constrained across at least four network levels. Compared to ecological processes, evolutionary processes generally showed stronger long-lasting effects on indirect interactions and dominated the network assembly of particle-associated communities in spatially homogeneous environments. Regarding the large network path distance, the contributions of either processes to species interactions generally decrease and almost disappear when network path distance is larger than six. Accordingly, we developed a novel mathematical model based on scale-free networks by considering the joint effects of evolutionary and ecological processes. We simulated the self-organization of microbial co-occurrence networks and found that long-lasting effects increased network stability via decreasing link gain or loss. Overall, these results revealed that evolutionary and ecological processes played key roles in the self-organization and modularization of microbial co-occurrence networks.

Ecological network complexity scales with area

Larger geographical areas contain more species-an observation raised to a law in ecology. Less explored is whether biodiversity changes are accompanied by a modification of interaction networks. We use data from 32 spatial interaction networks from different ecosystems to analyse how network structure changes with area. We find that basic community structure descriptors (number of species, links and links per species) increase with area following a power law. Yet, the distribution of links per species varies little with area, indicating that the fundamental organization of interactions within networks is conserved. Our null model analyses suggest that the spatial scaling of network structure is determined by factors beyond species richness and the number of links. We demonstrate that biodiversity-area relationships can be extended from species counts to higher levels of network complexity. Therefore, the consequences of anthropogenic habitat destruction may extend from species loss to wider simplification of natural communities.

Land snail assemblages and microhabitat preferences in the urban areas of Kolkata, India

Due to the minimal dispersal capabilities and dependency on particular microhabitat, the land snails are susceptible to anthropogenic and natural disturbances. Considering the increasing anthropogenic threats, especially in urban areas, information on species’ requirements for particular habitat is very essential for land snail conservation and sustenance. In the present commentary, diversity and distribution of small-sized land snails in relation to their microhabitat preference in urban habitats of Kolkata, West Bengal, had been carried out through the quadrat method. The information on the richness and abundance of snails and their habitat places in Kolkata, India, was used to construct a bipartite network. A total of 13 land snail species were linked with 16 microhabitats. The network indices were used to justify the specialist or generalist nature of the snail species in the context of microhabitat preference. The snail species Succinea daucina and Allopeas gracile were observed to be associated with the maximum number of habitats while species strength was highest for S. daucina. The low value of connectance (0.288, <0.5) and niche overlap (0.34), the high value of specialization index H2′ (0.58) and d′ (0.44) indicate that the snail–microhabitat interactions were highly specialized. The network ecology of snail–microhabitats illustrated in the present instance will enable the identification of preferred microhabitats, which are required for the enhancement of the population of land snails in urban areas like Kolkata, India.

Settling moths are the vital component of pollination in Himalayan ecosystem of North-East India, pollen transfer network approach revealed

Majority of the pollination related studies are based on the diurnal pollinators, and the nocturnal pollinators received less scientific attention. We reveal the significance of settling moths in pollination of angiosperm families in Himalayan ecosystem of North-East India. The refined and novel method of pollen extraction from the proboscides provides a more robust assessment of the pollen carrying capacity. The study is based on one of the largest data sets (140 pollen transporter moth species (PTMS)), with interpretation based on seasonal as well as altitudinal data. In the present study about 65% moths (91 species) carried sufficient quantities of pollen grains to be considered as potential pollinators (PPMS). Teliphasa sp. (Crambidae) and Cuculia sp. (Noctuidae) are found to carry the highest quantity of pollen. We found pollen grains of 21 plant families and the abundant pollen are from Betulaceae, Fabaceae, Rosaceae and Ericaceae. Species composition of PTMS and PPMS in pre-monsoon, monsoon, and post-monsoon revealed the dominance of Geometridae. Maximum diversity of PTMS and PPMS is found from 2000 to 2500 m altitude. The nocturnal pollen transfer network matrices exhibited high degree of selectivity (H₂' = 0.86).

Predator interference and complexity-stability in food webs

It is predicted that ecological communities will become unstable with increasing species numbers and subsequent interspecific interactions; however, this is contrary to how natural ecosystems with diverse species respond to changes in species numbers. This contradiction has steered ecologists toward exploring what underlying processes allow complex communities to stabilize even through varying pressures. In this study, a food web model is used to show an overlooked role of interference among multiple predator species in solving this complexity–stability problem. Predator interference in large communities weakens species interactions due to a reduction in consumption rates by prey-sharing species in the presence of predators in response to territorial and aggressive behavior, thereby playing a key stabilizing role in communities. Especially when interspecific interference is strong and a community has diverse species and dense species interactions, stabilization is likely to work and creates a positive complexity–stability relationship within a community. The clear positive effect of complexity on community stability is not reflected by/intraspecific interference, emphasizing the key role of interspecific interference among multiple predator species in maintaining larger systems.

Marine food webs are more complex but less stable in sub-Antarctic (Beagle Channel, Argentina) than in Antarctic (Potter Cove, Antarctic Peninsula) regions

Food web structure plays an important role in determining ecosystem stability against perturbations. High-latitude marine ecosystems are being affected by environmental stressors and biological invasions. In the West Antarctic Peninsula these transformations are mainly driven by climate change, while in the sub-Antarctic region by anthropogenic activities. Understanding the differences between these areas is necessary to monitor the changes that are expected to occur in the upcoming decades. Here, we compared the structure and stability of Antarctic (Potter Cove) and sub-Antarctic (Beagle Channel) marine food webs. We compiled species trophic interactions (predator-prey) and calculated complexity, structure and stability metrics. Even if both food webs presented the same connectance, we found important differences between them. The Beagle Channel food web is more complex, but less stable and sensitive to the loss of its most connected species, while the Potter Cove food web presented lower complexity and greater stability against perturbations.

Response of soil protozoa to acid mine drainage in a contaminated terrace

Acid mine drainage (AMD) system represents one of the most unfavorable habitats for microorganisms due to its low pH and high concentrations of metals. Compared to bacteria and fungi, our understanding regarding the response of soil protozoa to such extremely acidic environments remains limited. This study characterized the structures of protozoan communities inhabiting a terrace heavily contaminated by AMD. The sharp environmental gradient of this terrace was generated by annual flooding from an AMD lake located below, which provided a natural setting to unravel the environment-protozoa interactions. Previously unrecognized protozoa, such as Apicomplexa and Euglenozoa, dominated the extremely acidic soils, rather than the commonly recognized members (e.g., Ciliophora and Cercozoa). pH was the most important factor regulating the abundance of protozoan taxa. Metagenomic analysis of protozoan metabolic potential showed that many functional genes encoding for the alleviation of acid stress and various metabolic pathways were enriched, which may facilitate the survival and adaptation of protozoa to acidic environments. In addition, numerous co-occurrences between protozoa and bacterial or fungal taxa were observed, suggesting shared environmental preferences or potential bio-interactions among them. Future studies are required to confirm the ecological roles of these previously unrecognized protozoa as being important soil microorganisms.

Stability and selective extinction in complex mutualistic networks

We study species abundance in the empirical plant-pollinator mutualistic networks exhibiting broad degree distributions, with uniform intragroup competition assumed, by the Lotka-Volterra equation. The stability of a fixed point is found to be identified by the signs of its nonzero components and those of its neighboring fixed points. Taking the annealed approximation, we derive the nonzero components to be formulated in terms of degrees and the rescaled interaction strengths, which lead us to find different stable fixed points depending on parameters, and we obtain the phase diagram. The selective extinction phase finds small-degree species extinct and effective interaction reduced, maintaining stability and hindering the onset of instability. The nonzero minimum species abundances from different empirical networks show data collapse when rescaled as predicted theoretically.

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.

Dynamical systems on large networks with predator-prey interactions are stable and exhibit oscillations

We analyze the stability of linear dynamical systems defined on sparse, random graphs with predator-prey, competitive, and mutualistic interactions. These systems are aimed at modeling the stability of fixed points in large systems defined on complex networks, such as ecosystems consisting of a large number of species that interact through a food web. We develop an exact theory for the spectral distribution and the leading eigenvalue of the corresponding sparse Jacobian matrices. This theory reveals that the nature of local interactions has a strong influence on a system's stability. We show that, in general, linear dynamical systems defined on random graphs with a prescribed degree distribution of unbounded support are unstable if they are large enough, implying a tradeoff between stability and diversity. Remarkably, in contrast to the generic case, antagonistic systems that contain only interactions of the predator-prey type can be stable in the infinite size limit. This feature for antagonistic systems is accompanied by a peculiar oscillatory behavior of the dynamical response of the system after a perturbation, when the mean degree of the graph is small enough. Moreover, for antagonistic systems we also find that there exist a dynamical phase transition and critical mean degree above which the response becomes nonoscillatory.

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.

Network topology and patch connectivity affect dynamics in experimental and model metapopulations

Biological populations are rarely isolated in space and instead interact with others via dispersal in metapopulations. Theory predicts that network connectivity patterns can have critical effects on network robustness, as certain topologies, such as scale-free networks, are more tolerant to disturbances than other patterns. However, at present, experimental evidence of how these topologies affect population dynamics in a metapopulation framework is lacking. We used experimental metapopulations of the aquatic protist Paramecium tetraurelia to determine how network topology influences occupation patterns. We created metapopulations engineered to be comparable in linkage density, but differing in their degree distribution. We compared random networks to scale-free networks by evaluating local population occupancy and abundance throughout 18-30 protist generations. In parallel, we used simulations to explore differences in patch occupation patterns among topologies. Our experimental results highlighted the importance of the balance between dispersal and extinction in the interaction with spatial network topology. Under low dispersal conditions, random metapopulations of P. tetraurelia reached higher abundance and higher occupancy (proportion of occupied patches) compared to scale-free systems in both experimental and simulated systems. Under high dispersal conditions, we did not detect differences between types of metapopulations. Increasing patch degree (i.e. number of connections per patch) reduced the probability of extinction of local populations in both types of networks. We suggest the interaction between colonization/extinction rates and network topology alters the likelihood of rescue effects which results in differential patterns of occupancy and abundance in metapopulations.

Effects of different types of low-intensity management on plant-pollinator interactions in Estonian grasslands

In the face of global pollinator decline, extensively managed grasslands play an important role in supporting stable pollinator communities. However, different types of extensive management may promote particular plant species and thus particular functional traits. As the functional traits of flowering plant species (e.g., flower size and shape) in a habitat help determine the identity and frequency of pollinator visitors, they can also influence the structures of plant-pollinator interaction networks (i.e., pollination networks). The aim of this study was to examine how the type of low-intensity traditional management influences plant and pollinator composition, the structure of plant-pollinator interactions, and their mediation by floral and insect functional traits. Specifically, we compared mown wooded meadows to grazed alvar pastures in western Estonia. We found that both management types fostered equal diversity of plants and pollinators, and overlapping, though still distinct, plant and pollinator compositions. Wooded meadow pollination networks had significantly higher connectance and specialization, while alvar pasture networks achieved higher interaction diversity at a standardized sampling of interactions. Pollinators with small body sizes and short proboscis lengths were more specialized in their preference for particular plant species and the specialization of individual pollinators was higher in alvar pastures than in wooded meadows. All in all, the two management types promoted diverse plant and pollinator communities, which enabled the development of equally even and nested pollination networks. The same generalist plant and pollinator species were important for the pollination networks of both wooded meadows and alvar pastures; however, they were complemented by management-specific species, which accounted for differences in network structure. Therefore, the implementation of both management types in the same landscape helps to maintain high species and interaction diversity.

A roadmap towards predicting species interaction networks (across space and time)

Networks of species interactions underpin numerous ecosystem processes, but comprehensively sampling these interactions is difficult. Interactions intrinsically vary across space and time, and given the number of species that compose ecological communities, it can be tough to distinguish between a true negative (where two species never interact) from a false negative (where two species have not been observed interacting even though they actually do). Assessing the likelihood of interactions between species is an imperative for several fields of ecology. This means that to predict interactions between species-and to describe the structure, variation, and change of the ecological networks they form-we need to rely on modelling tools. Here, we provide a proof-of-concept, where we show how a simple neural network model makes accurate predictions about species interactions given limited data. We then assess the challenges and opportunities associated with improving interaction predictions, and provide a conceptual roadmap forward towards predictive models of ecological networks that is explicitly spatial and temporal. We conclude with a brief primer on the relevant methods and tools needed to start building these models, which we hope will guide this research programme forward. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

Impact of different types of anthropogenic pollution on bacterial community and metabolic genes in urban river sediments

Sediment bacterial communities play a crucial role in the biogeochemical cycle of nutrient elements in urban river. However, the distribution of nitrogen cycle genes on bacterial communities in urban rivers sediments is largely unknown. Here, 16S rRNA amplicon sequencing was used to analyze the composition, co-occurrence patterns and nitrogen cycle process of bacterial communities in urban river sediments under the influence of different exogenous pollution. The results revealed that bacterial communities had significant spatial heterogeneity in river sediments of different polluted areas, and the input of different exogenous pollutants shaped the abundance and distribution of nitrogen cycle-related genes in the sediments. In addition, denitrification process played a leading role in the nitrogen cycle of river sediments, and the genes associated with the nitrification process were rarely observed in all samples. The important bacterial taxonomic biomarkers of nitrogen cycling-related genes screened by random forest algorithm were Synergistia, WS6_Dojkabacteria and Caldisericia. Meanwhile, different co-occurrence patterns observed in different types of polluted areas clarified the impact of environmental filtration and niche differentiation on bacterial communities. In conclusion, this study reveals the nitrogen cycle process and the distribution of related genes mediated by bacterial communities under the impact of different anthropogenic contamination, and provides novel insights for the assembly of bacterial communities in urban river sediments.

Changes in native and introduced host–parasite networks

Introduced species can alter the dynamics and structure of a native community. Network analysis provides a tool to study host–parasite interactions that can help to predict the possible impact of biological invasions or other disturbances. In this study, we used weighted bipartite networks to assess differences in the interaction patterns between hosts and helminth parasites of native (Sea of Japan) and invasive (Black Sea and Sea of Azov) populations of Planiliza haematocheilus (Teleostei: Mugilidae). We employed three quantitative network descriptors, connectance, weighted nestedness and modularity, to gain insight into the structure of the host–parasite networks in the native and invaded areas. The role of parasite species in the networks was assessed using the betweenness centrality index. We analyzed networks encompassing the whole helminth community and subsets of species classified by their transmission strategy. The analyses were downscaled to host individual-level to consider intraspecific variation in parasite communities. We found significant differences between networks in the native and invaded areas. The latter presented a higher value of nestedness, which may indicate a co-occurrence between parasite species with many connections in the network and species with fewer interactions within the same individual-host. In addition, modularity was higher in the native area’s networks than those of the invaded area, with subgroups of host individuals that interact more frequently with certain parasite species than with others. Only the networks composed of actively transmitted parasites and ectoparasites did not show significant differences in modularity between the Sea of Azov and the Sea of Japan, which could be due to the introduction of a part of the native community into the invaded environment, with a lower diversity and abundance of species. We show that network analysis provides a valuable tool to illuminate the changes that occur in host–parasite interactions when an invasive species and its parasite community are introduced into a new area.

A plant-pollinator metanetwork along a habitat fragmentation gradient

To understand how plant-pollinator interactions respond to habitat fragmentation, we need novel approaches that can capture properties that emerge at broad scales, where multiple communities engage in metanetworks. Here we studied plant-pollinator interactions over 2 years on 29 calcareous grassland fragments selected along independent gradients of habitat size and surrounding landscape diversity of cover types. We associated network centrality of plant-pollinator interactions and grassland fragments with their ecological and landscape traits, respectively. Interactions involving habitat specialist plants and large-bodied pollinators were the most central, implying that species with these traits form the metanetwork core. Large fragments embedded in landscapes with high land cover diversity exhibited the highest centrality; however, small fragments harboured many unique interactions not found on larger fragments. Intensively managed landscapes have reached a point in which all remaining fragments matter, meaning that losing any further areas may vanish unique interactions with unknown consequences for ecosystem functioning.

Reconstructing large interaction networks from empirical time series data

Reconstructing interactions from observational data is a critical need for investigating natural biological networks, wherein network dimensionality is usually high. However, these pose a challenge to existing methods that can quantify only small interaction networks. Here, we proposed a novel approach to reconstruct high-dimensional interaction Jacobian networks using empirical time series without specific model assumptions. This method, named "multiview distance regularised S-map," generalised the state space reconstruction to accommodate high dimensionality and overcome difficulties in quantifying massive interactions with limited data. When evaluating this method using time series generated from theoretical models involving hundreds of interacting species, estimated strengths of interaction Jacobians were in good agreement with theoretical expectations. Applying this method to a natural bacterial community helped identify important species from the interaction network and revealed mechanisms governing the dynamical stability of a bacterial community. The proposed method overcame the challenge of high dimensionality in large natural dynamical systems.

Reinterpreting the relationship between number of species and number of links connects community structure and stability

For 50 years, ecologists have examined how the number of interactions (links) scales with the number of species in ecological networks. Here, we show that the way the number of links varies when species are sequentially removed from a community is fully defined by a single parameter identifiable from empirical data. We mathematically demonstrate that this parameter is network-specific and connects local stability and robustness, establishing a formal connection between community structure and two prime stability concepts. Importantly, this connection highlights a local stability-robustness trade-off, which is stronger in mutualistic than in trophic networks. Analysis of 435 empirical networks confirmed these results. We finally show how our network-specific approach relates to the classical across-network approach found in literature. Taken together, our results elucidate one of the intricate relationships between network structure and stability in community networks.

Graphery: interactive tutorials for biological network algorithms

Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts frequently used in network-based methods. Each tutorial describes a graph concept along with executable Python code that can be interactively run on a graph. Users navigate each tutorial using their choice of real-world biological networks that highlight the diverse applications of network algorithms. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. Graphery accepts ideas for new tutorials and datasets that will be shaped by both computational and biological researchers, growing into a community-contributed learning platform. Graphery is available at https://graphery.reedcompbio.org/.

Does refuge spillover affect arthropod food webs associated with Bt maize?

BACKGROUND

A high dose/refuge combination is the main tactic recommended for mitigating resistance selection of target herbivore species in crops expressing insecticidal proteins of the bacterium Bacillus thuringiensis (i.e. Bt proteins). The tactic consists of the simultaneous use of Bt crops expressing high levels of the Bt protein associated with neighboring areas of refuge of the same non-Bt crop species. Nonetheless, the approach faces controversy regarding its effectiveness and scale of adoption, at least in some regions. One concern focuses on its potential impact on the arthropod community, including its short-term and spatially dependent impact considering the likely biota spillover effect between Bt and non-Bt neighboring areas. Thus, the eventual spillover of Bt maize targeted and non-targeted arthropods was surveyed along transects extending from the refuge border to the center of the Bt maize area.

RESULTS

Arthropods were collected throughout the maize vegetative and reproductive stages. A total of 85 arthropod species were collected, but their richness and abundance did not vary with distance from the refuge. By contrast, cultivation season played a significant role in distinguishing the arthropod communities. Refuge distance from the sampling point within Bt-fields did not significantly affect the food web metrics, unlike season, which affected the number of nodes integrating each food web. Winter maize cultivation exhibited higher arthropod diversity and combined values of species numeric abundance and biomass at each trophic level.

CONCLUSIONS

No arthropod spillover was evident between the refuge edge and Bt maize, adding further controversy to the tactic currently subjected to lower usage in the region with a disputed cost-benefit relationship, because not even the target and its interdependent species were affected. © 2021 Society of Chemical Industry.

Large herbivores transform plant-pollinator networks in an African savanna

Pollination by animals is a key ecosystem service^1,2 and interactions between plants and their pollinators are a model system for studying ecological networks,^3,4 yet plant-pollinator networks are typically studied in isolation from the broader ecosystems in which they are embedded. The plants visited by pollinators also interact with other consumer guilds that eat stems, leaves, fruits, or seeds. One such guild, large mammalian herbivores, are well-known ecosystem engineers^5-7 and may have substantial impacts on plant-pollinator networks. Although moderate herbivory can sometimes promote plant diversity,⁸ potentially benefiting pollinators, large herbivores might alternatively reduce resource availability for pollinators by consuming flowers,⁹ reducing plant density,¹⁰ and promoting somatic regrowth over reproduction.¹¹ The direction and magnitude of such effects may hinge on abiotic context-in particular, rainfall, which modulates the effects of ungulates on vegetation.¹² Using a long-term, large-scale experiment replicated across a rainfall gradient in central Kenya, we show that a diverse assemblage of native large herbivores, ranging from 5-kg antelopes to 4,000-kg African elephants, limited resource availability for pollinators by reducing flower abundance and diversity; this in turn resulted in fewer pollinator visits and lower pollinator diversity. Exclusion of large herbivores increased floral-resource abundance and pollinator-assemblage diversity, rendering plant-pollinator networks larger, more functionally redundant, and less vulnerable to pollinator extinction. Our results show that species extrinsic to plant-pollinator interactions can indirectly and strongly alter network structure. Forecasting the effects of environmental change on pollination services and interaction webs more broadly will require accounting for the effects of extrinsic keystone species.

Distributive stress: individually variable responses to hypoxia expand trophic niches in fish

Environmental stress can reshape trophic interactions by excluding predators or rendering prey vulnerable, depending on the relative sensitivity of species to the stressor. Classical models of food web responses to stress predict either complete predator exclusion from stressed areas or complete prey vulnerability if predators are stress tolerant. However, if the consumer response to the stress is individually variable, the result may be a distributive stress model (DSM) whereby predators distribute consumption pressure across a range of prey guilds and their trophic niche is expanded. We test these models in one of the largest hypoxic “Dead Zones” in the world, the northern Gulf of Mexico, by combining geochemical tracers of hypoxia exposure and isotope ratios to assess individual‐level trophic responses. Hypoxia‐exposed fish occupied niche widths that were 14.8% and 400% larger than their normoxic counterparts in two different years, consistent with variable displacement from benthic to pelagic food webs. The degree of isotopic displacement depended on the magnitude of hypoxia exposure. These results are consistent with the DSM and highlight the need to account for individually variable sublethal effects when predicting community responses to environmental stress.

A modified niche model for generating food webs with stage-structured consumers: The stabilizing effects of life-history stages on complex food webs

Almost all organisms grow in size during their lifetime and switch diets, trophic positions, and interacting partners as they grow. Such ontogenetic development introduces life-history stages and flows of biomass between the stages through growth and reproduction. However, current research on complex food webs rarely considers life-history stages. The few previously proposed methods do not take full advantage of the existing food web structural models that can produce realistic food web topologies.We extended the niche model developed by Williams and Martinez (Nature, 2000, 404, 180-183) to generate food webs that included trophic species with a life-history stage structure. Our method aggregated trophic species based on niche overlap to form a life-history structured population; therefore, it largely preserved the topological structure of food webs generated by the niche model. We applied the theory of allometric predator-prey body mass ratio and parameterized an allometric bioenergetic model augmented with biomass flow between stages via growth and reproduction to study the effects of a stage structure on the stability of food webs.When life-history stages were linked via growth and reproduction, more food webs persisted, and persisting food webs tended to retain more trophic species. Topological differences between persisting linked and unlinked food webs were small to modest. The slopes of biomass spectra were lower, and weak interaction links were more prevalent in the linked food webs than the unlinked ones, suggesting that a life-history stage structure promotes characteristics that can enhance stability of complex food webs.Our results suggest a positive relationship between the complexity and stability of complex food webs. A life-history stage structure in food webs may play important roles in dynamics of and diversity in food webs.

Fungal-Bacterial Cooccurrence Patterns Differ between Arbuscular Mycorrhizal Fungi and Nonmycorrhizal Fungi across Soil Niches

Soil bacteria and fungi are known to form niche-specific communities that differ between actively growing and decaying roots. Yet almost nothing is known about the cross-kingdom interactions that frame these communities and the environmental filtering that defines these potentially friendly or competing neighbors. We explored the temporal and spatial patterns of soil fungal (mycorrhizal and nonmycorrhizal) and bacterial cooccurrence near roots of wild oat grass, Avena fatua, growing in its naturalized soil in a greenhouse experiment. Amplicon sequences of the fungal internal transcribed spacer (ITS) and bacterial 16S rRNA genes from rhizosphere and bulk soils collected at multiple plant growth stages were used to construct covariation-based networks as a step toward identifying fungal-bacterial associations. Corresponding stable-isotope-enabled metagenome-assembled genomes (MAGs) of bacteria identified in cooccurrence networks were used to inform potential mechanisms underlying the observed links. Bacterial-fungal networks were significantly different in rhizosphere versus bulk soils and between arbuscular mycorrhizal fungi (AMF) and nonmycorrhizal fungi. Over 12 weeks of plant growth, nonmycorrhizal fungi formed increasingly complex networks with bacteria in rhizosphere soils, while AMF more frequently formed networks with bacteria in bulk soils. Analysis of network-associated bacterial MAGs suggests that some of the fungal-bacterial links that we identified are potential indicators of bacterial breakdown and consumption of fungal biomass, while others intimate shared ecological niches.IMPORTANCE Soils near living and decomposing roots form distinct niches that promote microorganisms with distinctive environmental preferences and interactions. Yet few studies have assessed the community-level cooccurrence of bacteria and fungi in these soil niches as plant roots grow and senesce. With plant growth, we observed increasingly complex cooccurrence networks between nonmycorrhizal fungi and bacteria in the rhizosphere, while mycorrhizal fungal (AMF) and bacterial cooccurrence was more pronounced in soil further from roots, in the presence of decaying root litter. This rarely documented phenomenon suggests niche sharing of nonmycorrhizal fungi and bacteria, versus niche partitioning between AMF and bacteria; both patterns are likely driven by C substrate availability and quality. Although the implications of species cooccurrence are fiercely debated, MAGs matching the bacterial nodes in our networks possess the functional potential to interact with the fungi that they are linked to, suggesting an ecological significance of fungal-bacterial cooccurrence patterns.

Energetic constraints imposed on trophic interaction strengths enhance resilience in empirical and model food webs

Food web stability and resilience are at the heart of understanding the structure and functioning of ecosystems. Previous studies show that models of empirical food webs are substantially more stable than random ones, due to a few strong interactions embedded in a majority of weak interactions. Analyses of trophic interaction loops show that in empirical food webs the patterns of the interaction strengths prevent the occurrence of destabilizing heavy loops and thereby enhances resilience. Yet, it is still unexplored which biological mechanisms cause these patterns that enhance food web resilience. We quantified food web resilience using the real part of the maximum eigenvalue of the Jacobian matrix of the food web from a seagrass bed in the Yellow River Delta (YRD) wetland, that could be parametrized by the empirical data of the food web. We found that the empirically based Jacobian matrix of the YRD food web indicated a much higher resilience than random matrices with the same element values but arranged in random ways. Investigating the trophic interaction loops revealed that the high resilience was due to a negative correlation between the negative and positive interaction strengths (per capita top-down and bottom-up effects, respectively) within positive feedback loops with three species. The negative correlation showed that when the negative interaction strengths were strong the positive was weak, and vice versa. Our invented reformulation of loop weight in terms of biomasses and specific production rates showed that energetic properties of the trophic groups in the loop and mass-balance constraints, for example, the food uptake has to balance all losses, created the negative correlation between the interaction strengths. This result could be generalized using a dynamic intraguild predation model, which delivered the same pattern for a wide range of model parameters. Our results shed light on how energetic constraints at the trophic group and food web level create a pattern of interaction strengths within trophic interaction loops that enhances food web resilience.

Utilizing the simple graph convolutional neural network as a model for simulating influence spread in networks

The ability for people and organizations to connect in the digital age has allowed the growth of networks that cover an increasing proportion of human interactions. The research community investigating networks asks a range of questions such as which participants are most central, and which community label to apply to each member. This paper deals with the question on how to label nodes based on the features (attributes) they contain, and then how to model the changes in the label assignments based on the influence they produce and receive in their networked neighborhood. The methodological approach applies the simple graph convolutional neural network in a novel setting. Primarily that it can be used not only for label classification, but also for modeling the spread of the influence of nodes in the neighborhoods based on the length of the walks considered. This is done by noticing a common feature in the formulations in methods that describe information diffusion which rely upon adjacency matrix powers and that of graph neural networks. Examples are provided to demonstrate the ability for this model to aggregate feature information from nodes based on a parameter regulating the range of node influence which can simulate a process of exchanges in a manner which bypasses computationally intensive stochastic simulations.

Multiple urban stressors drive fish-based ecological networks in streams of Columbus, Ohio, USA

Integrating a network perspective into multiple-stressor research can reveal indirect stressor effects and simultaneously estimate both taxonomic and functional community characteristics, thus representing a novel approach to stressor paradigms in rivers. Using six years of data from twelve streams of Columbus, Ohio, USA, the effects of nutrients (N:P), impervious surface (%IS), and sedimentation on network properties were quantified. Variability in the strength and distribution of trophic interactions was assessed by incorporating biomass into networks. All stressors impacted some properties of network topology - linkage density (average number of links per species), connectance (fraction of all possible links realized in a network), and compartmentalization (degree to which networks contain discrete sub-webs), including synergistic interactive effects between sedimentation and stream size. We also found support for antagonistic effects between (1) sedimentation and %IS and between %IS and N:P on the weighted index mean link weight, which represents the magnitude of trophic interactions among species in a network, and (2) %IS and stream size on strength standard deviation, a measure of the distribution of total magnitude of all trophic interactions per species in a network. Overall, our results point to the potential for urban stressors such as impervious surfaces and sedimentation - alone and as interactions - to decrease network complexity, compartmentalization, and stability, likely through homogenizing habitat and limiting food resources. The observation that larger streams often buffered the negative effects of these stressors suggests that restoration and other management approaches might be most beneficial in smaller headwater streams of urban catchments.

Improving insect conservation across heterogeneous landscapes using species-habitat networks

Background

One of the biggest challenges in conservation is to manage multiple habitats for the effective conservation of multiple species, especially when the focal species are mobile and use multiple resources across heterogeneous protected areas. The application of ecological network tools and the analysis of the resulting species–habitat networks can help to describe such complex spatial associations and improve the conservation of species at the landscape scale.

Methods

To exemplify the application of species–habitat networks, we present a case study on butterflies inhabiting multiple grassland types across a heterogeneous protected area in North-East Italy. We sampled adult butterflies in 44 sites, each belonging to one of the five major habitat types in the protected area, that is, disturbed grasslands, continuous grasslands, evolved grasslands, hay meadows and wet meadows. First, we applied traditional diversity analyses to explore butterfly species richness and evenness. Second, we built and analyzed both the unipartite network, linking habitat patches via shared species, and the bipartite network, linking species to individual habitat patches.

Aims

(i) To describe the emerging properties (connectance, modularity, nestedness, and robustness) of the species–habitat network at the scale of the whole protected area, and (ii) to identify the key habitats patches for butterfly conservation across the protected area, that is, those supporting the highest number of species and those with unique species assemblages (e.g., hosting specialist species).

Results

The species–habitat network appeared to have a weak modular structure, meaning that the main habitat types tended to host different species assemblages. However, the habitats also shared a large proportion of species that were able to visit multiple habitats and use resources across the whole study area. Even butterfly species typically considered as habitat specialists were actually observed across multiple habitat patches, suggesting that protecting them only within their focal habitat might be ineffective. Our species–habitat network approach helped identifying both central habitat patches that were able to support the highest number of species, and habitat patches that supported rare specialist species.