Ecological networks--beyond food webs

Host-parasitoid trophic webs in complex agricultural systems

The composition and dynamics of ecological communities are complex because of the presence of large numbers of organisms, belonging to many different species, each with their own evolutionary history, and their numerous interactions. The construction and analysis of trophic webs summarize interactions across trophic levels and link community structure to properties such as ecosystem services. We focus on agroecological communities, which may be simpler than natural communities but nonetheless present considerable challenges to describe and understand. We review the characteristics and study of communities comprised of plants, phytophagous insects, and insect parasitoids with particular regard to the maintenance of sustainable agroecological communities and ecosystem services, especially biological pest control. We are constrained to largely overlook other members of these communities, such as hyperparasitoids, predators, parasites, and microbes. We draw chiefly on recent literature while acknowledging the importance of many advances made during the immediately preceding decades. Trophic web construction and analysis can greatly improve the understanding of the role and impact of herbivores and natural enemies in agroecological communities and the various species interactions, such as apparent competition, which assists biocontrol strategies. The study of trophic webs also helps in predicting community ecology consequences of externally driven changes to agroecosystems.

Neighbourhood benthic configuration reveals hidden co-occurrence social diversity

Ecological interactions among benthic communities are crucial for shaping marine ecosystems. Understanding these interactions is essential for predicting how ecosystems will respond to environmental changes, invasive species, and conservation management. However, determining the prevalence of species interactions at the community scale is challenging. To overcome this challenge, we employ tools from social network analysis, specifically exponential random graph modelling (ERGM). Our approach explores the relationships among animal and plant organisms within their neighbourhoods. Inspired by companion planting in agriculture, we use spatiotemporal co-occurrence as a measure of mixed species interaction. In other words, the variety of community interactions based on co-occurrence defines what we call 'co-occurrence social diversity'. Our objective is to use ERGM to quantify the proportion of interactions at both the simple paired level and the more complex triangle level, enabling us to measure and compare co-occurrence social diversity. Applying our approach to the Spanish coastal zone across eight sites, five depths, and sunlit/shaded aspects, we discover that 80% of sessile communities, consisting of over a hundred species, exhibit co-occurrence social diversity, with 5% of species consistently forming associations with other species. These organism-level interactions probably have a significant impact on the overall character of the site. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

The persistence of bipartite ecological communities with Lotka-Volterra dynamics

The assembly and persistence of ecological communities can be understood as the result of the interaction and migration of species. Here we study a single community subject to migration from a species pool in which inter-specific interactions are organised according to a bipartite network. Considering the dynamics of species abundances to be governed by generalised Lotka-Volterra equations, we extend work on unipartite networks to we derive exact results for the phase diagram of this model. Focusing on antagonistic interactions, we describe factors that influence the persistence of the two guilds, locate transitions to multiple-attractor and unbounded phases, as well as identifying a region of parameter space in which consumers are essentially absent in the local community.

Time is of the essence: A general framework for uncovering temporal structures of communities

Ecological communities are inherently dynamic: species constantly turn over within years, months, weeks or even days. These temporal shifts in community composition determine essential aspects of species interactions and how energy, nutrients, information, diseases and perturbations 'flow' through systems. Yet, our understanding of community structure has relied heavily on static analyses not designed to capture critical features of this dynamic temporal dimension of communities. Here, we propose a conceptual and methodological framework for quantifying and analysing this temporal dimension. Conceptually, we split the temporal structure into two definitive features, sequence and duration, and review how they are linked to key concepts in ecology. We then outline how we can capture these definitive features using perspectives and tools from temporal graph theory. We demonstrate how we can easily integrate ongoing research on phenology into this framework and highlight what new opportunities arise from this approach to answer fundamental questions in community ecology. As climate change reshuffles ecological communities worldwide, quantifying the temporal organization of communities is imperative to resolve the fundamental processes that shape natural ecosystems and predict how these systems may change in the future.

Multiple interaction networks reveal that Lepidoptera larvae and adults prefer various host plants for diet and pollination

Plant-Lepidoptera interactions are often studied using the pollination or herbivore networks only. Lepidoptera species are involved in two types of plant-insect interactions because they are herbivores as larvae and pollinators as adults. The study of entangled networks is critical, since the interaction of different networks can affect the overall network and community stability. Here, we studied the interaction of plants and Lepidoptera on the Yongxing Island, South China Sea. A plant-lepidopteran pollination network and a plant-lepidopteran herbivore network were built by using data from flower-pollinator and leaf-herbivore interactions. We then combined the two networks into a single network. We measured plant composition similarity within each sub-network and across sub-networks for Lepidoptera species. Our findings indicate that the plant-Lepidoptera pollination network and the herbivory network share significant proportions of Lepidoptera but small proportions of plant assemblages. The pollination network had higher nestedness and connectance than the herbivore network. Agrius convolvuli was the most specialized species, while Zizina otis had the highest species strength in the pollination network. Most Lepidoptera species were highly specialized in the herbivore network and their importance positively correlated across the two networks. Furthermore, there was no dietary composition similarity between the two networks for most Lepidoptera species. Our findings highlight the visible structural difference between the pollination and the herbivore networks. Adult Lepidoptera selects different plants for oviposition and feeding, a strategy that may benefit their reproduction and survival by sustaining adequate resources for their two life stages and the diversity of both plants and insects in oceanic island communities.

Predator-prey interactions across hunting mode, spatial domain size, and habitat complexities

Predator-prey interactions are a fundamental part of community ecology, yet the relative importance of consumptive and nonconsumptive effects (NCEs) (defined as a risk-induced response that alters prey fitness) has not been resolved. Theory suggests that the emergence and subsequent predominance of consumptive or NCEs depend on the given habitat's complexity as well as predator hunting mode and spatial domain sizes of both predator and prey, but their relative influence on the outcome of predator-prey interactions is unknown. We built agent-based models in NetLogo to simulate predator-prey interactions for three hunting modes-sit-and-wait, sit-and-pursue, and active-while concurrently simulating large versus small spatial domain sizes for both predators and prey. We studied (1) how hunting mode and spatial domain size interact to influence the emergence of consumptive or NCEs and (2) how, when NCEs do dominate, hunting mode and spatial domain separately or additively determine prey shifts in time, space, and habitat use. Our results indicate consumptive effects only dominate for active predators when prey habitat domains overlap completely with the predator's spatial domain and when sit-and-wait and sit-and-pursue predators and their prey both have large spatial domains. Prey are most likely to survive when they shift their time but most frequently shift their habitat. Our paper helps to better understand the underlying mechanisms that drive consumptive or NCEs to be most dominant.

Local and extensive fluctuations in sparsely interacting ecological communities

Ecological communities with many species can be classified into dynamical phases. In systems with all-to-all interactions, a phase where species abundances always reach a fixed point and a phase where they continuously fluctuate have been found. The dynamics when interactions are sparse, with each species interacting with only a few others, has remained largely unexplored. Here we study a system of sparse interactions, first when interactions are of constant strength and completely unidirectional, and then when adding variability and bidirectionality. We show that in this case a phase unique to the sparse setting appears in the phase diagram, where for the same control parameters different communities may reach either a fixed point or a state where the abundances of only a finite subset of species fluctuate, and we calculate the probability for each outcome. These fluctuating species are organized around short cycles in the interaction graph, and their abundances undergo large nonlinear fluctuations. We characterize the approach from this phase to a phase with extensively many fluctuating species, and show that the probability of fluctuations grows continuously to one as the transition is approached, and that the number of fluctuating species diverges. This is qualitatively distinct from the transition to extensive fluctuations coming from a fixed point phase, which is marked by a loss of linear stability. The differences are traced back to the emergent binary character of the dynamics when far from short cycles.

Individual diet variability shapes the architecture of Antarctic benthic food webs

Antarctic biodiversity is affected by seasonal sea-ice dynamics driving basal resource availability. To (1) determine the role of intraspecific dietary variability in structuring benthic food webs sustaining Antarctic biodiversity, and (2) understand how food webs and the position of topologically central species vary with sea-ice cover, single benthic individuals' diets were studied by isotopic analysis before sea-ice breakup and afterwards. Isotopic trophospecies (or Isotopic Trophic Units) were investigated and food webs reconstructed using Bayesian Mixing Models. As nodes, these webs used either ITUs regardless of their taxonomic membership (ITU-webs) or ITUs assigned to species (population-webs). Both were compared to taxonomic-webs based on taxa and their mean isotopic values. Higher resource availability after sea-ice breakup led to simpler community structure, with lower connectance and linkage density. Intra-population diet variability and compartmentalisation were crucial in determining community structure, showing population-webs to be more complex, stable and robust to biodiversity loss than taxonomic-webs. The core web, representing the minimal community 'skeleton' that expands opportunistically while maintaining web stability with changing resource availability, was also identified. Central nodes included the sea-urchin Sterechinus neumayeri and the bivalve Adamussium colbecki, whose diet is described in unprecedented detail. The core web, compartmentalisation and topologically central nodes represent crucial factors underlying Antarctica's rich benthic food web persistence.

A successional shift enhances stability in ant symbiont communities

Throughout succession, communities undergo structural shifts, which can alter the relative abundances of species and how they interact. It is frequently asserted that these alterations beget stability, i.e. that succession selects for communities better able to resist perturbations. Yet, whether and how alterations of network structure affect stability during succession in complex communities is rarely studied in natural ecosystems. Here, we explore how network attributes influence stability of different successional stages of a natural network: symbiotic arthropod communities forming food webs inside red wood ant nests. We determined the abundance of 16 functional groups within the symbiont community across 51 host nests in the beginning and end stages of succession. Nest age was the main driver of the compositional shifts: symbiont communities in old nests contained more even species abundance distributions and a greater proportion of specialists. Based on the abundance data, we reconstructed interaction matrices and food webs of the symbiont community for each nest. We showed that the enhanced community evenness in old nests leads to an augmented food web stability in all but the largest symbiont communities. Overall, this study demonstrates that succession begets stability in a natural ecological network by making the community more even.

Determining the plant-pollinator network in a culturally significant food and medicine garden in the Great Lakes region

Understanding the interactions between plants and pollinators within a system can provide information about pollination requirements and the degree to which species contribute to floral reproductive success. Past research has focused largely on interactions within monocultured agricultural systems and only somewhat on wild pollination networks. This study focuses on the culturally significant Three Sisters Garden, which has been grown and tended by many Indigenous peoples for generations in the Great Lakes Region. Here, the plant-pollinator network of the traditional Three Sisters Garden with the inclusion of some additional culturally significant plants was mapped. Important visitors in this system included the common eastern bumble bee, Bombus impatiens Cresson (Hymenoptera: Apidae), and the hoary squash bee, Xenoglossa pruinosa (Say) (Hymenoptera: Apidae), as determined by their abundances and pollinator service index (PSI) values. Understanding the key pollinators in the Three Sisters Garden links biological diversity to cultural diversity through the pollination of culturally significant plants. Further, this information could be of use in supporting Indigenous food sovereignty by providing knowledge about which wild pollinators could be supported to increase fruit and seed set within the Three Sisters Garden. Our findings can also lead to more effective conservation of important wild pollinator species.

Network topology mapping of chemical compounds space

We define bipartite and monopartite relational networks of chemical elements and compounds using two different datasets of inorganic chemical and material compounds, as well as study their topology. We discover that the connectivity between elements and compounds is distributed exponentially for materials, and with a fat tail for chemicals. Compounds networks show similar distribution of degrees, and feature a highly-connected club due to oxygen . Chemical compounds networks appear more modular than material ones, while the communities detected reveal different dominant elements specific to the topology. We successfully reproduce the connectivity of the empirical chemicals and materials networks by using a family of fitness models, where the fitness values are derived from the abundances of the elements in the aggregate compound data. Our results pave the way towards a relational network-based understanding of the inherent complexity of the vast chemical knowledge atlas, and our methodology can be applied to other systems with the ingredient-composite structure.

Unlocking ensemble ecosystem modelling for large and complex networks

The potential effects of conservation actions on threatened species can be predicted using ensemble ecosystem models by forecasting populations with and without intervention. These model ensembles commonly assume stable coexistence of species in the absence of available data. However, existing ensemble-generation methods become computationally inefficient as the size of the ecosystem network increases, preventing larger networks from being studied. We present a novel sequential Monte Carlo sampling approach for ensemble generation that is orders of magnitude faster than existing approaches. We demonstrate that the methods produce equivalent parameter inferences, model predictions, and tightly constrained parameter combinations using a novel sensitivity analysis method. For one case study, we demonstrate a speed-up from 108 days to 6 hours, while maintaining equivalent ensembles. Additionally, we demonstrate how to identify the parameter combinations that strongly drive feasibility and stability, drawing ecological insight from the ensembles. Now, for the first time, larger and more realistic networks can be practically simulated and analysed.

Power laws in species' biotic interaction networks can be inferred from co-occurrence data

Inferring biotic interactions from species co-occurrence patterns has long intrigued ecologists. Yet recent research revealed that co-occurrences may not reliably represent pairwise biotic interactions. We propose that examining network-level co-occurrence patterns can provide valuable insights into community structure and assembly. Analysing ten bipartite networks of empirically sampled biotic interactions and associated species spatial distribution, we find that approximately 20% of co-occurrences correspond to actual interactions. Moreover, the degree distribution shifts from exponential in co-occurrence networks to power laws in networks of biotic interactions. This shift results from a strong interplay between species' biotic (their interacting partners) and abiotic (their environmental requirements) niches, and is accurately predicted by considering co-occurrence frequencies. Our work offers a mechanistic understanding of the assembly of ecological communities and suggests simple ways to infer fundamental biotic interaction network characteristics from co-occurrence data.

A framework for untangling the consequences of artificial light at night on species interactions

Although much evidence exists showing organismal consequences from artificial light at night (ALAN), large knowledge gaps remain regarding ALAN affecting species interactions. Species interactions occur via shared spatio-temporal niches among species, which may be determined by natural light levels. We review how ALAN is altering these spatio-temporal niches through expanding twilight or full Moon conditions and constricting nocturnal conditions as well as creating patches of bright and dark. We review literature from a database to determine if ALAN is affecting species interactions via spatio-temporal dynamics. The literature indicates a growing interest in ALAN and species interactions: 58% of the studies we analysed have been published since 2020. Seventy-five of 79 studies found ALAN altered species interactions. Enhancements and reductions of species interactions were equally documented. Many studies revealed ALAN affecting species interactions spatially, but few revealed temporal alterations. There are biases regarding species interactions and ALAN-most studies investigated predator-prey interactions with vertebrates as predators and invertebrates as prey. Following this literature review, we suggest avenues, such as remote sensing and animal tracking, that can guide future research on the consequences of ALAN on species interactions across spatial and temporal axes. This article is part of the theme issue 'Light pollution in complex ecological systems'.

Host-microbiota-parasite interactions in two wild sparid fish species, Diplodus annularis and Oblada melanura (Teleostei, Sparidae) over a year: a pilot study

BACKGROUND

The microbiota in fish external mucus is mainly known for having a role in homeostasis and protection against pathogens, but recent evidence suggests it is also involved in the host-specificity of some ectoparasites. In this study, we investigated the influence of seasonality and environmental factors on both fish external microbiota and monogenean gill ectoparasites abundance and diversity and assessed the level of covariations between monogenean and bacterial communities across seasons. To do so, we assessed skin and gill microbiota of two sparid species, Oblada melanura and Diplodus annularis, over a year and collected their specific monogenean ectoparasites belonging to the Lamellodiscus genus.

RESULTS

Our results revealed that diversity and structure of skin and gill mucus microbiota were strongly affected by seasonality, mainly by the variations of temperature, with specific fish-associated bacterial taxa for each season. The diversity and abundance of parasites were also influenced by seasonality, with the abundance of some Lamellodiscus species significantly correlated to temperature. Numerous positive and negative correlations between the abundance of given bacterial genera and Lamellodiscus species were observed throughout the year, suggesting their differential interaction across seasons.

CONCLUSIONS

The present study is one of the first to demonstrate the influence of seasonality and related abiotic factors on fish external microbiota over a year. We further identified potential interactions between gill microbiota and parasite occurrence in wild fish populations, improving current knowledge and understanding of the establishment of host-specificity.

Toward a network perspective in coastal ecosystem management

Environmental management in coastal ecosystems has been challenged by the complex cumulative effects that occur when many small issues result in large ecological shifts. Current environmental management of these spaces focuses on identifying and limiting problematic stressors via a series of assessment techniques. Whilst there is a strong desire among managers to consider complexity in ecological responses to cumulative effects, current approaches for assessing risk focus on breaking down the issues into multiple cause and effect relationships. However, uncertainty arises when data and information for a place are limited, as is commonly the case, and this creates decision paralysis while more information is generated. Here, we discuss how ecological understanding of network interactions in coastal marine ecosystems can be used as a lens to bring together multiple lines of evidence and create actions. We list and describe four characteristics of marine ecosystem interaction networks including the possibility for; 1) indirect effects, 2) effects that emerge as stressor magnitude increases the number of network components implicated, 3) network interactions that amplify these indirect effects, and 4) feedbacks that reinforce or stabilise against indirect effects. We then link these four characteristics to three case studies of common coastal environmental issues to demonstrate how a general understanding of ecological interaction networks can enhance priorities for stressor management that can be applied even when specific data is limited.

Pajda-De La O J, McCary MA. Pattern of seasonal variation in rates of predation between spider families is temporally stable in a food web with widespread intraguild predation

Intraguild predation (IGP)-predation between generalist predators (IGPredator and IGPrey) that potentially compete for a shared prey resource-is a common interaction module in terrestrial food webs. Understanding temporal variation in webs with widespread IGP is relevant to testing food web theory. We investigated temporal constancy in the structure of such a system: the spider-focused food web of the forest floor. Multiplex PCR was used to detect prey DNA in 3,300 adult spiders collected from the floor of a deciduous forest during spring, summer, and fall over four years. Because only spiders were defined as consumers, the web was tripartite, with 11 consumer nodes (spider families) and 22 resource nodes: 11 non-spider arthropod taxa (order- or family-level) and the 11 spider families. Most (99%) spider-spider predation was on spider IGPrey, and ~90% of these interactions were restricted to spider families within the same broadly defined foraging mode (cursorial or web-spinning spiders). Bootstrapped-derived confidence intervals (BCI's) for two indices of web structure, restricted connectance and interaction evenness, overlapped broadly across years and seasons. A third index, % IGPrey (% IGPrey among all prey of spiders), was similar across years (~50%) but varied seasonally, with a summer rate (65%) ~1.8x higher than spring and fall. This seasonal pattern was consistent across years. Our results suggest that extensive spider predation on spider IGPrey that exhibits consistent seasonal variation in frequency, and that occurs primarily within two broadly defined spider-spider interaction pathways, must be incorporated into models of the dynamics of forest-floor food webs.

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

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

Dynamics of species-rich predator-prey networks and seasonal alternations of core species

In nature, entangled webs of predator-prey interactions constitute the backbones of ecosystems. Uncovering the network architecture of such trophic interactions has been recognized as the essential step for exploring species with great impacts on ecosystem-level phenomena and functions. However, it has remained a major challenge to reveal how species-rich networks of predator-prey interactions are continually reshaped through time in the wild. Here, we show that dynamics of species-rich predator-prey interactions can be characterized by remarkable network structural changes and alternations of species with greatest impacts on community processes. On the basis of high-throughput detection of prey DNA from 1,556 spider individuals collected in a grassland ecosystem, we reconstructed dynamics of interaction networks involving, in total, 50 spider species and 974 prey species and strains through 8 months. The networks were compartmentalized into modules (groups) of closely interacting predators and prey in each month. Those modules differed in detritus/grazing food chain properties, forming complex fission-fusion dynamics of belowground and aboveground energy channels across the seasons. The substantial shifts of network structure entailed alternations of spider species located at the core positions within the entangled webs of interactions. These results indicate that knowledge of dynamically shifting food webs is crucial for understanding temporally varying roles of 'core species' in ecosystem processes.

Quantifying and estimating ecological network diversity based on incomplete sampling data

An ecological network refers to the ecological interactions among sets of species. Quantification of ecological network diversity and related sampling/estimation challenges have explicit analogues in species diversity research. A unified framework based on Hill numbers and their generalizations was developed to quantify taxonomic, phylogenetic and functional diversity. Drawing on this unified framework, we propose three dimensions of network diversity that incorporate the frequency (or strength) of interactions, species phylogenies and traits. As with surveys in species inventories, nearly all network studies are based on sampling data and thus also suffer from under-sampling effects. Adapting the sampling/estimation theory and the iNEXT (interpolation/extrapolation) standardization developed for species diversity research, we propose the iNEXT.link method to analyse network sampling data. The proposed method integrates the following four inference procedures: (i) assessment of sample completeness of networks; (ii) asymptotic analysis via estimating the true network diversity; (iii) non-asymptotic analysis based on standardizing sample completeness via rarefaction and extrapolation with network diversity; and (iv) estimation of the degree of unevenness or specialization in networks based on standardized diversity. Interaction data between European trees and saproxylic beetles are used to illustrate the proposed procedures. The software iNEXT.link has been developed to facilitate all computations and graphics. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

The evolution and ecology of multiple antipredator defences

Prey seldom rely on a single type of antipredator defence, often using multiple defences to avoid predation. In many cases, selection in different contexts may favour the evolution of multiple defences in a prey. However, a prey may use multiple defences to protect itself during a single predator encounter. Such "defence portfolios" that defend prey against a single instance of predation are distributed across and within successive stages of the predation sequence (encounter, detection, identification, approach (attack), subjugation and consumption). We contend that at present, our understanding of defence portfolio evolution is incomplete, and seen from the fragmentary perspective of specific sensory systems (e.g., visual) or specific types of defences (especially aposematism). In this review, we aim to build a comprehensive framework for conceptualizing the evolution of multiple prey defences, beginning with hypotheses for the evolution of multiple defences in general, and defence portfolios in particular. We then examine idealized models of resource trade-offs and functional interactions between traits, along with evidence supporting them. We find that defence portfolios are constrained by resource allocation to other aspects of life history, as well as functional incompatibilities between different defences. We also find that selection is likely to favour combinations of defences that have synergistic effects on predator behaviour and prey survival. Next, we examine specific aspects of prey ecology, genetics and development, and predator cognition that modify the predictions of current hypotheses or introduce competing hypotheses. We outline schema for gathering data on the distribution of prey defences across species and geography, determining how multiple defences are produced, and testing the proximate mechanisms by which multiple prey defences impact predator behaviour. Adopting these approaches will strengthen our understanding of multiple defensive strategies.

Resource predictability modulates spatial-use networks in an endangered scavenger species

BACKGROUND

Changes in human-induced resource availability can alter the behaviour of free-living species and affect their foraging strategies. The future European Landfill Waste Directive and Circular Economy Action Plan will reduce the number of predictable anthropogenic food subsidies (PAFS), above all, by closing landfills to preclude negative effects on human health. Obligate avian scavengers, the most threatened group of birds worldwide, are the most likely group of species that will be forced to change their behaviour and use of space in response to landfill site closures. Here, we examine the possible consequences of these management decisions on the foraging patterns of Egyptian vultures (Neophron percnopterus) in an expanding population in the Iberian Peninsula.

METHODS

We tracked 16 individuals in 2018-2021, including breeders and non-breeders, and, using a combination of spatial-use and spatial-network modelling, assessed landscape connectivity between key resources based on movement patterns. We then carried out simulations of future scenarios based on the loss of PAFS to predict likely changes in the movement patterns of both non-breeders and breeders.

RESULTS

Our results show that foraging strategies in non-breeders and breeders differ significantly: non-breeders performed more dispersal movements than breeding birds across a spatial-use network. Non-breeding and breeding networks were found to be vulnerable to the removal of central foraging areas containing landfill sites, a highly predictable resource, while perturbation analysis showed dissimilar foraging responses to the gradual reduction of other predictable resources. Under a context of the non-availability of landfills for breeders and non-breeders, vultures will increase their use of extensive livestock as a trophic resource.

CONCLUSIONS

Future environmental policies should thus extend the areas used by scavengers in which livestock carcasses are allowed to remain in the wild, a strategy that will also mitigate the lack of food caused by any reduction in available waste if landfills close. In general, our results emphasize the capabilities of a spatial network approaches to address questions on movement ecology. They can be used to infer the behavioural response of animal species and, also demonstrate the importance of applying such approaches to endangered species conservation within a context of changing humanized scenarios.

Shortcomings of reusing species interaction networks created by different sets of researchers

Given the requisite cost associated with observing species interactions, ecologists often reuse species interaction networks created by different sets of researchers to test their hypotheses regarding how ecological processes drive network topology. Yet, topological properties identified across these networks may not be sufficiently attributable to ecological processes alone as often assumed. Instead, much of the totality of topological differences between networks-topological heterogeneity-could be due to variations in research designs and approaches that different researchers use to create each species interaction network. To evaluate the degree to which this topological heterogeneity is present in available ecological networks, we first compared the amount of topological heterogeneity across 723 species interaction networks created by different sets of researchers with the amount quantified from non-ecological networks known to be constructed following more consistent approaches. Then, to further test whether the topological heterogeneity was due to differences in study designs, and not only to inherent variation within ecological networks, we compared the amount of topological heterogeneity between species interaction networks created by the same sets of researchers (i.e., networks from the same publication) with the amount quantified between networks that were each from a unique publication source. We found that species interaction networks are highly topologically heterogeneous: while species interaction networks from the same publication are much more topologically similar to each other than interaction networks that are from a unique publication, they still show at least twice as much heterogeneity as any category of non-ecological networks that we tested. Altogether, our findings suggest that extra care is necessary to effectively analyze species interaction networks created by different researchers, perhaps by controlling for the publication source of each network.

Intraspecific variation in species interactions promotes the feasibility of mutualistic assemblages

Patterns of resource use observed at the species level emerge from the way individuals exploit the range of available resources. Hence, accounting for interindividual differences in resource use, such as pollinator use by plants, is essential to advance our understanding of community assembly and persistence. By using finely resolved data on plant-pollinator interactions, we evaluated how interindividual plant variation in pollinator use scales up to affect community structure and dynamics. All co-occurring plant species comprised specialists interacting with proper subsets of pollinators that visited generalists, and differences in interaction patterns were driven by among-individual trait variation. Furthermore, the nested structure and feasibility of plant-pollinator communities were maximised at higher levels of interindividual plant variation in traits and pollinator use. Our study sheds light on how pervasive properties of community structure arise from individual-level processes and contributes to elucidate the importance of preserving intraspecific variation in traits and resource use within populations.

Ecological Drivers of Community Cohesion

From protocellular to societal, networks of living systems are complex and multiscale. Discerning the factors that facilitate assembly of these intricate interdependencies using pairwise interactions can be nearly impossible. To facilitate a greater understanding, we developed a mathematical and computational model based on a synthetic four-strain Saccharomyces cerevisiae interdependent system. Specifically, we aimed to provide a greater understanding of how ecological factors influence community dynamics. By leveraging transiently structured ecologies, we were able to drive community cohesion. We show how ecological interventions could reverse or slow the extinction rate of a cohesive community. An interconnected system first needs to persist long enough to be a subject of natural selection. Our emulation of Darwin's "warm little ponds" with an ecology governed by transient compartmentalization provided the necessary persistence. Our results reveal utility across scales of organization, stressing the importance of cyclic processes in major evolutionary transitions, engineering of synthetic microbial consortia, and conservation biology. IMPORTANCE We are facing unprecedented disruption and collapse of ecosystems across the globe. To have any hope of mitigating this phenomenon, a much greater understanding of ecosystem dynamics is required. However, ecosystems are typically composed of highly dynamic networks of individual species. These interactions are further modulated by abiotic and biotic factors that vary temporally and spatially. Thus, ecological dynamics are obfuscated by this complexity. Here, we developed a theoretical model, informed by a synthetic experimental system, of Darwin's "warm little ponds." This cycling four-species system seeks to elucidate the ecological factors that drive or inhibit interaction. We show that these factors could provide an essential tool for avoiding the accelerating ecological collapse. Our study also provides a starting point to develop a more encompassing model to inform conservation efforts.

Impacts of extreme climatic events on trophic network complexity and multidimensional stability

Untangling the relationship between network complexity and ecological stability under climate change is an arduous challenge for theoretical and empirical ecology. Even more so, when considering extreme climatic events. Here, we studied the effects of extreme climatic events (heatwaves) on the complexity of realistic freshwater ecosystems using topological and quantitative trophic network metrics. Next, we linked changes in network complexity with the investigation of four stability components (temporal stability, resistance, resilience, and recovery) of community's functional, compositional, and energy flux stability. We found reduction in topological network complexity to be correlated with reduction of functional and compositional resistance. However, temperature-driven increase in link-weighted network complexity increased functional and energy flux recovery and resilience, but at the cost of increased compositional instability. Overall, we propose an overarching approach to elucidate the effects of climate change on multidimensional stability through the lens of network complexity, providing helpful insights for preserving ecosystems stability under climate change.

Why are biodiversity-ecosystem functioning relationships so elusive? Trophic interactions may amplify ecosystem function variability

The relationship between biodiversity and ecosystem functions (BEFs) has attracted great interest. Studies on BEF have so far focused on the average trend of ecosystem function as species diversity increases. A tantalizing but rarely addressed question is why large variations in ecosystem functions are often observed across systems with similar species diversity, likely obscuring observed BEFs. Here we use a multi-trophic food web model in combination with empirical data to examine the relationships between species richness and the variation in ecosystem functions (VEFs) including biomass, metabolism, decomposition, and primary and secondary production. We then probe the mechanisms underlying these relationships, focusing on the role of trophic interactions. While our results reinforce the previously documented positive BEF relationships, we found that ecosystem functions exhibit significant variation within each level of species richness and the magnitude of this variation displays a hump-shaped relationship with species richness. Our analyses demonstrate that VEFs is reduced when consumer diversity increases through elevated nonlinearity in trophic interactions, and/or when the diversity of basal species such as producers and decomposers decreases. This explanation is supported by a 34-year empirical food web time series from the Gulf of Riga ecosystem. Our work suggests that biodiversity loss may not only result in ecosystem function decline, but also reduce the predictability of functions by generating greater function variability among ecosystems. It thus helps to reconcile the debate on the generality of positive BEF relationships and to disentangle the drivers of ecosystem stability. The role of trophic interactions and the variation in their strengths mediated by functional responses in shaping ecosystem function variation warrants further investigations and better incorporation into biodiversity-ecosystem functioning research.

The distance backbone of directed networks

In weighted graphs the shortest path between two nodes is often reached through an indirect path, out of all possible connections, leading to structural redundancies which play key roles in the dynamics and evolution of complex networks. We have previously developed a parameter-free, algebraically-principled methodology to uncover such redundancy and reveal the distance backbone of weighted graphs, which has been shown to be important in transmission dynamics, inference of important paths, and quantifying the robustness of networks. However, the method was developed for undirected graphs. Here we expand this methodology to weighted directed graphs and study the redundancy and robustness found in nine networks ranging from social, biomedical, and technical systems. We found that similarly to undirected graphs, directed graphs in general also contain a large amount of redundancy, as measured by the size of their (directed) distance backbone. Our methodology adds an additional tool to the principled sparsification of complex networks and the measure of their robustness.

The Resilience of Plant-Pollinator Networks

There is growing awareness of pollinator declines worldwide. Conservation efforts have mainly focused on finding the direct causes, while paying less attention to building a systemic understanding of the fragility of these communities of pollinators. To fill this gap, we need operational measures of network resilience that integrate two different approaches in theoretical ecology. First, we should consider the range of conditions compatible with the stable coexistence of all of the species in a community. Second, we should address the rate and shape of network collapse once this safe operational space is exited. In this review, we describe this integrative approach and consider several mechanisms that may enhance the resilience of pollinator communities, chiefly rewiring the network of interactions, increasing heterogeneity, allowing variance, and enhancing coevolution. The most pressing need is to develop ways to reduce the gap between these theoretical recommendations and practical applications. This perspective shifts the emphasis from traditional approaches focusing on the equilibrium states to strategies that allow pollination networks to cope with global environmental change.

Behavioural ecology at the spatial-social interface

Spatial and social behaviour are fundamental aspects of an animal's biology, and their social and spatial environments are indelibly linked through mutual causes and shared consequences. We define the 'spatial-social interface' as intersection of social and spatial aspects of individuals' phenotypes and environments. Behavioural variation at the spatial-social interface has implications for ecological and evolutionary processes including pathogen transmission, population dynamics, and the evolution of social systems. We link spatial and social processes through a foundation of shared theory, vocabulary, and methods. We provide examples and future directions for the integration of spatial and social behaviour and environments. We introduce key concepts and approaches that either implicitly or explicitly integrate social and spatial processes, for example, graph theory, density-dependent habitat selection, and niche specialization. Finally, we discuss how movement ecology helps link the spatial-social interface. Our review integrates social and spatial behavioural ecology and identifies testable hypotheses at the spatial-social interface.

Dynamic network modeling of gut microbiota during Alzheimer's disease progression in mice

The intimate association between the gut microbiota (GM) and the central nervous system points to potential intervention strategies for neurological diseases. Nevertheless, there is currently no theoretical framework for selecting the window period and target bacteria for GM interventions owing to the complexity of the gut microecosystem. In this study, we constructed a complex network-based modeling approach to evaluate the topological features of the GM and infer the window period and bacterial candidates for GM interventions. We used Alzheimer's disease (AD) as an example and traced the GM dynamic changes in AD and wild-type mice at one, two, three, six, and nine months of age. The results revealed alterations of the topological features of the GM from a scale-free network into a random network during AD progression, indicating severe GM disequilibrium at the late stage of AD. Through stability and vulnerability assessments of the GM networks, we identified the third month after birth as the optimal window period for GM interventions in AD mice. Further computational simulations and robustness evaluations determined that the hub bacteria were potential candidates for GM interventions. Moreover, our GM functional analysis suggested that Lachnospiraceae UCG-001 - the hub and enriched bacterium in AD mice - was the keystone bacterium for GM interventions owing to its contributions to quinolinic acid synthesis. In conclusion, this study established a complex network-based modeling approach as a practical strategy for disease interventions from the perspective of the gut microecosystem.

Archetype models upscale understanding of natural pest control response to land-use change

Control of crop pests by shifting host plant availability and natural enemy activity at landscape scales has great potential to enhance the sustainability of agriculture. However, mainstreaming natural pest control requires improved understanding of how its benefits can be realized across a variety of agroecological contexts. Empirical studies suggest significant but highly variable responses of natural pest control to land-use change. Current ecological models are either too specific to provide insight across agroecosystems or too generic to guide management with actionable predictions. We suggest obtaining the full benefit of available empirical, theoretical, and methodological knowledge by combining trait-mediated understanding from correlative studies with the explicit representation of causal relationships achieved by mechanistic modeling. To link these frameworks, we adapt the concept of archetypes, or context-specific generalizations, from sustainability science. Similar responses of natural pest control to land-use gradients across cases that share key attributes, such as functional traits of focal organisms, indicate general processes that drive system behavior in a context-sensitive manner. Based on such observations of natural pest control, a systematic definition of archetypes can provide the basis for mechanistic models of intermediate generality that cover all major agroecosystems worldwide. Example applications demonstrate the potential for upscaling understanding and improving predictions of natural pest control, based on knowledge transfer and scientific synthesis. A broader application of this mechanistic archetype approach promises to enhance ecology's contribution to natural resource management across diverse regions and social-ecological contexts.

Statistical inference links data and theory in network science

The number of network science applications across many different fields has been rapidly increasing. Surprisingly, the development of theory and domain-specific applications often occur in isolation, risking an effective disconnect between theoretical and methodological advances and the way network science is employed in practice. Here we address this risk constructively, discussing good practices to guarantee more successful applications and reproducible results. We endorse designing statistically grounded methodologies to address challenges in network science. This approach allows one to explain observational data in terms of generative models, naturally deal with intrinsic uncertainties, and strengthen the link between theory and applications.

Theoretical models and structures recovered from measured data serve for analysis of complex networks. The authors discuss here existing gaps between theoretical methods and real-world applied networks, and potential ways to improve the interplay between theory and applications.

Human disturbances affect the topology of food webs

Networks describe nodes connected by links, with numbers of links per node, the degree, forming a range of distributions including random and scale-free. How network topologies emerge in natural systems still puzzles scientists. Based on previous theoretical simulations, we predict that scale-free food webs are favourably selected by random disturbances while random food webs are selected by targeted disturbances. We assume that lower human pressures are more likely associated with random disturbances, whereas higher pressures are associated with targeted ones. We examine these predictions using 351 empirical food webs, generally confirming our predictions. Should the topology of food webs respond to changes in the magnitude of disturbances in a predictable fashion, consistently across ecosystems and scales of organisation, it would provide a baseline expectation to understand and predict the consequences of human pressures on ecosystem dynamics.

Reconstruction and variability of tropical pollination networks in the Brazilian Atlantic Forest

Loss of biodiversity comprehends not only the extinction of individual species, but also the loss of the ecological interactions among them. Survival of species, continuation of ecosystem functioning in nature, and ecosystem services to humans depend on the maintenance of well-functioning networks of species interactions (e.g. plant–pollinator networks and food webs). Analyses of ecological networks often rely on biased and incomplete survey data, especially in species-rich areas, such as the tropics. We used a network inference method to reconstruct pollination data compiled from a large tropical rainforest habitat extent. To gain insight into the characteristics of plant–pollinator interactions across the region, we combined the reconstructed pollination network with species distribution modelling to obtain local pollination networks throughout the area. We explored how global network properties relate to natural forest cover and land cover heterogeneity. We found that some network properties (the sum and evenness of link weights, connectance and nestedness) are positively correlated with forest cover, indicating that networks in sites with more natural habitat have greater diversity of interactions. Modularity was not related to forest cover, but seemed to reflect habitat heterogeneity, due to the broad spatial scale of the study. We believe that the methodology suggested here can facilitate the use of incomplete network data in a reliable way and allow us to better understand and protect networks of species interactions in high biodiversity regions of the world.

Stability-instability transition in tripartite merged ecological networks

Although ecological networks are typically constructed based on a single type of interaction, e.g. trophic interactions in a food web, a more complete picture of ecosystem composition and functioning arises from merging networks of multiple interaction types. In this work, we consider tripartite networks constructed by merging two bipartite networks, one mutualistic and one antagonistic. Taking the interactions within each sub-network to be distributed randomly, we consider the stability of the dynamics of the network based on the spectrum of its community matrix. In the asymptotic limit of a large number of species, we show that the spectrum undergoes an eigenvalue phase transition, which leads to an abrupt destabilisation of the network as the ratio of mutualists to antagonists is increased. We also derive results that show how this transition is manifest in networks of finite size, as well as when disorder is introduced in the segregation of the two interaction types. Our random-matrix results will serve as a baseline for understanding the behaviour of merged networks with more realistic structures and/or more detailed dynamics.

Causality and correlation analysis for deciphering the microbial interactions in activated sludge

Time series data has been considered to be a massive information provider for comprehending more about microbial dynamics and interaction, leading to a causality inference in a complex microbial community. Granger causality and correlation analysis have been investigated and applied for the construction of a microbial causal correlation network (MCCN) and efficient prediction of the ecological interaction within activated sludge, which thereby exhibited ecological interactions at the OTU-level. Application of MCCN to a time series of activated sludge data revealed that the hub species OTU56, classified as the one belonging to the genus Nitrospira, was responsible for nitrification in activated sludge and interaction with Proteobacteria and Bacteroidetes in the form of amensal and commensal relationships, respectively. The phylogenetic tree suggested a mutualistic relationship between Nitrospira and denitrifiers. Zoogloea displayed the highest ncf value within the classified OTUs of the MCCN, indicating that it could be a foundation for activated sludge through the formation of characteristic cell aggregate matrices where other organisms embed during floc formation. Inclusively, the research outcomes of this study have provided a deep insight into the ecological interactions within the communities of activated sludge.

Construction of an Ecological Network Based on an Integrated Approach and Circuit Theory: A Case Study of Panzhou in Guizhou Province

Protecting ecological security has become the backbone of social and economic development since declines in ecological quality due to an increase in human dominance over the natural environment. The establishment of ecological networks is an effective, comprehensive spatial regulation means to ensure regional ecological security. Panzhou city, as a case study, is a typical karst county and has been confronted with the pressure of ecological degradation in recent decades. In this study, an integrated approach combining ecological quality (EQ), ecosystem function importance (EFI), and morphological spatial pattern analysis (MSPA) was developed to determine the ecological sources. Ecological corridors, ecological pinch areas, and ecological barriers were extracted using circuit theory to identify the restored and conserved priority areas of ecological security patterns. The results showed that (1) the remote sensing ecological index (RSEI) and EFI exhibited typical geographical distributions, with the highest values concentrated in the northern and southern parts of the study area and the lowest values scattered in the middle part; (2) 26 patches with forestland, grassland, and waterbodies as the main land cover types were selected as the ecological sources; (3) 63 ecological corridors, composed of 45 key ecological corridors and 18 inactive ecological corridors, were extracted, accounting for 203.12 km and 163.31 km, respectively; (4) 82.76 km2 of pinch areas and 320.29 km2 of barriers were identified, both of which were distributed on key ecological corridors and played different roles in ecological security; and (5) 4 types of ecological security zones were established according to ecological sources, corridors, pinch areas, and barriers. This integrated approach provides a scientific method for the identification and implementation of ecological networks that can contribute to protecting regional ecological security. Our findings can serve as applicable and reasonable guidance to land administrators and policy-makers for adopting suitable territorial spatial planning, urban planning, green cities, etc.

Network analysis reveals the regulatory effect of mixed stands on ecosystem structure and functions in the Loess Plateau, China

Afforestation, an important measure for ecological restoration, has been implemented all over the world, but fragile ecosystem structures and climate change endanger its ecological functions. One major obstacle to optimizing ecological function has been quantifying and characterizing a complex ecosystem structure. Here, the structure and functions of six types of land-use restoration were investigated in the hilly-gully region of the Loess Plateau, China. In total, 44 ecological factors from canopy, understory and soil were determined. We constructed the related network of reforestation ecosystems, quantified the structure of ecosystem through network topology, and explored the relationships between structure and functions. The results showed that changes in plantation type altered the network hubs, but some nodes, such as species height, breast-height diameter and understory biomass, were often keystone hubs. Mixed plantations enhanced the connectivity among different modules. In addition, we found that closeness of network connectivity was an important factor influencing ecological functions, while soil erodibility was the main limiting factor for reforestation ecosystem structure in this region. Moreover, mixed plantations tended to have more balanced topological metrics and ecological functions. Overall, this study suggests that mixed plantations or monoculture plantations should be designed according to the characteristics and ecological demands of the regional ecological environment. Although monoculture plantations may support local ecosystems, mixed plantations offer more resilience to a landscape because they were help to achieve a balance among the ecological functions.

Urban forest invertebrates: how they shape and respond to the urban environment

Invertebrates comprise the most diversified animal group on Earth. Due to their long evolutionary history and small size, invertebrates occupy a remarkable range of ecological niches, and play an important role as “ecosystem engineers” by structuring networks of mutualistic and antagonistic ecological interactions in almost all terrestrial ecosystems. Urban forests provide critical ecosystem services to humans, and, as in other systems, invertebrates are central to structuring and maintaining the functioning of urban forests. Identifying the role of invertebrates in urban forests can help elucidate their importance to practitioners and the public, not only to preserve biodiversity in urban environments, but also to make the public aware of their functional importance in maintaining healthy greenspaces. In this review, we examine the multiple functional roles that invertebrates play in urban forests that contribute to ecosystem service provisioning, including pollination, predation, herbivory, seed and microorganism dispersal and organic matter decomposition, but also those that lead to disservices, primarily from a public health perspective, e.g., transmission of invertebrate-borne diseases. We then identify a number of ecological filters that structure urban forest invertebrate communities, such as changes in habitat structure, increased landscape imperviousness, microclimatic changes and pollution. We also discuss the complexity of ways that forest invertebrates respond to urbanisation, including acclimation, local extinction and evolution. Finally, we present management recommendations to support and conserve viable and diverse urban forest invertebrate populations into the future.

Inter-cluster competition and resource partitioning may govern the ecology of Frankia

Microbes live in a complex communal ecosystem. The structural complexity of microbial community reflects diversity, functionality, as well as habitat type. Delineation of ecologically important microbial populations along with exploration of their roles in environmental adaptation or host-microbe interaction has a crucial role in modern microbiology. In this scenario, reverse ecology (the use of genomics to study ecology) plays a pivotal role. Since the co-existence of two different genera in one small niche should maintain a strict direct interaction, it will be interesting to utilize the concept of reverse ecology in this scenario. Here, we exploited an 'R' package, the RevEcoR, to resolve the issue of co-existing microbes which are proven to be a crucial tool for identifying the nature of their relationship (competition or complementation) persisting among them. Our target organism here is Frankia, a nitrogen-fixing actinobacterium popular for its genetic and host-specific nature. According to their plant host, Frankia has already been sub-divided into four clusters C-I, C-II, C-III, and C-IV. Our results revealed a strong competing nature of CI Frankia. Among the clusters of Frankia studied, the competition index between C-I and C-III was the largest. The other interesting result was the co-occurrence of C-II and C-IV groups. It was revealed that these two groups follow the theory of resource partitioning in their lifestyle. Metabolic analysis along with their differential transporter machinery validated our hypothesis of resource partitioning among C-II and C-IV groups.

Bibliometric Analysis of Global Research on Ecological Networks in Nature Conservation from 1990 to 2020

As a nature-based solution to land-use sustainability, ecological networks (ENs) have received substantial attention from researchers, planners, and decision-makers worldwide. To portray the global research on ENs in nature conservation during the period of 1990–2020, 1371 papers in 53 subject categories were reviewed with bibliometric methods and CiteSpace. The results showed a successive growth of publications at an annually averaged rate of 18.9% during the past three decades. Co-citation analysis indicated that the most popular topic was connectivity, on which the studies concentrated on quantifying connectivity, identifying priority areas, and integrating conservation planning. A recent hotspot is to study the landscape fragmentation effects on natural habitats or biodiversity under land-use changes in urbanized areas. Multidisciplinary approaches have been increasingly used to tackle more complex interplays among economic, social, ecological, and cultural factors, with the aim of alleviating ecological service losses attributed to human activities. Spatiotemporal dynamics and participatory design of ENs at different scales have become an emerging trend. In order to address increasing pressures on biodiversity or landscape connectivity brought about by land use and climate change, it is suggested to develop more research on the evaluation and management of the resilience of ENs.

Differences in prey availability across space and time lead to interaction rewiring and reshape a predator-prey metaweb

Space and time promote variation in network structure by affecting the likelihood of potential interactions. However, little is known about the relative roles of ecological and biogeographical processes in determining how species interactions vary across space and time. Here, we study the spatiotemporal variation in predator-prey interaction networks formed by anurans and arthropods and test for the effects of prey availability in determining interaction patterns, information that is often absent and limits the understanding of the determinants of network structure. We found that network dissimilarity between ecoregions and seasons was high and primarily driven by interaction rewiring. Interaction rewiring drove variation across seasons and ecoregions and species turnover was positively related to geographical distance. Using a null model approach to disentangle the effect of prey availability on the spatial and temporal variation we show that differences in prey availability were important in determining the variation in network structure between seasons and among areas. Our study reveals that fluctuations in prey abundance, along with limited dispersal abilities of anurans and their prey, may be responsible for the spatial patterns that emerged in our predator-prey metaweb. These findings contribute to our understanding of the assembly rules that maintain biotic processes in metacommunities and highlight the importance of prey availability to the structure of these systems.