Niche and neutral processes leave distinct structural imprints on indirect interactions in mutualistic networks

Networks of mutualistic interactions between animals and plants are considered a pivotal part of ecological communities. However, mutualistic networks are rarely studied from the perspective of species-specific roles, and it remains to be established whether those animal species more relevant for network structure also contribute more to the ecological functions derived from interactions. Here, we relate the contribution to seed dispersal of vertebrate species with their topological role in frugivore-plant interaction networks. For one year in two localities with remnant patches of Colombian tropical dry forest, we sampled abundance, morphology, behaviour and fruit consumption from fleshy-fruited plants of various frugivore species. We assessed the network topological role of each frugivore species by integrating their degree of generalization in interactions with plants with their contributions to network nestedness and modularity. We estimated the potential contribution of each frugivore species to community-wide seed dispersal, on the basis of a set of frugivore ecological, morphological and behavioural characteristics important for seed dispersal, together with frugivore abundance and frugivory degree. The various frugivore species showed strong differences in their network structural roles, with generalist species contributing the most to network modularity and nestedness. Frugivores also showed strong variability in terms of potential contribution to seed dispersal, depending on the specific combinations of frugivore abundance, frugivory degree and the different traits and behaviours. For both localities, the seed dispersal potential of a frugivore species responded positively to its contribution to network structure, evidencing that the most important frugivore species in the network topology were also those making the strongest contribution as seed dispersers. Contribution to network structure was correlated with frugivore abundance, diet and behavioural characteristics. This suggests that the species-level link between structure and function is due to the fact that the occurrence of frugivore-plant interactions depends largely on the characteristics of the frugivore involved, which also condition its ultimate role in seed dispersal.

Specialization of Mutualistic Interaction Networks Decreases toward Tropical Latitudes

Recently, several studies have focused on structural properties of ant–plant networks. However, little is known about the role of abiotic factors on these networks. As a result of different abiotic factors that can affect the patterns of ant–plant interactions, it was tested whether soil pH and canopy cover contribute to variation in the nestedness of mutualistic (plants with extrafloral nectar–EFN) and neutral (plants without EFN) ant–plant networks. It was shown that only mutualistic networks were affected by soil pH. It was suggested that this may occur because the variation in soil pH directly influences the secreted nectar, and as there is a preference for nectar composition by ants, this could change the patterns of interaction in mutualistic networks. As prey availability is possibly the main factor influencing ants' presence on plants without EFN, soil pH should have little or no influence on the patterns of interaction in neutral networks. On the other hand, nestedness was not affected by canopy cover in mutualistic and neutral networks. In spite of that canopy cover (light availability) is directly related to the amount of nectar secreted, the volume of nectar may not be important for the structure of the networks. However, canopy cover varied little in this study site. This small variation could not be enough to change the nested pattern in mutualistic and neutral networks. In short, the present results show that the abiotic factors that affect the availability and quality of food resources may have important effects on the structure of trophic interactions in non‐symbiotic ant–plant networks.

Ecological processes leave distinct structural imprints on the species interactions that shape the topology of animal-plant mutualistic networks. Detecting how direct and indirect interactions between animals and plants are organised is not trivial since they go beyond pairwise interactions, but may get blurred when considering global network descriptors. Recent work has shown that the meso-scale, the intermediate level of network complexity between the species and the global network, can capture this important information. The meso-scale describes network subgraphs representing patterns of direct and indirect interactions between a small number of species, and when these network subgraphs differ statistically from a benchmark, they are often referred to as 'network motifs'. Although motifs can capture relevant ecological information of species interactions, they remain overlooked in natural plant-pollinator networks. By exploring 60 empirical plant-pollinator networks from 18 different studies with wide geographical coverage, we show that some network subgraphs are consistently under- or over-represented, suggesting the presence of worldwide network motifs in plant-pollinator networks. In addition, we found a higher proportion of densely connected network subgraphs that, based on previous findings, could reflect that species relative abundances are the main driver shaping the structure of the meso-scale on plant-pollinator communities. Moreover, we found that distinct subgraph positions describing species ecological roles (e.g. generalisation and number of indirect interactions) are occupied by different groups of animal and plant species representing their main life-history strategies (i.e. functional groups). For instance, we found that the functional group of 'bees' was over-represented in subgraph positions with a lower number of indirect interactions in contrast to the rest of floral visitors groups. Finally, we show that the observed functional group combinations within a subgraph cannot be retrieved from their expected probabilities (i.e. joint probability distributions), indicating that plant and floral visitor associations within subgraphs are not random either. Our results highlight the presence of common network motifs in plant-pollinator communities that are formed by a non-random association of plants and floral visitors functional groups.

A fundamental fact about mutualisms is that these mutually beneficial interactions often harbor cheaters that benefit from the use of resources and services without providing any positive feedback to other species. The role of cheaters in the evolutionary dynamics of mutualisms has long been recognized, yet their broader impacts at the community level, beyond species they directly interact with, is still poorly understood. Because mutualisms form networks often involving dozens of species, indirect effects generated by cheaters may cascade through the whole community, reshaping trait evolution. Here, we study how cheating interactions can influence coevolution in mutualistic networks. We combined a coevolutionary model, empirical data on animal–plant mutualistic networks and numerical simulations to show that high trait disparity emerges as a consequence of the negative effect of cheaters on victim fitness, which in turn fuels selection favoring victim traits that are increasingly different from the cheaters' traits. Intermediate levels of cheating interactions in a network can lead to the formation of groups of species phenotypically similar to each other and distinct from species in other groups, generating clustered trait patterns. The resulting clustered trait pattern, in turn, changes the pattern of interaction in simulated networks, fostering the formation of modules of interacting species and reducing nestedness. Our results indicate that directional selection imposed by cheaters on their victims counteracts selection for trait convergence imposed by mutualists, leading to the emergence of modules of phenotypically similar interacting species but phenotypically distinct from other modules. Based on these results, we suggest that cheaters might be a fundamental missing element for our understanding of how multispecies selection shapes the trait distribution and structure of mutualistic networks.

Species interaction networks, which govern the maintenance of biodiversity and ecosystem processes within ecological communities, are being rapidly altered by anthropogenic activities worldwide. Studies on the response of species interaction networks to anthropogenic disturbance have almost exclusively focused on one interaction type at a time, such as mutualistic or antagonistic interactions, making it challenging to decipher how networks of different interaction types respond to the same anthropogenic disturbance. Moreover, few studies have simultaneously focused on the two main components of network structure: network topology (i.e., architecture) and network ecology (i.e., species identities and interaction turnover), thereby limiting our understanding of the ecological drivers underlying changes in network topology in response to anthropogenic disturbance. Here, we used 16,400 plant-pollinator and plant-herbivore interaction observations from 16 sites along an agricultural intensification gradient to compare changes in network topology and ecology between mutualistic and antagonistic networks. We measured two aspects of network topology-nestedness and modularity-and found that although the mutualistic networks were consistently more nested than antagonistic networks and antagonistic networks were consistently more modular, the rate of change in nestedness and modularity along the gradient was comparable between the two network types. Change in network ecology, however, was distinct between mutualistic and antagonistic networks, with partner switching making a significantly larger contribution to interaction turnover in the mutualistic networks than in the antagonistic networks, and species turnover being a strong contributor to interaction turnover in the antagonistic networks. The ecological and topological changes we observed in the antagonistic and mutualistic networks have different implications for pollinator and herbivore communities in agricultural landscapes, and support the idea that pollinators are more labile in their interaction partner choice, whereas herbivores form more reciprocally specialized, and therefore more vulnerable, interactions. Our results also demonstrate that studying both topological and ecological network structure can help to elucidate the effects of anthropogenic disturbance on ecological communities, with applications for conservation and restoration of species interactions and the ecosystem processes they maintain.

Indirect interactions play an essential role in governing population, community and coevolutionary dynamics across a diverse range of ecological communities. Such communities are widely represented as bipartite networks: graphs depicting interactions between two groups of species, such as plants and pollinators or hosts and parasites. For over thirty years, studies have used indices, such as connectance and species degree, to characterise the structure of these networks and the roles of their constituent species. However, compressing a complex network into a single metric necessarily discards large amounts of information about indirect interactions. Given the large literature demonstrating the importance and ubiquity of indirect effects, many studies of network structure are likely missing a substantial piece of the ecological puzzle. Here we use the emerging concept of bipartite motifs to outline a new framework for bipartite networks that incorporates indirect interactions. While this framework is a significant departure from the current way of thinking about bipartite ecological networks, we show that this shift is supported by analyses of simulated and empirical data. We use simulations to show how consideration of indirect interactions can highlight differences missed by the current index paradigm that may be ecologically important. We extend this finding to empirical plant–pollinator communities, showing how two bee species, with similar direct interactions, differ in how specialised their competitors are. These examples underscore the need to not rely solely on network‐ and species‐level indices for characterising the structure of bipartite ecological networks.

Time-Slotted Channel Hopping (TSCH) Media Access Control (MAC) has become a leading wireless technology for industrial applications, offering deterministic communication while balancing latency, bandwidth, and energy consumption. This study addresses the critical challenge of cell scheduling within TSCH MAC, emphasising the importance of selecting scheduling mechanisms based on application-specific quality of service parameters. Despite numerous proposals and evaluations, the lack of standardised scheduling methods and comprehensive performance metrics remains a significant obstacle. Traditional network metrics often fail to capture key issues in TSCH-based mesh networks, potentially overlooking indicators of network stability. To address this gap, we examine both application and network metrics from a mesh network perspective and propose a set of complementary metrics tailored to the characteristics of TSCH. These metrics provide a more detailed evaluation of how scheduling impacts network reliability and efficiency. Given the diverse applications and configurations in industrial environments, this study offers insights into employing these complementary metrics for a more accurate assessment of the impact of TSCH scheduling. Ultimately, our approach aims to improve TSCH scheduling evaluation and contribute to advancing industrial wireless communication systems.

Unauthorized access of personal or proprietary information seems to be a routine. A better understanding of the health of our networks can help us identify network anomalies that indicate malicious activity and other latent, systemic issues. Software-Defined Networks (SDN) enable the collection of network operational and configuration data that are not readily available, if available at all, from traditional networks. By accumulating and analyzing a time series data repository (TSDR) of SDN and traditional network metrics along with operational and configuration data we can establish known behavior and security patterns for specific network paths and segments. By comparing these patterns with data gathered at the time of use we can assess the dependability and security of the network path or segment being used. Our research provides a framework for a broad range of capabilities for administrators to use as well as for automated protection services. To narrow the scope of our research, this paper focuses on a subset of those capabilities as they apply to the analysis of a specific network path at the time of use or inspection. We developed a service that inspects a network path before and after sending sensitive information and compares this inspection to our known behavior and security patterns to provide a user with a dependability assessment of that specific network path. This dependability assessment allows users to decide whether a network path is secure enough for sending their information. Our research proposes techniques for a network path analysis service that can be used to identify latent systemic network problems, facilitate a more dependable network and to prevent the theft of information by malicious actors.

Identifying the determinants of biological interactions in mutualistic networks is key to understanding the rules that govern the organization of biodiversity. We used structural equation modeling and dissimilarities in nine ecological variables to investigate community processes underlying the turnover of species and their interaction frequencies (interaction pattern) among highly resolved plant–pollinator networks. Floral and pollinator community composition, i.e., species identities and their abundances, were strong determinants of the microstructure of pairwise interactions among the networks, explaining almost 69% of their variation. Flower and pollinator traits were directly related to interaction patterns, but were partly masked in the model by shared variance with community composition. Time of year and geographic location, floral and pollinator abundances independent of species identity, and relative abundance of exotic flowers had indirect and relatively weak effects on interaction patterns. Our analyses lead to precise predictions about the processes behind the interaction patterns in mutualistic networks. Future understanding of these processes will be aided by studies that evaluate these predictions experimentally at the network level.

Indirect Mutualism: Variations on a Theme by Stephen Levine

In recent years, an extended body of literature has focused on the importance of either temporal or spatial dynamics in shaping the structure of interacting plant and pollinator communities. This improvement from a previously static and aggregated perspective has allowed us to understand many of the ecological processes that shape community assembly. However, fewer are the studies that have simultaneously focused on spatial and temporal dynamics, and even fewer are those that collect data across different habitat types to assess the generality of their findings. Here, we used a dataset collected weekly throughout the full flowering season for two consecutive years and within two contrasting habitat types in N and SW Spain: a mountain grassland area and the understory of sparse pine forests. We evaluated species and interaction persistence through space and time, pollinator fidelity, and turnover patterns in interaction composition while providing a potential mechanistic explanation for the patterns observed. Our results show that although species generalization does not explain species or interaction persistence, moderately generalist species are those showing the greatest fidelity to the subset of plant species they visit through space and time. Further, we find that interaction turnover through time is mostly driven by changes in species composition, while through space it is mostly driven by interaction rewiring resulting from indirect competitive interactions between pollinator species. Our results help to shed light on the potential mechanisms driving community assembly patterns beyond niche or neutral processes by adding within‐trophic‐level interactions that can modify pollinator preferences.

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

Current understanding of mutualistic networks is grounded largely in data on interaction frequency, yet mutualistic network dynamics are also shaped by interaction quality—the functional outcomes of individual interactions on reproduction and survival. The difficulty of obtaining data on functional outcomes has resulted in limited understanding of functional variation among a network's pairwise species interactions, of the study designs that are necessary to capture major sources of functional variation, and of predictors of functional variation that may allow generalization across networks. In this community‐scale study, we targeted a key functional outcome in plant–frugivore networks: the impact of frugivore gut passage on seed germination. We used captive frugivore feeding trials and germination experiments in an island ecosystem, attaining species‐level coverage across all extant native frugivores and the plants they consume to (a) assess sources of functional variation, (b) separate effects of pulp removal from those of scarification via gut passage, and (c) test trait‐based correlates of gut passage effect sizes. We found antagonistic seed predation effects of a frugivore previously assumed to be a seed disperser, highlighting the need to consider functional outcomes rather than interaction frequency alone. The other frugivores each exhibited similar impacts for individual plant species, with benefits primarily caused by pulp removal rather than scarification, supporting the use of animal functional groups in this context. In contrast, plant species varied widely in impacts of gut passage on germination. Species with smaller seeds and more frugivore partners had larger benefits of gut passage, showing promise for network metrics and functional traits to predict functional variation among plants. Synthesis. Combining network and demographic approaches, we assessed the degree and sources of variation in a key functional outcome of plant–frugivore interactions across an entire network. Using a detailed study design, our work shows how simpler study designs can capture primary sources of functional variation and that functional traits and network metrics may allow generalization across networks. Efficiently measuring and generalizing sources of functional variation within mutualistic networks will strengthen our ability to model network dynamics and predict mutualist responses to global change.

Network theory provides a principled abstraction of the human brain: reducing a complex system into a simpler representation from which to investigate brain organisation. Recent advancement in the neuroimaging field are towards representing brain connectivity as a dynamic process in order to gain a deeper understanding of the interplay between functional modules for efficient information transport. In this work, we employ heat kernels to model the process of energy diffusion in functional networks. We extract node-based, multi-scale features which describe the propagation of heat over 'time' which not only inform the importance of a node in the graph, but also incorporate local and global information of the underlying geometry of the network. As a proof-of-concept, we test the efficacy of two heat kernel features for discriminating between motor and working memory functional networks from the Human Connectome Project. For comparison, we also classified task networks using traditional network metrics which similarly provide rankings of node importance. In addition, a variant of the Smooth Incremental Graphical Lasso Estimation algorithm was used to estimate non-sparse, precision matrices to account for non-stationarity in the time series. We illustrate differences in heat kernel features between tasks, and also between regions of the brain. Using a random forest classifier, we showed heat kernel metrics to capture intrinsic properties of functional networks that serve well as features for task classification.