Motifs in bipartite ecological networks: uncovering indirect interactions

Spatially explicit predictions of food web structure from regional-level data

Knowledge about how ecological networks vary across global scales is currently limited given the complexity of acquiring repeated spatial data for species interactions. Yet, recent developments in metawebs highlight efficient ways to first document possible interactions within regional species pools. Downscaling metawebs towards local network predictions is a promising approach to using the current data to investigate the variation of networks across space. However, issues remain in how to represent the spatial variability and uncertainty of species interactions, especially for large-scale food webs. Here, we present a probabilistic framework to downscale a metaweb based on the Canadian mammal metaweb and species occurrences from global databases. We investigated how our approach can be used to represent the variability of networks and communities between ecoregions in Canada. Species richness and interactions followed a similar latitudinal gradient across ecoregions but simultaneously identified contrasting diversity hotspots. Network motifs revealed additional areas of variation in network structure compared with species richness and number of links. Our method offers the potential to bring global predictions down to a more actionable local scale, and increases the diversity of ecological networks that can be projected in space. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

A One Health framework for exploring zoonotic interactions demonstrated through a case study

The eco-epidemiology of zoonoses is often oversimplified to host-pathogen interactions while findings derived from global datasets are rarely directly transferable to smaller-scale contexts. Through a systematic literature search, we compiled a dataset of naturally occurring zoonotic interactions in Austria, spanning 1975-2022. We introduce the concept of zoonotic web to describe the complex relationships between zoonotic agents, their hosts, vectors, food, and environmental sources. The zoonotic web was explored through network analysis. After controlling for research effort, we demonstrate that, within the projected unipartite source-source network of zoonotic agent sharing, the most influential zoonotic sources are human, cattle, chicken, and some meat products. Analysis of the One Health 3-cliques (triangular sets of nodes representing human, animal, and environment) confirms the increased probability of zoonotic spillover at human-cattle and human-food interfaces. We characterise six communities of zoonotic agent sharing, which assembly patterns are likely driven by highly connected infectious agents in the zoonotic web, proximity to human, and anthropogenic activities. Additionally, we report a frequency of emerging zoonotic diseases in Austria of one every six years. Here, we present a flexible network-based approach that offers insights into zoonotic transmission chains, facilitating the development of locally-relevant One Health strategies against zoonoses.

Networking nutrients: How nutrition determines the structure of ecological networks

Nutrients can shape ecological interactions but remain poorly integrated into ecological networks. Concepts such as nutrient-specific foraging nevertheless have the potential to expose the mechanisms structuring complex ecological systems. Nutrients also present an opportunity to predict dynamic processes, such as interaction rewiring and extinction cascades, and increase the accuracy of network analyses. Here, we propose the concept of nutritional networks. By integrating nutritional data into ecological networks, we envisage significant advances to our understanding of ecological processes from individual to ecosystem scales. We show that networks can be constructed with nutritional data to illuminate how nutrients structure ecological interactions in natural systems through an empirical example. Throughout, we identify fundamental ecological hypotheses that can be explored in a nutritional network context, alongside methods for resolving those networks. Nutrients influence the structure and complexity of ecological networks through mechanistic processes and concepts including nutritional niche differentiation, functional responses, landscape diversity, ecological invasions and ecosystem robustness. Future research on ecological networks should consider nutrients when investigating the drivers of network structure and function.

Connections between soil microbes, land use and European climate: Insights for management practices

Soil microbial biomass and activity strongly depend on land use, vegetation cover, climate, and soil physicochemical properties. In most cases, this dependence was assessed by one-to-one correlations while by employing network analysis, information about network robustness and the balance between stochasticity and determinism controlling connectivity, was revealed. In this study, we further elaborated on the hypothesis of Smith et al. (2021) that cropland soils depended more on climate variables and therefore are more vulnerable to climate change. We used the same dataset with that of Smith et al. (2021) that contains seasonal microbial, climate and soil variables collected from 881 soil points representing the main land uses in Europe: forests, grassland, cropland. We examined complete (both direct and indirect relationships) and incomplete networks (only direct relationships) and recorded higher robustness in the former. Partial Least Square results showed that on average more than 45% of microbial attributes' variability was predicted by climate and habitat drivers denoting medium to strong effect of habitat filtering. Network architecture slightly affected by season or land use type; it followed the core/periphery structure with positive and negative interactions and no hub nodes. Microbial attributes (biomass, activity and their ratio) mostly belong to core block together with Soil Organic Carbon (SOC), while climate and soil variables to periphery block with the exception of cropland networks, denoting the higher dependence between microbial and climate variables in these latter. All complete networks appeared robust except for cropland and forest in summer, a finding that disagrees with our initial hypothesis about cropland. Networks' connectivity was controlled stronger by stochasticity in forest than in croplands. The lack of human interventions in forest soils increase habitat homogeneity enhancing the influence of stochastic agents such as microbial unlimited dispersal and/or stochastic extinction. The increased stochasticity implies the necessity for proactive management actions.

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

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

Generalist and topologically central avian frugivores promote plant invasion unequally across land-bridge islands

Seed dispersal by frugivorous birds facilitates plant invasions, but it is poorly known how invasive plants integrate into native communities in fragmented landscapes. We surveyed plant-frugivore interactions, including an invasive plant (Phytolacca americana), on 22 artificial land-bridge islands (fragmented forests) in the Thousand Island Lake, China. Focusing on frugivory interactions that may lead to seed dispersal, we built ecological networks of studied islands both at the local island (community) and at landscape (metacommunity) levels. On islands with P. americana, we found that P. americana impacted local avian frugivory networks more on islands with species-poor plant communities and on isolated islands. Moreover, as P. americana interacted mainly with local core birds (generalists), this indicates reduced seed dispersal of native plants on invaded islands. At the landscape level, P. americana had established strong interactions with generalist birds that largely maintain seed-dispersal functions across islands, as revealed by their topologically central roles both in the regional plant-bird trophic network and in the spatial metanetwork. This indicates that generalist frugivorous birds may have facilitated the dispersal of P. americana across islands, making P. americana well integrated into the plant-frugivore mutualistic metacommunity. Taken together, our study demonstrates that the impact of plant invasion is context-dependent and that generalist native frugivores with high dispersal potential may accelerate plant invasion in fragmented landscapes. These findings highlight the importance of taking the functional roles of animal mutualists and habitat fragmentation into account when managing plant invasions and their impact on native communities.

Neural circuit disruptions of eye gaze processing in autism spectrum disorder and schizophrenia: An activation likelihood estimation meta-analysis

BACKGROUND

Impairment in social cognition, particularly eye gaze processing, is a shared feature common to autism spectrum disorder (ASD) and schizophrenia. However, it is unclear if a convergent neural mechanism also underlies gaze dysfunction in these conditions. The present study examined whether this shared eye gaze phenotype is reflected in a profile of convergent neurobiological dysfunction in ASD and schizophrenia.

METHODS

Activation likelihood estimation (ALE) meta-analyses were conducted on peak voxel coordinates across the whole brain to identify spatial convergence. Functional coactivation with regions emerging as significant was assessed using meta-analytic connectivity modeling. Functional decoding was also conducted.

RESULTS

Fifty-six experiments (n = 30 with schizophrenia and n = 26 with ASD) from 36 articles met inclusion criteria, which comprised 354 participants with ASD, 275 with schizophrenia and 613 healthy controls (1242 participants in total). In ASD, aberrant activation was found in the left amygdala relative to unaffected controls during gaze processing. In schizophrenia, aberrant activation was found in the right inferior frontal gyrus and supplementary motor area. Across ASD and schizophrenia, aberrant activation was found in the right inferior frontal gyrus and right fusiform gyrus during gaze processing. Functional decoding mapped the left amygdala to domains related to emotion processing and cognition, the right inferior frontal gyrus to cognition and perception, and the right fusiform gyrus to visual perception, spatial cognition, and emotion perception. These regions also showed meta-analytic connectivity to frontoparietal and frontotemporal circuitry.

CONCLUSION

Alterations in frontoparietal and frontotemporal circuitry emerged as neural markers of gaze impairments in ASD and schizophrenia. These findings have implications for advancing transdiagnostic biomarkers to inform targeted treatments for ASD and schizophrenia.

Using individual-based trait frequency distributions to forecast plant-pollinator network responses to environmental change

Determining how and why organisms interact is fundamental to understanding ecosystem responses to future environmental change. To assess the impact on plant-pollinator interactions, recent studies have examined how the effects of environmental change on individual interactions accumulate to generate species-level responses. Here, we review recent developments in using plant-pollinator networks of interacting individuals along with their functional traits, where individuals are nested within species nodes. We highlight how these individual-level, trait-based networks connect intraspecific trait variation (as frequency distributions of multiple traits) with dynamic responses within plant-pollinator communities. This approach can better explain interaction plasticity, and changes to interaction probabilities and network structure over spatiotemporal or other environmental gradients. We argue that only through appreciating such trait-based interaction plasticity can we accurately forecast the potential vulnerability of interactions to future environmental change. We follow this with general guidance on how future studies can collect and analyse high-resolution interaction and trait data, with the hope of improving predictions of future plant-pollinator network responses for targeted and effective conservation.

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

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

Exploring neural heterogeneity in inattention and hyperactivity

Inattention and hyperactivity are cardinal symptoms of Attention Deficit Hyperactivity Disorder (ADHD). These characteristics have also been observed across a range of other neurodevelopmental conditions, such as autism and dyspraxia, suggesting that they might best be studied across diagnostic categories. Here, we evaluated the associations between inattention and hyperactivity behaviours and features of the structural brain network (connectome) in a large transdiagnostic sample of children (Centre for Attention, Learning, and Memory; n = 383). In our sample, we found that a single latent factor explains 77.6% of variance in scores across multiple questionnaires measuring inattention and hyperactivity. Partial Least-Squares (PLS) regression revealed that variability in this latent factor could not be explained by a linear component representing nodewise properties of connectomes. We then investigated the type and extent of neural heterogeneity in a subset of our sample with clinically-elevated levels of inattention and hyperactivity. Multidimensional scaling combined with k-means clustering revealed two neural subtypes in children with elevated levels of inattention and hyperactivity (n = 232), differentiated primarily by nodal communicability-a measure which demarcates the extent to which neural signals propagate through specific brain regions. These different clusters had similar behavioural profiles, which included high levels of inattention and hyperactivity. However, one of the clusters scored higher on multiple cognitive assessment measures of executive function. We conclude that inattention and hyperactivity are so common in children with neurodevelopmental difficulties because they emerge through multiple different trajectories of brain development. In our own data, we can identify two of these possible trajectories, which are reflected by measures of structural brain network topology and cognition.

Rapid monitoring of ecological persistence

Effective conservation of ecological communities requires accurate and up-to-date information about whether species are persisting or declining to extinction. The persistence of an ecological community is supported by its underlying network of species interactions. While the persistence of the network supporting the whole community is the most relevant scale for conservation, in practice, only small subsets of these networks can be monitored. There is therefore an urgent need to establish links between the small snapshots of data conservationists can collect, and the "big picture" conclusions about ecosystem health demanded by policymakers, scientists, and societies. Here, we show that the persistence of small subnetworks (motifs) in isolation-that is, their persistence when considered separately from the larger network of which they are a part-is a reliable probabilistic indicator of the persistence of the network as a whole. Our methods show that it is easier to detect if an ecological community is not persistent than if it is persistent, allowing for rapid detection of extinction risk in endangered systems. Our results also justify the common practice of predicting ecological persistence from incomplete surveys by simulating the population dynamics of sampled subnetworks. Empirically, we show that our theoretical predictions are supported by data on invaded networks in restored and unrestored areas, even in the presence of environmental variability. Our work suggests that coordinated action to aggregate information from incomplete sampling can provide a means to rapidly assess the persistence of entire ecological networks and the expected success of restoration strategies.

The non-random assembly of network motifs in plant-pollinator 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.

Generalism drives abundance: A computational causal discovery approach

A ubiquitous pattern in ecological systems is that more abundant species tend to be more generalist; that is, they interact with more species or can occur in wider range of habitats. However, there is no consensus on whether generalism drives abundance (a selection process) or abundance drives generalism (a drift process). As it is difficult to conduct direct experiments to solve this chicken-and-egg dilemma, previous studies have used a causal discovery method based on formal logic and have found that abundance drives generalism. Here, we refine this method by correcting its bias regarding skewed distributions, and employ two other independent causal discovery methods based on nonparametric regression and on information theory, respectively. Contrary to previous work, all three independent methods strongly indicate that generalism drives abundance when applied to datasets on plant-hummingbird communities and reef fishes. Furthermore, we find that selection processes are more important than drift processes in structuring multispecies systems when the environment is variable. Our results showcase the power of the computational causal discovery approach to aid ecological research.

Ever since Aristotle, the chicken-or-egg causality dilemma has baffled researchers. Such causality dilemmas are abundant in ecological research, where causal directions are often assumed but not tested. An archetypal example is whether being a generalist causes a species to be more abundant, or whether being more abundant causes a species to be generalists. Without doubt, the gold standard to establish causal directions is controlled experiments. However, controlled experiments that can disentangle the direction of causality in this case are challenging because it involves controlling biotic or abiotic niche breadth. These challenges create an opportunity for computational tools to detect the most likely causal direction. Here, by adapting a set of recently developed computational methods, we provide strong evidence that generalism drives abundance, overturning the previously established direction. We hope our work raises awareness of the potential for computational discovery methods to address long-standing questions in ecology, especially increasingly large datasets become available.

Advancing biological invasion hypothesis testing using functional diversity indices

Pioneering investigations on the effects of introduced populations on community structure, ecosystem functioning and services have focused on the effects of invaders on taxonomic diversity. However, taxonomic-based diversity metrics overlook the heterogeneity of species roles within and among communities. As the homogenizing effects of biological invasions on community and ecosystem processes can be subtle, they may require the use of functional diversity indices to be properly evidenced. Starting from the listing of major functional diversity indices, alongside the presentation of their strengths and limitations, we focus on studies pertaining to the effects of invasive species on native communities and recipient ecosystems using functional diversity indices. By doing so, we reveal that functional diversity of the recipient community may strongly vary at the onset of the invasion process, while it stabilizes at intermediate and high levels of invasion. As functional changes occurring during the lag phase of an invasion have been poorly investigated, we show that it is still unknown whether there are consistent changes in functional diversity metrics that could indicate the end of the lag phase. Thus, we recommend providing information on the invasion stage under consideration when computing functional diversity metrics. For the existing literature, it is also surprising that very few studies explored the functional difference between organisms from the recipient communities and invaders of the same trophic levels, or assessed the effects of non-native organism establishment into a non-analogue versus an analogue community. By providing valuable tools for obtaining in-depth diagnostics of community structure and functioning, functional diversity indices can be applied for timely implementation of restoration plans and improved conservation strategies. To conclude, our work provides a first synthetic guide for their use in hypothesis testing in invasion biology.

The disruption of a keystone interaction erodes pollination and seed dispersal networks

Understanding the impacts of global change on ecological communities is a major challenge in modern ecology. The gain or loss of particular species and the disruption of key interactions are both consequences and drivers of global change that can lead to the disassembly of ecological networks. We examined whether the disruption of a hummingbird-mistletoe-marsupial mutualism by the invasion of non-native species can have cascading effects on both pollination and seed dispersal networks in the temperate forest of Patagonia, Argentina. We focused on network motifs, subnetworks composed of a small number of species exhibiting particular patterns of interaction, to examine the structure and diversity of mutualistic networks. We found that the hummingbird-mistletoe-marsupial mutualism plays a critical role in the community by increasing the complexity of pollination and seed dispersal networks through supporting a high diversity of interactions. Moreover, we found that the disruption of this tripartite mutualism by non-native ungulates resulted in diverse indirect effects that led to less complex pollination and seed dispersal networks. Our results demonstrate that the gains and losses of particular species and the alteration of key interactions can lead to cascading effects in the community through the disassembly of mutualistic networks.

A keystone mutualism promotes resistance to invasion

It is not uncommon for one or a few species, and their interactions, to have disproportionate effects on other species in ecological communities. Such keystone interactions might affect how communities respond to the invasion of non-native species by preventing or inhibiting the establishment, spread or impact of non-native species. We explore whether a keystone mutualism among a hummingbird-mistletoe-marsupial promotes ecological resistance to an invasive pollinator, the bumblebee Bombus terrestris, by comparing data collected at sites prior to bumblebee invasion to data collected 11 years after the invasion in sites with and without the keystone mutualism. We built pollination networks and focused on network motifs, regarded as building blocks of networks, to identify the central pollinators and estimate the change in their interactions after invasion of B. terrestris. We also estimated the interaction rewiring across the season in post-invasion networks and tested it as a possible mechanism explaining how the keystone mutualism increased ecological resistance to invasion. We found two times more species in post-invasion sites with the keystone mutualism than in post-invasion sites without the keystone mutualism. Moreover, we found that invasive bumblebee reduced the strength and interaction niche of the five central pollinator species while increasing its own strength and interaction niche, suggesting a replacement of interactions. Also, we found that the keystone mutualism promoted resistance to B. terrestris invasion by reducing its negative impacts on central species. In the presence of the keystone mutualism, central species had three times more direct interactions than in sites without this keystone mutualism. The higher interaction rewiring, after invasion of B. terrestris, in sites with the keystone mutualism indicates greater chances of central pollinators to form new interactions and reduces their competence for resources with the non-native bumblebee. Our results demonstrate that a keystone mutualism can enhance community resistance against the impacts of a non-native invasive pollinator by increasing species diversity and promoting interaction rewiring in the community. This study suggests that the conservation of mutualisms, especially those considered keystone, could be essential for long-term preservation of natural communities under current and future impacts of global change.

Functional traits driving species role in the structure of terrestrial vertebrate scavenger networks

Species assemblages often have a non-random nested organization, which in vertebrate scavenger (carrion-consuming) assemblages is thought to be driven by facilitation in competitive environments. However, not all scavenger species play the same role in maintaining assemblage structure, as some species are obligate scavengers (i.e., vultures) and others are facultative, scavenging opportunistically. We used a database with 177 vertebrate scavenger species from 53 assemblages in 22 countries across five continents to identify which functional traits of scavenger species are key to maintaining the scavenging network structure. We used network analyses to relate ten traits hypothesized to affect assemblage structure with the "role" of each species in the scavenging assemblage in which it appeared. We characterized the role of a species in terms of both the proportion of monitored carcasses on which that species scavenged, or scavenging breadth (i.e., the species "normalized degree"), and the role of that species in the nested structure of the assemblage (i.e., the species "paired nested degree"), therefore identifying possible facilitative interactions among species. We found that species with high olfactory acuity, social foragers, and obligate scavengers had the widest scavenging breadth. We also found that social foragers had a large paired nested degree in scavenger assemblages, probably because their presence is easier to detect by other species to signal carcass occurrence. Our study highlights differences in the functional roles of scavenger species and can be used to identify key species for targeted conservation to maintain the ecological function of scavenger assemblages.

Divide-and-conquer: machine-learning integrates mammalian and viral traits with network features to predict virus-mammal associations

Our knowledge of viral host ranges remains limited. Completing this picture by identifying unknown hosts of known viruses is an important research aim that can help identify and mitigate zoonotic and animal-disease risks, such as spill-over from animal reservoirs into human populations. To address this knowledge-gap we apply a divide-and-conquer approach which separates viral, mammalian and network features into three unique perspectives, each predicting associations independently to enhance predictive power. Our approach predicts over 20,000 unknown associations between known viruses and susceptible mammalian species, suggesting that current knowledge underestimates the number of associations in wild and semi-domesticated mammals by a factor of 4.3, and the average potential mammalian host-range of viruses by a factor of 3.2. In particular, our results highlight a significant knowledge gap in the wild reservoirs of important zoonotic and domesticated mammals' viruses: specifically, lyssaviruses, bornaviruses and rotaviruses.

Pollinator interaction flexibility across scales affects patch colonization and occupancy

Global change alters ecological communities and may disrupt ecological interactions and the provision of ecosystem functions. As ecological communities respond to global change, species may either go locally extinct or form novel interactions. To date, few studies have assessed how flexible species are in their interaction patterns, mainly due to the scarcity of data spanning long time series. Using a ten-year species-level dataset on the assembly of mutualistic networks from the Central Valley in California, we test whether interaction flexibility affects pollinators' colonization and persistence and their resulting habitat occupancy in a highly modified landscape. We propose three metrics of interaction flexibility associated with different scales of organization within ecological communities and explore which species' traits affect them. Our results provide empirical evidence linking species' ability to colonize habitat patches across a landscape to the role they play in networks. Phenological breadth and body size had contrasting effects on interaction flexibility. We demonstrate the relationship between mutualistic networks and species' ability to colonize and persist in the landscape, suggesting interaction flexibility as a potential mechanism for communities to maintain ecosystem function despite changes in community composition.

Pathways for Novel Epidemiology: Plant-Pollinator-Pathogen Networks and Global Change

Multiple global change pressures, and their interplay, cause plant-pollinator extinctions and modify species assemblages and interactions. This may alter the risks of pathogen host shifts, intra- or interspecific pathogen spread, and emergence of novel population or community epidemics. Flowers are hubs for pathogen transmission. Consequently, the structure of plant-pollinator interaction networks may be pivotal in pathogen host shifts and modulating disease dynamics. Traits of plants, pollinators, and pathogens may also govern the interspecific spread of pathogens. Pathogen spillover-spillback between managed and wild pollinators risks driving the evolution of virulence and community epidemics. Understanding this interplay between host-pathogen dynamics and global change will be crucial to predicting impacts on pollinators and pollination underpinning ecosystems and human wellbeing.

Restoration of Degraded Alpine Meadows Improves Pollination Network Robustness and Function in the Tibetan Plateau

Ecological restoration is widely used to mitigate the negative impacts of anthropogenic activities. There is an increasing demand to identify suitable restoration management strategies for specific habitat and disturbance types to restore interactions between organisms of degraded habitats, such as pollination. In the Tibetan Plateau, alpine meadows have suffered severe degradation due to overgrazing and climate change. Protecting vegetation by fencing during the growing season is a widely applied management regime for restoration of degraded grasslands in this region. Here, we investigated the effect of this restoration strategy on plant–pollinator communities and plant reproduction in the eastern Tibetan Plateau. We collected interaction and seed set data monthly across three grazed (grazed all year) and three ungrazed (fenced during growing season) alpine meadows in growing seasons of two consecutive years. We found ungrazed meadows produced more flowers and attracted more pollinator visits. Many common network metrics, such as nestedness, connectance, network specialization, and modularity, did not differ between grazing treatments. However, plants in ungrazed meadows were more robust to secondary species extinction than those in grazed meadows. The observed changes in the networks corresponded with higher seed set of plants that rely on pollinators for reproduction. Our results indicate that protection from grazing in growing seasons improves pollination network stability and function and thus is a viable restoration approach for degraded meadows.

Evolutionary stability of plant-pollinator networks: efficient communities and a pollination dilemma

Mutualistic interactions between species are ubiquitous in nature and essential for ecosystem functioning. Often dozens or even hundreds of species with different degrees of specialisation form complex networks. How this complexity evolves is a fundamental question in ecology. Here, we present a new game theoretical approach to model complex coevolutionary processes and apply it to pollination networks. A theoretical analysis reveals multiple evolutionary stable network structures that depend on the availability of pollination service. In particular, we find efficient communities, in which a high percentage of pollen are transported conspecifically, to evolve only when plant and pollinator abundances are well balanced. Both pollinator shortage and oversupply select for more inefficient network structures. The results suggest that availability of pollination services is a key factor structuring pollination networks and may offer a new explanation for geographical differences in pollination communities that have long been recognised by ecologists.

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

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

Community-level reorganizations following migratory pollinator dynamics along a latitudinal gradient

Predicting how communities re-arrange in response to changes in species composition remains a key challenge in ecology. Migratory species, which enter and leave communities across latitudinal gradients, offer us a unique opportunity to evaluate community- and species-level responses to a shift in community composition. We focused on a migratory hummingbird and the communities that host it along a latitudinal and species diversity gradient. Our results show higher niche overlap in more diverse communities, allowing resident species to compensate for the loss of the migrant in providing pollination services. Contrastingly, in less diverse communities, the migrant behaves as a specialist, monopolizing abundant resources. In its absence, its role is not fully covered by resident species, resulting in a decrease in the fruit set of the migrant's preferred plant species. These results help us understand the potential impacts of biodiversity loss and have important implications for community persistence given expected changes in the migratory behaviours of some species.