Analysing ecological networks of species interactions

Australia's recently established predators restore complexity to food webs simplified by extinction

Since prehistory, humans have altered the composition of ecosystems by causing extinctions and introducing species. However, our understanding of how waves of species extinctions and introductions influence the structure and function of ecological networks through time remains piecemeal. Here, focusing on Australia, which has experienced many extinctions and introductions since the Late Pleistocene, we compared the functional trait composition of Late Pleistocene (130,00-115,000 years before present [ybp]), Holocene (11,700-3,000 ybp), and current Australian mammalian predator assemblages (≥70% vertebrate meat consumption; ≥1 kg adult body mass). We then constructed food webs for each period based on estimated prey body mass preferences. We found that introduced predators are functionally distinct from extinct Australian predators, but they rewire food webs toward a state that closely resembles the Late Pleistocene, prior to the megafauna extinctions. Both Late Pleistocene and current-day food webs consist of an apex predator and three smaller predators. This leads to food web networks with a similar total number of links, link densities, and compartmentalizations. However, this similarity depends on the presence of dingoes: in their absence, food webs become simplified and reminiscent of those following the Late Pleistocene extinctions. Our results suggest that recently established predators, even those implicated in species extinctions and declines, can restore complexity to food webs simplified by extinction.

Navigating the microalgal maze: a comprehensive review of recent advances and future perspectives in biological networks

MAIN CONCLUSION

PPI analysis deepens our knowledge in critical processes like carbon fixation and nutrient sensing. Moreover, signaling networks, including pathways like MAPK/ERK and TOR, provide valuable information in how microalgae respond to environmental changes and stress. Additionally, species-species interaction networks for microalgae provide a comprehensive understanding of how different species interact within their environments. This review examines recent advancements in the study of biological networks within microalgae, with a focus on the intricate interactions that define these organisms. It emphasizes how network biology, an interdisciplinary field, offers valuable insights into microalgae functions through various methodologies. Crucial approaches, such as protein-protein interaction (PPI) mapping utilizing yeast two-hybrid screening and mass spectrometry, are essential for comprehending cellular processes and optimizing functions, such as photosynthesis and fatty acid biosynthesis. The application of advanced computational methods and information mining has significantly improved PPI analysis, revealing networks involved in critical processes like carbon fixation and nutrient sensing. The review also encompasses transcriptional networks, which play a role in gene regulation and stress responses, as well as metabolic networks represented by genome-scale metabolic models (GEMs), which aid in strain optimization and the prediction of metabolic outcomes. Furthermore, signaling networks, including pathways like MAPK/ERK and TOR, are crucial for understanding how microalgae respond to environmental changes and stress. Additionally, species-species interaction networks for microalgae provide a comprehensive understanding of how different species interact within their environments. The integration of these network biology approaches has deepened our understanding of microalgal interactions, paving the way for more efficient cultivation and new industrial applications.

Ecological associations distribution modelling of marine plankton at a global scale

Marine plankton communities form intricate networks of interacting organisms at the base of the food chain, and play a central role in regulating ocean biogeochemical cycles and climate. However, predicting plankton community shifts in response to climate change remains challenging. While species distribution models are valuable tools for predicting changes in species biogeography under climate change scenarios, they generally overlook the key role of biotic interactions, which can significantly shape ecological processes and ecosystem responses. Here, we introduce a novel statistical framework, association distribution modelling (ADM), designed to model and predict ecological associations distribution in space and time. Applied on a Tara Oceans genome-resolved metagenomics dataset, the present-day biogeography of ADM-inferred marine plankton associations revealed four major biogeographic biomes organized along a latitudinal gradient. We predicted the evolution of these biome-specific communities in response to a climate change scenario, highlighting differential responses to environmental change. Finally, we explored the functional potential of impacted plankton communities, focusing on carbon fixation, outlining the predicted evolution of its geographical distribution and implications for ecosystem function.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Quantifying stability and resilience of eco-social keystone species complexes for coastal marine ecosystems of the Caribbean Sea and eastern Pacific: applications in conservation and monitoring programmes

The local stability and resilience of 13 eco-social keystone species complexes (eco-social KSCs)-considered as conservation and monitoring units-were quantified in coastal marine ecosystems located in the Caribbean and eastern Pacific. Based on Routh-Hurwitz's criterion and Levins' criteria, the eco-social KSCs corresponding to Islas Marietas National Park (Mexico) emerged as the most locally stable and resilient ecosystem. To the contrary, the eco-social KSCs determined for Guala Guala Bay (Chile) and Xcalak Reef National Park (Caribbean) were the least stable and resilient, respectively. In terms of sensitivity, the eco-social KSCs corresponding to El Cobre Bay (Chile) presented the greatest number of sensitive components. The ecological section of the KSCs is formed by a tri-trophic network, dominating self-negative feedbacks. In the case of the socio-economic section, the fisher could exhibit the three types of self-feedbacks, and instead, the demand should be controlled. The identification of eco-social KSCs and the quantification of their stabilities and resiliences allow us to approach ecosystem-based fisheries management under a climate change context. Therefore, we suggest assessing and monitoring the persistence of the eco-social KSCs herein analysed over time, as a way to conserve the fundamental network structure of these ecosystems intervened by fishing.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Modeling freshwater plankton community dynamics with static and dynamic interactions using graph convolution embedded long short-term memory

Given the frequent association between freshwater plankton and water quality degradation, several predictive models have been devised to understand and estimate their dynamics. However, the significance of biotic and abiotic interactions has been overlooked. In this study, we aimed to address the importance of the interaction term in predicting plankton community dynamics by applying graph convolution embedded long short-term memory networks (GC-LSTM) models, which can incorporate interaction terms as graph signals. Temporal graph series comprising plankton genera or environmental drivers as node features and their relationships for edge features from two distinct water bodies, a reservoir and a river, were utilized to develop these models. To assess the predictability, the performances of the GC-LSTM models on community dynamics were compared those of LSTM and GCN models at various lead times. Moreover, GNNExplainer was used to examine the global and local importance of the nodes and edges for all predictions and specific predictions, respectively. The GC-LSTM models outperformed the LSTM models, consistently showing higher prediction accuracy. Although all the models exhibited performance degradation at longer lead times, the GC-LSTM models consistently demonstrated better performance regarding each graph signal and plankton genus. GNNExplainer yielded interpretable explanations for important genera and interaction pairs among communities, revealing consistent importance patterns across different lead times at both global and local scales. These findings underscore the potential of the proposed modeling approach for forecasting community dynamics and emphasize the critical role of graph signals with interaction terms in plankton communities.

What's on the menu? A novel molecular gut content analysis to investigate the feeding behavior of phytophagous insects

The relationship between phytophagous insects and plants is a central aspect of food webs and ecosystem functioning. The introduction of new species into an environment can have significant impacts on the food web of a native ecosystem. In many cases, there is a lack of knowledge on the biology and feeding behavior of invasive species prior their introduction and in the invaded regions. Gut content analyses of insects have provided valuable information on the host spectrum of insects. However, current approaches are time-consuming and costly. Here, we describe a new molecular gut content analysis (GCA) approach using the Oxford Nanopore (ONT) Flongle sequencing platform to characterize the plant DNA present in the gut of the highly polyphagous insect species Halyomorpha halys. We demonstrate that this technique efficiently amplifies and correctly identifies plant DNA in a mock community. We performed a feeding experiment to determine the sensitivity of this approach and to assess how long the plant DNA can be detected. All plants used in the feeding experiment were correctly identified and detected after 56 days. Surprisingly, we also detected various plant genera that were not included in the feeding experiment and thus were likely ingested months before the experiment. Our study suggests that the GCA using the ONT Flongle sequencing platform represents a rapid and cost-efficient diagnosis of the dietary preferences, host range, and the diversity of consumed plant species of pest insects with high precision.

Interspecific interaction network of mites associated with mango trees

Direct and indirect ecological interactions, environmental factors, and the phenology of host plants can shape the way mites interact. These relationships interfere with species occurrence and consequently alter the structure and stability of the intraplant community. As predatory mites act as regulators of herbivorous mites, we hypothesized that these mites may occupy a central position in a network of interactions among mite species associated with mango trees, and the occurrence of these species is mediated by environmental variables and the phenological stage of the host plant. We evaluated the global structure of the interaction network of mites associated with individual Mangifera indica plants and analyzed the interspecific relationships of the species using an undirected Bayesian network approach. Additionally, we observed a correlation between mite population density and plant phenological stage. Environmental variables, such as average monthly temperature, monthly precipitation, and average monthly relative humidity at different sampling date were used in the correlation analysis. The modularity at the mite-plant network level showed a low specialization index H2 = 0.073 (generalist) and high robustness (R = 0.93). Network analysis revealed that Amblyseius largoensis, Bdella ueckermanni, Parapronematus acaciae, and Tuckerella ornata occupied central positions in the assembly of mites occurring on mango trees. Environmental variables, average monthly temperature, and monthly precipitation were correlated with the occurrence of Brachytydeus formosa, Cisaberoptus kenyae, Oligonychus punicae, T. ornata, and Vilaia pamithus. We also observed a correlation between the plant phenological stage and population densities of Neoseiulus houstoni, O. punicae, P. acaciae, and V. pamithus.

Biodiversity in changing environments: An external-driver internal-topology framework to guide intervention

Accompanying the climate crisis is the more enigmatic biodiversity crisis. Rapid reorganization of biodiversity due to global environmental change has defied prediction and tested the basic tenets of conservation and restoration. Conceptual and practical innovation is needed to support decision making in the face of these unprecedented shifts. Critical questions include: How can we generalize biodiversity change at the community level? When are systems able to reorganize and maintain integrity, and when does abiotic change result in collapse or restructuring? How does this understanding provide a template to guide when and how to intervene in conservation and restoration? To this end, we frame changes in community organization as the modulation of external abiotic drivers on the internal topology of species interactions, using plant-plant interactions in terrestrial communities as a starting point. We then explore how this framing can help translate available data on species abundance and trait distributions to corresponding decisions in management. Given the expectation that community response and reorganization are highly complex, the external-driver internal-topology (EDIT) framework offers a way to capture general patterns of biodiversity that can help guide resilience and adaptation in changing environments.

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.

Effects of plant diversity and community structure on ecosystem multifunctionality under different grazing potentials in the eastern Eurasian steppe

Grazing potential represents the potential carrying capacity of steppe livestock production. Understanding the impact of changes in plant diversity and community structure on ecosystem multifunctionality (EMF) at different grazing potentials is crucial for the sustainable management of steppe ecosystems. We examined the associations between plant diversity, community structure, above-ground ecosystem multifunctionality (AEMF), and below-ground ecosystem multifunctionality (BEMF) at various grazing potentials. Our assessment employed generalized linear mixed-effects models and structural equation models to determine the impact of these factors on ecosystem multifunctionality. Our study results indicated that ecosystem multifunctionality differed depending on the level of grazing potential and decreased as grazing potential declined. The impact of plant diversity and community structure on above- and below-ground ecosystem multifunctionality varied. Plant diversity and community structure correlated more with AEMF than BEMF. Plant diversity had the most significant effect on EMF under high grazing potential, while community structure had the greatest effect on EMF under moderate and low grazing potential. These improve our understanding of the correlation between steppe plant diversity, community structure, and above- and below-ground ecosystem multifunctionality. This understanding is necessary to develop strategies to increase plant diversity or regulate community structure and the sustainability of steppes.

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.

Network motifs in cellular neurophysiology

Concepts from network science and graph theory, including the framework of network motifs, have been frequently applied in studying neuronal networks and other biological complex systems. Network-based approaches can also be used to study the functions of individual neurons, where cellular elements such as ion channels and membrane voltage are conceptualized as nodes within a network, and their interactions are denoted by edges. Network motifs in this context provide functional building blocks that help to illuminate the principles of cellular neurophysiology. In this review we build a case that network motifs operating within neurons provide tools for defining the functional architecture of single-neuron physiology and neuronal adaptations. We highlight the presence of such computational motifs in the cellular mechanisms underlying action potential generation, neuronal oscillations, dendritic integration, and neuronal plasticity. Future work applying the network motifs perspective may help to decipher the functional complexities of neurons and their adaptation during health and disease.

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.

Ecological setting of phlebotomine sand flies in the Republic of Kosovo

Sand flies (Diptera, Psychodidae) are the principal vectors of Leishmania spp., the causative agents of leishmaniasis, as well as phleboviruses. In the Balkans, the endemicity and spreading of sand fly-borne diseases are evident, particularly in the Republic of Kosovo, a country with a predominantly humid continental climate. To date, understanding the drivers behind the spatial structure and diversity patterns of sand fly communities in humid continental regions remains limited. Therefore, elucidating the geographical and ecological factors contributing to the presence of potential vector species in the country is crucial. We aimed to enhance our understanding of factors influencing sand fly occurrence in cool and wet wintering humid continental areas, which could serve as a model for other countries with similar climatic conditions. Therefore, we assessed the currently known sand fly fauna through detailed environmental analyses, including Voronoi tessellation patterns, entropy calculations, Principal Coordinate and Component Analyses, Hierarchical Clustering, Random Trees, and climatic suitability patterns. Notable differences in the ecological tolerance of the species were detected, and the most important climatic features limiting sand fly presence were wind speed and temperature seasonality. Sand flies were observed to prefer topographical environments with little roughness, and the modelled climatic suitability values indicated that, dominantly, the western plain regions of Kosovo harbour the most diverse sand fly fauna; and are the most threatened by sand fly-borne diseases. Phlebotomus neglectus and P. perfiliewi, both confirmed vectors for L. infantum and phleboviruses, were identified as two main species with vast distribution in Kosovo. Contrary to this, most other present species are relatively sparse and restricted to temperate rather than humid continental regions. Our findings reveal a diverse potential sand fly fauna in Kosovo, indicating the need for tailored strategies to address varying risks across the country's western and eastern regions in relation to leishmaniasis control amidst changing environmental conditions.

Distinct multitrophic biodiversity composition and community organization in a freshwater lake and a hypersaline lake on the Tibetan Plateau

Alpine lakes play pivotal roles in plateau hydrological processes but are highly sensitive to climate change, yet we lack comprehensive knowledge of their multitrophic biodiversity patterns. Here, we compared the biodiversity characteristics of diverse taxonomic groups across water depths and in surface sediments from a freshwater lake and a hypersaline lake on the northwestern Tibetan Plateau. Using multi-marker environmental DNA metabarcoding, we detected 134 cyanobacteria, 443 diatom, 1,519 invertebrate, and 28 vertebrate taxa. Each group had a substantially different community composition in the two lakes, and differences were also found between water and sediments within each lake. Cooccurrence network analysis revealed higher network complexity, lower modularity, and fewer negative cohesions in the hypersaline lake, suggesting that high salinity may destabilize ecological networks. Our results provide the first holistic view of Tibetan lake biodiversity under contrasting salinity levels and reveal structural differences in the ecological networks that may impact ecosystem resilience.

The propagation of disturbances in ecological networks

Despite the development of network science, we lack clear heuristics for how far different disturbance types propagate within and across species interaction networks. We discuss the mechanisms of disturbance propagation in ecological networks, and propose that disturbances can be categorized into structural, functional, and transmission types according to their spread and effect on network structure and functioning. We describe the properties of species and their interaction networks and metanetworks that determine the indirect, spatial, and temporal extent of propagation. We argue that the sampling scale of ecological studies may have impeded predictions regarding the rate and extent that a disturbance spreads, and discuss directions to help ecologists to move towards a predictive understanding of the propagation of impacts across interacting communities and ecosystems.

Properties of vertebrate predator-prey networks in the high Arctic

Predation is an important ecological process that can significantly impact the maintenance of ecosystem services. In arctic environments, the relative ecological importance of predation is thought to be increasing due to climate change, partly because of increased productivity with rising temperatures. Therefore, understanding predator-prey interactions in arctic ecosystems is vital for the sustainable management of these northern regions. Network theory provides a framework for quantifying the structures of ecological interactions. In this study, we use dietary observations on mammalian and avian predators in a high arctic region, including isolated peninsulas on Ellesmere Island and north Greenland, to construct bipartite trophic networks. We quantify the complexity, specialization, and nested as well as modular structures of these networks and also determine if these properties varied among the peninsulas. Mammal prey remains were the dominant diet item for all predators, but there was spatial variation in diet composition among peninsulas. The predator-prey networks were less complex, had more specialized interactions, and were more nested and more modular than random expectations. However, the networks displayed only moderate levels of modularity. Predator species had less specialized interactions with prey than prey had with predators. All network properties differed among the peninsulas, which highlights that ecosystems often show complex responses to environmental characteristics. We suggest that gaining knowledge about spatial variation in the characteristics of predator-prey interactions can enhance our ability to manage ecosystems exposed to environmental perturbations, particularly in high arctic environments subject to rapid environmental change.

The reorganization of predator-prey networks over 20 million years explains extinction patterns of mammalian carnivores

Linking the species interactions occurring at the scale of local communities to their potential impact at evolutionary timescales is challenging. Here, we used the high-resolution fossil record of mammals from the Iberian Peninsula to reconstruct a timeseries of trophic networks spanning more than 20 million years and asked whether predator-prey interactions affected regional extinction patterns. We found that, despite small changes in species richness, trophic networks showed long-term trends, gradually losing interactions and becoming sparser towards the present. This restructuring of the ecological networks was driven by the loss of medium-sized herbivores, which reduced prey availability for predators. The decrease in prey availability was associated with predator longevity, such that predators with less available prey had greater extinction risk. These results not only reveal long-term trends in network structure but suggest that prey species richness in ecological communities may shape large scale patterns of extinction and persistence among predators.

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.

Plant networks are more connected by invasive brome and native shrub facilitation in Central California drylands

Dominant vegetation in many ecosystems is an integral component of structure and habitat. In many drylands, native shrubs function as foundation species that benefit other plants and animals. However, invasive exotic plant species can comprise a significant proportion of the vegetation. In Central California drylands, the facilitative shrub Ephedra californica and the invasive Bromus rubens are widely dispersed and common. Using comprehensive survey data structured by shrub and open gaps for the region, we compared network structure with and without this native shrub canopy and with and without the invasive brome. The presence of the invasive brome profoundly shifted the network measure of centrality in the microsites structured by a shrub canopy (centrality scores increased from 4.3 under shrubs without brome to 6.3, i.e. a relative increase of 42%). This strongly suggests that plant species such as brome can undermine the positive and stabilizing effects of native foundation plant species provided by shrubs in drylands by changing the frequency that the remaining species connect to one another. The net proportion of positive and negative associations was consistent across all microsites (approximately 50% with a total of 14% non-random co-occurrences on average) suggesting that these plant-plant networks are rewired but not more negative. Maintaining resilience in biodiversity thus needs to capitalize on protecting native shrubs whilst also controlling invasive grass species particularly when associated with shrubs.

Re-oligotrophication and warming stabilize phytoplankton networks

Phytoplankton taxa are strongly interconnected as a network, which could show temporal dynamics and non-linear responses to changes in drivers at both seasonal and long-term scale. Using a high quality dataset of 20 Danish lakes (1989-2008), we applied extended Local Similarity Analysis to construct temporal network of phytoplankton communities for each lake, obtained sub-network for each sampling month, and then measured indices of network complexity and stability for each sub-network. We assessed how lake re-oligotrophication, climate warming and grazers influenced the temporal dynamics on network complexity and stability of phytoplankton community covering three aspects: seasonal trends, long-term trends and detrended variability. We found strong seasonality for the complexity and stability of phytoplankton network, an increasing trend for the average degree, modularity, nestedness, persistence and robustness, and a decreasing trend for connectance, negative:positive interactions and vulnerability. Our study revealed a cascading effect of lake re-oligotrophication, climate warming and zooplankton grazers on phytoplankton network stability through changes in network complexity characterizing diversity, interactions and topography. Network stability of phytoplankton increased with average degree, modularity, nestedness and decreased with connectance and negative:positive interactions. Oligotrophication and warming stabilized the phytoplankton network (enhanced robustness, persistence and decreased vulnerability) by enhancing its average degree, modularity, nestedness and by reducing its connectance, while zooplankton richness promoted stability of phytoplankton network through increases in average degree and decreases in negative interactions. Our results further indicate that the stabilization effects might lead to more closed, compartmentalized and nested interconnections especially in the deeper lakes, in the warmer seasons and during bloom periods. From a temporal dynamic network view, our findings highlight stabilization of the phytoplankton community as an adaptive response to lake re-oligotrophication, climate warming and grazers.

Dietary metabarcoding reveals the simplification of bird-pest interaction networks across a gradient of agricultural cover

Agriculture is vital for supporting human populations, but its intensification often leads to landscape homogenization and a decline in non-provisioning ecosystem services. Ecological intensification and multifunctional landscapes are suggested as nature-based alternatives to intensive agriculture, using ecological processes like natural pest regulation to maximize food production. Birds are recognized for their role in increasing crop yields by consuming invertebrate pests in several agroecosystems. However, the understanding of how bird species, their traits and agricultural land cover influence the structure of bird-pest interactions remains limited. We sampled bird-pest interactions monthly for 1 year, at four sites within a multifunctional landscape, following a gradient of increasing agricultural land cover. We analysed 2583 droppings of 55 bird species with DNA metabarcoding and detected 225 pest species in 1139 samples of 42 bird species. As expected, bird-pest interactions were highly variable across bird species. Dietary pest richness was lower in the fully agricultural site, while predation frequency remained consistent across the agricultural land cover gradient. Network analysis revealed a reduction in the complexity of bird-pest interactions as agricultural coverage increased. Bird species abundance affected the bird's contribution to the network structure more than any of the bird traits analysed (weight, phenology, invertebrate frequency in diet and foraging strata), with more common birds being more important to network structure. Overall, our results show that increasing agricultural land cover increases the homogenization of bird-pest interactions. This shows the importance of maintaining natural patches within agricultural landscapes for biodiversity conservation and enhanced biocontrol.

Novel community data in ecology-properties and prospects

New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce 'novel community data' as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation. We conclude that novel community data offer many opportunities to advance our understanding of fundamental ecological processes, including community assembly, biotic interactions, micro- and macroevolution, and overall ecosystem functioning.

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.

Fungal complexity and stability across afforestation areas in changing desert environments

The great achievements in combating desertification are attributed to large-scale afforestation, yet we lack verification of how the stability of the fungal community changes in afforestation areas in desert environments. Here, we present the fungal network structure from different niches (root and bulk soil) of plantations of Mongolian pine, a crucial species for afforestation introduced widely in desertification regions. We assessed changes in community complexity and stability of root-associated fungi (RAF) and soil fungi (SF) among different introduction sites: the Hulunbuir Desert (HB), the Horqin Desert (HQ) and the Mu Us Desert (MU). To illuminate the complexity and stability of the fungal network, the differences in topological properties, fungal function, and vegetation and environmental factors between introduction sites were fully considered. We showed that (1) the SF networks had more nodes and edges than the RAF networks. There was a lower ratio of negative:positive cohesion of RAF networks in HB and MU. For SF but not for RAF, across the three introduction sites, a higher modularity and ratio of negative:positive cohesion indicated higher stability. (2) Ectomycorrhizal (EcM) fungi were the dominant functional group in the RAF network (especially in HQ), and were only significantly correlated with vegetation factor. There was a higher relative abundance and number of OTUs of saprophytic fungi in the SF network and they showed positive correlations with soil nutrients. (3) RAF and SF network complexity and stability showed different responses to environmental and vegetation variables. The key determinant of the complexity and stability of the SF networks in Mongolian pine plantations was soil nutrients, followed by climate conditions. The composition and structure of the RAF community was closely related to host plants. Therefore, clarifying the complexity and stability of fungal communities in afforestation areas in changing desert environments is helpful for understanding the interactions between the environment, plants and fungi.

Intraspecific plasticity and co-variation of leaf traits facilitate Ficus tinctoria to acclimate hemiepiphytic and terrestrial habitats

Despite intensive studies on plant functional traits, the intraspecific variation and their co-variation at the multi-scale remains poorly studied, which holds the potential to unveil plant responses to changing environmental conditions. In this study, intraspecific variations of 16 leaf functional traits of a common fig species, Ficus tinctoria G. Frost., were investigated in relation to different scales: habitat types (hemiepiphytic and terrestrial), growth stages (small, medium and large) and tree crown positions (upper, middle and lower) in Xishuangbanna, Southwest China. Remarkable intraspecific variation was observed in leaf functional traits, which was mainly influenced by tree crown position, growth stage and their interaction. Stable nitrogen isotope (δ15N) and leaf area (LA) showed large variations, while stable carbon isotope (δ13C), stomata width and leaf water content showed relatively small variations, suggesting that light- and nitrogen-use strategies of F. tinctoria were plastic, while the water-use strategies have relatively low plasticity. The crown layers are formed with the growth of figs, and leaves in the lower crown increase their chlorophyll concentration and LA to improve the light energy conversion efficiency and the ability to capture weak light. Meanwhile, leaves in the upper crown increase the water-use efficiency to maintain their carbon assimilation. Moreover, hemiepiphytic medium (transitional stage) and large (free-standing stage) figs exhibited more significant trait differentiation (chlorophyll concentration, δ13C, stomata density, etc.) within the crown positions, and stronger trait co-variation compared with their terrestrial counterparts. This pattern demonstrates their acclimation to the changing microhabitats formed by their hemiepiphytic life history. Our study emphasizes the importance of multi-scaled intraspecific variation and co-variation in trait-based strategies of hemiepiphyte and terrestrial F. tinctoria, which facilitate them to cope with different environmental conditions.

Exploring interactions between parasites and their hosts in the Pantanal floodplain using an ecological network approach

The study of host-parasite interactions is essential to understand the role of each host species in the parasitic transmission cycles in a given community. The use of ecological network highlights the patterns of interactions between hosts and parasites, allowing us to evaluate the underlying structural features and epidemiological roles of different species within this context. Through network analysis, we aimed to understand the epidemiological roles of mammalian hosts species (n = 67) and their parasites (n = 257) in the Pantanal biome. Our analysis revealed a modular pattern within the network, characterized by 14 distinct modules, as well as nestedness patterns within these modules. Some key nodes, such as the multi-host parasites Trypanosoma cruzi and T. evansi, connect different modules and species. These central nodes showed us that various hosts species, including those with high local abundances, contribute to parasite maintenance. Ectoparasites, such as ticks and fleas, exhibit connections that reflect their roles as vectors of certain parasites. Overall, our findings contribute to a comprehensive understanding of the structure of host-parasite interactions in the Pantanal ecosystem, highlighting the importance of network analysis as a tool to identifying the main transmission routes and maintenance of parasites pathways. Such insights are valuable for parasitic disease control and prevention strategies and shed light on the broader complexities of ecological communities.

Plant interaction networks reveal the limits of our understanding of diversity maintenance

Species interactions are key drivers of biodiversity and ecosystem stability. Current theoretical frameworks for understanding the role of interactions make many assumptions which unfortunately, do not always hold in natural, diverse communities. This mismatch extends to annual plants, a common model system for studying coexistence, where interactions are typically averaged across environmental conditions and transitive competitive hierarchies are assumed to dominate. We quantify interaction networks for a community of annual wildflowers in Western Australia across a natural shade gradient at local scales. Whilst competition dominated, intraspecific and interspecific facilitation were widespread in all shade categories. Interaction strengths and directions varied substantially despite close spatial proximity and similar levels of local species richness, with most species interacting in different ways under different environmental conditions. Contrary to expectations, all networks were predominantly intransitive. These findings encourage us to rethink how we conceive of and categorize the mechanisms driving biodiversity in plant systems.

Environment and traits affect parasite and host species positions but not roles in flea-mammal networks

We studied spatial variation in the effects of environment and network size on species positions and roles in multiple flea-mammal networks from four biogeographic realms. We asked whether species positions (measured as species strength [SS], the degree of interaction specialization [d'], and the eigenvector centrality [C]) or the roles of fleas and their hosts in the interaction networks: (a) are repeatable/conserved within a flea or a host species; (b) vary in dependence on environmental variables and/or network size; and (c) the effects of environment and network size on species positions or roles in the networks depend on species traits. The repeatability analysis of species position indices for 441 flea and 429 host species, occurring in at least two networks, demonstrated that the repeatability of SS, d', and C within a species was significant, although not especially high, suggesting that the indices' values were affected by local factors. The majority of flea and host species in the majority of networks demonstrated a peripheral role. A value of at least one index of species position was significantly affected by environmental variables or network size in 41 and 36, respectively, of the 52 flea and 52 host species that occurred in multiple networks. In both fleas and hosts, the occurrence of the significant effect of environment or network size on at least one index of species position, but not on a species' role in a network, was associated with some species traits.

Matrix community models for ecology and evolution

Ecological communities are shaped by biotic interactions as well as environmental forces, and both must be incorporated to obtain models capable of forecasting realistic community dynamics. Many community models first specify pairwise biotic interactions and then secondarily examine how extrinsic factors such as abiotic conditions affect species abundances. A disadvantage of this approach is that the species interactions themselves are often environment and context specific, making parameterization difficult. We propose an alternative approach, matrix community models (MCMs), which are sets of matrix population models linked by an assumption of aggregate density dependence. MCMs incorporate detailed species autecology but are neutral with respect to pairwise species interactions, instead allowing interactions to be revealed within the model structure. These model-revealed species interactions, including competitive exclusion, facilitation, and interference competition, shape the distribution and abundance of species within communities and generate empirically testable predictions about species interactions. We develop a framework for building MCMs using vital rates in a stochastic, multispecies framework. Single-species matrix population models are connected via an assumption of aggregate density dependence, pairwise species interactions are estimated with sensitivity analysis, and community trajectories are analyzed under different environmental regimes using standard statistical tools and network analysis. MCMs have the advantage that pairwise species interactions need not be specified a priori, and that mechanistic demographic-environment linkages permit forecasting of community dynamics under novel, non-stationary environmental regimes. A challenge is that species' autecological vital rates, such as fecundity, growth and survivorship, must be measured under a diverse range of environmental conditions to parameterize the models. We illustrate the approach with examples and discuss prospects for future theoretical and empirical developments.

Ecological network structure in response to community assembly processes over evolutionary time

The dynamic structure of ecological communities results from interactions among taxa that change with shifts in species composition in space and time. However, our ability to study the interplay of ecological and evolutionary processes on community assembly remains relatively unexplored due to the difficulty of measuring community structure over long temporal scales. Here, we made use of a geological chronosequence across the Hawaiian Islands, representing 50 years to 4.15 million years of ecosystem development, to sample 11 communities of arthropods and their associated plant taxa using semiquantitative DNA metabarcoding. We then examined how ecological communities changed with community age by calculating quantitative network statistics for bipartite networks of arthropod-plant associations. The average number of interactions per species (linkage density), ratio of plant to arthropod species (vulnerability) and uniformity of energy flow (interaction evenness) increased significantly in concert with community age. The index of specializationH 2 ' has a curvilinear relationship with community age. Our analyses suggest that younger communities are characterized by fewer but stronger interactions, while biotic associations become more even and diverse as communities mature. These shifts in structure became especially prominent on East Maui (~0.5 million years old) and older volcanos, after enough time had elapsed for adaptation and specialization to act on populations in situ. Such natural progression of specialization during community assembly is probably impeded by the rapid infiltration of non-native species, with special risk to younger or more recently disturbed communities that are composed of fewer specialized relationships.

Parasite-host network analysis provides insights into the evolution of two mistletoe lineages (Loranthaceae and Santalaceae)

Mistletoes are ecologically important parasitic plants, with > 1600 species from five lineages worldwide. Mistletoe lineages exhibit distinct patterns of species diversification and host specificity, however, the mechanisms underlying these differences are poorly understood. In this study, we analysed a comprehensive parasite-host network, including 280 host species from 60 families and 22 mistletoe species from two lineages (Santalaceae and Loranthaceae) in Xishuangbanna, located in a biodiversity hotspot of tropical Asia. We identified the factors that predict the infection strength of mistletoes. We also detected host specificity and the phylogenetic signal of mistletoes and their hosts. We found that this interaction network could be largely explained by a model based on the relative abundance of species. Host infection was positively correlated with diameter at breast height and tree coverage, but negatively correlated with wood density. Overall, closely related mistletoe species tend to interact more often with similar hosts. However, the two lineages showed a significantly different network pattern. Rates of host generality were higher in Loranthaceae than in Santalaceae, although neither lineage showed phylogenetic signal for host generality. This study demonstrates that the neutral interaction hypothesis provides suitable predictions of the mistletoe-host interaction network, and mistletoe species show significant phylogenetic signals for their hosts. Our findings also indicate that high species diversification in Loranthaceae may be explained by high rates of host generality and the evolutionary history shared by Loranthaceae species with diverse host plants in the tropics.

DNA metabarcoding reveals the dietary profiles of a benthic marine crustacean, Nephrops norvegicus

Norwegian lobster, Nephrops norvegicus, are a generalist scavenger and predator capable of short foraging excursions but can also suspension feed. Existing knowledge about their diet relies on a combination of methods including morphology-based stomach content analysis and stable isotopes, which often lack the resolution to distinguish prey items to species level particularly in species that thoroughly masticate their prey. DNA metabarcoding overcomes many of the challenges associated with traditional methods and it is an attractive approach to study the dietary profiles of animals. Here, we present the diet of the commercially valuable Nephrops norvegicus using DNA metabarcoding of gut contents. Despite difficulties associated with host amplification, our cytochrome oxidase I (COI) molecular assay successfully achieves higher resolution information than traditional approaches. We detected taxa that were likely consumed during different feeding strategies. Dinoflagellata, Chlorophyta and Bacillariophyta accounted for almost 50% of the prey items consumed, and are associated with suspension feeding, while fish with high fisheries discard rates were detected which are linked to active foraging. In addition, we were able to characterise biodiversity patterns by considering Nephrops as natural samplers, as well as detecting parasitic dinoflagellates (e.g., Hematodinium sp.), which are known to influence burrow related behaviour in infected individuals in over 50% of the samples. The metabarcoding data presented here greatly enhances a better understanding of a species' ecological role and could be applied as a routine procedure in future studies for proper consideration in the management and decision-making of fisheries.

The declines of heterogeneity and stability in diatom communities are associated with human activity

Anthropogenic forcing caused the biodiversity loss and stability decline of communities. There is still controversy over whether the decline in biodiversity will lead to a decrease in community stability. The stability of biological communities is related to both biodiversity and structure, and this paper aims to reveal the human impacts on diatom communities' biodiversity and structure. We studied the richness, β-diversity and network distance of diatom communities in Qinghai-Xizang, Yunnan-Sichuan and Lower Yangtze River Basin, China through empirical dataset and simulation method. The results showed that the diatoms richness in the Qinghai-Xizang and the Yunnan-Sichuan region was lower and the network distance was higher than that of the Lower Yangtze River Basin. β-diversity in the Lower Yangtze River Basin was the lowest and the diatom network distance responds negatively to human population densities in China. The simulation showed that the network distance kept constant during random species loss, and declined while specialist species were lost or replaced by generalist species. The results suggested diatom communities' homogeneity and stability decline were associated with human activities. Human impacts may cause biodiversity loss targeted to specialist species or no biodiversity loss while generalist species replace those specialist species. This study showed that how diversity changes determined ecological stability depends on the type of species changes.

Ecological network analysis reveals cancer-dependent chaperone-client interaction structure and robustness

Cancer cells alter the expression levels of metabolic enzymes to fuel proliferation. The mitochondrion is a central hub of metabolic reprogramming, where chaperones service hundreds of clients, forming chaperone-client interaction networks. How network structure affects its robustness to chaperone targeting is key to developing cancer-specific drug therapy. However, few studies have assessed how structure and robustness vary across different cancer tissues. Here, using ecological network analysis, we reveal a non-random, hierarchical pattern whereby the cancer type modulates the chaperones' ability to realize their potential client interactions. Despite the low similarity between the chaperone-client interaction networks, we highly accurately predict links in one cancer type based on another. Moreover, we identify groups of chaperones that interact with similar clients. Simulations of network robustness show that this group structure affects cancer-specific response to chaperone removal. Our results open the door for new hypotheses regarding the ecology and evolution of chaperone-client interaction networks and can inform cancer-specific drug development strategies.

Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long-term rodent datasets

The increasing frequency and cost of zoonotic disease emergence due to global change have led to calls for the primary surveillance of wildlife. This should be facilitated by the ready availability of remotely sensed environmental data, given the importance of the environment in determining infectious disease dynamics. However, there has been little evaluation of the temporal predictiveness of remotely sensed environmental data for infection reservoirs in vertebrate hosts due to a deficit of corresponding high-quality long-term infection datasets. Here we employ two unique decade-spanning datasets for assemblages of infectious agents, including zoonotic agents, in rodents in stable habitats. Such stable habitats are important, as they provide the baseline sets of pathogens for the interactions within degrading habitats that have been identified as hotspots for zoonotic emergence. We focus on the enhanced vegetation index (EVI), a measure of vegetation greening that equates to primary productivity, reasoning that this would modulate infectious agent populations via trophic cascades determining host population density or immunocompetence. We found that EVI, in analyses with data standardised by site, inversely predicted more than one-third of the variation in an index of infectious agent total abundance. Moreover, in bipartite host occupancy networks, weighted network statistics (connectance and modularity) were linked to total abundance and were also predicted by EVI. Infectious agent abundance and, perhaps, community structure are likely to influence infection risk and, in turn, the probability of transboundary emergence. Thus, the present results, which were consistent in disparate forest and desert systems, provide proof-of-principle that within-site fluctuations in satellite-derived greenness indices can furnish useful forecasting that could focus primary surveillance. In relation to the well-documented global greening trend of recent decades, the present results predict declining infection burden in wild vertebrates in stable habitats; but if greening trends were to be reversed, this might magnify the already upwards trend in zoonotic emergence.

The role of phenotypic plasticity in shaping ecological networks

Plasticity-mediated changes in interaction dynamics and structure may scale up and affect the ecological network in which the plastic species are embedded. Despite their potential relevance for understanding the effects of plasticity on ecological communities, these effects have seldom been analysed. We argue here that, by boosting the magnitude of intra-individual phenotypic variation, plasticity may have three possible direct effects on the interactions that the plastic species maintains with other species in the community: may expand the interaction niche, may cause a shift from one interaction niche to another or may even cause the colonization of a new niche. The combined action of these three factors can scale to the community level and eventually expresses itself as a modification in the topology and functionality of the entire ecological network. We propose that this causal pathway can be more widespread than previously thought and may explain how interaction niches evolve quickly in response to rapid changes in environmental conditions. The implication of this idea is not solely eco-evolutionary but may also help to understand how ecological interactions rewire and evolve in response to global change.

Estimating co-extinction threats in terrestrial ecosystems

The biosphere is changing rapidly due to human endeavour. Because ecological communities underlie networks of interacting species, changes that directly affect some species can have indirect effects on others. Accurate tools to predict these direct and indirect effects are therefore required to guide conservation strategies. However, most extinction-risk studies only consider the direct effects of global change-such as predicting which species will breach their thermal limits under different warming scenarios-with predictions of trophic cascades and co-extinction risks remaining mostly speculative. To predict the potential indirect effects of primary extinctions, data describing community interactions and network modelling can estimate how extinctions cascade through communities. While theoretical studies have demonstrated the usefulness of models in predicting how communities react to threats like climate change, few have applied such methods to real-world communities. This gap partly reflects challenges in constructing trophic network models of real-world food webs, highlighting the need to develop approaches for quantifying co-extinction risk more accurately. We propose a framework for constructing ecological network models representing real-world food webs in terrestrial ecosystems and subjecting these models to co-extinction scenarios triggered by probable future environmental perturbations. Adopting our framework will improve estimates of how environmental perturbations affect whole ecological communities. Identifying species at risk of co-extinction (or those that might trigger co-extinctions) will also guide conservation interventions aiming to reduce the probability of co-extinction cascades and additional species losses.

Bacterial inoculation of Quercus pyrenaica trees alters co-occurrence patterns but not the composition of the rhizosphere bacteriome in wild conditions

Quercus pyrenaica is a woody species of high landscape value, however, its forests show an advanced state of degradation in the Iberian Peninsula. Afforestation typically has low success, thus, it is necessary to improve the fitness of oaks plantlets to be transplanted, for instance, by inoculating beneficial microorganisms. In adding microorganisms to ecosystems, there must be balanced efficacy with potential effects on native microbial communities. We addressed changes in diversity, richness, composition and co-occurrence networks of prokaryotic communities in the rhizosphere of inoculated and control trees outplanted to three different sites located in the Sierra Nevada National and Natural Park (Spain). After 18 months in wild conditions, we did not detect changes due to the inoculation in the richness, diversity and structure in none of the sites. However, we observed an increase in the complexity of the co-occurrence networks in two experimental areas. Modularization of the networks changed as a result of the inoculation, although the sense of the change depended on the site. Although it was impossible to unravel the effect of bacterial inoculation, our results highlighted that inoculation alters the association of rhizosphere bacteria without entailing other changes, so networks should be analysed prior to inoculating the plantlets.

Network and parasitological analyses reveal latitudinal gradient in bats-ectoparasitic fly interactions across the Neotropic

Ecological interactions between parasites and their hosts play a fundamental role in evolutionary processes. Selection pressures are exerted on parasites and their hosts, usually resulting in high levels of specificity. Such is the case of ectoparasitic bat-flies, but how large-scale spatial gradients affect the dynamics of their interactions with their bat hosts is still unknown. In the present study, we investigated interaction patterns between bats and their ectoparasitic flies (Streblidae and Nycteribiidae), both presenting their peak of diversity in the Neotropical region, along a latitudinal gradient. Using network analyses and parasitic indices, grounded on the latitudinal diversity gradient pattern, we evaluated how spatial gradients affect species interactions and parasitic indices at the biogeopraphic scale, with increasing species richness in interaction networks closer to the tropics, leading to increases in network modularity, size, and specialization, and to a decrease in nesting and connectivity. We conducted a literature review, focusing on studies done in the Neotropical region, and own data. We obtained a bat richness of 97 species parasitized by 128 species of ectoparasitic flies, distributed into 57 interaction networks between latitudes 29° S and 19° N in the Neotropic. Network metrics and parasitic indices varied along the latitudinal gradient, with changes in the richness of bats and their ectoparasitic flies and in the structure of their interactions; network specialization, modularity, and connectance increase with latitude, while network size decreases with latitude. Regions closer to the equator had higher parasite loads. Our results show that interaction network metrics present a latitudinal gradient and that such interactions, when observed at a local scale, hide variations that only become perceptible at larger scales. In this way, ectoparasites such as bat flies are not only influenced by the ecology and biology of their hosts, but also by other environmental factors acting directly on their distribution and survival.

Impact of biological rhythms on the importance hierarchy of constituents in time-dependent functional brain networks

Biological rhythms are natural, endogenous cycles with period lengths ranging from less than 24 h (ultradian rhythms) to more than 24 h (infradian rhythms). The impact of the circadian rhythm (approximately 24 h) and ultradian rhythms on spectral characteristics of electroencephalographic (EEG) signals has been investigated for more than half a century. Yet, only little is known on how biological rhythms influence the properties of EEG-derived evolving functional brain networks. Here, we derive such networks from multiday, multichannel EEG recordings and use different centrality concepts to assess the time-varying importance hierarchy of the networks' vertices and edges as well as the various aspects of their structural integration in the network. We observe strong circadian and ultradian influences that highlight distinct subnetworks in the evolving functional brain networks. Our findings indicate the existence of a vital and fundamental subnetwork that is rather generally involved in ongoing brain activities during wakefulness and sleep.

Honey bees (Apis mellifera) modify plant-pollinator network structure, but do not alter wild species' interactions

Honey bees (Apis mellifera) are widely used for honey production and crop pollination, raising concern for wild pollinators, as honey bees may compete with wild pollinators for floral resources. The first sign of competition, before changes appear in wild pollinator abundance or diversity, may be changes to wild pollinator interactions with plants. Such changes for a community can be measured by looking at changes to metrics of resource use overlap in plant-pollinator interaction networks. Studies of honey bee effects on plant-pollinator networks have usually not distinguished whether honey bees alter wild pollinator interactions, or if they merely alter total network structure by adding their own interactions. To test this question, we experimentally introduced honey bees to a Canadian grassland and measured plant-pollinator interactions at varying distances from the introduced hives. We found that honey bees increased the network metrics of pollinator and plant functional complementarity and decreased interaction evenness. However, in networks constructed from just wild pollinator interactions, honey bee abundance did not affect any of the metrics calculated. Thus, all network structural changes to the full network (including honey bee interactions) were due only to honey bee-plant interactions, and not to honey bees causing changes in wild pollinator-plant interactions. Given widespread and increasing use of honey bees, it is important to establish whether they affect wild pollinator communities. Our results suggest that honey bees did not alter wild pollinator foraging patterns in this system, even in a year that was drier than the 20-year average.

Toward a cohesive understanding of ecological complexity

Ecological systems are quintessentially complex systems. Understanding and being able to predict phenomena typical of complex systems is, therefore, critical to progress in ecology and conservation amidst escalating global environmental change. However, myriad definitions of complexity and excessive reliance on conventional scientific approaches hamper conceptual advances and synthesis. Ecological complexity may be better understood by following the solid theoretical basis of complex system science (CSS). We review features of ecological systems described within CSS and conduct bibliometric and text mining analyses to characterize articles that refer to ecological complexity. Our analyses demonstrate that the study of complexity in ecology is a highly heterogeneous, global endeavor that is only weakly related to CSS. Current research trends are typically organized around basic theory, scaling, and macroecology. We leverage our review and the generalities identified in our analyses to suggest a more coherent and cohesive way forward in the study of complexity in ecology.

A perturbation-based approach to identifying potentially superfluous network constituents

Constructing networks from empirical time-series data is often faced with the as yet unsolved issue of how to avoid potentially superfluous network constituents. Such constituents can result, e.g., from spatial and temporal oversampling of the system's dynamics, and neglecting them can lead to severe misinterpretations of network characteristics ranging from global to local scale. We derive a perturbation-based method to identify potentially superfluous network constituents that makes use of vertex and edge centrality concepts. We investigate the suitability of our approach through analyses of weighted small-world, scale-free, random, and complete networks.

Responses of Fungal Assembly and Co-Occurrence Network of Rhizosphere Soil to Amaranthus palmeri Invasion in Northern China

The interaction between invasive plants and soil microbial communities is critical for plant establishment. However, little is known about the assembly and co-occurrence patterns of fungal communities in the rhizosphere soil of Amaranthus palmeri. The soil fungal communities and co-occurrence networks were investigated in 22 invaded patches and 22 native patches using high-throughput Illumina sequencing. Despite having little effect on alpha diversity, plant invasion significantly altered the composition of the soil fungal community (ANOSIM, p < 0.05). Fungal taxa associated with plant invasion were identified using linear discriminant analysis effect size (LEfSe). In the rhizosphere soil of A. palmeri, Basidiomycota was significantly enriched, while Ascomycota and Glomeromycota were significantly reduced when compared to native plants. At the genus level, the invasion of A. palmeri dramatically increased the abundance of beneficial fungi and potential antagonists such as Dioszegia, Tilletiopsis, Colacogloea, and Chaetomium, while it significantly decreased the abundance of pathogenic fungi such as Alternaria and Phaeosphaeria. Plant invasion reduced the average degree and average path length, and increased the modularity value, resulting in a less complex but more effective and stable network. Our findings improved the knowledge of the soil fungal communities, network co-occurrence patterns, and keystone taxa in A. palmeri-invaded ecosystems.

Facilitative interaction networks in experimental microbial community dynamics

Facilitative interactions between microbial species are ubiquitous in various types of ecosystems on the Earth. Therefore, inferring how entangled webs of interspecific interactions shift through time in microbial ecosystems is an essential step for understanding ecological processes driving microbiome dynamics. By compiling shotgun metagenomic sequencing data of an experimental microbial community, we examined how the architectural features of facilitative interaction networks could change through time. A metabolic modeling approach for estimating dependence between microbial genomes (species) allowed us to infer the network structure of potential facilitative interactions at 13 time points through the 110-day monitoring of experimental microbiomes. We then found that positive feedback loops, which were theoretically predicted to promote cascade breakdown of ecological communities, existed within the inferred networks of metabolic interactions prior to the drastic community-compositional shift observed in the microbiome time-series. We further applied "directed-graph" analyses to pinpoint potential keystone species located at the "upper stream" positions of such feedback loops. These analyses on facilitative interactions will help us understand key mechanisms causing catastrophic shifts in microbial community structure.

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.

Subgingival host-microbiome metatranscriptomic changes following scaling and root planing in grade II/III periodontitis

AIM

To assess the effects of scaling and root planing (SRP) on the dynamics of gene expression by the host and the microbiome in subgingival plaque samples.

MATERIALS AND METHODS

Fourteen periodontitis patients were closely monitored in the absence of periodontal treatment for 12 months. During this period, comprehensive periodontal examination and subgingival biofilm sample collection were performed bi-monthly. After 12 months, clinical attachment level (CAL) data were compiled and analysed using linear mixed models (LMM) fitted to longitudinal CAL measurements for each tooth site. LMM classified the sites as stable (S), progressing (P), or fluctuating (F). After the 12-month visit, subjects received SRP, and at 15 months they received comprehensive examination and supportive periodontal therapy. Those procedures were repeated at the 18-month visit, when patients were also sampled. Each patient contributed with one S, one P, and one F site collected at the 12- and 18-month visits. Samples were analysed using Dual RNA-Sequencing to capture host and bacterial transcriptomes simultaneously.

RESULTS

Microbiome and host response behaviour were specific to the site's progression classification (i.e., S, P, or F). Microbial profiles of pre- and post-treatment samples exhibited specific microbiome changes, with progressing sites showing the most significant changes. Among them, Porphyromonas gingivalis was reduced after treatment, while Fusobacterium nucleatum showed an increase in proportion. Transcriptome analysis of the host response showed that interleukin (IL)-17, TNF signalling pathways, and neutrophil extracellular trap formation were the primary immune response activities impacted by periodontal treatment.

CONCLUSIONS

SRP resulted in a significant "rewiring" of host and microbial activities in the progressing sites, while restructuring of the microbiome was minor in stable and fluctuating sites.

Microscale dynamics of dark zone alterations in anthropized karstic cave shows abrupt microbial community switch

Strong anthropization of karstic caves may result in formation of various wall alterations including dark zones, whose microbial community differs from that of non-altered surfaces nearby. Dark zones grow quickly and without gradual visual changes, leading to the hypothesis of a simple process rather than complex microbial successions, but this is counter-intuitive as underground microbial changes are typically slow and dark zones are microbiologically very distinct from unmarked surfaces. We tested this hypothesis in Paleolithic Lascaux Cave, across two years of microscale sampling. Indeed, Illumina MiSeq metabarcoding evidenced only three community stages for bacteria, fungi and all microeukaryotes together (i.e. unmarked surfaces, newly-formed dark zones and intermediate/old dark zones) and just two stages for archaea (unmarked surfaces vs dark zones), indicating abrupt community changes. The onset of dark zone formation coincided with the development of Ochroconis fungi, Bacteroidota and the bacterial genera Labrys, Nonomuraea and Sphingomonas, in parallel to Pseudomonas counter-selection. Modeling of community assembly processes highlighted that the dynamics of rare taxa in unmarked surfaces adjacent to dark zones and in newly-formed dark zones were governed in part by deterministic processes. This suggests that cooperative relationships between these taxa might be important to promote dark zone formation. Taken together, these findings indicate an abrupt community switch as these new alterations form on Lascaux cave walls.

Food webs reveal coexistence mechanisms and community organization in carnivores

Globally, massive carnivore guild extirpations have led to trophic downgrading and compromised ecosystem services. However, the complexity of multi-carnivore food webs complicates accurate identification of species interactions and community organization. Here, we used fecal DNA metabarcoding to investigate three communities that together encompass eight large- and meso-carnivore species and their 44 prey taxa of the Qinghai-Tibet Plateau (QTP), one of the last places on Earth that still harbors intact carnivore assemblages. Quantitative food-web analyses revealed pronounced interspecific variations in the carnivores' prey compositions and dietary partitioning both between and within guilds. Additionally, body masses of the carnivores and their prey exhibited consistent hump-shaped correlations across communities. Overall, differences in prey diversity, size category, and proportional utilization among the carnivore species result in trophic niche segregation that likely promotes carnivore coexistence in the harsh QTP environment. Network structure analyses detected significant modularity in all food webs but nestedness in only one. Furthermore, network characterization identified pikas (Ochotona spp.), bharal (Pseudois nayaur), and domestic yak (Bos grunniens) as potential keystone prey across the areas. Our results paint a holistic and detailed picture of the QTP carnivore assemblages' trophic networks and demonstrate that the combined use of the molecular dietary approach and network analysis can generate structural insights into carnivore coexistence and can identify functionally important species in complex communities. Such knowledge can help safeguard carnivore guild integrity and enhance community resilience to environmental perturbations in the sensitive QTP ecosystems.