Stability of ecological communities and the architecture of mutualistic and trophic networks

Ecological impacts of treated effluent on multitrophic biodiversity and their interactions

The reuse of water, particularly treated effluent from wastewater treatment plants (WWTPs), is a crucial and sustainable strategy for mitigating water scarcity, especially in megacities with high water demand and limited resources. However, the ecological risks associated with effluent discharge into receiving waterbodies have gained significant global attention. Understanding the dynamic effects of WWTP effluent on multi-trophic groups and their interactions is essential for assessing ecological impacts in aquatic ecosystems and informing management strategies. In this study, we examined five taxonomic groups representing different trophic levels of the freshwater food web - bacteria (decomposers), algae (primary producers), zooplankton (primary consumers), and benthic macroinvertebrates and fish (predators) - across two rivers to elucidate ecological responses to WWTP effluent from a multi-trophic perspective. Our results revealed significant but variable biological responses among these groups, depending on river conditions and trophic level. In the nutrient-rich river, primary consumers (zooplankton) were most affected, whereas in the nutrient-poor river, primary producers (algae) exhibited the strongest responses primarily derived from environmental disturbances. Notably, interactions between environmental variables and taxa were highly diverse, with trophic dynamics influenced by both bottom-up and top-down processes in the nutrient-rich river, whereas bottom-up effects dominated in the nutrient-poor river. Furthermore, niche overlap in algae-zooplankton networks was higher in the nutrient-rich river than in the nutrient-poor river. This study underscores the importance of integrating multi-trophic biodiversity profiling and trophic interaction analyses to comprehensively assess the ecological effects of WWTP effluent in receiving aquatic ecosystems with contrasting environmental contexts. Our findings highlight the importance of conservation and sustainable management practices, especially in urban aquatic ecosystems located in (semi-)arid regions that experience prolonged periods of low precipitation.

Community stability of free-living and particle-attached prokaryotes in coastal waters across four seasons: insights from 9.5 years of weekly sampling

Free-living (FL) and particle-attached (PA) prokaryotes, having distinct ecological niches, play significant roles in marine ecosystems. These communities respond rapidly to environmental changes and exhibit seasonal patterns. However, their temporal stability, crucial for maintaining microbial community structure and function, remains poorly understood. This study assessed community stability, particularly in terms of resistance to environmental perturbations, and inferred regulatory mechanisms using weekly collected samples over 9.5 years from FL and PA communities in coastal water. Short-read amplicon sequencing revealed habitat-specific microbial compositions, with Actinobacteria and Euryarchaeota dominating FL community, while Planctomycetes and Verrucomicrobia prevailed in PA community. Network analysis, constructed based on relative abundance, uncovered seasonal co-occurrence patterns and highlighted keystone taxa, such as Nitrosopumilus in FL and Synechococcus in PA community, as critical for maintaining stability within specific seasons and niches. Seasonal variations in community stability indices suggest that higher network complexity can enhance resistance; however, excessive interactions with greater complexity may also undermine it. Furthermore, it was found that FL community stability was primarily affected by abiotic factors, likely due to direct exposure to environmental changes, whereas PA community stability was more influenced by biotic factors, as their association with particles fosters localized interactions and biological processes. These findings reveal the intricate balance between network complexity and stability and the importance of niche-specific approaches in ecological research. Our results contribute to a deeper understanding of marine microbial niche partitioning and provide insights into ecosystem management and conservation strategies, particularly regarding keystone taxa.

Distinct co-succession of dissolved organic matter and bacterial generalists and specialists in inflow rivers of Baiyangdian Lake

Dissolved organic matter (DOM) significantly affects the stability of river microorganisms, but the seasonal regulatory mechanisms of generalists and specialists remain unclear. Through spectral measurement and high-throughput sequencing techniques, the structural, network, and evolutionary characteristics of generalists and specialists in Baiyangdian lake inflow rivers from 2021 to 2023 were analyzed, and the influences of environmental factors and DOM on their dynamics were quantified. Parallel factor analysis (PARAFAC) identified two protein-like components (C1+C2) and one humus-like component (C3). Among them, the protein-like components were significantly higher in urban reclaimed water (URW) than in non-urban reclaimed water (NRW), while the humus-like component was higher in summer than in winter (P < 0.001). The relative concentration of DOM was higher in summer, showing overall low humification and strong autochthonous characteristics (FI > 1.8, HIX <4). Actinobacteriota and Proteobacteria were the main components of generalists and specialists. Species replacement had a much greater impact on β-diversity than richness differences. The network structure of winter and NRW exhibited more complex topological properties, and the stability of generalist networks was lower than that of specialists. Stochastic processes dominated the community assembly process (63.73 %-93.94 %), with generalists in summer being more influenced by stochastic processes, while the opposite was true in winter. The BiSSE model indicated that specialists exhibited higher diversification potential than generalists. Path analysis showed that in summer URW, diversity and protein-like components had the greatest impact on the network stability of generalists and specialists, respectively. In NRW, humus-like component had the greatest impact on the network stability of specialists. This study clarified the mechanism by which the seasonal characteristics of DOM drive the ecological strategy differentiation of generalists and specialists in rivers, providing a theoretical basis for watershed ecological management.

Distinct patterns and processes of eukaryotic phytoplankton communities along a steep elevational gradient in highland rivers

Phytoplankton play a crucial role in biogeochemical cycling and aquatic food webs while also susceptible to environmental variations. However, their response to altitude gradients remains poorly understood. In this study, we applied a metabarcoding approach to explore eukaryotic phytoplankton community structure, co-occurrence networks, and assembly processes along a steep altitudinal gradient (590-4500 m) in the Nyang River and the lower reaches of the Yarlung Zangbo River on the Qinghai-Tibetan Plateau during dry and wet seasons. Using 18S rDNA sequencing, we obtained 2852 amplicon sequence variants. Our results demonstrated that Ochrophyta was the dominant taxon in the eukaryotic phytoplankton community across both seasons. Alpha diversity exhibited distinct seasonal patterns, decreasing monotonically with increasing altitude in the dry season whereas the highest diversity was observed at medium altitudes in the wet season. Phytoplankton co-occurrence networks became more topologically complex as species diversity increased. Among environmental factors, altitude (r = 0.62), water temperature (r = 0.52) and pH (r = 0.51) significantly influenced phytoplankton communities. Stochastic processes globally dominated phytoplankton community assembly (66 %) and became increasingly influential from dry season (51 %) to wet season (71 %). Their impact gradually increased from low altitude (57 %) to medium altitude (64 %), but deterministic processes overwhelming dominated community assembly at the higher altitude in both seasons (dry season: 95 %, wet season 71 %). In summary, these findings enhance our understanding of the spatial and temporal dynamics of eukaryotic phytoplankton communities in highland rivers and the maintenance of planktonic diversity along elevational gradients.

Key concepts and a world-wide look at plant recruitment networks

Plant-plant interactions are major determinants of the dynamics of terrestrial ecosystems. There is a long tradition in the study of these interactions, their mechanisms and their consequences using experimental, observational and theoretical approaches. Empirical studies overwhelmingly focus at the level of species pairs or small sets of species. Although empirical data on these interactions at the community level are scarce, such studies have gained pace in the last decade. Studying plant-plant interactions at the community level requires knowledge of which species interact with which others, so an ecological networks approach must be incorporated into the basic toolbox of plant community ecology. The concept of recruitment networks (RNs) provides an integrative framework and new insights for many topics in the field of plant community ecology. RNs synthesise the set of canopy-recruit interactions in a local plant assemblage. Canopy-recruit interactions describe which ("canopy") species allow the recruitment of other species in their vicinity and how. Here we critically review basic concepts of ecological network theory as they apply to RNs. We use RecruitNet, a recently published worldwide data set of canopy-recruit interactions, to describe RN patterns emerging at the interaction, species, and community levels, and relate them to different abiotic gradients. Our results show that RNs can be sampled with high accuracy. The studies included in RecruitNet show a very high mean network completeness (95%), indicating that undetected canopy-recruit pairs must be few and occur very infrequently. Across 351,064 canopy-recruit pairs analysed, the effect of the interaction on recruitment was neutral in an average of 69% of the interactions per community, but the remaining interactions were positive (i.e. facilitative) five times more often than negative (i.e. competitive), and positive interactions had twice the strength of negative ones. Moreover, the frequency and strength of facilitation increases along a climatic aridity gradient worldwide, so the demography of plant communities is increasingly strongly dependent on facilitation as aridity increases. At network level, species can be ascribed to four functional types depending on their position in the network: core, satellite, strict transients and disturbance-dependent transients. This functional structure can allow a rough estimation of which species are more likely to persist. In RecruitNet communities, this functional structure most often departs from random null model expectation and could allow on average the persistence of 77% of the species in a local community. The functional structure of RNs also varies along the aridity gradient, but differently in shrubland than in forest communities. This variation suggests an increase in the probability of species persistence with aridity in forests, while such probability remains roughly constant along the gradient in shrublands. The different functional structure of RNs between forests and shrublands could contribute to explaining their co-occurrence as alternative stable states of the vegetation under the same climatic conditions. This review is not exhaustive of all the topics that can be addressed using the framework of RNs, but instead aims to present some of the interesting insights that it can bring to the field of plant community ecology.

Assessing the effects of urban effluent pollution on freshwater biodiversity and community networks using eDNA metabarcoding

Aquatic ecosystems provide essential services, yet they face increasing pressures from anthropogenic activities, including land-use change, eutrophication, browning, and contaminant pollution. While the ecological effects of these stressors are documented, the impacts of complex contaminant mixtures, particularly those from wastewater treatment plant (WWTP) effluents, remain poorly understood. Mixtures effects are typically assessed using traditional species-by-species toxicological approaches, which, though the gold standard, are time-intensive, require test animals, and have limited extrapolability. New Approach Methodologies (NAMs), such as environmental DNA (eDNA), offer a non-invasive alternative, enabling broader assessments of taxa responses across trophic levels. Here, we apply an eDNA approach to assess community-wide responses to effluent discharge in the St. Lawrence River, one of North America's most diverse freshwater ecosystems. We sampled water and aquatic communities along the effluent plume of the Montréal WWTP, analyzing taxa-specific responses across trophic levels using high-throughput sequencing. We evaluated the influence of water physico-chemistry and per- and polyfluoroalkyl substances (PFAS) on aquatic beta diversity and network structure. To validate our eDNA results, we compared fish-specific detections with traditional fishing surveys. Our findings highlight how wastewater-derived contaminants influence biodiversity patterns and species interactions, with taxonomic responses varying across trophic levels. Network analyses revealed shifts in ecological stability, with changes in species connectivity and modularity influenced by effluent exposure. This study demonstrates the value of eDNA for characterizing biodiversity responses to anthropogenic stressors and provides insights into the broader implications of point-source pollution for freshwater ecosystem resilience.

Spatiotemporal patterns of soil myxomycetes in subtropical managed forests and their potential interactions with bacteria

Soil myxomycetes are crucial soil protists with important ecological functions. Yet, our understanding of their diversity patterns in managed forests and the interactions with their food is far behind other taxa. This study investigates the spatiotemporal patterns of soil myxomycetes in four northern subtropical managed forest types across seasons and aims to identify assembly processes, main predictors of myxomycete communities, and the potential interactions between myxomycetes and bacteria. Results showed that no significant difference in α diversity of myxomycete communities among forest types was observed, but a significant difference was observed in community structures. Significant differences were observed in α diversity and community structures of myxomycetes among seasons. Deterministic processes in each forest type and season dominated myxomycete community assemblies. Soil physicochemical properties and bacterial communities have a significant direct impact on the myxomycete community, while forest types, seasons, and enzyme activities have an indirect effect. There is a significant synergistic covariation between the soil myxomycete community and bacterial community. The genera of the phyla Acidobacteriota, Actinobacteriota, and Bacteroidota have a strong correlation with the richness of myxomycete genera. Overall, this study provides new insight into the diversity of soil myxomycetes and their influence by bacteria, crucial for myxomycetes ecology.IMPORTANCESoil myxomycetes are an important component of soil protists. Our study revealed for the first time the community structure of soil myxomycetes in managed forests of the northern subtropical regions and systematically investigated the seasonal variation patterns of soil myxomycetes. Meanwhile, we further investigated the potential interactions between soil myxomycetes and bacteria. This study will greatly enhance our understanding of the ecology of soil myxomycetes and their biological roles.

Architecture and stability of tripartite ecological networks with two interaction types

Over the past few decades, studies on empirical ecological networks have primarily focused on single antagonistic or mutualistic interactions. However, many species engage in multiple interactions that support distinct ecosystem functions. The architecture of networks integrating these interactions, along with their cascading effects on community dynamics, remains underexplored in ecological research. In this study, we compiled two datasets of empirical plant-herbivore/host-parasitoid (PHP) and pollinator-plant-herbivore (PPH) networks, representing two common types of tripartite networks in terrestrial ecosystems: antagonism-antagonism and mutualism-antagonism. We identified the patterns of subnetwork structures and interconnection properties in these networks and examined their relationships with community stability. Our findings revealed distinct pathway effects of network architecture on persistence and local stability in both PHP and PPH networks, with subnetwork modularity and nestedness showing a few strong direct effects and mediating the indirect effects of subnetwork size and connectance. In PHP networks, subnetwork modularity enhanced persistence and local stability, whereas subnetwork nestedness directly undermined them. However, both subnetwork topologies consistently mediated the destabilizing effects of subnetwork size and connectance on the entire network. In PPH networks, persistence was primarily affected by the plant-herbivore subnetwork, while the size, connectance, and modularity of different subnetworks had opposing effects on local stability. Regarding interconnection properties, the correlation of interaction similarity destabilized PHP networks, whereas the correlation of interaction degree promoted local stability in PPH networks. Further analysis indicated that structure-persistence relationships vary significantly across guilds, and the network-level effects of network architecture can be reversed, negligible, or biased in specific guilds. These findings advance our understanding of how network architecture influences ecosystem stability and underscore the importance of considering multiple interaction types when predicting community dynamics.

Trends, stasis and trajectories for plant and animal domestications: possibilistic models alert on resource overexploitation

The transition from hunter-gatherer communities to farming societies is a pivotal shift in human history, hinging on the emergence, selection and diffusion of domestic plants and animals. However, the sequence and order of these steps remain only partially understood. In this study, we used a possibilistic formalism to model the emergence and development of farming. This first attempt, based on an intentionally limited number of qualitative and discrete rules, represents the interactions between domestic and wild plants and animals, and human societies. This initial case study focuses on the emergence of farming in Southwest Asia. We constructed a theoretical model including a minimum number of five components and 18 processes. We explored three models representing increasing exploitation of resources from no overexploitation, to overexploitation of both wild and domestic resources. Our findings revealed possible scenarios for the emergence and development of farming, where animal domestication possibly emerged before plant domestication, contradicting the most accepted temporality. We also generated alternative hypotheses concerning the initiation of plant and animal domestications. The possible ecosystem development with resource overexploitation underscores the importance of wild resources for sustainable societies. This initial attempt at possibilistic modelling can be further developed and expanded to address a broad range of archaeological questions.This article is part of the theme issue 'Unravelling domestication: multi-disciplinary perspectives on human and non-human relationships in the past, present and future'.

Divergent Driving Mechanisms Shape the Temporal Dynamics of Benthic Prokaryotic and Eukaryotic Microbial Communities in Coastal Subtidal Zones

Benthic microbial communities are a vital component of coastal subtidal zones, playing an essential role in nutrient cycling and energy flow, and are fundamental to maintaining the stability and functioning of marine ecosystems. However, the response of benthic prokaryotic and eukaryotic microbial communities to environmental changes remains poorly understood. Herein, we conducted a nearly semimonthly annual sampling survey to investigate the temporal patterns and underlying mechanisms of benthic prokaryotic and eukaryotic microbial communities in the subtidal sediments of Sanshan Island, situated in the eastern Laizhou Bay of the Bohai Sea, China. The results showed that the temporal variations in benthic microbial communities followed a distinct seasonal pattern, with turnover playing a more dominant role in community succession. Nonetheless, contrasting temporal variations were observed in the alpha diversity of benthic prokaryotic and eukaryotic microbial communities, as well as in the dominant taxa across different microbial communities. Water temperature, dissolved oxygen, electrical conductivity, salinity, total nitrogen (TN), NH4+, and PO43- were identified as the predominant environmental drivers. The assembly of benthic microbial communities was driven by different ecological processes, in which stochastic processes mainly shaped the benthic prokaryotic communities, while deterministic processes dominated the assembly of benthic eukaryotic microbial communities. Interactions within benthic microbial communities were primarily characterized by mutualistic or cooperative relationships, but the ability of prokaryotic and eukaryotic microbial communities to maintain stability under environmental disturbances showed notable differences. These results shed light on the temporal dynamics and potential driving mechanisms of benthic prokaryotic and eukaryotic microbial communities under environmental disturbances, highlighting the distinct roles of prokaryotic and eukaryotic communities in coastal subtidal zones and providing valuable insights for the management and conservation of coastal subtidal marine ecosystems.

Deciphering the role of traditional flipping crafts in medium-temperature Daqu fermentation: Microbial succession and metabolic phenotypes

Medium-temperature Daqu (MTD) serves as the saccharification and fermentation starter for Nongxiangxing Baijiu. Flipping Daqu (FD) during fermentation is a key craft in traditional MTD preparation. However, the mechanism underlying this flipping craft remains unclear. To address this, we systematically compared FD with non-flipping Daqu (NFD) to elucidate microbial succession dynamics, metabolic phenotypes, and environmental drivers. Our results demonstrated divergent microbial community succession patterns between FD and NFD during the stable fermentation phase (days 9-25). FD exhibited significantly higher enzyme activities and volatile ketone content, along with lower core temperatures compared to NFD. Metabolite production in FD was influenced by both bacteria and fungi, whereas fungi predominantly controlled metabolite production in NFD. Co-occurrence network analysis revealed that the microbial community in FD was simpler yet more stable compared to that in NFD. Microbial succession in MTD was primarily driven by interspecies interactions and environmental factors. Furthermore, deterministic processes and stochastic processes jointly governed microbial assembly both FD and NFD, with temperature, moisture, and acidity as the key driving factors. These findings highlight the pivotal role of the flipping crafts in enhancing microbial functionality and metabolic diversity, offering a theoretical basis for optimizing MTD production and advancing intelligent fermentation systems.

Connecting the dots: Managing species interaction networks to mitigate the impacts of global change

Global change is causing unprecedented degradation of the Earth's biological systems and thus undermining human prosperity. Past practices have focused either on monitoring biodiversity decline or mitigating ecosystem services degradation. Missing, but critically needed, are management approaches that monitor and restore species interaction networks, thus bridging existing practices. Our overall aim here is to lay the foundations of a framework for developing network management, defined here as the study, monitoring, and management of species interaction networks. We review theory and empirical evidence demonstrating the importance of species interaction networks for the provisioning of ecosystem services, how human impacts on those networks lead to network rewiring that underlies ecosystem service degradation, and then turn to case studies showing how network management has effectively mitigated such effects or aided in network restoration. We also examine how emerging technologies for data acquisition and analysis are providing new opportunities for monitoring species interactions and discuss the opportunities and challenges of developing effective network management. In summary, we propose that network management provides key mechanistic knowledge on ecosystem degradation that links species- to ecosystem-level responses to global change, and that emerging technological tools offer the opportunity to accelerate its widespread adoption.

Seaweed feed enhance the long-term recovery of bacterial community and carbon-nitrogen sequestration in eutrophic coastal wetland

Seaweed feed offers a promising approach to enhance sustainability in aquaculture. While much research has focused on its effects on aquatic organisms, the impact of seaweed feed residuals on sediment carbon sequestration and bacterial community dynamics remains underexplored. This study aimed to address this gap through a 96-day incubation experiment using sediment from the coastal wetlands of Zhuhai in southern China. We evaluated the effects of seaweed feed derived from the red seaweed Gracilaria lemaneiformis by analyzing temporal changes in sediment physicochemical properties and microbial community dynamics. Our findings reveal that seaweed feed significantly improved sediment organic carbon and nitrogen storage (p < 0.01), enhanced the recovery of dissolved oxygen levels (p < 0.001) and bacterial α-diversity (p < 0.01) compared to normal feed. Additionally, the variability in microbial community structure (p < 0.01) and functional potential (p < 0.05) due to seaweed feed was less pronounced than that caused by normal feed. This reduced variability may result from the role of seaweed feed in stabilizing microbial community assembly, which helps mitigate fluctuations in bacterial structure and function. Overall, this study offers valuable insights for managing aquaculture ponds and coastal wetlands, contributing to the understanding of seaweed carbon sequestration and highlighting the potential of seaweed feed as a significant carbon sink beyond traditional cultivation practices.

Insect-flower interactions, ecosystem functions, and restoration ecology in the northern Sahel: current knowledge and perspectives

Actions for ecological restoration under the Great Green Wall (GGW) initiative in the northern Sahel have been plant focused, paying scant attention to plant-animal interactions that are essential to ecosystem functioning. Calls to accelerate implementation of the GGW make it timely to develop a more solid conceptual foundation for restoration actions. As a step towards this goal, we review what is known in this region about an important class of plant-animal interactions, those between plants and flower-visiting insects. Essential for pollination, floral resources also support insects that play important roles in many other ecosystem processes. Extensive pastoralism is the principal subsistence mode in the region, and while recent analyses downplay the impact of livestock on vegetation dynamics compared to climatic factors, they focus primarily on rangeland productivity, neglecting biodiversity, which is critical for long-term sustainability. We summarise current knowledge on insect-flower interactions, identify information gaps, and suggest research priorities. Most insect-pollinated plants in the region have open-access flowers exploitable by diverse insects, an advantageous strategy in environments with low productivity and seasonal and highly variable rainfall. Other plant species have diverse traits that constrain the range of visitors, and several distinct flower types are represented, some of which have been postulated to match classical "pollination syndromes". As in most ecosystems, bees are among the most important pollinators. The bee fauna is dominated by ground-nesting solitary bees, almost all of which are polylectic. Many non-bee flower visitors also perform various ecosystem services such as decomposition and pest control. Many floral visitors occupy high trophic levels, and are indicators of continued functioning of the food webs on which they depend. The resilience of insect-flower networks in this region largely depends on trees, which flower year-round and are less affected by drought than forbs. However, the limited number of abundant tree species presents a potential fragility. Flowering failure of a crucial "hub" species during exceptionally dry years could jeopardise populations of some flower-visiting insects. Furthermore, across Sahelian drylands, browsers are increasingly predominant over grazers. Although better suited to changing climates, browsers exert more pressure on trees, potentially weakening insect-flower interaction networks. Understanding the separate and combined effects of climate change and land-use change on biotic interactions will be key to building a solid foundation to facilitate effective restoration of Sahelian ecosystems.

Abundant top predators increase species interaction network complexity in northeastern Chinese forests

Species interactions remain a cornerstone in shaping community dynamics and structure, alongside other factors, such as climate conditions and human activities. Although network structure is known to influence community stability and ecosystem functioning, the roles of top predators in shaping interaction network structure remain obscure. We examined a 5-7-year time series of species detections for mammal communities in multiple protected areas to investigate the association between top predators and interaction network structure. Our findings suggest that abundant species, day-active species and species with wide habitat breadth interact with more species, as did species that were more affected by vehicle disturbance. With increased densities of top predators, interaction networks exhibited greater complexity, with increased connectance, nestedness and average degree. An increased density of mesopredators, such as yellow-throated martens and badgers, was associated with sparser, less nested, but more centralized interaction networks. Top predators reduced the degree of highly interactive species, making them more specialized, and increased the degree of less abundant species, making them more general. In particular, this redistribution of interactions was not driven by direct changes in species density of top predators but seemingly by non-consumptive or indirect effects. Our findings emphasize the pivotal role of the main predators in structuring interactions within northeastern China's mammal communities, with large implications for conservation and management.

The network architecture and phylogeographic drivers of interactions between rodents and seed plants at continental scales

Rodents are known to interact with seed plants in three different ways, including predation in situ, scatter hoarding and larder hoarding of seeds. These behaviours span a spectrum from mutualistic seed dispersal to predation, and they are related to species' and environmental characteristics. We used interaction networks to evaluate the structure and drivers of rodent-seed plant interactions, including geography, phylogeny and traits at continental scales. We constructed five aggregated networks, each representing a continent and containing three subnetworks defined by foraging behaviours, tested questions about their network structures and analysed the driving signals shaping rodent-seed plant interactions at network and species levels. Rodent-seed plant networks varied across continents. We found most rodents exhibited a significant propensity for one foraging behaviour and detected significant modular structures in both aggregated networks and subnetworks. We detected significant co-phylogenetic signals between rodents and seed plants. Distance matrix-based regressions on interaction and module dissimilarity of rodents suggest geographical and phylogenetic forces are important in the assembly of rodent-seed plant networks. In addition, multiple species traits correlated with the roles of rodents within aggregated networks; however, the specific traits associated with these roles varied among interaction types. Our results highlight that geography and phylogenetics are dominant in structuring the architecture of rodent-seed plant networks at continental scales and reveal challenges regarding spatial and taxa coverage in rodent-seed plant interactions.

Thousands-years-old deep-sea DNA viruses reveal the evolution of human pathogenic viruses

INTRODUCTION

In the last two decades, outbreaks of pathogenic viruses have led to significant human mortality and economic repercussions. Despite extensive investigations into tracing these viruses in terrestrial environments, their origins remain enigmatic.

OBJECTIVES

The Earth's biosphere encompasses both sunlight-dependent terrestrial and surface ocean ecosystems, as well as the sunlight-independent deep-sea ecosystem. However, the traceability of human pathogenic viruses in the deep sea has not been thoroughly explored. This study aimed to investigate the presence of human pathogenic viruses in the deep sea.

METHODS

In this study, we performed a viral metagenomic analysis using a global deep-sea sediment virome 2.0 dataset which contained 159 deep-sea sediment samples with geologic ages from 2,500 to 7,750 years.

RESULTS

A total of 554,664 viral operational taxonomic units (vOTUs) were identified and further obtained 2,254 potential pathogenic viruses of vertebrates. Among them, 23 vOTUs exhibited high homology with 12 species of human pathogenic viruses which belonged to 4 viral families. Notably, variola virus, the first human pathogenic virus eradicated from humans and now only found in laboratories, was discovered in the ancient deep-sea sediments. The evolution analysis showed that these DNA viruses might represent the ancestors or variants of human pathogenic viruses, suggesting that the deep sea could be a crucial reservoir for human pathogenic viruses.

CONCLUSION

Our findings present all the ancient pathogenic DNA viruses of humans found in the deep sea for the first time, highlighting the source of the future epidemics. It is imperative to implement the stringent virus monitoring and management measures for human activities in marine environments to address the emerging challenges of marine biosecurity and promote sustainable use of oceans.

Role of Cyanobacteria in the assembly and dynamics of microbial communities on glacier surfaces

Glacier surface habitats are dynamic ecosystems that respond to local climatic and thermal changes, although the assembly mechanisms of microbial communities in these environments remain unclear. This study examined microbial communities on the surface of Baishui Glacier No. 1 across the accumulation, the intense melt, and the late melt periods. The absolute abundance of Cyanobacteria increased significantly, becoming the most abundant phylum by the end of the melt period. Cyanobacteria were strongly associated with other local microorganisms, especially in community structure, community assembly, and co-occurrence networks. The correlations between Cyanobacteria and other microorganisms shifted from predominantly mutualistic interactions, to being predominantly competitive interactions, and finally to mutualistic interactions with a portion of the community. Additionally, Cyanobacteria abundance positively correlated with nitrogen metabolism multifunctionality in other microorganisms, indicating a potential link between Cyanobacteria and nitrogen cycling. These findings provide new insights into microbial community dynamics and survival strategies on glacier surfaces.

Soil Microbial Recovery to the Rubber Tree Replanting Process in Ivory Coast

The resistance and resilience of soil microbial communities to an environmental disturbance are poorly documented, due to the lack on onfield diachronic experiments, limiting our ability to design adapted agroecological practices. This is especially true in rubber plantations, one of the most planted tree in tropical areas. We aimed to understand (1) how soil disturbances occurring during the rubber replanting phase affect the soil microbiome, (2) how agricultural practices combining legumes cover crops and tree logging residues shape community resilience and (3) how microbial responses vary across different edaphic contexts. In two plantations with distinct soil properties in Ivory Coast, soil microbial communities were surveyed every 6 months for 24 months after soil perturbation. Community structure, functioning and networks were described based on a 16S/18S rRNA gene investigation. Prokaryotes were generally more resistant to soil perturbation than microeukaryote communities. Prokaryotic resilience dynamics were faster than those of microeukaryotes, the latter being deeply modulated by cover treatments. These specific dynamics were exacerbated in the sandy site. Co-occurrence network modelling provided useful insights into microbial resilience trajectories. We argue that this tool should be more widely used to describe microbial community dynamics. Practices involving a combination of logging residues and legume cover crops have shown beneficial effects on the community resilience in the sandy site and appears as promising agroecological practices. However, the major influence of soil texture warns of the need to consider pedological context when designing pertinent agroecological practices.

Identifying habitat modification by Chinese pangolin in subtropical forests of southern China

The excavation of Chinese pangolin (Manis pentadactyla) is expected to alter habitat heterogeneity and thus affect the functioning and structure of forest ecosystems. In this study, the bioturbation of Chinese pangolin on forest soils in three regions (Heping, Tianjingshan, and Wuqinzhang) across Guangdong province was quantified. Overall, a mean of 2.66 m3·ha-1 and 83.1 m2·ha-1 of burrows and bare mounds, respectively, was excavated by Chinese pangolin; the disturbed soils had significantly lower water content and P, C, available N concentrations, but higher bulk density, pH, and microbial abundance than those undisturbed soils. The unevenness of habitat heterogeneity improvement was mainly ascribed to the stronger soil disturbance caused in resting burrows by pangolins. Patterns of altering habitat heterogeneity were site-specific, with high-intensity soil disturbance occurring most in shrubs, meadows, steep habitats at high elevations, and mountain tops in Heping, while in broad-leaved, coniferous and mixed coniferous and broad-leaved forests away from human settlements in Tianjingshan and upper mountains at high elevations far away from roads and human settlements in Wuqinzhang. Road networks are the main interference for the burrow distribution in Heping and Wuqinzhang and should be programmed.

Interaction Outcomes in Mutualism-Antagonism Continua: Context Dependency and Instantaneous Effects of the Interactions

AbstractIt is increasingly evident that most interactions are not static and move along a continuum ranging from pure mutualism (i.e., in which each species in the interaction has a net benefit in the long term) to pure antagonism (i.e., in which each species in the interaction has a net damage in the long term). Despite numerous experimental and theoretical works on this concept, predicting interaction outcomes within an ecological community continues to pose a significant challenge. This article aims to tackle this challenge by presenting a theoretical methodology for predicting the interaction outcomes within the common mutualism-antagonism modeling framework. Specifically, my main finding is to describe the influence of the population abundance of the species, the interaction effects, and the ecological context on the interaction outcomes and to quantify their relative contribution. I found that the interaction outcomes depend on the number of interacting species. In particular, when the number of interacting species increases, the trend is to skip situations where all species benefit from the interactions.

Long-term ammonium nitrate addition strengthens soil microbial cross-trophic interactions in a Tibetan alpine steppe

Global nitrogen (N) enrichment is modifying microbial interactions, which can be represented by network complexity. While a number of studies have explored how N addition influences the microbial intra-trophic network, its effects on the inter-trophic network have rarely been investigated. Here, we examined the effects of 8 years of multilevel N additions (i.e., 0, 1, 2, 4, 8, 16, 24 and 32 g N m-2 year-1) on inter-trophic interactions of soil microbial communities (i.e., protist-fungi, protist-prokaryote and fungi-prokaryote) in a Tibetan alpine steppe. Generally, there was a first increasing and then saturated trend of the complexity of inter-trophic networks along the N-addition gradient, which contrasts with the simplified or minimal response of intra-trophic network complexity reported previously. The intensified cross-trophic interactions were mainly explained by increased plant and litter biomass, which indicates that the N-induced increases in carbon supplies may have alleviated microbial energy limitations and thus resulted in more active metabolic processes, consequently stimulating various biotic interactions (e.g., predation, competition, and commensalism). Further, the enhanced inter-trophic network relationships were found to be associated with increased soil carbon and N mineralization processes. Overall, these findings highlight the importance of microbial cross-trophic interactions and indicate that they should be considered in predictions of ecosystem functioning under global N enrichment.

Data-Driven Approach for Designing Eco-Friendly Heterocyclic Compounds for the Soil Microbiome

Soil microbiota plays crucial roles in maintaining the health, productivity, and nutrient cycling of terrestrial ecosystems. The persistence and prevalence of heterocyclic compounds in soil pose significant risks to soil health. However, understanding the links between heterocyclic compounds and microbial responses remains challenging due to the complexity of microbial communities and their various chemical structures. This study developed a machine-learning approach that integrates the properties of chemical structures with the diversity of soil bacteria and functions to predict the impact of heterocyclic compounds on the microbial community and improve the design of eco-friendly heterocyclic compounds. We screened the key chemical structures of heterocyclic compounds─particularly those with topological polar surface areas (<74.2 Å2 or 111.3-154.1 Å2), carboxyl groups, and dissociation constant, which maintained high soil bacterial diversity and functions, revealing threshold effects where specific structural parameters dictated microbial responses. These eco-friendly compounds stabilize communities and increase beneficial carbon and nitrogen cycle functions. By applying these design parameters, we quantitatively assessed the eco-friendliness scores of 811 heterocyclic compounds, providing a robust foundation for guiding future applications. Our study disentangles the critical chemical structure-related properties that influence the soil microbial community and establishes a computational framework for designing eco-friendly compounds with ecological benefits from an ecological perspective.

Siderophore synthetase-receptor gene coevolution reveals habitat- and pathogen-specific bacterial iron interaction networks

Bacterial social interactions play crucial roles in various ecological, medical, and biotechnological contexts. However, predicting these interactions from genome sequences is notoriously difficult. Here, we developed bioinformatic tools to predict whether secreted iron-scavenging siderophores stimulate or inhibit the growth of community members. Siderophores are chemically diverse and can be stimulatory or inhibitory depending on whether bacteria have or lack corresponding uptake receptors. We focused on 1928 representative Pseudomonas genomes and developed an experimentally validated coevolution algorithm to match encoded siderophore synthetases to corresponding receptor groups. We derived community-level iron interaction networks to show that siderophore-mediated interactions differ across habitats and lifestyles. Specifically, dense networks of siderophore sharing and competition were observed among environmental and nonpathogenic species, while small, fragmented networks occurred among human-associated and pathogenic species. Together, our sequence-to-ecology approach empowers the analyses of social interactions among thousands of bacterial strains and offers opportunities for targeted intervention to microbial communities.

Dispersal promotes stability and persistence of exploited yeast mutualisms

Multispecies mutualistic interactions are ubiquitous and essential in nature, yet they face several threats, many of which have been exacerbated in the Anthropocene era. Understanding the factors that drive the stability and persistence of mutualism has become increasingly important in light of global change. Although dispersal is widely recognized as a crucial spatially explicit process in maintaining biodiversity and community structure, knowledge about how the dispersal of mutualists contributes to the persistence of mutualistic systems remains limited. In this study, we used a synthetic mutualism formed by genetically modified budding yeast to investigate the effect of dispersal on the persistence and stability of mutualisms under exploitation. We found that dispersal increased the persistence of exploited mutualisms by 80% compared to the isolated systems. Furthermore, our results showed that dispersal increased local diversity, decreased beta diversity among local communities, and stabilized community structure at the regional scale. Our results indicate that dispersal can allow mutualisms to persist in meta-communities by reintroducing species that are locally competitively excluded by exploiters. With limited dispersal, e.g. due to increased fragmentation of meta-communities, mutualisms might be more prone to breakdown. Taken together, our results highlight the critical role of dispersal in facilitating the persistence of mutualism.

Understanding pesticide-induced tipping in plant-pollinator networks across geographical scales: Prioritizing richness and modularity over nestedness

Mutually beneficial interactions between plants and pollinators are crucial for biodiversity, ecosystem stability, and crop production. A threat to a mutualistic network is the occurrence of a tipping point at which the species abundances collapse to a near zero level. In modern agriculture, there is widespread use of pesticides. What are the effects of extensive pesticide use on mutualistic networks? We develop a plant-pollinator-pesticide model and study its dynamics using 123 mutualistic networks across the globe. We demonstrate that pesticide exposure can lead to a tipping point. Furthermore, while the network characteristics such as richness and modularity exhibit a strong association with pesticide-induced tipping, nestedness shows a weak association. A surprising finding is that the mutualistic networks in the African continent are less pesticide tolerant than those in Europe. We articulate and test a pragmatic intervention strategy through targeted management of pesticide levels within specific plant species to delay or avert the tipping point. Our study provides quantitative insights into the phenomenon of pesticide-induced tipping for safeguarding mutualistic networks that are fundamental to agriculture and ecosystems.

Effects of reduced flow gradient on benthic biofilm communities' ecological network and community assembly

The intensification of human activities has led to flow reduction and cut-off in most global rivers, seriously affecting riverine organisms and the biogeochemical processes. As key indicators of river ecosystems' structure and function, benthic biofilms play a critical role in driving primary production and material cycling in rivers. This research aimed to investigate the characteristics of microbial communities' complexity and stability during river flow reduction. Benthic biofilms were grown in artificial channels and subjected to eight gradients of flow reduction (represented by flow velocity from 0.4 to 110 cm/s). Biofilms' biodiversity, ecological networks and community assembly of bacteria, fungi and algae were investigated by high-throughput sequencing. Results showed significant differences in community composition and structure under different flow conditions. The eight flow gradients' microbial communities were divided into three groups: low, medium and high flows. The flow reduction led to significant decreases in bacterial and fungal communities' Chao1 index. Low flow conditions enriched the bacterial phyla Oxyphotobacteria, Alphaproteobacteria and Mollicutes, but significantly decreased the fungal phylum Chytridiomycota. Lowering flow reduced the fungal network's number of nodes and increased the algal network's number of edges. Cross-domain interactions network analysis showed a gradual increase in node and edge numbers with decreasing flow, while decreasing average path length. The neutral model predicted stochastic processes primarily drove biofilm community assembly, and that model's explanations decreased as the flow gradient decreased. The null model analysis revealed diffusion limitation as the most common stochastic ecological process for bacterial and algal communities, with reduced flow reducing heterogeneous selection and increasing diffusion-limited processes. This study provides an in-depth analysis of flow reduction's effects on biofilm communities' ecological networks and community assembly.

A Probabilistic View of Forbidden Links: Their Prevalence and Their Consequences for the Robustness of Plant-Hummingbird Communities

The presence in ecological communities of unfeasible species interactions, termed forbidden links, due to physiological or morphological exploitation barriers has been long debated, but little direct evidence has been found. Forbidden links are likely to make ecological communities less robust to species extinctions, stressing the need to assess their prevalence. Here, we used a dataset of plant-hummingbird interactions, coupled with a Bayesian hierarchical model, to assess the importance of exploitation barriers in determining species interactions. We found evidence for exploitation barriers between flowers and hummingbirds across the 32 studied communities; however, the proportion of forbidden links changed drastically among communities because of changes in trait distributions. The higher the proportion of forbidden links, the more they decreased network robustness because of constraints on interaction rewiring. Our results suggest that exploitation barriers are not rare in plant-hummingbird communities and have the potential to limit the rescue of species experiencing partner extinction.

Assembly of soil multitrophic community regulates multifunctionality via multifaceted biotic factors in subtropical ecosystems

Soil biodiversity underpins multiple ecosystem functions and services essential for human well-being. Understanding the determinants of biodiversity-ecosystem function relationships (BEFr) is critical for the conservation and management of soil ecosystems. Community assembly processes determine community diversity and structure. However, there remains limited systematic research on how the assembly processes of multiple organismal groups affect soil ecosystem functions through their influence on biodiversity and species interactions. Here, we analyzed 331 soil samples from different land-use types (cropland, forest, and grassland) in the Qinling-Daba Mountains to investigate the drivers, assembly processes, and network stability of multitrophic organisms. High-throughput sequencing was used to examine archaea, bacteria, fungi, algae, protozoa, and invertebrates, while enzyme activity assays were used to assess ecosystem multifunctionality related to nutrient provisioning. Our results indicated that biotic factors contributed to 62.81-94.97 % of α-diversity and 4.19-52.37 % of β-diversity in multitrophic organisms, even when considering the influence of abiotic factors. Protozoan α- and β-diversity most significantly explained the α- and β-diversity of bacteria, fungi, algae, and invertebrates in soil ecosystems, serving as important indicators for assessing soil multifunctionality and ecosystem health. Furthermore, the assembly processes in prokaryotes were primarily governed by stochasticity (>50 %), whereas those in eukaryotic groups were dominated by deterministic processes (<50 %). Diversity and network stability increased with greater stochasticity in bacterial communities where stochastic processes predominated. Conversely, in fungal and protozoan communities dominated by deterministic processes, diversity and network stability decreased as deterministic processes intensified. Importantly, stochastic processes in soil multitrophic assembly enhanced ecosystem multifunctionality by increasing α-diversity, β-diversity, and network stability. These findings provide valuable insights into the regulation of BEFr by multitrophic assembly processes. Future research should further explore the role of these assembly processes in soil ecosystem functioning under land-use change scenarios.

Assessing the health of climate-sensitive trees in a subalpine ecosystem through microbial community dynamics

Climate change has significantly affected the subalpine ecosystems, leading to mass die-offs of the Korean fir tree, a key climate-sensitive species in these environments. Proactive analysis of the phenotypic responses of these trees to climate change or the establishment of preemptive strategies for trees to adapt to these environmental changes remains a challenge. The current study aimed to investigate the impact of climate change on the health of Korean fir (Abies koreana) in the subalpine ecosystem of Jirisan Mountain, South Korea. We integrated soil physicochemical analyses, microbial community dynamics, neutral community model, and network analyses to examine the relationships between tree health and microbial communities. Our findings revealed significant changes in soil chemical properties, including pH and nutrient concentrations, across the various health statuses of trees. Microbial community analysis demonstrated shifts in bacterial and fungal communities corresponding to the health continuum of the trees, with decreased diversity and altered composition in the declining trees. A remarkable increase in modularity of the microbial network and a clear transition from stochastic to deterministic microbial community assembly processes were observed as the trees progressed from a healthy to a dead stage. Two bacterial genera, Bradyrhizobium and Burkholderia, along with an unclassified fungal group from Basidiomycota, were identified as key microbial indicators of good tree health. This study highlighted the importance of microbial communities as bioindicators for assessing the health of subalpine ecosystem and its resilience to climate change, offering valuable insights into the conservation and management strategies for subalpine ecosystems.

Persistent biological invasions alter ecological network topology, impacting disease transmission during community assembly

Ecological networks experiencing persistent biological invasions may exhibit distinct topological properties, complicating the understanding of how network topology affects disease transmission during invasion-driven community assembly. We developed a trait-based network model to assess the impact of network topology on disease transmission, measured as community- and species-level disease prevalence. We found that trait-based feeding interactions between host species determine the frequency distribution of the niche of co-occurring species in steady-state communities, being either bimodal or multimodal. The width of the growth kernel influences the degree-biomass relationship of species, being either weakly positive or strongly negative. When this relationship is weakly positive, species-level disease prevalence is primarily correlated with biomass. However, when the degree-biomass relationship is strongly negative, species-level disease prevalence is determined by the difference between a host species' in-degree and out-degree closeness centrality. At the community level, disease prevalence is generally amplified by increasing host richness, community biomass, and the standard deviation of interaction generality, while it is diluted by higher network connectance. Our framework verifies the amplification effects of host richness during invasion-driven community assembly and offers valuable insights for estimating disease prevalence based on host network topology.

Biotic interactions and environmental modifications determine symbiotic microbial diversity and stability

Taking amphibians as island models, we examined the effects of interspecific interaction on the diversity and stability of microbial ecological. As skin area increased, the diversity and stability of skin microbes decreased, but the strength of negative interactions increased significantly. In contrast, as gut area increased, the diversity and stability of gut microbes increased, but the strength of interactions remained constant. These results indicate that microbial interactions are affected by habitat properties. When living in fluctuating environments without strong filtering, microorganisms can enhance their negative interactions with other taxa by changing the pH of their surroundings. In contrast, the pH of the gut is relatively stable, and colonized microorganisms cannot alter the gut pH and inhibit other colonizers. This study demonstrates that in the field of microbiology, diversity and stability are predominantly influenced by the intensity of interspecies interactions. The findings in this study deepen our understanding of microbial diversity and stability and provide a mechanistic link between species interactions, biodiversity, and stability in microbial ecosystems.

Bifurcations and multistability in empirical mutualistic networks

Individual species may experience diverse outcomes, from prosperity to extinction, in an ecological community subject to external and internal variations. Despite the wealth of theoretical results derived from random matrix ensembles, a theoretical framework still remains to be developed to understand species-level dynamical heterogeneity within a given community, hampering real-world ecosystems' theoretical assessment and management. Here, we consider empirical plant-pollinator mutualistic networks, additionally including all-to-all intragroup competition, where species abundance evolves under a Lotka-Volterra-type equation. Setting the strengths of competition and mutualism to be uniform, we investigate how individual species persist or go extinct under varying these interaction strengths. By taking a dynamical systems approach, we meticulously study how increments in these interactions create particular sequences of extinctions and find the interaction strengths threshold values in which multistability arises. Hence, we are able to elucidate interaction strength regimes where, depending on the initial abundances of the species, different extinction scenarios arise within an ecological network.

Urban environments increase generalization of hummingbird-plant networks across climate gradients

Urbanization has reshaped the distribution of biodiversity on Earth, but we are only beginning to understand its effects on ecological communities. While urbanization may have homogenization effects strong enough to blur the large-scale patterns in interaction networks, urban community patterns may still be associated with climate gradients reflecting large-scale biogeographical processes. Using 103 hummingbird-plant mutualistic networks across continental Americas, including 176 hummingbird and 1,180 plant species, we asked how urbanization affects species interactions over large climate gradients. Urban networks were more generalized, exhibiting greater interaction overlap. Higher generalization was also associated with lower precipitation in both urban and natural areas, indicating that climate affects networks irrespective of habitat type. Urban habitats also showed lower hummingbird functional trait diversity and over/underrepresentation of specific clades. From the plant side, urban communities had a higher prevalence of nonnative nectar plants, which were more frequently visited by the hummingbird species occurring in both urban and natural areas. Therefore, urbanization affected hummingbird-plant interactions through both the composition of species and traits, as well as floral resource availability. Taken together, we show that urbanization consistently modifies ecological communities and their interactions, but climate still plays a role in affecting the structure of these novel communities over the scale of continents.

Typical alien invasive aquatic-plant species changed the stability rather than the diversity of plankton community in fresh water

Alien invasive aquatic-plant (AIA) species are severely threatening the aquatic ecosystems worldwide, especially biodiversity. Although plankton have been used to monitor and address biodiversity, some gaps remain in understanding of the relationships between plankton communities and AIA species. Here, the effects of two typical AIA species (Pistia stratiotes and Eichhornia crassipes) on plankton communities in freshwater with a native plant Vallisneria natans were investigated using a 50-d microcosm experiment. Results showed that AIA species significantly decreased water pH and dissolved oxygen while increased oxidation-reduction potential (p < 0.05). AIA species, especially P. stratiotes, significantly inhibited dry biomass accumulation in V. natans by an average rate of 39.0 %, decreased water pH by up to 14.62 %, and increased aboveground lengths and chlorophyll contents of V. natans by up to 36.2 % and 63.7 % (p < 0.05), respectively. These species further modified the growth strategy of V. natans from dry biomass accumulation to aboveground elongation. Although the AIA species did not alter plankton diversity (p > 0.05), but they changed their dominant species, functional communities (e.g., Groups D and TB), and co-occurrence networks. P. stratiotes decreased the average degree of the networks by 12.37-19.02 % and the graph density by 10.53-14.47 %, while E. crassipes decreased the modularity of the networks by 10.24 % compared with the control (without AIA species), respectively. Overall, AIA species inhibited the growth of V. natans and decreased the stability of plankton communities and their resistance to environmental disturbances. These findings enhance our understanding of how AIA species affect the growth of native plants and variations in plankton communities, thereby providing a theoretical basis for improving the ecological function and safety of freshwater.

Seasonal variations in soil microbial community co-occurrence network complexity respond differently to field-simulated warming experiments in a northern subtropical forest

Global warming may reshape seasonal changes in microbial community diversity and co-occurrence network patterns, with significant implications for terrestrial ecosystem function. We conducted a 2-year in situ field simulation of the effects of warming on the seasonal dynamics of soil microbial communities in a northern subtropical Quercus acutissima forest. Our study revealed that warming had no significant effect on the richness or diversity of soil bacteria or fungi in the growing season, whereas different warming gradients had different effects on their diversity in the nongrowing season. Warming also changed the microbial community structure, increasing the abundance of some thermophilic microbial species and decreasing the abundance of some symbiotrophic microorganisms. The co-occurrence network analysis of the microbial community showed that warming decreased the complexity of the intradomain network in the soil bacterial community in the growing and nongrowing seasons but increased it in the fungal community. Moreover, increasing warming temperatures increased the complexity of the interdomain network between bacteria and fungi in the growing season but decreased it in the nongrowing season, and the keystone species in the interdomain network changed with warming. Warming also reduced the proportion of positive microbial community interactions, indicating that warming reduced the mutualism, commensalism, and neutralism of microorganisms as they adapted to soil environmental stress. The factors affecting the fungal community varied considerably across warming gradients, with the bacterial community being significantly affected by soil temperature, MBC, NO3--N and NH4+-N, moreover, SOC and TN significantly affected fungal communities in the 4 °C warming treatment. These results suggest that warming increases seasonal differences in the diversity and complexity of soil microbial communities in the northern subtropical region, significantly influencing soil dynamic processes regulating forest ecosystems under global warming.

Glacier Retreat Induces Contrasting Shifts in Bacterial Biodiversity Patterns in Glacial Lake Water and Sediment : Bacterial Communities in Glacial Lakes

Glacial lake ecosystems are experiencing rapid changes due to accelerated glacier retreat. As glaciers recede, their influence on downstream habitats diminishes, potentially affecting the biodiversity of glacial lake microbial communities. However, there remains a knowledge gap regarding how bacterial biodiversity patterns in glacial lakes are altered by diminishing glacial influence. Here, we investigated shifts in bacterial communities in paired water and sediment samples collected from seven glacial lakes on the Tibetan Plateau, using a space-for-time substitution approach to understand the consequences of glacier retreat. Our findings reveal that bacterial diversity in lake water increases significantly with a higher glacier index (GI), whereas sediment bacterial diversity exhibits a negative correlation with GI. Both the water and sediment bacterial communities display significant structural shifts along the GI gradient. Notably, reduced glacial influence decreases the complexity of bacterial co-occurrence networks in lake water but enhances the network complexity in sediment. This divergence in diversity and co-occurrence patterns highlights that water and sediment bacterial communities respond differently to changes in glacial influence in these lake ecosystems. This study provides insights into how diminishing glacial influence impacts the bacterial biodiversity in glacial lake water and sediments, revealing contrasting patterns between the two habitats. These findings emphasize the need for comprehensive monitoring to understand the implications of glacier retreat on these fragile ecosystems.

Constructing more comprehensive pollination networks: integrating diurnal and nocturnal pollen data with visitation in a subalpine wetland community

Introduction

Sampling for describing plant-pollinator interaction networks has been performed using techniques that either focus on the plants (with flower-visit data) or the animals (with analyzing pollen on the body surface of flower visitors). The differences in the structure of the networks obtained using these methods likely influences our understanding of the contribution of nocturnal pollinators, yet this key finding has yet to be the focus of study.

Methods

In this study, we conducted an intensive diurnal field survey in the subalpine meadows of the Dajiuhu Wetland and supplemented the data with an analysis of diurnal and nocturnal pollen data to examine the changes in pollination networks.

Results

We observed 41 plant and 154 pollinator species, corresponding to 665 specific interactions. Visitation and pollen analyses showed significant differences in the composition and interaction between network plants and pollinators, resulting in important structural changes in the network. Given that the diurnal pollen data showed new links that were preferentially attached to highly connected nodes, the level of asymmetric specialization did not decrease; however, nestedness increased 1.3-fold, and mean pollinator connectivity from 3.1 to 5.1. As the behaviors of nocturnal pollinators tended to be more specialized, the inclusion of nocturnal pollen data led to an increase in the number of extreme-specialist pollinator species. Consequently, nestedness decreased 0.8-fold, but mean plant connectivity went from 14.2 to 16.2.

Discussion

These findings suggest that the structure of pollination networks is influenced by the sampling methods and the level of detail of the investigation. Our study has strong implications for the development of monitoring schemes for plant-pollinator interactions. Due to the practical difficulties of nocturnal field visitation, when conducting research, combining diurnal field visitation with both diurnal and nocturnal pollen analyses is the most convenient and realistic method to capture the full complexity of these networks.

Does warming erode network stability and ecosystem multifunctionality?

Environmental warming is thought to alter food web stability and functioning, but whether warming reduces food web resistance and resilience to further climatic events remains surprisingly unexplored. Warming experiments that superimpose acute disturbances are urgently needed to understand how extreme events further threaten the stability and multifunctionality of ecological networks.

Local and regional processes drive distance decay in structure in a spatial multilayer plant-pollinator network

Understanding spatial variation in species distribution and community structure is at the core of community ecology. Nevertheless, the effect of distance on metacommunity structure remains little studied. We examine how plant-pollinator community structure changes across geographical distances at a regional scale and disentangle its underlying local and regional processes. We use a multilayer network to represent linked plant-pollinator communities as a metacommunity in the Canary Islands. We used modularity (i.e. the extent to which the community is partitioned into groups of densely interacting species) to quantify distance decay in structure across space. In multilayer modularity, the same species can belong to different modules in different communities, and modules can span communities. This enabled quantifying how similarity in module composition varied with distance between islands. We developed three null models, each controlling for a separate component of the multilayer network, to disentangle the role of species turnover, interaction rewiring and local factors in driving distance decay in structure. We found a pattern of distance decay in structure, indicating that islands tended to share fewer modules with increasing distance. Species turnover (but not interaction rewiring) was the primary regional process triggering distance decay in structure. Local interaction structure also played an essential role in determining the structure similarity of communities at a regional scale. Therefore, local factors that determine species interactions occurring at a local scale drive distance decay in structure at a regional scale. Our work highlights the interplay between local and regional processes underlying community structure. The methodology, and specifically the null models, we developed provides a general framework for linking communities in space and testing different hypotheses regarding the factors generating spatial structure.

Networks as tools for defining emergent properties of microbiomes and their stability

The potential promise of the microbiome to ameliorate a wide range of societal and ecological challenges, from disease prevention and treatment to the restoration of entire ecosystems, hinges not only on microbiome engineering but also on the stability of beneficial microbiomes. Yet the properties of microbiome stability remain elusive and challenging to discern due to the complexity of interactions and often intractable diversity within these communities of bacteria, archaea, fungi, and other microeukaryotes. Networks are powerful tools for the study of complex microbiomes, with the potential to elucidate structural patterns of stable communities and generate testable hypotheses for experimental validation. However, the implementation of these analyses introduces a cascade of dichotomies and decision trees due to the lack of consensus on best practices. Here, we provide a road map for network-based microbiome studies with an emphasis on discerning properties of stability. We identify important considerations for data preparation, network construction, and interpretation of network properties. We also highlight remaining limitations and outstanding needs for this field. This review also serves to clarify the varying schools of thought on the application of network theory for microbiome studies and to identify practices that enhance the reproducibility and validity of future work. Video Abstract.

The Interplay of Binary and Quantitative Structure on the Stability of Mutualistic Networks

Understanding how the structure of biological systems impacts their resilience (broadly defined) is a recurring question across multiple levels of biological organization. In ecology, considerable effort has been devoted to understanding how the structure of interactions between species in ecological networks is linked to different broad resilience outcomes, especially local stability. Still, nearly all of that work has focused on interaction structure in presence-absence terms and has not investigated quantitative structure, i.e., the arrangement of interaction strengths in ecological networks. We investigated how the interplay between binary and quantitative structure impacts stability in mutualistic interaction networks (those in which species interactions are mutually beneficial), using community matrix approaches. We additionally examined the effects of network complexity and within-guild competition for context. In terms of structure, we focused on understanding the stability impacts of nestedness, a structure in which more-specialized species interact with smaller subsets of the same species that more-generalized species interact with. Most mutualistic networks in nature display binary nestedness, which is puzzling because both binary and quantitative nestedness are known to be destabilizing on their own. We found that quantitative network structure has important consequences for local stability. In more-complex networks, binary-nested structures were the most stable configurations, depending on the quantitative structures, but which quantitative structure was stabilizing depended on network complexity and competitive context. As complexity increases and in the absence of within-guild competition, the most stable configurations have a nested binary structure with a complementary (i.e., anti-nested) quantitative structure. In the presence of within-guild competition, however, the most stable networks are those with a nested binary structure and a nested quantitative structure. In other words, the impact of interaction overlap on community persistence is dependent on the competitive context. These results help to explain the prevalence of binary-nested structures in nature and underscore the need for future empirical work on quantitative structure.

Global effects of land-use intensity and exotic plants on the structure and phylogenetic signal of plant-herbivore networks

Interactions between plants and herbivorous insects are often phylogenetically structured, with closely related insect species using similar sets of species or lineages of plants, while phylogenetically closer plants tend to share high proportions of their herbivore insect species. Notably, these phylogenetic constraints in plant-herbivore interactions tend to be more pronounced among internal plant-feeding herbivores (i.e., endophages) than among external feeders (i.e., exophages). In the context of growing human-induced habitat conversion and the global proliferation of exotic species, it is crucial to understand how ecological networks respond to land-use intensification and the increasing presence of exotic plants. In this study, we analyzed plant-herbivore network data from various locations of the World to ascertain the degree to which land-use intensity and the prevalence of exotic plants induce predictable changes in their network topology - measured by levels of nestedness and modularity - and phylogenetic structures. Additionally, we investigated whether the intimacy of plant-herbivore interactions, contrasting endophagous with exophagous networks, modulate changes in network structure. Our findings reveal that most plant-herbivore networks are characterized by significant phylogenetic and topological structures. However, neither these structures did not show consistent changes in response to increased levels of land-use intensify. On the other hand, for the networks composed of endophagous herbivores, the level of nestedness was higher in the presence of a high proportion of exotic plants. Additionally, for networks of exophagous herbivores, we observed an increase in the phylogenetic structure of interactions due to exotic host dominance. These results underscore the differential impacts of exotic species and land-use intensity on the phylogenetic and topological structures of plant-herbivore networks.

DyMMM-LEAPS: An ML-based framework for modulating evenness and stability in synthetic microbial communities

There have been a growing number of computational strategies to aid in the design of synthetic microbial consortia. A framework to identify regions in parametric space to maximize two essential properties, evenness and stability, is critical. In this study, we introduce DyMMM-LEAPS (dynamic multispecies metabolic modeling-locating evenness and stability in large parametric space), an extension of the DyMMM framework. Our method explores the large parametric space of genetic circuits in synthetic microbial communities to identify regions of evenness and stability. Due to the high computational costs of exhaustive sampling, we utilize adaptive sampling and surrogate modeling to reduce the number of simulations required to map the vast space. Our framework predicts engineering targets and computes their operating ranges to maximize the probability of the engineered community to have high evenness and stability. We demonstrate our approach by simulating five cocultures and one three-strain culture with different social interactions (cooperation, competition, and predation) employing quorum-sensing-based genetic circuits. In addition to guiding circuit tuning, our pipeline gives an opportunity for a detailed analysis of pockets of evenness and stability for the circuit under investigation, which can further help dissect the relationship between the two properties. DyMMM-LEAPS is easily customizable and can be expanded to a larger community with more complex interactions.

Temporal shifts in the phytoplankton network in a large eutrophic shallow freshwater lake subjected to major environmental changes due to human interventions

Phytoplankton communities are crucial components of aquatic ecosystems, and since they are highly interactive, they always form complex networks. Yet, our understanding of how interactive phytoplankton networks vary through time under changing environmental conditions is limited. Using a 29-year (339 months) long-term dataset on Lake Taihu, China, we constructed a temporal network comprising monthly sub-networks using "extended Local Similarity Analysis" and assessed how eutrophication, climate change, and restoration efforts influenced the temporal dynamics of network complexity and stability. The network architecture of phytoplankton showed strong dynamic changes with varying environments. Our results revealed cascading effects of eutrophication and climate change on phytoplankton network stability via changes in network complexity. The network stability of phytoplankton increased with average degree, modularity, and nestedness and decreased with connectance. Eutrophication (increasing nitrogen) stabilized the phytoplankton network, mainly by increasing its average degree, while climate change, i.e., warming and decreasing wind speed enhanced its stability by increasing the cohesion of phytoplankton communities directly and by decreasing the connectance of network indirectly. A remarkable shift and a major decrease in the temporal dynamics of phytoplankton network complexity (average degree, nestedness) and stability (robustness, persistence) were detected after 2007 when numerous eutrophication mitigation efforts (not all successful) were implemented, leading to simplified phytoplankton networks and reduced stability. Our findings provide new insights into the organization of phytoplankton networks under eutrophication (or re-oligotrophication) and climate change in subtropical shallow lakes.

Ecosystem engineering and food web stability

Ecosystem engineering, which involves organism-triggered physical modification of the environment, is a widespread phenomenon. Despite this, the role of engineering in ecological communities remains poorly understood. This study employs a food web model to uncover the key roles of ecosystem engineering in maintaining food webs. While engineers facilitating population growth and suppressing consumers' foraging activity can help maintain complex communities with diverse species, engineering effects that suppress population growth and facilitate consumers' foraging activity can largely destabilize community dynamics. Furthermore, in the middle levels of engineering-related species within a community, an increase in species richness can increase community stability, contrary to classical ecological prediction. The study findings suggest that ecosystem engineering can explain biodiversity persistence in nature, but it depends on the proportion of engineering-related species and how engineering affects organisms.

The structure of bacteria-fungi bipartite networks along elevational gradients in contrasting climates

Climate change is altering species distribution and modifying interactions in microbial communities. Understanding microbial community structure and their interactions is crucial to interpreting ecosystem responses to climate change. Here, we examined the assemblages of stream bacteria and fungi, and the associations between the two groups along elevational gradients in two regions with contrasting precipitation and temperature, that is the Galong and Qilian mountains of the Tibetan Plateau. In the wetter and warmer region, the species richness significantly increased and decreased with elevation for bacteria and fungi, respectively, while were nonsignificant in the drier and colder region. Their bipartite network structure was also different by showing significant increases in connectance and nestedness towards higher elevations only in the wetter and warmer region. In addition, these correlation network structure generally exhibited similar positive association with species richness in the wetter and warmer region and the drier and colder region. In the wetter and warmer region, climatic change along elevation was more important in determining connectance and nestedness, whereas microbial species richness exerted a stronger influence on network structure and robustness in the drier and colder region. These findings indicate substantial forthcoming changes in microbial diversity and network structure in warming climates, especially in wetter and warmer regions on Earth, advancing the understanding of microbial bipartite interactions' response to climate change.

Community connectivity and local heterogeneity explain animal species co-occurrences within pond communities

Metacommunity processes have the potential to determine most features of the community structure. However, species diversity has been the dominant focus of studies. Nestedness, modularity and checkerboard distribution of species occurrences are main components of biodiversity organisation. Within communities, these patterns emerge from the interaction between functional diversity, spatial heterogeneity and resource availability. Additionally, the connectivity determines the pool of species for community assembly and, eventually, the pattern of species co-occurrence within communities. Despite the recognised theoretical expectations, the change in occurrence patterns within communities along ecological gradients has seldom been considered. Here, we analyse the spatial occurrence of animal species along sampling units within 18 temporary ponds and its relationship with pond environments and geographic isolation. Isolated ponds presented a nested organisation of species with low spatial segregation-modularity and checkerboard-and the opposite was found for communities with high connectivity. A pattern putatively explained by high functional diversity in ponds with large connectivity and heterogeneity, which determines that species composition tracks changes in microhabitats. On the contrary, nestedness is promoted in dispersal-limited communities with low functional diversity, where microhabitat filters mainly affect richness without spatial replacement between functional groups. Vegetation biomass promotes nestedness, probably due to the observed increase in spatial variance in biomass with the mean biomass. Similarly, the richness of vegetation reduced the spatial segregation of animals within communities. This result may be due to the high plant diversity of the pond that is observed similarly along all sampling units, which promotes the spatial co-occurrence of species at this scale. In the study system, the spatial arrangement of species within communities is related to local drivers as heterogeneity and metacommunity processes by means of dispersal between communities. Patterns of species co-occurrence are interrelated with community biodiversity and species interactions, and consequently with most functional and structural properties of communities. These results indicate that understanding the interplay between metacommunity processes and co-occurrence patterns is probably more important than previously thought to understand biodiversity assembly and functioning.

Stability, resilience and eco-evolutionary feedbacks of mutualistic networks to rising temperature

Ecological networks comprising of mutualistic interactions can suddenly transition to undesirable states, such as collapse, due to small changes in environmental conditions such as a rise in local environmental temperature. However, little is known about the capacity of such interaction networks to adapt to a rise in temperature and the occurrence of critical transitions. Here, combining quantitative genetics and mutualistic dynamics in an eco-evolutionary framework, we evaluated the stability and resilience of mutualistic networks to critical transitions as environmental temperature increases. Specifically, we modelled the dynamics of an optimum trait that determined the tolerance of species to local environmental temperature as well as to species interaction. We then evaluated the impact of individual trait variation and evolutionary dynamics on the stability of feasible equilibria, the occurrence of threshold temperatures at which community collapses, and the abruptness of such community collapses. We found that mutualistic network architecture, that is the size of the community and the arrangement of species interactions, interacted with evolutionary dynamics to impact the onset of network collapses. Some networks had more capacity to track the rise in temperatures than others and thereby increased the threshold temperature at which the networks collapsed. However, such a result was modulated by the amount of heritable trait variation species exhibited, with high trait variation in the mean optimum phenotypic trait increasing the environmental temperature at which networks collapsed. Furthermore, trait variation not only increased the onset of temperatures at which networks collapsed but also increased the local stability of feasible equilibria. Our study argued that mutualistic network architecture interacts with species evolutionary dynamics and increases the capacity of networks to adapt to changes in temperature and thereby delayed the occurrence of community collapses.

Microbial communities assembly in wastewater treatment plants in China

Community assembly processes determine community structure. Deterministic processes are essential for optimizing activated sludge (AS) bioreactor performance. However, the debate regarding the relative importance of determinism versus stochasticity remains contentious, and the influencing factors are indistinct. This study used large-scale 16S rRNA gene data derived from 252 AS samples collected from 28 cities across China to explore the mechanism of AS community assembly. Results showed that the northern communities possessed lower spatial turnover and more significant dispersal limitation than those in the south, whereas the latter had more substantial deterministic processes than the former (14.46 % v.s. 9.12 %). Meanwhile, the communities in the south exhibited lower network complexity and stability. We utilized a structural equation model to explore the drivers of deterministic processes. Results revealed that low network complexity (r = -0.56, P < 0.05) and high quorum sensing bacteria abundance (r = 0.25, P < 0.001) promoted deterministic assembly, which clarifies why determinism was stronger in southern communities than northern ones. Furthermore, total phosphorus and hydraulic retention time were found to be the primary abiotic drivers. These findings provide evidence to understand the community deterministic assembly, which is crucial for resolving community structure and improving bioreactor performance.