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Microbial network complexity is an important indicator for assessing the effectiveness of vegetation restoration. However, the response of the microbial network complexity of bacteria and fungi to different vegetation restoration types is unclear. Therefore, in this study, we selected four vegetation restoration types (Pinus sylvestris var. mongholica , Larix principis- rupprechtii , Populus tomentosa , and Ulmus pumila), while selected the nature grassland as a control, in the Zhangjiakou Tunken Forest Farm, which is a typical agricultural pastoral ecotone in northern China, to investigate the response of soil microbial diversity and network complexity to different vegetation restoration types. Our result showed that the bacterial Shannon and Chao indices of P. sylvestris var. mongholica were significantly 7.77 and 22.39% higher than those of grassland in the 20–40 cm soil layer, respectively. The fungal Chao indices of U. pumila were significantly 85.70 and 146.86% higher than those of grassland in the 20–40 cm and 40–60 cm soil layer, respectively. Compared to natural grassland, soil microbial networks became more complex in plantation forests restoration types (P. sylvestris var. mongholica , L. principis- rupprechtii , P. tomentosa , and U. pumila). Microbial network complexity increased with soil carbon and nitrogen. P. tomentosa is suitable for planting in the agricultural pastoral ecotone of Zhangjiakou, because of its high soil carbon, nitrogen and microbial network complexity. Bacterial community composition was found to be closely related to soil organic carbon (SOC), total nitrogen (TN), while that of fungi was closely related to SOC, clay and silt content. This improvement in microbial complexity enhances the ecological service function of the agricultural pastoral ecotone. These findings offer theoretical basis and technical support for the vegetation restoration of ecologically fragile areas in agricultural pastoral ecotone. [ABSTRACT FROM AUTHOR]

Pesticide application is essential for stabilizing agricultural production. However, the effects of increasing pesticide diversity on soil microbial functions remain unclear, particularly under varying nitrogen (N) fertilizer management practices. In this study, we investigated the stochasticity of soil microbes and multitrophic networks through amplicon sequencing, assessed soil community functions related to carbon (C), N, phosphorus (P), and sulfur (S) cycling, and characterized the dominant bacterial life history strategies via metagenomics along a gradient of increasing pesticide diversity under two N addition levels. Our findings show that higher pesticide diversity enriches the abundance of bacterial specialists and opportunists capable of degrading or resisting pesticides, reducing the proportion of bacterial generalists in the absence of N addition. These shifts can complicate multitrophic microbial networks. Under increased pesticide diversity, selective pressure may drive bacteria to streamline their average genome size to conserve energy while enhancing C, N, P, and S metabolic capacities, thus accelerating soil nutrient loss. In comparison, N addition was found to reduce bacterial niche differentiation at higher pesticide diversity, mitigating the impacts of network complexity and functional traits associated with pesticide diversity, ultimately alleviating soil nutrient loss. Our results reveal the contrasting impacts of pesticide diversity on microbial functions under different N input scenarios and emphasize that strategic N fertilizer management can mitigate the ecological effects of pesticide use in agricultural systems. [ABSTRACT FROM AUTHOR]

Machine learning technologies have recently emerged as transformative tools for enhancing project management accuracy and efficiency. This study introduces a data-driven model that leverages the hybrid eXtreme Gradient Boosting-Simulated Annealing (XGBoost-SA) algorithm to predict the time and cost of construction projects. By accounting for the complexity of activity networks and uncertainties within project environments, the model aims to address key challenges in project forecasting. Unlike traditional methods such as Earned Value Management (EVM) and Earned Schedule Method (ESM), which rely on static metrics, the XGBoost-SA model adapts dynamically to project data, achieving 92% prediction accuracy. This advanced model offers a more precise forecasting approach by incorporating and optimizing features from historical data. Results reveal that XGBoost-SA reduces cost prediction error by nearly 50% and time prediction error by approximately 80% compared to EVM and ESM, underscoring its effectiveness in complex scenarios. Furthermore, the model's ability to manage limited and evolving data offers a practical solution for real-time adjustments in project planning. With these capabilities, XGBoost-SA provides project managers with a powerful tool for informed decision-making, efficient resource allocation, and proactive risk management, making it highly applicable to complex construction projects where precision and adaptability are essential. The main limitation of the developed model in this study is the reliance on data from similar projects, which necessitates additional data for application to other industries. [ABSTRACT FROM AUTHOR]

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Organic management enhances the formation of distinct and stable soil microbial communities, however, its influence on the temporal recovery of microbiome and multifunctionality of sterilized soil remains poorly understood.We used amplicon sequencing and metagenomic sequencing to investigate the effects of microbial communities in long‐term organic and conventional managed soils on restoring soil microbiome and functionality. We calculated multifunctionality of soils at days 30 and 90 of recolonization using the averaging approach.Results showed that organic management (O) significantly increased alpha diversity, niche width and network complexity of microbial community compared to conventional management (C). The alpha diversity, niche width and network complexity of microbial community in soils with organic soil suspension were significantly increased compared to conventional management at days 30 and 90 of recolonization. Soil multifunctionality of sterilized organic managed soil inoculated with organic soil suspension (OO) was 14.6% to 70.6% higher than that of the rest treatments. Macrogenomic analysis revealed that O significantly enriched functional pathways of ABC transporters, carbon metabolism, biosynthesis of amino acids, two‐component and nitrogen metabolism as well as most of the functional genes for carbon degradation, carbon fixation, nitrogen cycling and phosphorus cycles compared to C. These functional pathways and genes were also significantly enriched in soils with organic soil suspension at day 30 and 90 of recolonization. Furthermore, alpha diversity, niche width, network complexity, functional pathways and functional genes of microbiome correlated positively with soil multifunctionality.Synthesis and applications. Our results emphasize the importance of organic management induced changes in diversity, network complexity, and functionality of microbial communities for promoting recovery to soil microbial and functional losses, providing the theoretical basis for sustainable impact of organic management in agronomic production on soil microbiome and function. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Mountain regions play a crucial role in maintaining global biodiversity, with altitude exerting a significant influence on soil microbial diversity by altering plant diversity, soil nutrients, and microclimate. However, differences in microbial community composition between topsoil (0–10 cm deep) and subsoil (10–20 cm deep) remain poorly understood. Here, we aimed to assess soil microbial diversity, microbial network complexity, and microbial community assembly in the topsoil and subsoil layers of the dry–hot Jinsha River valley in southwestern China. Using high-throughput sequencing in soil samples collected along an altitudinal gradient, we found that bacterial diversity in topsoil decreased with increasing altitude, while bacterial diversity in subsoil showed no altitude-dependent changes. Fungal diversity in topsoil also varied with altitude, while subsoil fungal diversity showed no change. These findings suggest that microbial diversity in topsoil was more sensitive to changes in altitude than subsoil. Bacterial community assembly tended to be governed by stochastic processes, while fungal assembly was deterministic. Soil bacterial and fungal network complexity was enhanced with increasing altitude but reduced as diversity increased. Interestingly, the presence of woody plant species negatively affected bacterial and fungal community composition in both soil layers. Soil pH and water content also negatively affected microbial community composition, while organic carbon and total nitrogen positively influenced the microbial community composition. Simultaneously, herb and woody plant diversity mainly affected soil bacterial diversity in the topsoil and subsoil, respectively, while woody plant diversity mainly affected soil fungal diversity in subsoil and soil nutrients had more effect on soil fungal diversity. These findings suggest that altitude directly and indirectly affects microbial diversity in topsoil, subsequently influencing microbial diversity in subsoil through nutrient availability. [ABSTRACT FROM AUTHOR]

Microbial network complexity is an important indicator for assessing the effectiveness of vegetation restoration. However, the response of the microbial network complexity of bacteria and fungi to different vegetation restoration types is unclear. Therefore, in this study, we selected four vegetation restoration types (Pinus sylvestris var. mongholica, Larix principis- rupprechtii, Populus tomentosa, and Ulmus pumila), while selected the nature grassland as a control, in the Zhangjiakou Tunken Forest Farm, which is a typical agricultural pastoral ecotone in northern China, to investigate the response of soil microbial diversity and network complexity to different vegetation restoration types. Our result showed that the bacterial Shannon and Chao indices of P. sylvestris var. mongholica were significantly 7.77 and 22.39% higher than those of grassland in the 20–40 cm soil layer, respectively. The fungal Chao indices of U. pumila were significantly 85.70 and 146.86% higher than those of grassland in the 20–40 cm and 40–60 cm soil layer, respectively. Compared to natural grassland, soil microbial networks became more complex in plantation forests restoration types (P. sylvestris var. mongholica, L. principis- rupprechtii, P. tomentosa, and U. pumila). Microbial network complexity increased with soil carbon and nitrogen. P. tomentosa is suitable for planting in the agricultural pastoral ecotone of Zhangjiakou, because of its high soil carbon, nitrogen and microbial network complexity. Bacterial community composition was found to be closely related to soil organic carbon (SOC), total nitrogen (TN), while that of fungi was closely related to SOC, clay and silt content. This improvement in microbial complexity enhances the ecological service function of the agricultural pastoral ecotone. These findings offer theoretical basis and technical support for the vegetation restoration of ecologically fragile areas in agricultural pastoral ecotone.

Summary: Intercropping leads to different plant roots directly influencing belowground processes and has gained interest for its promotion of increased crop yields and resource utilization. However, the precise mechanisms through which the interactions between rhizosphere metabolites and the microbiome contribute to plant production remain ambiguous, thus impeding the understanding of the yield‐enhancing advantages of intercropping.This study conducted field experiments (initiated in 2013) and pot experiments, coupled with multi‐omics analysis, to investigate plant–metabolite–microbiome interactions in the rhizosphere of maize.Field‐based data revealed significant differences in metabolite and microbiome profiles between the rhizosphere soils of maize monoculture and intercropping. In particular, intercropping soils exhibited higher microbial diversity and metabolite chemodiversity. The chemodiversity and composition of rhizosphere metabolites were significantly related to the diversity, community composition, and network complexity of soil microbiomes, and this relationship further impacted plant nutrient uptake. Pot‐based findings demonstrated that the exogenous application of a metabolic mixture comprising key components enriched by intercropping (soyasapogenol B, 6‐hydroxynicotinic acid, lycorine, shikimic acid, and phosphocreatine) significantly enhanced root activity, nutrient content, and biomass of maize in natural soil, but not in sterilized soil.Overall, this study emphasized the significance of rhizosphere metabolite–microbe interactions in enhancing yields in intercropping systems. It can provide new insights into rhizosphere controls within intensive agroecosystems, aiming to enhance crop production and ecosystem services. [ABSTRACT FROM AUTHOR]

Temporal change in vegetation complexity and field management may interactively affect the structure of predator–prey networks in agroecosystems and consequently alter the biocontrol potential of predators. There is a limited number of studies that have addressed these questions for generalist predator–prey networks.We investigated how vegetation complexity during crop development and management type (conventional vs. organic) affect the trophic networks of orb‐weaving spiders and their prey in rainfed lowland rice ecosystems in southern Thailand. Specifically, we investigated orb‐weaving spiders and prey composition, prey selectivity and network structure.Overall, orb‐weaving spiders captured mostly detritus‐associated Diptera, aquatic‐associated Ephemeroptera and Hemiptera pests. The increasing vegetation complexity during rice development significantly restructured the network of orb‐weaving spiders and prey, while field management had only a marginal effect. The increased vegetation complexity during rice development led to an increased number of weak trophic interactions in comparison to few but strong interactions in simple vegetation.Our results indicate that increasing the number of spider species per prey taxon (prey vulnerability) in late rice season may enhance their top‐down control of prey including rice pests. This study also highlights that the network complexity and the stability of rice ecosystems increased during the rice growing season as the vegetation became more complex.Future practices could look for a way to support the densities of detritus and aquatic insects and to artificially increase habitat complexity during the early stage of rice development to improve the biocontrol services provided by the orb‐weaving spiders. [ABSTRACT FROM AUTHOR]

Chinese medicine plays a crucial role in maintaining the equilibrium of the intestinal microbiome, and this microbiome, in turn, plays a pivotal role in mediating the pharmacological effects of Chinese medicine on the host. Despite the significance of this interplay, there is a paucity of studies investigating the impact of orally administered Traditional Chinese Medicine (TCM) on the co-occurrence patterns of intestinal gut bacteria. In the present study, we incorporated Coix seed, Chinese yam, Semen euryales, and their combination into the diet of mice. Subsequently, we assessed the effects of these TCM on the diversity, community composition, and co-occurrence networks of gut bacteria by oral administration. Our findings underscored the substantial influence of the three TCM varieties and their mixture on the diversity and community composition of gut bacteria. Notably, all TCM utilized in our study exhibited the ability to enrich beneficial gut bacteria and inhibit pathogenic bacteria within the intestinal microbiome. Furthermore, oral administration of Coix seed, Chinese yam, Semen euryales, or their combinations resulted in increased thymus and spleen indices. Examination of network topological features revealed marked dissimilarities between the control group and the TCM oral administration groups. The co-occurrence pattern of bacteria in the TCM oral administration groups exhibited less complexity but greater stability compared to that in the control groups. These observations suggest that the bacterial community in TCM oral administration groups is more resilient to disturbances than in the control groups. [ABSTRACT FROM AUTHOR]

This study introduces a novel methodology to explore the network dynamics of Physarum polycephalum, an organism celebrated for its remarkable adaptive capabilities. We used two innovative techniques to analyse its growth behaviour and network modifications under stress conditions, including starvation and differential epinephrine exposures. The first method provided a quantitative assessment of growth and exploration over time. The second method provided a detailed examination of vein diameter and contraction patterns, illuminating the physiological adjustments P. polycephalum undergoes in response to environmental challenges. By integrating these approaches, we were able to estimate the total network volume of the organism, with a focus on the normalized estimated volume, unveiling insightful aspects of its structural adaptations. While starvation reduced the volume, indicating a significant structural compromise, low and high epinephrine concentrations maintained a volume-to-area ratio comparable with the control. Determining the fractal dimension of the networks over time revealed a fine-tuning of the network complexity in response to environmental conditions, with significant reductions under stress indicating a constrained network adaptation strategy. These methods, novel in their application to P. polycephalum, provide a framework for future studies and a basis for exploring complex network behaviours with potential applications in bioengineering and adaptive network design.

The relationship between biodiversity and ecosystem functioning has mainly focused on plant communities, with comparably little known about soil microbial‐driven ecosystem functions. Climate change severely threatens soil microbial roles, but how soil microbial communities determine soil multifunctionality under climate change is poorly understood.Here, we evaluated the effects of diverse bacterial and fungal properties, including microbial gene abundance, diversity and network complexity, on soil multifunctionality (nine soil functions) across a 3000 km transect along a natural precipitation gradient in Tibetan alpine grasslands. Variation partitioning analyses were performed to disentangle the relative importance of bacterial and fungal properties to the variation of soil multifunctionality. Moreover, structural equation modelling was adopted to explore the influencing pathways of precipitation‐induced changes in plant and edaphic factors to soil microbial properties and, consequently, soil multifunctionality.Soil multifunctionality was positively associated with bacterial and fungal gene abundance, diversity and network complexity. Microbial gene abundance was the more important driver influencing soil multifunctionality than microbial diversity and network complexity. In addition, microbial gene abundance was mainly determined by precipitation‐induced changes in soil pH. Meanwhile, the effects of bacterial properties on soil multifunctionality were much larger than those of fungi. Soil multifunctionality was closely associated with different bacterial (cellulolysis, ligninolysis, nitrogen reduction, denitrification and nitrate fixation etc.) and fungal (soil saprotrophs, arbuscular mycorrhizal and plant pathogens etc.) functional guilds, which exert vital regulations on an array of soil biogeochemical cycling processes.Our results provide the large‐scale evidence of the relative contribution of soil microbial gene abundance, diversity and network complexity to the variation of soil multifunctionality in alpine grasslands with changing precipitation, which is pivotal for understanding microbial roles in modulating and predicting soil multifunctionality under future precipitation changes. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

The biodiversity and activity of microorganisms are crucial for litter decomposition, but how litter traits at different stages of decomposition drive changes in microbial communities has yet to be thoroughly explored. In the typical alpine hilly area of the Qinghai–Tibet Plateau, three types of litter at different decomposition stages were selected under a natural Picea crassifolia (Picea crassifolia Kom.) forest: undecomposed (A-1), partially decomposed (A-2), and fully decomposed (A-3). By measuring physicochemical indicators, microbial diversity, and the composition of the litter at different decomposition stages, this study investigates the community changes and responses of bacteria to litter characteristic changes at different decomposition levels. The results show that with the increase in decomposition level, bacterial diversity increases, community structure changes, and network complexity gradually increases, while the changes in fungal communities are insignificant. Structural equation modeling indicates that the first principal component (PC1) of litter properties is significantly negatively correlated with bacterial diversity and positively correlated with bacterial community composition. There is no significant correlation between fungal diversity and community composition, indicating a closer relationship between bacteria and litter characteristics than fungi. In summary, with an increase in litter decomposition level, the diversity and network complexity of bacterial and fungal communities will significantly increase, which is related to the changes in various litter characteristics. This study provides a scientific basis for the regulatory mechanism of litter decomposition and turnover in the alpine hilly area of the Qinghai–Tibet Plateau, specifically in Picea crassifolia forests. [ABSTRACT FROM AUTHOR]

Supply chain social capitals argued to be the driver for attaining sustainability along the supply chain. However, the role of network complexity and supply chain resilience to transform supply chain social capitals into sustainability remains poorly understood. We draw from social capital theory to argue that supply chain resilience is the mechanism to curb negative effects of network complexity to transform supply chain social capital into supply chain sustainability. Hypotheses were tested employing structural equation modeling technique on a sample (n = 274) of Bangladeshi apparel suppliers, and supplemented by the fuzzy set qualitative comparative analysis to identify all plausible underlying causal configurations. Our results suggest that supply chain social capitals positively influence supply chain sustainability both directly and indirectly via supply chain resilience. Contrary to our hypothesis, we found that network complexity in the presence of supply chain resilience positively influences social capitals to bolster supply chain sustainability. Findings of this research imply that supply chain resilience is a crucial conduit that facilitates leveraging supply chain social capitals as well as withstanding challenges that emerge from network complexity to embolden supply chain sustainability. Findings of this research provide novel insights to existing literature by exploring the complex dynamisms and reaffirming the interrelationships among the four vital constructs of supply chain literature. Our finding can help supply chain managers to improve resilience and sustainability. [ABSTRACT FROM AUTHOR]

Machine learning technologies have recently emerged as transformative tools for enhancing project management accuracy and efficiency. This study introduces a data-driven model that leverages the hybrid eXtreme Gradient Boosting-Simulated Annealing (XGBoost-SA) algorithm to predict the time and cost of construction projects. By accounting for the complexity of activity networks and uncertainties within project environments, the model aims to address key challenges in project forecasting. Unlike traditional methods such as Earned Value Management (EVM) and Earned Schedule Method (ESM), which rely on static metrics, the XGBoost-SA model adapts dynamically to project data, achieving 92% prediction accuracy. This advanced model offers a more precise forecasting approach by incorporating and optimizing features from historical data. Results reveal that XGBoost-SA reduces cost prediction error by nearly 50% and time prediction error by approximately 80% compared to EVM and ESM, underscoring its effectiveness in complex scenarios. Furthermore, the model’s ability to manage limited and evolving data offers a practical solution for real-time adjustments in project planning. With these capabilities, XGBoost-SA provides project managers with a powerful tool for informed decision-making, efficient resource allocation, and proactive risk management, making it highly applicable to complex construction projects where precision and adaptability are essential. The main limitation of the developed model in this study is the reliance on data from similar projects, which necessitates additional data for application to other industries.

ABSTRACTMicroorganisms regulate numerous ecosystem functions and show considerable differences along a latitudinal gradient. Although studies have revealed the latitudinal patterns of microbial community structure and single ecosystem function, the latitudinal patterns of ecosystem multifunctionality (EMF) and how microbial communities affect EMF along a latitudinal gradient remain unclear. Here, we collected channel sediments, riparian rhizosphere soils, and riparian bulk soils from 30 rivers across China and calculated EMF using 18 variables related to nitrogen cycling, nutrient pool, plant productivity, and water quality. We also determined microbial diversity (taxonomic and functional) and microbial network complexity using metagenomic sequencing. The results showed that EMF significantly decreased with increasing latitude in riparian rhizosphere and bulk soils but not in channel sediments. Microbial taxonomic and functional richness (observed species) in channel sediments were significantly higher in the low-latitude group than in the high-latitude group. However, microbial co-occurrence networks were more complex in the high-latitude group compared with the low-latitude group. Abiotic factors, primarily geographic and climatic factors, contributed more to EMF than microbial diversity and network complexity parameters in which only betweenness centralization had a significant relationship with EMF. Together, this study provides insight into the latitudinal pattern of EMF in rivers and highlights the importance of large-scale factors in explaining such latitudinal patterns.IMPORTANCEEcosystem multifunctionality (EMF) is the capacity of an ecosystem to provide multiple functions simultaneously. Microorganisms, as dominant drivers of belowground processes, have a profound effect on ecosystem functions. Although studies have revealed the latitudinal patterns of microbial community structure and single ecosystem function, the latitudinal patterns of EMF and how microbial communities affect EMF along a latitudinal gradient remain unclear. We collected channel sediments, riparian rhizosphere soils, and riparian bulk soils from 30 rivers along a latitudinal gradient across China and calculated EMF using 18 variables related to nitrogen cycling, nutrient pool, plant productivity, and water quality. This study fills a critical knowledge gap regarding the latitudinal patterns and drivers of EMF in river ecosystems and gives new insights into how microbial diversity and network complexity affect EMF from a metagenomic perspective.

The Plateau pika, a native burrowing mammal in alpine ecosystems, induces significant alterations in both the diversity and functions of the above-ground plant community; however, their effects on the below-ground soil microbial community and its multifunctionality remain unclear. Here, we examined the impact of plateau pika disturbance on soil microbial diversity, composition, and network patterns and assessed the relationships of this microbial response with soil multifunctionality, including soil carbon, nitrogen, and phosphorus cycling, based on a field investigation of alpine grassland in the Qinghai-Tibetan Plateau. Results showed that as the distance from the pika holes decreased, moisture, soil organic carbon, dissolved organic carbon, and C:N ratios significantly decreased, while available potassium and phosphorus, nitrate contents, and soil multifunctionality increased. Pika disturbance increased soil bacterial and fungal diversity (e.g., Chao estimator, richness, and Shannon index), and altered the community composition, with a higher relative abundance of Actinobacterial and a lower relative abundance of Acidobacterial in disturbed habitats than in undisturbed habitats. The bacterial and fungal network complexity (including the node and edge numbers, linkage density, and average clustering coefficient) increased as the distance from the pika holes decreased. Network complexity explained most variations of soil multifunctionality, although there were significant linear positive relationships between microbial diversity, network complexity, and soil multifunctionality. These results indicated that plateau pika activity benefits the below-ground community diversity and soil multifunctionality of alpine grassland. This highlights the importance of microbial network complexity in linking the microbial community with soil multifunctionality.

Microbial communities regulating multiple ecosystem functions in agricultural ecosystems remain unclear, limiting our ability to predict how agricultural systems will respond to nutrient management. Here, we assessed the effects of 5‐year different fertilization treatments (CK, no‐fertilization; M, organic fertilization; MNPK, combined inorganic and organic fertilization; NPK, inorganic fertilization) on the bacterial and fungal composition, co‐occurrence networks complexity and the relationship of keystone taxa with soil multifunctionality. Our results showed that fertilization shifted the bacterial and fungal community composition. The increased nodes of degree and decreased average path length with the application of organic fertilizer suggested a more stable network. The improved soil multifunctionality was also observed in combined organic and inorganic fertilization treatment, which positively correlated with the fungal community composition rather than bacterial, indicating that fungi are important in driving soil functions. Notably, the keystone taxa fOTU3995 and fOTU2868 belong to Sordariomycetes and were correlated with soil organic carbon, total nitrogen, total phosphorus, and alkaline phosphatase. These indicated that the keystone taxa play an important role in increasing in soil nutrient, C cycling, and P cycling. Together, our findings highlight that combined organic and inorganic fertilization increases the network complexity and soil multifunctionality, further confirming the role of keystone taxa Sordariomycetes in driving soil multifunctionality. This suggested that combined organic and inorganic have the potential to preserve agroecosystem sustainability and strengthen the role of microorganisms in ecosystem functions. [ABSTRACT FROM AUTHOR]

Banks generally enhance their competitiveness through credit diversification. However, credit diversification may trigger serious systemic risk through the effect of fire sales. Using data from the Chinese banking market, we quantify the fire sales of credits and provide empirical evidence for the impact of credit diversification on systemic risk. The results reveal that an increased level of credit diversification promotes systemic risk and is more pronounced among small banks. Both the credit loss and network complexity of individual banks contribute to the impact of credit diversification on systemic risk. Declining economic prospects will also promote credit diversification to cause more systemic risk. However, tight macroprudential regulation helps to mitigate the promotion of credit diversification. These findings provide regulatory insights for systemic risk prevention. [ABSTRACT FROM AUTHOR]

Fish artificial breeding and release is an important method to restore wild populations of endemic fish species around the world. Schizothorax wangchiachii (SW) is an endemic fish in the upper Yangtze River and is one of the most important species for the artificial breeding and release program implemented in the Yalong River drainage system in China. It is unclear how artificially bred SW adapts to the changeable wild environment post‐release, after being in a controlled and very different artificial environment. Thus, the gut samples were collected and analyzed for food composition and microbial 16S rRNA in artificially bred SW juveniles at day 0 (before release), 5, 10, 15, 20, 25, and 30 after release to the lower reaches of the Yalong River. The results indicated that SW began to ingest periphytic algae from the natural habitat before day 5, and this feeding habit is gradually stabilized at day 15. Prior to release, Fusobacteria are the dominant bacteria in the gut microbiota of SW, while Proteobacteria and Cyanobacteria generally are the dominant bacteria after release. The results of microbial assembly mechanisms illustrated that deterministic processes played a more prominent role than stochastic processes in the gut microbial community of artificially bred SW juveniles after releasing into the wild. Overall, the present study integrates the macroscopic and microscopic methods to provide an insight into the food and gut microbial reorganization in the released SW. This study will be an important research direction to explore the ecological adaptability of artificially bred fish after releasing into the wild. [ABSTRACT FROM AUTHOR]

Climatic change conditions (elevated CO2 and warming) have been known to threaten agricultural sustainability and grain yield. Soil fungi play an important role in maintaining agroecosystem functions. However, little is known about the responses of fungal community in paddy field to elevated CO2 and warming. Herein, using internal transcribed spacer (ITS) gene amplicon sequencing and co-occurrence network methods, the responses of soil fungal community to factorial combinations of elevated CO2 (550 ppm), and canopy warming (+2 °C) were explored in an open-air field experiment for 10 years. Elevated CO2 significantly increased the operational taxonomic unit (OTU) richness and Shannon diversity of fungal communities in both rice rhizosphere and bulk soils, whereas the relative abundances of Ascomycota and Basidiomycota were significantly decreased and increased under elevated CO2, respectively. Co-occurrence network analysis showed that elevated CO2, warming, and their combination increased the network complexity and negative correlation of the fungal community in rhizosphere and bulk soils, suggesting that these factors enhanced the competition of microbial species. Warming resulted in a more complex network structure by altering topological roles and increasing the numbers of key fungal nodes. Principal coordinate analysis indicated that rice growth stages rather than elevated CO2 and warming altered soil fungal communities. Specifically, the changes in diversity and network complexity were greater at the heading and ripening stages than at the tillering stage. Furthermore, elevated CO2 and warming significantly increased the relative abundances of pathotrophic fungi and reduced those of symbiotrophic fungi in both rhizosphere and bulk soils. Overall, the results indicate that long-term CO2 exposure and warming enhance the complexity and stability of soil fungal community, potentially threatening crop health and soil functions through adverse effects on fungal community functions. [ABSTRACT FROM AUTHOR]

The co-occurrence of bacteria and microeukaryote species is a ubiquitous ecological phenomenon, but there is limited cross-domain research in aquatic environments. We conducted a network statistical analysis and visualization of microbial cross-domain co-occurrence patterns based on DNA sampling of a typical subtropical bay during four seasons, using high-throughput sequencing of both 18S rRNA and 16S rRNA genes. First, we found obvious relationships between network stability and network complexity indices. For example, increased cooperation and modularity were found to weaken the stability of cross-domain networks. Secondly, we found that bacterial operational taxonomic units (OTUs) were the most important contributors to network complexity and stability as they occupied more nodes, constituted more keystone OTUs, built more connections, more importantly, ignoring bacteria led to greater variation in network robustness. Gammaproteobacteria, Alphaproteobacteria, Bacteroidetes, and Actinobacteria were the most ecologically important groups. Finally, we found that the environmental drivers most associated with cross-domain networks varied across seasons (in detail, the network in January was primarily constrained by temperature and salinity, the network in April was primarily constrained by depth and temperature, the network in July was mainly affected by depth, temperature, and salinity, depth was the most important factor affecting the network in October) and that environmental influence was stronger on bacteria than on microeukaryotes. [ABSTRACT FROM AUTHOR]

Schizophrenia (SZ) and bipolar disorder (BD) are two of the most frequent mental disorders. These disorders exhibit similar psychotic symptoms, making diagnosis challenging and leading to misdiagnosis. Yet, the network complexity changes driving spontaneous brain activity in SZ and BD patients are still unknown. Functional entropy (FE) is a novel way of measuring the dispersion (or spread) of functional connectivities inside the brain. The FE was utilized in this study to examine the network complexity of the resting-state fMRI data of SZ and BD patients at three levels, including global, modules, and nodes. At three levels, the FE of SZ and BD patients was considerably lower than that of normal control (NC). At the intra-module level, the FE of SZ was substantially higher than that of BD in the cingulo-opercular network. Moreover, a strong negative association between FE and clinical measures was discovered in patient groups. Finally, we classified using the FE features and attained an accuracy of 66.7% (BD vs. SZ vs. NC) and an accuracy of 75.0% (SZ vs. BD). These findings proposed that network connectivity's complexity analyses using FE can provide important insights for the diagnosis of mental illness. [ABSTRACT FROM AUTHOR]

Soil microbes play vital roles in mediating the functions and services of terrestrial ecosystems in the context of ongoing climate change and human disturbance. There are complex interactions between soil microbial taxa. However, research on the drivers of soil microbial network complexity and stability based on microbial taxa interactions is still in its infancy. We examined network structure and the complexity and stability of soil microbial communities across a large-scale environmental gradient in semi-arid grasslands of northern China by combining network theory and high-throughput sequencing. We found that aridity was the strongest driver of soil microbial network structure. Increasing aridity directly reduced the complexity and stability of soil microbial networks by decreasing the ratio of microbial taxa that participated in network construction and the ratio of potential positive and negative interactions of networks. Soil heterogeneity enhanced microbial network complexity and stability by potentially promoting diverse host plants and mediating uneven distribution of soil resources. These findings suggest that aridity and decreasing soil heterogeneity may have detrimental influences on soil microbial functions and the associated plant performance. This study provides new insights into the controls of climatic and/or edaphic variables in regulating soil microbial networks and highlights the importance of environmental heterogeneity in community assembly mechanisms of soil microbes.

Long-term intensive fertilization profoundly alters soil properties including microbial diversity and co-occurrence associations, but little is known about the relative and combined importance of biotic and abiotic factors for the stability of soil microbial mediated functions (MMF) to biodiversity loss. Here, we experimentally manipulated microbial α-diversity by inoculating diluted soil suspensions into sterilized soil to tease apart the biotic and abiotic effects on the microbiomes and temporal shifts in MMF in soils subjected to different fertilization treatments during a 3-month re-colonization. We showed that bacterial and fungal biomass remained similar between different diversity levels at each sampling date (0, 7, 15, 30, and 90 days). Organic fertilization accelerated the resilience of copiotrophic bacterial assemblages to biodiversity loss compared with non-fertilization and mineral fertilization and increased the strength of positive relationships between soil MMF and diversity and network complexity of bacterial rather than fungal community. A suite of biotic and abiotic factors were found to account for up to 73% of the variation in MMF, with the combined effects of diversity and microbiome complexity accounting for 43% of the variation in MMF. Moreover, the overall diversity of keystone taxa, primarily driven by soil organic carbon, was particularly important for promoting soil MMF (P < 0.001), with the abundances of oligotrophic- (Blastocatellaceae) and copiotrophic-selected (Comamonadaceae) keystone taxa positively and negatively relating to soil MMF, respectively. Collectively, our study indicates the importance of fertilization-induced shifts in network complexity and microbial life strategies for maintaining the stability of MMF following biodiversity decline and calls for organically based microbiome complexity conservation strategies to mitigate negative impacts of biodiversity loss on multiple agroecosystem functions. [ABSTRACT FROM AUTHOR]

Mulching regimes have a promoted impact on the soil hydrothermal environments and crop productions. However, the time‐dependent variations in root‐associated microbial communities under distinct mulching regimes in the Loess Plateau have not been thoroughly explored. Here, we investigated the regulatory impacts of plastic film mulching (FM) and ridge‐furrow mulching system (RF) on the microbial community compositions, diversities, and ecological networks in the distinct compartments (e.g., root, rhizosphere, and bulk soil) at jointing and flowering periods of proso millet, and we compared these two regimes to no mulching (NM). Mulching regimes improved the bulk and rhizosphere soil quality at jointing period, whereas reduced them at flowering period. Bacterial structure and composition of the three compartments were significantly influenced by growth periods and mulching regimes. Furthermore, mulching regimes effectively increased the alpha diversities of rhizosphere and root communities at flowering period. Soil temperature and total N were the most essential variables affecting the bulk soil and rhizosphere community structure, respectively. With the growth and development of proso millet, the network complexity and stability increased, and the abundance of different modules in the three compartments were regulated by mulching regimes. Proteobacteria and Acidobacteriota were the keystone species at jointing period, whereas, at flowering period, only Proteobacteria were the keystone species. In addition, FM regime significantly increased the species interaction and abundance of keystone taxa than those of non‐mulching at both periods. These results highlighted that mulching regimes were observed to be a recommended selection for improving soil quality, regulating bacterial diversity and structure, and stabilizing the species interaction, thereby providing guidance for choosing the ideal cultivation techniques from the perspective of microbial ecology in the Loess Plateau. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms of biological invasion is critical to biodiversity protection. Previous studies have produced inconsistent relationships between native species richness and invasibility, referred to as the invasion paradox. Although facilitative interactions among species have been proposed to explain the non-negative diversity–invasibility relationship, little is known about the facilitation of plant-associated microbes in invasions. We established a two-year field biodiversity experiment with a native plant species richness gradient (1, 2, 4, or 8 species) and analyzed the effects of community structure and network complexity of leaf bacteria on invasion success. Our results indicated a positive relationship between invasibility and network complexity of leaf bacteria of the invader. Consistent with previous studies, we also found that native plant species richness increased the leaf bacterial diversity and network complexity. Moreover, the results of the leaf bacteria community assembly of the invader suggested that the complex bacteria community resulted from higher native diversity rather than higher invader biomass. We concluded that increased leaf bacterial network complexity along the native plant diversity gradient likely facilitated plant invasion. Our findings provided evidence of a potential mechanism by which microbes may affect the plant community invasibility, hopefully helping to explain the non-negative relationship between native diversity and invasibility. [ABSTRACT FROM AUTHOR]

The use of information–theoretical methodologies to assess graph-based systems has received a significant amount of attention. Evaluating a graph's structural information content is a classic issue in fields such as cybernetics, pattern recognition, mathematical chemistry, and computational physics. Therefore, conventional methods for determining a graph's structural information content rely heavily on determining a specific partitioning of the vertex set to obtain a probability distribution. A network's entropy based on such a probability distribution is obtained from vertex partitioning. These entropies produce the numeric information about complexity and information processing which, as a consequence, increases the understanding of the network. In this paper, we study the Benes network and its novel-derived classes via different entropy measures, which are based on information functionals. We construct different partitions of vertices of the Benes network and its novel-derived classes to compute information functional dependent entropies. Further, we present the numerical applications of our findings in understanding network complexity. We also classify information functionals which describe the networks more appropriately and may be applied to other networks. [ABSTRACT FROM AUTHOR]

Land-use changes have widespread impacts on terrestrial ecosystems. However, few studies have focused on the responses of soil environmental factors, soil microbial properties, and links between primary productivity, soil microbes, and soil multifunctionality during land-use change in the ecologically sensitive alpine areas on the Qinghai-Tibetan Plateau. In this study, we evaluated the effects of land-use changes from alpine grassland to farmland to shrubland on soil factors and soil microbial characteristics and investigated the associations between aboveground biomass, soil microbial diversity, network complexity, and soil multifunctionality in the Qinghai Lake Basin. The results showed that soil environmental factors and microbial community composition exhibited patterns of gradual recovery toward natural grassland along with the conversion of farmland to shrubland, and soil phosphorus content played a regulatory role in soil microbial restoration along with the conversion of land-use. Furthermore, we found that the recovery of soil microbial co-occurrence network complexity would require a longer time than that of microbial community composition and functional taxa after the conversion of farmland to shrubland. Importantly, we showed that network complexity is an important microbial property mediating the association between primary productivity and soil multifunctionality during land-use changes. These findings address the gap in our understanding of farmland during land-use change surrounding saltwater lake habitats, with great significance for broadening our understanding of land-use change and promoting the development of restoration decisions for alpine ecosystems worldwide. • Plant shrubs is a useful method of restoration in the Qinghai Lake Basin. • Soil phosphorus mainly regulates soil fungal and bacterial community compositions. • Recovery of soil microbial network complexity will require a longer time. • Soil microbial network complexity plays a more important role than its diversity. [ABSTRACT FROM AUTHOR]

Deep Convolutional Neural Networks (CNNs) have been widely used in various domains due to their impressive capabilities. These models are typically composed of a large number of 2D convolutional (Conv2D) layers with numerous trainable parameters. To manage the complexity of such networks, compression techniques can be applied, which typically rely on the analysis of trained deep learning models. However, in certain situations, training a new CNN from scratch may be infeasible due to resource limitations. In this paper, we propose an alternative parameterization to Conv2D filters with significantly fewer parameters without relying on compressing a pre-trained CNN. Our analysis reveals that the effective rank of the vectorized Conv2D filters decreases with respect to the increasing depth in the network. This leads to the development of the Depthwise Convolutional Eigen-Filter (DeCEF) layer, which is a low rank version of the Conv2D layer with significantly fewer trainable parameters and floating point operations (FLOPs). The way we define the effective rank is different from previous work, and it is easy to implement and interpret. Applying this technique is straightforward – one can simply replace any standard convolutional layer with a DeCEF layer in a CNN. To evaluate the effectiveness of DeCEF layers, experiments are conducted on the benchmark datasets CIFAR-10 and ImageNet for various network architectures. The results have shown a similar or higher accuracy using about 2/3 of the original parameters and reducing the number of FLOPs to 2/3 of the base network. Additionally, analyzing the patterns in the effective rank provides insights into the inner workings of CNNs and highlights opportunities for future research. [ABSTRACT FROM AUTHOR]

Soil nematodes play a crucial role in maintaining agroecosystem functions and are sensitive to fluctuations in precipitation. However, the impact of soil nematode biodiversity on regulating agroecosystem multifunctionality under altered precipitation remains poorly understood. This study conducted a field experiment in a dryland agroecosystem in China's loess tableland region, manipulating precipitation levels (ambient, 1/3 decreased, and 1/3 increased) with and without nematode inhibitor application (10 % fosthiazate granules). The effects of altered precipitation on agroecosystem multifunctionality and the role of soil nematode biodiversity were explored. Seventeen variables related to crop productivity, nutrient supply, organic carbon decomposition, and pathogen control were investigated during wheat harvest period to assess agroecosystem multifunctionality. Soil nematode communities were analyzed using high-throughput sequencing targeting V4 region of 18 S rDNA, examing multiple dimensions of nematode biodiversity, such as taxonomic, functional, and phylogenetic diversity, and network complexity. Results indicated that increased precipitation positively influenced agroecosystem multifunctionality (rising from −0.02–0.29), driven by improved pathogen control, organic carbon decomposition and crop productivity functions, despite a decline in nutrient supply function. Concurrently, increased precipitation led to higher taxonomic, functional, and phylogenetic diversity, and network complexity of soil nematodes. This was evidenced by simultaneous rises in metrics such as Chao1, PD_whole_tree, functional divergence, multidimensional diversity, as well as node and edge numbers, betweenness centrality, and clustering coefficient within nematode networks. A positive correlation was observed between nematode multidimenstional diversity and agroecosystem multifunctionality (R2=0.072, P < 0.05). Further analysis revealed that higher precipitation levels enriched nematode diversity by improving soil water content, consequently amplifying nematode network complexity and ultimately enhancing agroecosystem multifunctionality. However, nematode inhibitor application substantially reduced nematode abundance across precipitation levels (reducing by 26.25 %-69.63 %), and decreased multidimensional nematode diversity under increased precipitation (decreasing from 0.34 to −0.15), thereby counteracting the multifunctionality benefits of precipitation. These findings underscore the significance of soil nematode biodiversity in enhancing agroecosystem multifunctionality under altered precipitation, offering guidance for sustainable agroecosystem management in the Loess Plateau and comparable environments impacted by climate change. [Display omitted] • Agroecosystem multifunctionality increases with increasing precipitation. • Increased precipitation positively impacts soil nematode biodiversity across multiple dimensions. • Greater nematode diversity and network complexity enhance agroecosystem multifunctionality. • Nematode biodiversity is crucial in driving agroecosystem multifunctionality under altered precipitation. [ABSTRACT FROM AUTHOR]

Cover crops litter decay is a vital component of nutrient cycling in agroecosystems; however, how litter quality affect decay process via microbial facets at different decay stage remains unclear. Here, we performed a 112-d decay experiment using the litter of two winter cover crop species (a legume and a grass) to clarify the relationship between the temporal dynamics of litter-inhabiting microbes and litter decay in agroecosystems. Legume litter decayed faster (k = 0.064 ± 0.002 days−1) than grass litter (k = 0.053 ± 0.003 days−1) during the early stage (0–28 D) of decay. Wood saprotrophs and bacteria, capable of performing lignin degradation, were generally more abundant in legume litter (0.003 % and 47.77 %, respectively) than in grass litter (0.002 % and 39.24 %, respectively) during the early stage of decay. Litter quality affected the decay process through its effects on microbial functional profiles and interactions; legume litter decay increased as the abundance of specific functional guilds increased and network complexity decreased. Overall, our findings indicated that litter quality affected litter decay process and relevant litter-inhabiting microbial facets is restricted to the early stage of decay. [Display omitted] • Legume litter decayed faster during the early stage of decay. • Legume litter had greater metabolic functional involved in litter decay at the early stage of decay. • Legume litter had a less complex network during the early stage of decay. • Microbial functional characteristics and interactions may explain the decay rate. [ABSTRACT FROM AUTHOR]

Island biotas are in imminent threat from anthropogenic impacts. Of these impacts, the negative effects of exotic species on the taxonomic and functional diversity of the local fauna are of major concern. Exotics may also have a detrimental effect on interspecific interactions which, in turn, can destabilize ecological networks. Species co-occurrence networks can detect species-to-species associations and are used to predict ecological interaction networks and utilized as tools to assess environmental impacts on community structure. Here, we aim to investigate whether or not topological differences of the arthropod co-occurrence networks among native forest fragments from seven Azorean islands can reveal the influence of the abiotic environment and exotic species on these networks. Co-occurrence networks were sensitive to environmental and community dissimilarities, showing a clear separation between islands and pinpointed differences between indigenous and exotic networks. Most exotics were little connected and exotic networks had a large proportion of unconnected species. The resulting decreased connectance and the increased modularity with the increase of the proportions of exotics in the networks suggest that most exotics have too low prevalence to show associations with other species, and only a few dominants drive co-occurrences. The proportion of negative links, as indicators of competition, did not increase with the increase of exotics in the habitats, suggesting that exotics provided new functional roles when they colonized native forest remnants. However, when the theoretical networks consisting of only indigenous species were investigated, connectance decreased and closeness increased with the increase of exotics, suggesting processes of network degradation. Since our study provides ample evidence for the usefulness of co-occurrence network analysis in studying island ecosystems, we recommend the use of this tool for ecosystem assessments, early warning systems and decision-making in island biodiversity conservation.

Plants can alter microbial communities through root exudates, and change the characteristics of the soil. However, the relationship between soil microbial communities and environmental factors is not well understood. Here, we studied bacterial and fungal communities and their relationships with environmental factors. We integrated data of environmental factors, microbial composition, diversity, functional prediction, and co‐occurrence network from uncultivated, maize, cabbage, and cocozelle soils in a karst area of Southwest China. Soil bacterial and fungal community composition differed with plant types. Maize soil had more taxa and greater alpha diversity of bacteria and fungi than other soils. In maize soil, the relative abundance of Actinobacteria and Ascomycota was significantly lower than that in uncultivated soil, while its contents of soil organic matter (OM), alkali‐hydrolyzable nitrogen, and total nitrogen (TN) showed the opposite trend. These indicators were not significantly different between cabbage and cocozelle soils. The results of the Mantel test and the RDA analysis indicated that TN and OM were important drivers of bacterial and fungal communities. Functional prediction and network analysis showed that maize soil had a high nitrogen fixation capacity and a complex and stable network. To summarize, maize soil not had a low relative abundance of Ascomycota and high content of TN and OM, nitrogen fixation ability, and a rich microbial community. Therefore, cultivating maize is suitable for improving soil microbial community. These findings might help in formulating a reasonable cultivation management program to prevent land degradation in the karst areas. [ABSTRACT FROM AUTHOR]

Introduction: Long-term grazing profoundly affects grassland ecosystems, whereas how the soil microbiome and multiple soil ecosystem functions alter in response to two-decades of grazing, especially how soil microbiome (diversity, composition, network complexity, and stability) forms soil multifunctionality is rarely addressed. Methods: We used a long-term buffalo grazing grassland to measure the responses of soil physicochemical attributes, stoichiometry, enzyme activities, soil microbial niche width, structure, functions, and networks to grazing in a subtropical grassland of Guizhou Plateau, China. Results: The evidence from this work suggested that grazing elevated the soil hardness, available calcium content, and available magnesium content by 6.5, 1.9, and 1.9 times (p = 0.00015-0.0160) and acid phosphatase activity, bulk density, pH by 59, 8, and 0.5 unit (p = 0.0014-0.0370), but decreased the soil water content, available phosphorus content, and multifunctionality by 47, 73, and 9-21% (p = 0.0250-0.0460), respectively. Grazing intensified the soil microbial carbon limitation (+78%, p = 0.0260) as indicated by the increased investment in the soil b-glucosidase activity (+90%, p = 0.0120). Grazing enhanced the complexity and stability of the bacterial and fungal networks but reduced the bacterial Simpson diversity (p < 0.05). The bacterial diversity, network complexity, and stability had positive effects, while bacterial and fungal compositions had negative effects on multifunctionality. Discussions: This work is an original attempt to show that grazing lowered multifunctionality via the reduced bacterial diversity and shifted soil bacterial and fungal compositions rather than the enhanced bacterial and fungal network complexities and stability by grazing. Protecting the bacterial diversity from decreasing, optimizing the composition of bacteria and fungi, and enhancing the complexity and stability of bacterial network may be conducive to improving the soil multifunction of grazing grassland, on a subtropical grassland. [ABSTRACT FROM AUTHOR]