Unraveling emergent network indeterminacy in complex ecosystems: A random matrix approach.

Indeterminacy of ecological networks-the unpredictability of ecosystem responses to persistent perturbations-is an emergent property of indirect effects a species has on another through interaction chains. Thus, numerous indirect pathways in large, complex ecological communities could make forecasting the long-term outcomes of environmental changes challenging. However, a comprehensive understanding of ecological structures causing indeterminacy has not yet been reached. Here, using random matrix theory (RMT), we provide mathematical criteria determining whether network indeterminacy emerges across various ecological communities. Our analytical and simulation results show that indeterminacy intricately depends on the characteristics of species interaction. Specifically, contrary to conventional wisdom, network indeterminacy is unlikely to emerge in large competitive and mutualistic communities, while it is a common feature in top-down regulated food webs. Furthermore, we found that predictable and unpredictable perturbations can coexist in the same community and that indeterminate responses to environmental changes arise more frequently in networks where predator-prey relationships predominate than competitive and mutualistic ones. These findings highlight the importance of elucidating direct species relationships and analyzing them with an RMT perspective on two fronts: It aids in 1) determining whether the network's responses to environmental changes are ultimately indeterminate and 2) identifying the types of perturbations causing less predictable outcomes in a complex ecosystem. In addition, our framework should apply to the inverse problem of network identification, i.e., determining whether observed responses to sustained perturbations can reconstruct their proximate causalities, potentially impacting other fields such as microbial and medical sciences.

Ecologic, Geoclimatic, and Genomic Factors Modulating Plague Epidemics in Primary Natural Focus, Brazil.

Plague is a deadly zoonosis that still poses a threat in many regions of the world. We combined epidemiologic, host, and vector surveillance data collected during 1961-1980 from the Araripe Plateau focus in northeastern Brazil with ecologic, geoclimatic, and Yersinia pestis genomic information to elucidate how these factors interplay in plague activity. We identified well-delimited plague hotspots showing elevated plague risk in low-altitude areas near the foothills of the plateau's concave sectors. Those locations exhibited distinct precipitation and vegetation coverage patterns compared with the surrounding areas. We noted a seasonal effect on plague activity, and human cases linearly correlated with precipitation and rodent and flea Y. pestis positivity rates. Genomic characterization of Y. pestis strains revealed a foundational strain capable of evolving into distinct genetic variants, each linked to temporally and spatially constrained plague outbreaks. These data could identify risk areas and improve surveillance in other plague foci within the Caatinga biome.

Generalized synchronization in a tritrophic food web metacommunity.

Complete synchronization among the metacommunity is known to elevate the risk of their extinction due to stochasticity and other environmental perturbations. Owing to the inherent heterogeneous nature of the metacommunity, we demonstrate the emergence of generalized synchronization among the patches of dispersally connected tritrophic food web using the framework of an auxiliary system approach and the mutual false nearest neighbor. We find that the critical value of the dispersal rate increases significantly with the size of the metacommunity for both unidirectional and bidirectional dispersals, which in turn corroborates that larger metacommunities are more stable than smaller ones. Further, we find that the critical value of the dispersal for the onset of generalized synchronization is smaller(larger) for bidirectional dispersal than that for unidirectional dispersal for smaller(larger) metacommunities. Most importantly, complete synchronization error remains finite even after the onset of generalized synchronization in a wider range of dispersal rate elucidating that the latter can serve as an early warning signal for the extinction of the metacommunity.

Ocean acidification alters microeukaryotic and bacterial food web interactions in a eutrophic subtropical mesocosm.

Ocean acidification (OA) is known to influence biological and ecological processes, mainly focusing on its impacts on single species, but little has been documented on how OA may alter plankton community interactions. Here, we conducted a mesocosm experiment with ambient (∼410 ppmv) and high (1000 ppmv) CO2 concentrations in a subtropical eutrophic region of the East China Sea and examined the community dynamics of microeukaryotes, bacterioplankton and microeukaryote-attached bacteria in the enclosed coastal seawater. The OA treatment with elevated CO2 affected taxa as the phytoplankton bloom stages progressed, with a 72.89% decrease in relative abundance of the protist Cercozoa on day 10 and a 322% increase in relative abundance of Stramenopile dominated by diatoms, accompanied by a 29.54% decrease in relative abundance of attached Alphaproteobacteria on day 28. Our study revealed that protozoans with different prey preferences had differing sensitivity to high CO2, and attached bacteria were more significantly affected by high CO2 compared to bacterioplankton. Our findings indicate that high CO2 changed the co-occurrence network complexity and stability of microeukaryotes more than those of bacteria. Furthermore, high CO2 was found to alter the proportions of potential interactions between phytoplankton and their predators, as well as microeukaryotes and their attached bacteria in the networks. The changes in the relative abundances and interactions of microeukaryotes between their predators in response to high CO2 revealed in our study suggest that high CO2 may have profound impacts on marine food webs.

The persistence of bipartite ecological communities with Lotka-Volterra dynamics.

The assembly and persistence of ecological communities can be understood as the result of the interaction and migration of species. Here we study a single community subject to migration from a species pool in which inter-specific interactions are organised according to a bipartite network. Considering the dynamics of species abundances to be governed by generalised Lotka-Volterra equations, we extend work on unipartite networks to we derive exact results for the phase diagram of this model. Focusing on antagonistic interactions, we describe factors that influence the persistence of the two guilds, locate transitions to multiple-attractor and unbounded phases, as well as identifying a region of parameter space in which consumers are essentially absent in the local community.

The non-negligible contribution of foundation species to artificial reef construction revealed by Ecopath models.

The seabed desertification has increasingly highlighted the importance of benthic habitat restoration. Strategically engineered artificial reefs emerges as pivotal in achieving restoration objectives. However, the significant influence of foundation species on biotic components and ecosystem attributes within diverse artificial reefs has been underrecognized. This study collated twenty Ecopath models of artificial reefs and their corresponding natural control ecosystems along the coasts of the Yellow Sea and Bohai Sea, China, categorizing them into five distinct system types predicated on the biomass and productivity of foundational species. Our results suggest that dimensionless indices, rather than actual system values, were posited to facilitate inter-comparative analysis. The comparative analysis revealed differences in biomass distribution, energy utilization, and trophic structure across the five ecosystem types. All the artificial reef systems collectively enhanced the utilization of primary production. Foundation species components formed the cornerstone of system functionality, significantly impacting ecosystem stability through modulation of energy flow dynamics. Distinct impacts were observed from shellfish and macroalgae; the former augmenting the detrital food chain, while the latter bolstering the grazing food chain. Consequently, the model-based integrated analysis enabled a robust comparison among various types of artificial reef ecosystems and confirmed that promoting the colonization of foundation species was a non-negligible factor in the design and deployment of artificial reefs.

Construction of ecological network in Qujing city based on MSPA and MCR models.

With the rapid advancement of urbanization and industrialization, ecological patches within cities and towns are fragmented and ecological corridors are cut off, regional ecological security is threatened and sustainable development is hindered. Building an ecological network that conforms to regional realities can connect fragmented patches, protect biodiversity and regional characteristics, and provide scientific reference for regional ecological protection and ecological network planning. By taking Qilin District, the main urban area of Qujing City as an example, and using geospatial data as the main data source, based on morphological spatial pattern analysis (MSPA) and minimum cumulative resistance (MCR), this study identified ecological source areas, extracted ecological corridors, and build & optimize ecological networks. (1) All landscape types are identified based on MSPA, the proportion of core area was the highest among all landscape types, which was 80.69%, combined with the connectivity evaluation, 14 important ecological source areas were selected. (2) 91 potential ecological corridors were extracted through MCR and gravity models, there were 16 important ones. (3) The network connectivity analysis method is used to calculate the α, ß, and γ indexes of the ecological network before optimization, which were 2.36, 6.5, and 2.53, while after optimization, α, ß and γ indices were 3.8, 9.5 and 3.5, respectively. The combined application of MSPA-MCR model and ecological network connectivity analysis evaluation is conducive to improving the structure and functionality of ecological network.

Multiplex dependence analysis of China's interprovincial virtual water based on an ecological network.

The interprovincial circulation of goods and services has formed virtual water flows between regions, which can redistribute water resources. Based on previous virtual water trade research, this study further explored the multiple dependencies of virtual water, i.e., direct, indirect, and complete dependence. This study examined the direct, indirect, and complete dependence of virtual water between provinces in China by constructing multilayer dependence networks and identified the key regions and paths of virtual water trade network. The results showed direct dependence was the densest and had the largest overall dependence degree, but indirect dependence was the most stable and orderly. Second, the dominant provinces were Guangxi, Hunan, Sichuan, Xinjiang, and Anhui, referred to as "core‒five‒region," and the flow relevant to them accounted for approximately 30% of the virtual water. The seven provinces of Shanxi, Zhejiang, Shandong, Hubei, Guangdong, Shaanxi, and Gansu depend both directly and indirectly on the "core‒five‒region." Shanxi and Zhejiang have close direct and indirect dependence, with more than one of the "core‒five‒region." Guangdong was the province with the most direct and indirect input of virtual water from the "core‒five‒region." The study provides a scientific basis for multiregional identification for the collaborative management of water resources in China from the perspective of dependence.

Understanding the relations between Solanaceae crops and their pollinators: a global meta-network.

Crop-pollinator interactions are essential for world food security. Studying crop pollination from a network approach allows identification of target pollinators for conservation and management, and gaps in our knowledge. Solanaceae represents the third highest ranked family based on economic value, and its production is highly improved by animal pollination. This study aimed to integrate global data on solanaceous crop pollination and analyse the interaction patterns using a meta-network approach. Our questions were: (i) how are interactions structured and what are the structuring roles of species; and (ii) what are the main gaps in our knowledge? Data were obtained through a systematic review of the main scientific databases. The network structure was described using connectivity and modularity calculations, and the role of species using centrality metrics. The 251 pollinator species reported were in seven orders, mainly Hymenoptera (84.9%). The generalists Bombus and Apis species were the most common pollinators. The meta-network was modular, and all modules mostly included bees. Most species were peripherals, around 12% were connectors, and there were no module hubs. Apis mellifera was the only network hub (supergeneralist). The most important pollinators are the most managed pollinators worldwide; however, many native species play a role in structuring the meta-network. Main gaps include species of importance to pepper pollination, lack of species-specific identification, and the need for more robust experimental studies evaluating the pollination efficiency of native, manageable bees.

Microeukaryotic plankton community dynamics under ecological water replenishment: Insights from eDNA metabarcoding.

Ecological water replenishment (EWR) is an important strategy for river restoration globally, but timely evaluation of its ecological effects at a large spatiotemporal scale to further adjust the EWR schemes is of great challenge. Here, we examine the impact of EWR on microeukaryotic plankton communities in three distinct river ecosystems through environmental DNA (eDNA) metabarcoding. The three ecosystems include a long-term cut-off river, a short-term connected river after EWR, and long-term connected rivers. We analyzed community stability by investigating species composition, stochastic and deterministic dynamics interplay, and ecological network robustness. We found that EWR markedly reduced the diversity and complexity of microeukaryotic plankton, altered their community dynamics, and lessened the variation within the community. Moreover, EWR disrupted the deterministic patterns of community organization, favoring dispersal constraints, and aligning with trends observed in naturally connected rivers. The shift from an isolated to a temporarily connected river appeared to transition community structuring mechanisms from deterministic to stochastic dominance, whereas, in permanently connected rivers, both forces concurrently influenced community assembly. The ecological network in temporarily connected rivers post-EWR demonstrated significantly greater stability and intricacy compared to other river systems. This shift markedly bolstered the resilience of the ecological network. The eDNA metabarcoding insights offer a novel understanding of ecosystem resilience under EWR interventions, which could be critical in assessing the effects of river restoration projects throughout their life cycle.

[Ecological network optimization of Jiuquan City, Gansu, China based on complex network theory and circuit model]. / åŸºäºŽå¤æ‚ç½‘ç»œç†è®ºå’Œç”µè·¯æ¨¡åž‹çš„é ’æ³‰å¸‚ç”Ÿæ€ç½‘ç»œä¼˜åŒ–.

Building a scientific and reasonable ecological network is the key for optimizing the pattern of territorial development and protection, and is of great significance for ensuring regional ecological security and promoting the virtuous cycle of ecosystems. In previous studies, nodal attack method (destruction of ecological source area) was often used in the "robustness" evaluation of ecological networks. Actually, the ecological corridor is more fragile than the source area, and thus the nodal attack method is not reasonable. In this study, taking Jiuquan City as the research area, based on the circuit model to construct the ecological network, we carried out the topology optimization of ecological network by using three strategies (random edge increase, node degree and priority edge increase with low node intermedium number) in complex network theory. We compared and analyzed the "robustness" of ecological network before and after optimization by constructing edge attack strategy, and selected the best network optimization strategy. The results showed that 65 ecological source areas were identified in Jiuquan City, with a total area of 20275.15 km2, and that grassland accounted for 89.5% of the source area. We identified 179 ecological corridors with a total length of 6387.16 km, 158 ecological barrier points with a total area of 1385.5 km2. The unused land accounted for 92.2% of the total barrier points area. We identified 63 ecological pinch points, mainly concentrated in the source edge and corridor intersection. Among them, the spatial distribution of 11 barrier points and pinch points was consistent, which was the key area to be repaired in ecological network optimization. The three optimization strategies had significantly improved the stability of ecological network in Jiuquan City. The relative size of the maximum connected subgraph and the edge connected rate of the ecological network of the optimization strategy of adding edges according to degree were all the most stable under random attack mode and deliberate attack mode, which was the best optimization scheme for ecological network in Jiuquan City.

[Construction of ecological network with protected areas as the main region in Guangzhou City, China]. / 以自然保护地为主体的广州市域生态网络构建.

In the context of the national ecological security development strategy, constructing regional ecological networks centered on protected areas and ecological corridors has become an urgent issue in protected areas system development of China. We focused on strengthening ecological connections between protected areas in Guangzhou, identified the ecological resource patches, ecological corridors, and ecological nodes by using Invest model, connectivity analysis, circuit theory models, and graph-theoretical network structure evaluation, and constructed an ecological network for the Guangzhou with nature reserves as the core. The results showed that 52 ecological resource patches were identified in the study area, covering a total area of 1450.01 km2. Nature reserves accounted for 76.4% of the total area, forming the main part of the ecological resource patches. 115 ecological corridors were identified, with a total length of 900.56 km and an average length of 7.83 km. Furthermore, 72 ecological key points were identified, covering a total area of 17.57 km2, and 81 ecological breakpoints, with a total area of 35.9 km2. The network structure indices (α=0.65, ß=2.21, and γ=0.77) indicated a reasonably structured and well-connected network. By exploring pathways for constructing regional ecological networks under the protected areas system and enriching the application of circuit theory models in ecological network construction, this study provides scientific basis for regional ecological security and biodiversity conservation.

Phyllosphere bacterial community dynamics in response to bacterial wildfire disease: succession and interaction patterns.

Plants interact with complex microbial communities in which microorganisms play different roles in plant development and health. While certain microorganisms may cause disease, others promote nutrient uptake and resistance to stresses through a variety of mechanisms. Developing plant protection measures requires a deeper comprehension of the factors that influence multitrophic interactions and the organization of phyllospheric communities. High-throughput sequencing was used in this work to investigate the effects of climate variables and bacterial wildfire disease on the bacterial community's composition and assembly in the phyllosphere of tobacco (Nicotiana tabacum L.). The samples from June (M1), July (M2), August (M3), and September (M4) formed statistically separate clusters. The assembly of the whole bacterial population was mostly influenced by stochastic processes. PICRUSt2 predictions revealed genes enriched in the M3, a period when the plant wildfire disease index reached climax, were associated with the development of the wildfire disease (secretion of virulence factor), the enhanced metabolic capacity and environmental adaption. The M3 and M4 microbial communities have more intricate molecular ecological networks (MENs), bursting with interconnections within a densely networked bacterial population. The relative abundances of plant-beneficial and antagonistic microbes Clostridiales, Bacillales, Lactobacillales, and Sphingobacteriales, showed significant decrease in severally diseased sample (M3) compared to the pre-diseased samples (M1/M2). Following the results of MENs, we further test if the correlating bacterial pairs within the MEN have the possibility to share functional genes and we have unraveled 139 entries of such horizontal gene transfer (HGT) events, highlighting the significance of HGT in shaping the adaptive traits of plant-associated bacteria across the MENs, particularly in relation to host colonization and pathogenicity.

Temporal and spatial differences in nitrogen and phosphorus biogeochemistry and ecosystem functioning of a hypertrophic lagoon (Curonian Lagoon, SE Baltic Sea) revealed via Ecological Network Analysis.

In coastal lagoons, eutrophication and hydrology are interacting factors that produce distortions in biogeochemical nitrogen (N) and phosphorus (P) cycles. Such distortions affect nutrient relative availability and produce cascade consequences on primary producer's community and ecosystem functioning. In this study, the seasonal functioning of a coastal lagoon was investigated with a multielement approach, via the construction and analysis of network models. Spring and summer networks, both for N and P flows, have been simultaneously compiled for the northern transitional and southern confined area of the hypertrophic Curonian Lagoon (SE Baltic Sea). Ecological Network Analysis was applied to address the combined effect of hydrology and seasonality on biogeochemical processes. Results suggest that the ecosystem is more active and presents higher N and P fluxes in summer compared to spring, regardless of the area. Furthermore, larger internal recycling characterizes the confined compared to the transitional area, regardless of the season. The two areas differed in the fate of available nutrients. The transitional area received large riverine inputs that were mainly transferred to the sea without the conversion into primary producers' biomass. The confined area had fewer inputs but proportionally larger conversion into phytoplankton biomass. In summer, particularly in the confined area, primary production was inefficiently consumed by herbivores. Most phytoplanktonic N and P, in the confined area more than in the transitional area, were conveyed to the detritus pathway where P, more than N, was recycled, contributing to the unbalance in N:P stoichiometry and favouring N-fixing cyanobacteria over other phytoplankton groups. The findings of this study provide a comprehensive understanding of N and P circulation patterns in lagoon areas characterized by different hydrology. They also support the importance of a stoichiometric approach to trace relative differences in N and P recycling and abundance, that promote blooms, drive algal communities and whole ecosystem functioning.

New insights into substrates shaped nutrients removal, species interactions and community assembly mechanisms in tidal flow constructed wetlands treating low carbon-to-nitrogen rural wastewater.

A limited understanding of microbial interactions and community assembly mechanisms in constructed wetlands (CWs), particularly with different substrates, has hampered the establishment of ecological connections between micro-level interactions and macro-level wetland performance. In this study, CWs with distinct substrates (zeolite, CW_A; manganese ore, CW_B) were constructed to investigate the nutrient removal efficiency, microbial interactions, metabolic mechanisms, and ecological assembly for treating rural sewage with a low carbon-to-nitrogen ratio. CW_B showed higher removal of ammonia nitrogen and total nitrogen by about 1.75-6.75 % and 3.42-5.18 %, respectively, compared to CW_A. Candidatus_Competibacter (denitrifying glycogen-accumulating bacteria) was the dominant microbial genus in CW_A, whereas unclassified_f_Blastocatellaceae (involved in carbon and nitrogen transformation) dominated in CW_B. The null model revealed that stochastic processes (drift) dominated community assembly in both CWs; however, deterministic selection accounted for a higher proportion in CW_B. Compared to those in CW_A, the interactions between microbes in CW_B were more complex, with more key microbes involved in carbon, nitrogen, and phosphorus conversion; the synergistic cooperation of functional bacteria facilitated simultaneous nitrification-denitrification. Manganese ores favour biofilm formation, increase the activity of the electron transport system, and enhance ammonia oxidation and nitrate reduction. These results elucidated the ecological patterns exhibited by microbes under different substrate conditions thereby contributing to our understanding of how substrates shape distinct microcosms in CW systems. This study provides valuable insights for guiding the future construction and management of CWs.

Impacts of mixed ferrous sulfate-biochar additives on humification and bacterial community during electric field-assisted aerobic composting.

This study assessed the impact of nine mixed ferrous sulfates and biochars on electric field-assisted aerobic composting (EAC), focusing on the spectroscopy of dissolved organic matter (DOM) and microbial communities. Adding 1.05% ferrous sulfate and 5.25% biochar to EAC increased the specific ultraviolet absorbances at 254 and 280 nm by 142.3% and 133.9% on day 35, respectively. This ratio accelerated the early response of carboxyl groups (-COOH) and lignin (CꘌC), enhancing the relative abundance of Thermobifida (4.0%) and Thermopolyspora (4.3%). The condition contributed to humus precursor formation on day 5, increasing the maximum fluorescence intensity of the humus-like component by 74.2% compared to the control on day 35. This study is the first to develop a combined and efficient organic and inorganic additive by multiple-variable experimentation for DOM humification. Consequently, it optimizes EAC for solid waste recycling.

Short-term exposure to antibiotics begets long-term disturbance in gut microbial metabolism and molecular ecological networks.

BACKGROUND: Antibiotic exposure can occur in medical settings and from environmental sources. Long-term effects of brief antibiotic exposure in early life are largely unknown. RESULTS: Post a short-term treatment by ceftriaxone to C57BL/6 mice in early life, a 14-month observation was performed using 16S rRNA gene-sequencing technique, metabolomics analysis, and metagenomics analysis on the effects of ceftriaxone exposure. Firstly, the results showed that antibiotic pre-treatment significantly disturbed gut microbial α and ß diversities (P < 0.05). Both Chao1 indices and Shannon indices manifested recovery trends over time, but they didn't entirely recover to the baseline of control throughout the experiment. Secondly, antibiotic pre-treatment reduced the complexity of gut molecular ecological networks (MENs). Various network parameters were affected and manifested recovery trends over time with different degrees, such as nodes (P < 0.001, R2 = 0.6563), links (P < 0.01, R2 = 0.4543), number of modules (P = 0.0672, R2 = 0.2523), relative modularity (P = 0.6714, R2 = 0.0155), number of keystones (P = 0.1003, R2 = 0.2090), robustness_random (P = 0.79, R2 = 0.0063), and vulnerability (P = 0.0528, R2 = 0.28). The network parameters didn't entirely recover. Antibiotic exposure obviously reduced the number of key species in gut MENs. Interestingly, new keystones appeared during the recovery process of network complexity. Changes in network stability might be caused by variations in network complexity, which supports the ecological theory that complexity begets stability. Besides, the metabolism profiles of the antibiotic group and control were significantly different. Correlation analysis showed that antibiotic-induced differences in gut microbial metabolism were related to MEN changes. Antibiotic exposure also caused long-term effects on gut microbial functional networks in mice. CONCLUSIONS: These results suggest that short-term antibiotic exposure in early life will cause long-term negative impacts on gut microbial diversity, MENs, and microbial metabolism. Therefore, great concern should be raised about children's brief exposure to antibiotics if the results observed in mice are applicable to humans. Video Abstract.

Biogeographic and co-occurrence network differentiation of fungal communities in warm-temperate montane soils.

Studying the biogeographic patterns of fungal communities across altitudinal and soil depth gradients is essential for understanding how environmental variations shape the diversity and functionality of these complex ecological assemblages. Here, we evaluated the response and assembly patterns of fungal communities to altitude and soil depth, and the co-occurrence patterns influencing soil fungal metabolic preferences on Dongling Mountain. We observed significant variations in fungal ß-diversity, driven by elevation and soil depth, with climatic parameters (MAT and MAP) and nutrient concentrations (TOC, TP, and TN) serving as prominent influencers. Additionally, we found that the multiple substrate-induced respiration rate of fungi degrading various carbon substrates was diminished in high-altitude and subsurface soils compared to low-altitude and surface soils. Stochastic processes play a more important role in controlling fungal community assembly than deterministic processes, with dispersal limitation emerging as the main driver of community assembly. While greater network complexity was evident in the topsoil compared to the subsoil, both layers harbored altitude-sensitive OTUs (asOTUs) that belonging to distinct modules. Moreover, fungal groups sensitive to the same altitude exhibited similar metabolic preferences. The asOTUs designated for lower altitude areas favored unstable carbon substrates (glucose and sucrose), while those designated as higher altitude areas exhibited a preference for recalcitrant carbon (xylan and lignin). This evidence suggests that soil fungal communities respond to environmental changes by trading off their life strategies and metabolic characteristics.

Unveiling potential roles of earthworms in mitigating the presence of virulence factor genes in terrestrial ecosystems.

Earthworms can redistribute soil microbiota, and thus might affect the profile of virulence factor genes (VFGs) which are carried by pathogens in soils. Nevertheless, the knowledge of VFG profile in the earthworm guts and its interaction with earthworm gut microbiome is still lacking. Herein, we characterized earthworm gut and soil microbiome and VFG profiles in natural and agricultural ecosystems at a national scale using metagenomics. VFG profiles in the earthworm guts significantly differed from those in the surrounding soils, which was mainly driven by variations of bacterial communities. Furthermore, the total abundance of different types of VFGs in the earthworm guts was about 20-fold lower than that in the soils due to the dramatic decline (also by approximately 20-fold) of VFG-carrying bacterial pathogens in the earthworm guts. Additionally, five VFGs related to nutritional/metabolic factors and stress survival were identified as keystones merely in the microbe-VFG network in the earthworm guts, implying their pivotal roles in facilitating pathogen colonization in earthworm gut microhabitats. These findings suggest the potential roles of earthworms in reducing risks related to the presence of VFGs in soils, providing novel insights into earthworm-based bioremediation of VFG contamination in terrestrial ecosystems.

Ecological threshold of phosphorus load in Baiyangdian Lake based on a PCLake model and ecological network analysis.

Ecological thresholds are a useful indicator for implementing ecological management. Many studies determine the thresholds for nutrient loads in lakes based on the maximum allowable concentration of chlorophyll a (Chla), although this neglects the overall performance of the ecosystem. A PCLake model of Baiyangdian (BYD) Lake in northern China was constructed with six ecological network analysis (ENA) indicators that characterized the ecosystem function, system maturity, and food web structure to quantify the overall status of the BYD ecosystem. To my knowledge, this is the first study on the system level responses of the BYD Lake to phosphorus load interference. Different phosphorus load scenarios were designed to simulate the ecological responses of BYD Lake. The simulated results were employed to calculate the ENA indicators. Ecological thresholds were determined through the driving response relationship between the phosphorus load gradient and the ENA indicators. The results show a non-linear transition response of ENA indicator under phosphorus load gradient. As phosphorus load increases, D/H, SOI, and FCI decreases while A/DC, TPP/TR, and TPP/TB increases. This indicates that the overall structure and function of the ecosystem will deteriorate if phosphorus load increases. The phosphorus load thresholds for the overall performance of BYD Lake were 0.50-1.32 mg m-2 d-1, slightly wider than that of Chla (0.53-1.26 mg m-2 d-1). The model results clearly indicate that there is a time-lag phenomenon at the switch points in the response of ENA indicators compared to that of single functional group. In addition, the A/DC, TPP/TR, SOI, and FCI present more time-lag than that of other ENA indicators. These time-lag effects provide a particular opportunity for biodiversity conservation. Therefore, a possible management strategy is proposed to combine system-level and function group-level thresholds, with the ENA-based threshold as the bottom line and the phytoplankton's threshold as the early-warning indicator. This design is expected to be more precise and efficient, by exploiting the advantages of two thresholds, and may benefit for ecological management practices.