Neutral Model Research Articles

Benthic Microbes on the Shore of Southern Lake Taihu Exhibit Ecological Significance and Toxin-Producing Potential Through Comparison with Planktonic Microbes

Water quality and aquatic ecosystems along lakeshores are vital for ecological balance and human well-being. However, research has primarily focused on plankton, with benthic niches being largely overlooked. To enhance understanding of benthic microbial communities, we utilized 16S and 18S rRNA sequencing alongside multivariate statistical methods to analyze samples from the shoreline of Lake Taihu in Huzhou City, Zhejiang Province. Our results reveal a marked difference in species composition between benthic and planktonic microorganisms, with benthic cyanobacteria predominantly comprising filamentous genera like Tychonema, while 95% of planktonic cyanobacteria were Cyanobium. The β-diversity of benthic microorganisms was notably higher than that of planktonic counterparts. The neutral community model indicated that stochastic processes dominated planktonic microbial assembly, while deterministic processes prevailed in benthic communities. Null models showed that homogeneous selection influenced benthic community assembly, whereas planktonic communities were affected by undominated processes and dispersal limitation. Network analysis indicated that planktonic networks were more stable than benthic networks. Importantly, dominant benthic cyanobacterial genera posed potential toxin risks, highlighting the need for enhanced monitoring and ecological risk assessment. Overall, these findings enhance our understanding of benthic and planktonic microbial communities in lakeshores and offer valuable insights for aquatic assessment and management in eutrophicated environments.

Empirical Model of SSUSI‐Derived Auroral Ionization Rates

AbstractWe present an empirical model for auroral (90–150 km) electron–ion pair production rates, ionization rates for short, derived from Special Sensor Ultraviolet Spectrographic Imager electron energy and flux data. Using the Fang et al. (2010, https://doi.org/10.1029/2010gl045406) parametrization for mono‐energetic electrons, and the NRLMSISE‐00 neutral atmosphere model (Picone et al., 2002, https://doi.org/10.1029/2002ja009430), the calculated ionization rate profiles are binned in 2‐hr magnetic local time and 3.6°geomagnetic latitude to yield time series of ionization rates at 5‐km altitude steps. We fit each of these time series to the geomagnetic indices Kp, PC, and Ap, the 81‐day averaged solar radio flux index, and a constant term. The resulting empirical model can easily be incorporated into coupled chemistry–climate models to include particle precipitation effects.

Associations Between Gut Microbiota Diversity and a Host Fitness Proxy in a Naturalistic Experiment Using Threespine Stickleback Fish.

The vertebrate gut microbiota is a critical determinant of organismal function, yet whether and how gut microbial communities affect host fitness under natural conditions remains largely unclear. We characterised associations between a fitness proxy-individual growth rate-and bacterial gut microbiota diversity and composition in threespine stickleback fish introduced to large semi-natural ponds. We detected a 63% higher richness of bacterial taxa (α-diversity) in the guts of high-fitness fish compared to low-fitness fish, which might be driven by stronger bacterial dispersal among high-fitness fish according to the fit of a neutral community model. Further, microbial communities of high-fitness fish were more similar to one another (i.e., exhibited lower β-diversity) than those of low-fitness fish. The lower β-diversity found to be associated with higher host fitness is consistent with the Anna Karenina principle-that there are fewer ways to have a functional microbiota than a dysfunctional microbiota. Our study links differences in α- and β-diversity to a fitness-related trait in a vertebrate species reared under naturalistic conditions and our findings provide a basis for functional tests of the fitness consequences of host-microbiota interactions.

Effects of different feeding patterns on growth, enzyme activity, and intestinal microbiome of the juvenile Pacific abalone Haliotis discus hannai

In northern China, the predominant food sources for abalone farming include fresh kelp, salted kelp, and formulated diets, and abalone can also endure prolonged starvation when food is scarce. While there is a dearth of comprehensive investigation into the effects of these feeding patterns on the temporal dynamics of enzyme activity, and intestinal microbiome of abalone. In this study, a total of 3600 juvenile Pacific abalones were allocated to 12 tanks, randomly divided into four groups based on the feeding patterns: fresh kelp (labeled as FK), salted kelp (SK), formulated feed (FF), and starved group (S). After a 60-day feeding trial, the results showed that abalone in the FK, SK, and FF groups exhibited significant positive effects on both weight and shell growth compared to the S group (P<0.05). Notably, the FF group displayed the highest values of the growth performance. The activity of digestive enzymes and antioxidant enzymes in the FF group had an up-regulated trend over the course of feeding trial, whereas amylase and lipase activity in abalone declined along with starvation. Moreover, the microbial Shannon index showed an overall decreasing trend over time in the FF, FK, and SK groups except for the S group. The ANOSIM analysis revealed that both feeding pattern and cultivating time significantly influenced the structure of the microbial communities. Across the feeding trial, Proteobacteria, Fusobacteriota, and Firmicutes were identified as the dominant phyla in the intestinal microbiome of abalone under different feeding patterns. The core genera were Psychrilyobacter, Mycoplasma, and Vibrio. Additionally, the neutral model analysis revealed that stochastic processes both play a key role in shaping the assembly of microbial communities in different feeding patterns. This study could offer valuable insights into the impact of different feeding patterns on growth and physiology of abalone, thereby contributing to the enhancement of management strategies in the northern Chinese abalone aquaculture industry.

Mycobacterium avium subspecies paratuberculosis (MAP) infection, and its impact on gut microbiome of individuals with multiple sclerosis

The microbial ecology of Mycobacterium avium subspecies paratuberculosis infections (MAP) within the context of Multiple Sclerosis (MS) is largely an unexplored topic in the literature. Thus, we have characterized the compositional and predicted functional differences of the gut microbiome between MS patients with MAP (MAP+) and without (MAP−) infection. This was done in the context of exposome differences (through self-reported filled questionnaires), principally in anthropometric and sociodemographic patterns to gain an understanding of the gut microbiome dynamics. 16S rRNA microbiome profiling of faecal samples (n = 69) was performed for four groups, which differed by disease and MAP infection: healthy cohort (HC) MAP−; HC MAP+ ; MS MAP−; and MS MAP+ . Using a dynamic strategy, with MAP infection and time of sampling as occupancy models, we have recovered the core microbiome for both HC and MS individuals. Additional application of neutral modeling suggests key genera that are under selection pressure by the hosts. These include members of the phyla Actinobacteriota, Bacteroidota, and Firmicutes. As several subjects provided multiple samples, a Quasi Conditional Association Test that incorporates paired-nature of samples found major differences in Archaea. To consolidate treatment groups, confounders, microbiome, and the disease outcome parameters, a mediation analysis is performed for MS cohort. This highlighted certain genera i.e., Sutterella, Akkermansia, Bacteriodes, Gastranaerophilales, Alistipes, Balutia, Faecalibacterium, Lachnospiraceae, Anaerostipes, Ruminococcaceae, Eggerthellaceae and Clostridia-UCG-014 having mediatory effect using disease duration as an outcome and MAP infection as a treatment group. Our analyses indicate that the gut microbiome may be an important target for dietary and lifestyle intervention in MS patients with and without MAP infection.

Impact of ionization and transport on pedestal density structure in DIII-D and Alcator C-Mod

Abstract This paper investigates the role of ionization on the pedestal structure using both measurements and modeling for H-mode plasmas on DIII-D and Alcator C-Mod to enhance our ability to predict pedestal behavior in future pilot plants. The impact of the neutral penetration depth on the pedestal density is investigated using dimensionally matching hydrogen and deuterium DIII-D H-mode discharges at low and high electron density. The DIII-D Lyman-α diagnostic measurements show that hydrogen neutrals penetrate deeper inside the plasma on both the high field and low field side, while the pedestal electron density structure is similar for both isotopes. However, as the opaqueness increases we observe that the pedestal density gradient becomes stiff, similar to prior observations on DIII-D and C-Mod (Mordijck 2020 Nuclear Fusion 60 082006). In addition, these results also confirm prior measured and modeled poloidal asymmetries in neutral densities, indicating that to make transport predictions, 2D neutral modeling is necessary. The first direct validation of SOLPS-ITER for the measured brightness, emissivity and neutral densities for three different confinement regimes on C-Mod is introduced. The SOLPS-ITER model shows good agreement, within the constrains of the model for all regimes. In addition, a comparison of SOLPS-ITER modeling for DIII-D and C-Mod shows that as opaqueness increases, the role of divertor fueling and thus poloidal asymmetries in the neutral density profiles decreases. Based on these experimental and modeling results we estimate the size of a potential particle pinch using typical values for the diffusion coefficient for both DIII-D and C-Mod H-mode discharges.

Exploring Community Succession, Assembly Patterns, and Metabolic Functions of Ester-Producing-Related Microbiota during the Production of Nongxiangxing baijiu.

Esters are vital flavor compounds in Chinese Nongxiangxing baijiu and greatly affect the quality of baijiu. Microbial communities inhabiting fermented grains (FGs) have a marked impact on esters. However, the specific microorganisms and their assembly patterns remain unclear. This study utilized high-throughput sequencing and a culture-based method to reveal ester-producing microorganisms. A total of 33 esters were detected, including 19 ethyl esters, 9 linear chain esters, and 2 branched chain esters. A correlation analysis indicated that the bacterial genus Lactobacillus (relative abundance in average: 69.05%) and fungal genera Pichia (2.40%), Aspergillus (11.84%), Wickerhamomyces (0.60%), Thermomyces (3.57%), Saccharomycopsis (7.87%), Issatchenkia (0.96%), and Thermoascus (10.83%) were dominant and associated with esters production and their precursors. The numbers of esters positively correlated with them were 1, 17, 3, 2, 1, 1, 1, and 1, respectively. The modified stochasticity ratio (MST) index and Sloan neutral model revealed that bacteria were predominantly governed by deterministic processes while fungal assemblies were more stochastic. Saturnispora silvae and Zygosaccharomyces bailii were isolated and identified with ester synthesis potential. PICRUSt2 analysis showed that fungi in FG had a high potential for synthesizing ethanol, while 14 enzymes related to esters synthesis were all produced by bacteria, especially enzymes catalyzing the synthesis of acyl-CoA. In addition, ester synthesis was mainly catalyzed by carboxylesterase, acylglycerol lipase and triacylglycerol lipase. These findings may provide insights into ester production mechanism and potential strategies to improve the quality of Nongxiangxing baijiu.

Deciphering stratified structure and microbiota assembly of biofilms from a pyrite-based biofilter driven by mixotrophic denitrification

The precise structure and assembly process of pyrite-based biofilms remain poorly understood. The polysaccharides (PN), proteins (PS), and extracellular DNA were enriched in the soluble extracellular polymeric substance (EPS), loosely bound EPS, and tightly bound EPS, respectively, indicating a significant stratified structure of biofilms. The tryptophan facilitated mixotrophic metabolic processes. Both dominant (>1%) and rare species (<0.01 %) harbored core bacteria, including sulfur autotrophic bacteria, sulfate-reducing bacteria, and heterotrophic bacteria. Furthermore, partial least-squares path modeling quantified the contributions of total phosphorus (TP) (λ = 0.32), dissolved organic matter (DOC) (λ = 0.29), and NH4+–N (λ = 0.26) to variations in the microbial community. Nonmetric multidimensional scaling analysis revealed three distinct stages in biofilm development: colonization (0–36 d), succession (36–149 d), and maturation/old (149–215 d). Furthermore, neutral community model indicated that stochastic processes drove the colonization and maturation/old stages, while deterministic processes dominated the succession stage. This study offered valuable insights into the regulation of pyrite-based engineered ecosystems.

Molecular Identification and Genetic Diversity Analysis of Papaya Leaf Curl China Virus Infecting Ageratum conyzoides.

Papaya leaf curl China virus (PaLCuCNV) is a damaging plant pathogen causing substantial losses to crop. The complete genomes of three PaLCuCNV isolates from Ageratum conyzoides were obtained and combined with the 68 reference isolates in GenBank for comprehensive genetic diversity analyses using specialized computational tools. Sequence alignment revealed nucleotide sequence similarity ranging from 85.3% to 99.9% among 71 PaLCuCNV isolates. Employing phylogenetic analysis, 71 PaLCuCNV sequences were clustered into five groups, with no significant correlation observed between genetic differentiation and either host species or geographical origin. Additionally, 13 recombination events across all PaLCuCNV isolates were identified. Genetic diversity analysis indicated the ongoing expansion and evolution of PaLCuCNV populations, supported by a neutral model. Moreover, significant genetic differentiation was observed among distinct viral populations, primarily attributed to genetic drift. Overall, our findings provide valuable insights into the detection, genetic variation, and evolutionary dynamics of PaLCuCNV.

Bacterial community and antibiotic resistance genes assembly processes were shaped by different mechanisms in the deep-sea basins of the Western Pacific Ocean.

As the intrinsic property of microorganisms, antibiotic resistance genes (ARGs) are fundamentally coupled to microbially-linked biogeochemical processes within ecosystems. However, human activities often obscure the natural distribution of ARGs through deterministic selective pressures. The deep-sea basin of the western Pacific Ocean is one of the least disturbed areas globally by human activities, providing a natural laboratory to investigate the intrinsic mechanisms governing ARGs in natural environments. In this study, we analyzed bacterial community and ARG diversity in 15 surface sediment samples from three deep-sea basins in the western Pacific Ocean. The relative abundance of ARGs in the surface sediments ranged from 3.10 × 10-3 to 5.37 × 10-2 copies/16S rRNA copies, with multidrug and β-lactam resistance genes dominated in all samples (49.06%-100%). The bacteria were mainly dominated by the Proteobacteria. The principal coordinate analysis (PCoA) showed significant spatial heterogeneity of ARGs and bacteria among the three basins. Null model, neutral community models (NCM), and normalized stochasticity ratio (NST) indicated that bacterial community was dominated by stochastic assembly, driven by geographic barriers leading to independent evolution. Conversely, the NST revealed that the ARGs profile was mainly shaped by deterministic processes. Environmental factors are more crucial than geographical factors and bacterial community for ARG occurrence among the selected factors. Meanwhile, we found that the spread of ARGs was mainly through vertical gene transfer in the pre-antibiotic era. The disparity between the assembly processes of bacterial community and ARGs may be attributed to the fact that ARG hosts were not the dominant bacteria in the community. This study first reported the distribution and assembly processes of ARGs and bacterial community in surface sediments of the western Pacific.

Unique ecology of biofilms and flocs: Bacterial composition, assembly, interaction, and nitrogen metabolism within deteriorated bioreactor inoculated with mature partial nitrification-anammox sludge

This work unraveled discrepant ecological patterns between biofilms and flocs in a deteriorated bioreactor inoculated with mature partial nitrification-anammox (PN/A) sludge. Based on 16S rRNA analysis, a comprehensive evaluation of neutral and null models, along with niche width, delineated that the bacterial community assembly in biofilms and flocs was dominantly driven by the stochastic process, and dispersal limitation critically shaped the community assembly. Co-occurrence network analysis revealed that environmental stress caused decentralized and fragmented bacterial colonies, and anammox bacteria were mainly peripheral in biofilms network and less involved in interspecific interactions. Simultaneous PN/A and partial denitrification-anammox (PD/A) processes were identified, whereas PN and PD process primarily occurred in the biofilms and flocs, respectively, as evidenced by metagenomics. Collectively, these outcomes are expected to deepen the basic understanding of complex microbial community and nitrogen metabolism under environmental disturbance, thereby better characterizing and serving the artificial ecosystems.

Through-focus performance and off-axis effects in aspheric monofocal intraocular lenses.

This study aimed to determine the through-focus performance and the effect of misalignment on the optical quality of different aspheric monofocal intraocular lenses (IOLs). To this end, optical quality was assessed in three IOL models with different optic surfaces: standard aberration neutral model and two spherical aberration (SA) correcting, one of which utilizes higher-order aspheric terms. The optical quality was measured by means of the modulation transfer function at 3- and 4.5-mm pupils and under monochromatic and polychromatic light with different corneal SA. The optically derived range of vision and tolerance to misalignment were also tested. The study demonstrated that the type of IOL surface affects the monofocal implant's performance. Although a standard primary-SA correction may improve scotopic image quality, misalignment may diminish this advantage. The higher-order aspheric surface used to correct SA provided an improved performance against decentration and offered a higher optical quality than the aberration-neutral design when tested in a model eye. The latter, however, demonstrated a high tolerance to misalignment, offering a slight extension of the range of vision, potentially resulting from uncorrected optical aberrations.

Selection promotes age-dependent degeneration of the mitochondrial genome.

Somatic mutations in mitochondrial genomes (mtDNA) accumulate exponentially during aging. Using single cell sequencing, we characterize the spectrum of age-accumulated mtDNA mutations in mouse and human liver and identify directional forces that accelerate the accumulation of mutations beyond the rate predicted by a neutral model. "Driver" mutations that give genomes a replicative advantage rose to high cellular abundance and carried along "passenger" mutations, some of which are deleterious. In addition, alleles that alter mtDNA-encoded proteins selectively increased in abundance overtime, strongly supporting the idea of a "destructive" selection that favors genomes lacking function. Overall, this combination of selective forces acting in hepatocytes promotes somatic accumulation of mutations in coding regions of mtDNA that are otherwise conserved in evolution. We propose that these selective processes could contribute to the population prevalence of mtDNA mutations, accelerate the course of heteroplasmic mitochondrial diseases and promote age-associated erosion of the mitochondrial genome.

Differential insights into the distribution characteristics of archaeal communities and their response to typical pollutants in the sediments and soils of deep-water reservoir

This study focused on the Fengshuba deep-water reservoir in South China, and systematically explored the distribution characteristics of archaeal communities in the sediment and soil in water level fluctuation zones and their response mechanisms to typical pollutants. The results show that Euryarchaeota and Bathyarchaeota are the dominant phyla in sediment archaeal communities, while Thaumarchaeota dominates in soil. The absolute abundance of archaea in the sediments was lower than that in the soils, but the diversity and richness of archaeal communities were higher than those in the soils. Seasonal changes affected the composition of sediment archaeal communities, and the archaeal compositions in the two habitats also showed significant differences. The neutral community model indicates that the assembly of archaeal communities in sediments is mainly governed by stochastic processes, while deterministic processes dominate in soils. The responses of archaeal communities to pollutants in the two habitats were significantly different. Among them, the carbon-nitrogen ratio and tetracycline concentration are the key factors driving seasonal changes in the archaeal communities in the sediment. Structural equation modeling further showed that the archaeal community in the sediment was positively correlated with organochlorine pesticides and antibiotics, while the archaeal community in the soil showed an opposite trend. This study provides new insights into the complexity of interactions between archaeal communities and typical contaminants in reservoir systems.

Pipe material and natural organic matter impact drinking water biofilm microbial community, pathogen profiles and antibiotic resistome deciphered by metagenomics assembly

Biofilms in drinking water distribution systems (DWDSs) are a determinant to drinking water biosafety. Yet, how and why pipe material and natural organic matter (NOM) affect biofilm microbial community, pathogen composition and antibiotic resistome remain unclear. We characterized the biofilms’ activity, microbial community, antibiotic resistance genes (ARGs), mobile genetic elements (MGEs) and pathogenic ARG hosts in Centers for Disease Control and Prevention (CDC) reactors with different NOM dosages and pipe materials based on metagenomics assembly. Biofilms in cast iron (CI) pipes exhibited higher activity than those in polyethylene (PE) pipes. NOM addition significantly decreased biofilm activity in CI pipes but increased it in PE pipes. Pipe material exerted more profound effects on microbial community structure than NOM. Azospira was significantly enriched in CI pipes and Sphingopyxis was selected in PE pipes, while pathogen (Ralstonia pickettii) increased considerably in NOM-added reactors. Microbial community network in CI pipes showed more edges (CI 13520, PE 7841) and positive correlation proportions (CI 72.35%, PE 61.69%) than those in PE pipes. Stochastic processes drove assembly of both microbial community and antibiotic resistome in DWDS biofilms based on neutral community model. Bacitracin, fosmidomycin and multidrug ARGs were predominant in both PE and CI pipes. Both pipe materials and NOM regulated the biofilm antibiotic resistome. Plasmid was the major MGE co-existing with ARGs, facilitating ARG horizontal transfer. Pathogens (Achromobacter xylosoxidans and Ralstonia pickettii) carried multiple ARGs (qacEdelta1, OXA-22 and aadA) and MGEs (integrase, plasmid and transposase), which deserved more attention. Microbial community contributed more to ARG change than MGEs. Structure equation model (SEM) demonstrated that turbidity and ammonia affected ARGs by directly mediating Shannon diversity and MGEs. These findings might provide a technical guidance for controlling pathogens and ARGs from the point of pipe material and NOM in drinking water.

A Closer Look at Race, Ethnicity, and Gender Neutral Models

Abstract Litigation cases involving the expected earnings of minor children provide an ideal environment to examine the implications of public policies that attempt to mitigate racial, ethnic, and gender discrimination in the calculation of economic damages. This paper extends the existing literature on the implications of race, ethnicity, and gender neutral models by evaluating both educational attainment probabilities and estimated lifetime earnings within educational attainment categories. Recent related studies have focused on the educational attainment portion of the calculation only. We perform thousands of simulations of a child’s lifetime earnings using neutral estimations—a proxy for removing discrimination—and compare those estimates to ones in which race, ethnicity, and gender are taken into account. We find wide variation within racial and ethnic groups when earnings are incorporated into the analysis, consistent with prior research. Importantly, however, our findings pertain primarily to females, suggesting that interactions between gender and race and ethnicity are an added complexity. The practical implication of our findings is that neutral models can adversely impact individual members of protected groups. The results provide further guidance to policymakers who might be interested in the real-world outcomes associated with legislation that restricts how economists calculate economic damages.

Density functional theory study of physisorption of ionic liquid pairs on hydroxylated and oxygen terminated α-SiO2 (001) surfaces

In this work, we investigate the ion pair tetramethylphosphonium cation, [P1,1,1,1]+, and bis(oxalato)borate anion, [BOB]−, as a model system for the study of ionic liquids interacting with both hydroxylated and oxygen terminated α-SiO2 (001) surfaces, using first-principles electronic structure theory. We use a single ionic pair and clusters of ion pairs, in order to have exclusively neutral supercell slab models. We use dispersion-corrected density functional theory (DFT) to ascertain that both the strong physical binding between the ions, dominated by ionic binding, and the weaker physical binding of ions to the different surfaces are correctly described. We have found that the binding of ion pairs is stronger to the hydroxylated α-SiO2 (001) surface compared to the oxygen terminated surface, which is attributed to the formation of H-binding with the oxygen atom(s) of the [BOB]− anion. Through rotation of ionic pair(s), we estimate the surface-ions energy barrier for translational movement and, thus, the strength of H-binding of the ions. At the surface of hydroxylated α-SiO2 (001), we have studied how water molecules form a network of H-binding with the OH groups of the surface and the [BOB]− anion, which offers an explanation for the reduction in the friction of ionic liquids on the inclusion of water. We suggest modeling protocols for simulation of ion pairs on surfaces, which can open up the possibility to use DFT to aid in designing and understanding the physicochemical mechanism of interactions of ionic materials (including ionic liquids) in various technological applications.

Integration of deep neutral network modeling and LC-MS-based pseudo-targeted metabolomics to discriminate easily confused ginseng species

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus and P. japonicus var. major, containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM, and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

A Kinetic-magnetohydrodynamic Model with Adaptive Mesh Refinement for Modeling Heliosphere Neutral-plasma Interaction

The charge exchange between the interstellar medium and the solar wind plasma is crucial for determining the structures of the heliosphere. Since both the neutral-ion and neutral–neutral collision mean free paths are either comparable to or larger than the size of the heliosphere, the neutral phase space distribution can deviate far away from the Maxwellian distribution. A kinetic description for the neutrals is crucial for accurately modeling the heliosphere. It is computationally challenging to run three-dimensional time-dependent kinetic simulations due to the large number of macroparticles. In this paper, we present the new highly efficient Solar Wind with Hydrogen Ion Exchange and Large-scale Dynamics-2 model with a kinetic model of neutrals and a magnetohydrodynamic model for the ions and electrons. To improve the simulation efficiency, we implement adaptive mesh refinement and particle splitting and merging algorithms for the neutral particles to reduce the particle number that is required for an accurate simulation. We present several tests to verify and demonstrate the capabilities of the model.

Glufosinate-ammonium increased nitrogen and phosphorus content in water and shaped microbial community in epiphytic biofilm of Hydrilla verticillata

Glufosinate-ammonium (GLAM) can be released into adjacent water bodies with rainfall runoff and return water from farmland irrigation. However, impacts of GLAM on aquatic organisms remain unclear. In this study, changes in water quality, plant physiological parameters and epiphytic microbial community were investigated in wetlands with Hydrilla verticillata exposed to GLAM for 24 days. We found GLAM addition damaged cell and reduced chlorophyll a content in Hydrilla verticillata leaves, and increased ammonium and phosphorus in water (p < 0.001). The α-diversity increased in bacterial community but decreased in eukaryotic community with GLAM exposure. Neutral community models explained 62.3 % and 55.0 % of the variance in bacterial and eukaryotic communities, respectively. Many GLAM micro-biomarkers were obtained, including some clades from Proteobacteria, Bacteroidete, Actinobacteriota, Phragmoplastophyta, Annelida and Arthropoda. Redundancy analysis revealed that GLAM concentration was positively correlated to Flavobacterium, Gomphonema and Closterium but negatively to Methyloglobulus and Methylocystis. Network analysis revealed that 15 mg/L GLAM disturbed the interactions among phytoplankton, protozoa, metazoan and bacteria and reduced the stability of the microbial communities compared to 8 mg/L GLAM. GLAM shaped the nitrogen and phosphorus cycle related bacterial genes. This study highlights that herbicides are non-neglectable factors affecting the efficiency of aquatic ecological restoration in agricultural areas to control agricultural non-point source pollution.