Search Results (1,191)

Dissimilar friction stir welding (FSW) of titanium alloys offers a route to spatially optimized aerospace structures, but the asymmetric thermomechanical environment produces heterogeneous microstructures and textures whose interaction with mechanical performance is not well characterized. A near-α/α+β combination of titanium alloys, Ti–6242 SG (advancing side, ADV) and Ti–54M (retreating side, RET), was welded across a matrix of rotation speeds (225–325 rpm) and traverse speeds (100–150 mm·min⁻¹), spanning rotation-to-traverse-speed ratios N/v of 1.80–2.75, which was used throughout as an empirical processing index that orders the conditions of this matrix rather than as a measure of specific heat input. Microstructure, phase identification, relative diffracted-intensity trends, and crystallographic textures were characterized by 2D-XRD at three cross-section locations (ADV, weld nugget center [CEN], RET) and correlated with transverse tensile properties and fracture locations. Partial pole figures were plotted in the simple-shear reference frame with ideal-orientation overlays, intensities in multiples of a random distribution (m.r.d.). The CEN develops the strongest textures, dominated by a basal {002}_α component (20–31 m.r.d.) with poles near the normal direction; this concentration lies away from the ideal shear fiber loci and is more readily explained by orientation inheritance during the β→α transformation on cooling than by direct shear, although unambiguous identification of variant selection would require orientation-resolved measurements. The RET develops {101}_α and {100}_α pole concentrations clustering near the ideal P-fiber loci, consistent with deformation-related texture development, intensifying with both rotation and traverse speed. The ADV shows mixed textures varying non-monotonically with parameters. Two conditions of nearly identical N/v obtained from different parameter combinations (225 rpm/125 mm·min⁻¹ and 275 rpm/150 mm·min⁻¹) nevertheless develop measurably different streak morphologies, microstructures, textures, and tensile responses, showing directly that N/v orders but does not determine the thermomechanical state. Yield strength is uniform (≈900–940 MPa) across the full matrix, consistent with a Schmid-factor estimate in which the basal-near-ND CEN texture gives a very low resolved shear stress on basal systems under transverse loading; joint efficiencies reach ≈90–96%. Ductility, in contrast, tracks consolidation quality rather than texture severity: fracture strain rises almost monotonically with N/v, from ≈0.6–1.4% at N/v ≈ 1.8 (defect-driven, erratic failure) to ≈5.4–6.0% at N/v = 2.60, despite the latter condition carrying the strongest RET pyramidal texture. Full-field strain measurement shows the weld nugget to carry the lowest strain and the highest apparent stiffness of any zone in every condition for which the load record is reliable, with strain accumulating on the advancing side. Consolidated conditions fracture on the advancing side where deformation concentrates, whereas the lowest N/v and longest-exposure conditions fracture in the nugget center; all fracture surfaces are ductile, with the crack path following continuous α layers at prior-β grain boundaries. A favorable processing range within the investigated parameter matrix is N/v ≈ 2.2–2.6, with the best overall combination at 325 rpm and 125 mm·min⁻¹ (N/v = 2.60: UTS ≈ 1010 MPa, ≈5.4–6.0% elongation). Within the parameter range examined here, consolidation quality is the first-order design variable for this dissimilar system, with the zonal texture architecture setting the yield strength level. Full article

Rapid seismic intensity estimation supports situational awareness, emergency response, and the assessment of earthquake-induced structural risk. Instrument-based systems provide authoritative measurements, but limited deployment density and installation cost can restrict spatial coverage. Video sensing offers a complementary route by converting the visible motion of a calibrated target into physical motion indicators; its reliability, however, depends on stable frame-wise localisation under illumination variation, blur, and target deformation. This paper presents FAMTrack, a vision-based seismic intensity prediction framework whose tracking module augments a one-stream Vision Transformer with a parallel Frequency-Aware Matching branch that encodes patch-wise Fourier amplitude and phase. A Cross-Domain Fusion Module exchanges spatial and frequency evidence through bidirectional cross-attention without modifying the detection head or tracking loss. On LaSOT, FAMTrack-256 attains a 75.1% AUC, 4.0 percentage points above OSTrack-256. On GOT-10K, it reaches 77.9% AO, a gain of 4.2 points. In the held-out seismic-video evaluation, FAMTrack reduces the displacement RMSE from 0.523 to 0.332 mm and improves window-level intensity prediction accuracy from 80.0% to 86.7% relative to OSTrack-256. Under the fixed calibrated-video pipeline and the evaluated controlled conditions, these results indicate that frequency-aware localisation is associated with improved public-benchmark tracking, motion recovery, and seismic intensity estimation. Full article

Diversified crop rotations and cover crops are increasingly promoted as climate-smart management strategies for improving soil organic carbon (SOC) while minimizing nitrous oxide (N₂O) emissions in semiarid agroecosystems. However, regional-scale assessment of SOC–N₂O trade-offs remains computationally challenging because process-based simulations across large spatial and climatic domains are highly demanding. This study combined long-term DSSAT simulations with machine-learning (ML) surrogate models to quantify and spatially predict SOC and N₂O responses to diversified rotations and cover-crop systems across the Texas High Plains (THP). Random Forest models were trained using DSSAT outputs representing multiple crop rotations, climate scenarios, and soil conditions. Two complementary modeling frameworks were developed: (i) BAU-relative responses, which quantified SOC and N₂O changes relative to baseline management, and (ii) added cover-crop effects, which isolated the additional benefits of diversified cover-crop systems relative to a simplified no-cover crop improved rotation system. Model interpretation was conducted using permutation importance and SHAP analysis to identify the dominant environmental and management controls. The surrogate models accurately reproduced DSSAT-derived responses, particularly for BAU-relative SOC and N₂O changes reaching R² ≈ 0.90, while added cover crop SOC was less predictable than added N₂O. Spatial predictions revealed strong geographic variability in climate-smart response zones, with larger SOC benefits generally observed under future climate conditions, particularly during the 2070s. However, some regions also exhibited stronger N₂O trade-offs, highlighting the need for spatially targeted management strategies. The results demonstrate the potential of combining process-based simulations with ML surrogates to generate computationally efficient decision-support tools for climate-smart agriculture in semiarid cropping systems. Full article

The eastern Pre-Caspian Depression and northern margin of the Tarim Basin are two Paleozoic craton-based basins that were impacted by different late Paleozoic collisional systems—the Uralides and the South Tian Shan. A comparative analysis was performed on their Paleozoic petroleum source rocks as part of this research project. This comparison utilized an identical methodological process across both basins. Data on total organic carbon content (TOC), Rock-Eval pyrolysis and vitrinite reflectance (Ro) were obtained from 15 wells (eight in the eastern Pre-Caspian Depression and seven in the Tarim Basin). In addition to these new datasets, published regional databases and sediment accumulation rates calculated at 40 locations were used. The Pre-Caspian source rocks contained TOC values ranging from 1.9 wt% to 6.0 wt% (average = 3.5 wt%) and had hydrogen indices (HI) ranging from 279 to 500 mg hydrocarbons per gram TOC; they were characterized as oil-prone Type II kerogens and were mature to late-mature (Ro = 0.85–1.40%). The Tarim source rocks contained less TOC (range = 1.2–4.8 wt%; average = 2.6 wt%) and had HI values that were generally lower and highly variable (range = 80–350 mg hydrocarbons per gram TOC); they were composed of Type I–II to III kerogens and were significantly more mature than those found in the Pre-Caspian Basin (range = Ro = 0.80–2.00%), with some areas reaching the dry-gas window. Sediment Accumulation Rates (SARs) were approximately equal in magnitude (maximum SARs ranged from 60 to 64 m per million years) but differed in terms of spatial distribution. While SARs were primarily focused along the southern margin of the Tian Shan mountain range in the Tarim Basin, SARs were relatively evenly distributed throughout the intracratonic eastern Pre-Caspian Depression. Therefore, it can be concluded that the type of orogenic system is responsible for determining when source rocks enter the oil and gas windows, providing a transferable methodology for distinguishing oil- from gas-prone fairways within orogen-flanked cratonic basins. Full article

Closed-flume spatial constraints may bias swimming-performance data used in fish-passage design. Two independent experiments were conducted using different size classes of juvenile grass carp (Ctenopharyngodon idella). Fish with a mean body length (BL) of 7.92 ± 0.61 cm were used to assess five test-section lengths (8, 6, 4, 3.5, and 3 BL), whereas fish with a mean BL of 15.76 ± 0.97 cm were used to assess three blockage ratios (1.88%, 9.26%, and 15.31%). Incremental-velocity tests quantified critical swimming speed and behavior, and three-dimensional simulations examined the local flow field under the 9.26% blockage. Relative critical swimming speed was similar at 4–8 BL (9.71–9.95 BL/s) but decreased by 10.96% from 4 to 3.5 BL. Increasing blockage from 1.88% to 9.26% and 15.31% reduced it from 6.99 to 5.34 and 5.24 BL/s, respectively. Behavioral responses also depended on spatial constraint: shorter sections reduced the space available for forward movement and postural adjustment, whereas higher blockage restricted lateral body and tail movements. As velocity increased, fish intensified tail beating; under higher blockage, compensation relied increasingly on tail-beat frequency because amplitude adjustment was constrained, with greater variation among individuals. Simulations showed that local streamwise velocity near the maximum fish cross-section was 20.8–25.0% above inlet velocity. At least 4 BL is recommended for fish comparable to those in the length experiment. Below 5% is suggested as a precautionary blockage target. Full article

Unmanned aerial vehicle (UAV) remote sensing can reveal spatial variability in maize, but its value depends on whether observations support timely and reliable management. This structured critical review synthesizes UAV applications from stand establishment and canopy development to water and nutrient assessment, stress monitoring, yield prediction, and decision support. The evidence corpus comprised 82 sources, including 51 core maize–UAV studies, evaluated by growth stage, validation strength, and operational endpoint. RGB, multispectral, hyperspectral, thermal, and three-dimensional methods provide complementary information for plant counting, canopy traits, treatment-related water and nitrogen responses, visible stress mapping, and within-experiment yield variation. Most evidence, however, comes from experimental or site-specific settings. Independent testing across sites, years, cultivars, and production environments remains uncommon, as do physiological confirmation of interacting stresses and translation of diagnostic maps into machinery-ready operations. UAV sensing should therefore be viewed as complementary to satellite observations and field scouting, with its advantage determined by target, scale, timing, and decision requirements. Future research should prioritize phenology-aware acquisition, independent field validation, uncertainty relative to management thresholds, interoperable prescription and machinery data, and closed-loop evaluation of input use, crop response, yield, and economic return. These steps are needed to move from high-resolution mapping toward reproducible precision management in maize. Full article

Surface ozone (O₃) adversely affects winter wheat production. However, due to the lack of spatially continuous ozone exposure datasets directly linked to crop yield responses, the assessment of ozone-induced crop losses remains uncertain. Winter wheat, a major food crop in China, is highly sensitive to ozone. Its primary cultivation region—the North China Plain (NCP)—overlaps with severe ozone pollution areas, creating significant risk asuperposition. To address this, we employed a spatiotemporal LightGBM (ST-LightGBM) model with ground observations, atmospheric reanalysis, and satellite retrievals to reconstruct a 10 km resolution dataset of daily 7 h average (M7) and daytime accumulated ozone exposure index (AOT40) across China from 2015 to 2022. The model performed robustly; SHAP analysis showed that downward solar radiation and 2 m temperature explained over 42% of ozone variability. From 2015 to 2022, despite pollution controls and the COVID-19 pandemic, surface ozone showed a phased upward trend (0.83 μg m⁻³ yr⁻¹), with O₃ concentrations increasing across 79.22% of the study area and the NCP most affected. Applying M7 and AOT40, the average annual relative yield loss of winter wheat ranged from 3.44% to 7.20% (M7) and from 26.50% to 36.54% (AOT40), corresponding to economic losses of 2.21–4.44 billion USD and 16.16–26.08 billion USD. Both metrics showed consistent trends, but AOT40 losses were substantially higher, highlighting the need to incorporate cumulative high-concentration exposure into agricultural risk assessments. These findings demonstrate that O₃ pollution poses a substantial threat to winter wheat production in China. The reconstructed exposure metrics provide a quantitative basis for identifying high-risk agricultural regions and inform targeted mitigation strategies to safeguard food security under intensifying O₃ pollution. Full article

Epidemiological studies have identified the developing brain as a target of concern for polychlorinated biphenyls (PCBs). In animal models, behavioral deficits caused by developmental exposure to PCBs have been associated with altered patterns of dendritic arborization in functionally relevant brain regions. In vitro studies revealed that PCB 95 promoted dendritic growth in primary rat hippocampal neuron–glia co-cultures via ryanodine receptor 1 (RYR1)-dependent Ca²⁺ signaling. However, it is not yet known whether RYR1 dysregulation contributes to disruption of dendritic morphogenesis in the intact developing brain or whether PCB 95 affects translationally relevant behavioral endpoints in juvenile animals. To address these data gaps, we assessed Morris water maze (MWM) performance and dendritic arborization of hippocampal CA1 pyramidal neurons in C57BL/6 mice heterozygous for the human R163C-RYR1 gain-of-function mutation (HET) and congenic wildtype (WT) littermates exposed to vehicle or PCB 95 at 0.1, 1.0, or 6.0 mg/kg/d in the dam’s diet from conception through weaning. MWM performance was not altered in HET vehicle controls relative to WT vehicle controls; however, compared to genotype-matched vehicle controls, spatial learning was impaired in WT and HET male and female weanlings in the 1.0 mg/kg/d PCB 95 dose group and WT males in the 6.0 mg/kg/d PCB 95 dose group. Spatial memory was altered only in WT females exposed to 1.0 or 6.0 mg/kg/d PCB 95. Sholl analyses of Golgi-stained hippocampal neurons in male and female WT and HET weanlings from the 1.0 mg/kg/d PCB 95 and vehicle groups indicated that relative to WT vehicle controls, basal dendritic arborization was significantly increased in HET vehicle controls and in PCB 95-exposed WT weanlings; however, PCB 95 did not alter basal dendritic growth in HET weanlings relative to genotype-matched vehicle controls. PCB 95 significantly reduced training-induced dendritic arborization in WT but not HET weanlings. Measurement of tritiated ryanodine ([³H]Ry) binding in cortical tissue from these same animals revealed interactions between genotype, PCB 95 exposure, and dose that altered [³H]Ry binding relative to WT vehicle controls. Quantitative analyses confirmed a dose-dependent increase in PCB tissue burden that was not significantly altered by genotype, MWM training, or sex. Serum levels of progesterone, estradiol, cortisol, and thyroid hormone (TH) and brain transcript levels of TH-responsive genes were not significantly altered by genotype or PCB 95 dose. These data demonstrate that PCB 95 caused behavioral deficits coincident with altered patterns of basal and training-induced dendritic arborization. Furthermore, behavioral and dendritic responses to PCB 95 were altered by expression of the human R163C-RYR1 gain-of-function mutation, supporting the involvement of RYR1-dependent mechanisms in PCB 95 DNT in vivo. Full article

Water management is a key factor affecting crop physiology and rhizosphere microbial ecology in protected agriculture. However, the responses of root development and bacterial community structure to different lower irrigation limits and drip irrigation flow rates in coir substrates remain poorly understood. This study investigated greenhouse-grown tomatoes in the Gobi region under three lower irrigation limits (30%, 50%, and 70% of substrate water-holding capacity) and two drip irrigation flow rates (1 and 2 L·h⁻¹). Substrate moisture, root traits, bacterial community structure, co-occurrence networks, and functional potential were evaluated. Increasing the lower irrigation limit maintained higher and more stable substrate moisture and generally enhanced root length, root surface area, root tip number, and root activity. W3Q1 promoted greater spatial expansion of the root system, whereas W2Q2 produced the largest root volume and maintained relatively high root activity. Irrigation combination significantly altered bacterial community structure but had limited effects on bacterial richness. W2Q1 enriched Bacillota-related taxa, whereas W2Q2 enriched Pseudomonadota and exhibited greater bacterial network connectivity and modularity. FAPROTAX-based functional prediction indicated that the bacterial communities were mainly associated with chemoheterotrophy, organic matter decomposition, and nitrogen transformation. Overall, the lower irrigation limit primarily regulated substrate moisture and root traits, whereas the effects of drip irrigation flow rate were trait- and irrigation-limit-dependent, with significant main and interaction effects on root volume. These findings provide a basis for optimizing precision irrigation in coir-substrate tomato cultivation in arid greenhouse systems. Full article

Parameter sensitivity analysis is an important method for quantitatively measuring the contribution of uncertain input variables to structural response outputs, and is of great significance for identifying key parameters in geotechnical constitutive models and simplifying analytical models. To address the limitation that existing parameter sensitivity analyses for rockfill dams are mostly confined to a single section or a limited number of nodal displacements, making it difficult to capture the spatial distribution characteristics of sensitivity, this paper proposes a spatial sensitivity analysis method for rockfill dam material parameters that considers multiple sections and material zoning. The method constructs a surrogate model for structural analysis based on sPCE, employs OMP to reconstruct polynomial basis functions to improve the efficiency of high-dimensional analysis, and quantifies the global sensitivity of each parameter using Sobol indices. In the analysis, multiple transverse and longitudinal sections of the dam body are selected, and a systematic parameter sensitivity analysis is performed for all nodes. Simultaneously, the material zoning of the dam is further considered to reveal the spatial distribution patterns of material parameter sensitivity in each zone. Taking a large concrete face rockfill dam as a case study and the DuncanChang E-B model as the analytical object, the results demonstrate that the sPCE surrogate model maintains good simulation accuracy even with a relatively small sample size (RMSPE < 0.047, MAPE < 0.03, R > 0.88). The parameter sensitivity of displacements in different directions varies across sections, but overall, the parameters n, K_b, and φ₀ exhibit high sensitivity. The high-sensitivity regions are mainly concentrated within the corresponding material zone and exhibit significant spatial distribution characteristics along both the transverse and longitudinal directions. The proposed method reveals the spatial patterns of parameter sensitivity, providing a new reference for material parameter inversion and structural reliability assessment of rockfill dams. Full article

Background: Wastewater and Environmental Surveillance (WES) has become a useful public health tool as an early-warning system revealing emergence/re-emergence of pathogenic diseases and spread of antimicrobial resistance (AMR). We characterized the taxonomic composition, relative abundance, and antibiotic resistance genes (ARGs) of wastewater-identified bacterial pathogens across socioeconomically and epidemiologically diverse sewerage catchments in Nairobi, Kenya—a key East African urban city representing a low- and middle-income country (LMIC). Results: Metagenomic analysis of Nairobi’s wastewater revealed distinct bacterial and antimicrobial resistance (AMR) profiles. Campylobacteraceae (52.5% ± 17.9%) and Bacteroidaceae (19.8% ± 9.9%) dominated the communities. While Arcobacter cryaerophilus was ubiquitous, Bacteroides fragilis and A. suis abundances varied by neighborhood socioeconomic status. We detected critical clinical pathogens—including Escherichia coli, Vibrio cholerae, Mycobacterium tuberculosis, and the ESKAPE species—alongside 207 distinct ARGs conferring resistance to 11 antibiotic classes. Both taxonomic and ARG compositions showed high spatial heterogeneity, with maximum variation in low-income areas. Temporal analysis captured shifting pathogen dynamics, and metagenomic abundances for Vibrio cholerae and Klebsiella pneumoniae were validated via qPCR. Conclusions: Our findings underscore the utility of WES as a scalable, non-invasive public health tool. By capturing community-level pathogen composition and AMR dynamics, WES bypasses the limitations of clinical diagnostic access, providing a vital early-warning system for underserved urban populations. To maximize its public health utility, environmental genomic signals must serve as actionable triggers for coordinated One Health responses, including targeted clinical diagnostics, localized antimicrobial stewardship reviews, proactive risk communication, and prioritized sanitation infrastructure upgrades. Full article

This paper presents an analytical and numerical benchmark verification framework for explicit time integration procedures applied to the one-dimensional wave equation. The study combines an exact analytical solution, a closed-form discrete central-difference solution, and explicit finite element models implemented in LS-DYNA and in the in-house academic FEM code PAK-Multiphysics. Two benchmark problems with the same first sinusoidal spatial mode and homogeneous Dirichlet boundary conditions are considered. The first problem, defined by sinusoidal initial displacement and zero initial velocity, is used to analyse the central-difference discretization and its convergence behaviour. The closed-form discrete response enables direct comparison with the analytical solution and confirms the expected second-order accuracy under coupled mesh and time-step refinement at a fixed Courant number. The second problem, defined by zero initial displacement and sinusoidal initial velocity, introduces a phase-shifted temporal response suitable for explicit finite element verification. Four meshes are analysed over five periods of the first longitudinal mode. The numerical responses are assessed using displacement histories, maximum absolute errors, RMS errors, relative RMS errors, amplitude errors, and an energy check. The PAK-Multiphysics results show very close agreement with the analytical solution and a systematic reduction of the error measures, consistent with the lumped-mass central-difference formulation. The LS-DYNA results provide an independent commercial-code comparison, showing decreasing displacement errors under refinement and bounded total-energy variation. The proposed framework provides a transparent and reproducible benchmark for verifying one-dimensional explicit wave propagation models. Full article

The increasing integration density of electronic packaging places growing demands on electrically insulating materials with improved heat dissipation. Here, molecular dynamics simulations were used to investigate randomly dispersed boron nitride nanosheet (BNNS)/epoxy composites and clarify how BNNS loading affects structure, thermal transport, and thermomechanical response under a fixed crosslinked network. Atomistic DGEBF–TETA epoxy models with a crosslinking degree of 35% were constructed with BNNS loadings of 12, 15, 18, and 21 wt.%. Thermal conductivity was calculated using non-equilibrium molecular dynamics, while density, mesh-derived void fraction, elastic moduli, volumetric thermal expansion, and vibrational density of states were analyzed to connect molecular structure with macroscopic properties. The average thermal conductivity increased monotonically with BNNS loading, reaching 0.53 W/(m·K) at 21 wt.%, approximately 119% higher than neat epoxy. This improvement cannot be explained by density alone. Although composite density increased with BNNS content, surface mesh analysis showed that BNNS incorporation also increased the void fraction relative to neat epoxy, indicating that global densification coexists with local disruption of polymer packing. Spatial analysis further suggested that higher BNNS loadings reduce nanosheet separation, providing qualitative structural information for interpreting the thermal conductivity trend. VDOS analysis showed that BNNS suppresses low-frequency collective motions (0–5 THz) while enhancing intermediate-frequency vibrational modes (5–20 THz), which qualitatively accompanies the loading-dependent thermal conductivity enhancement. Thermomechanical calculations showed an overall increase in Young’s modulus and a reduction in volumetric thermal expansion, whereas shear modulus was less sensitive to BNNS loading. These results indicate that BNNS/epoxy performance is associated with coupled changes in density, local packing disorder, nanosheet distribution, and vibrational response, providing molecular-level guidance for designing thermally conductive and electrically insulating epoxy composites. Full article

Forest fire impacts increasingly reflect coupled environmental and human influences, especially in mountain regions where terrain, vegetation, hydroclimate, and accessibility vary sharply over short distances. We examined the spatiotemporal heterogeneity of forest fire burn severity and its associations with environmental and anthropogenic predictors in Guizhou Province, Southwest China, using fire events from 2003 to 2016 and event-level mean relative differenced Normalized Burn Ratio (RdNBR). The study region supports a heterogeneous subtropical forest mosaic comprising evergreen broadleaved, mixed conifer–broadleaved, subalpine coniferous, and secondary deciduous broadleaved forests. Vegetation, topographic, meteorological, anthropogenic, and socioeconomic variables were integrated, and spatial autocorrelation analysis, nested linear models, random forest modeling, and quantile regression were used to identify consistent predictors and upper-tail responses. Burn severity was right-skewed, dominated by low- and moderate-severity events, with a distinct upper tail of high-severity fires. Interannual variation was not significant, whereas monthly differences were pronounced. Spatial clustering was evident, with hotspots concentrated mainly in central-western and southwestern Guizhou. Across modeling approaches, NDVI and elevation were the most consistent predictors, indicating that vegetation condition and mountain terrain provide the underlying template for burn severity. Meteorological and human-related variables showed weaker mean effects but stronger nonlinear, scale-dependent, and heterogeneous responses. Quantile regression further indicated that high-severity fires were not simply the upper end of average fire behavior, but reflected distinct upper-tail predictor responses. These findings show that severe fire impacts in mountainous subtropical regions are spatially uneven and shaped by coupled vegetation, terrain, weather, and human influences, supporting hotspot-oriented adaptation and risk reduction in regional human–environment systems. Full article

Habitat transition can reorganize plant-associated microbial communities, yet whether rhizosphere bacteria and fungi respond similarly to the transition from native to introduced habitats remains unclear. Here, we investigated this question in the endangered plant Paeonia ludlowii by comparing rhizosphere bacterial and fungal communities across three native and two introduced sites in Xizang. Both bacterial and fungal communities showed significant site-associated differentiation and strongly concordant spatial patterns. However, their responses differed markedly: bacterial richness remained relatively stable despite compositional turnover, whereas fungal communities showed reduced richness at the Lhasa introduction site, lower OTU sharing among habitats, and significantly greater divergence from native assemblages than bacterial communities. Soil pH and available phosphorus were the environmental variables most consistently associated with differentiation in both microbial groups. These findings demonstrate that rhizosphere bacteria and fungi exhibit concordant spatial differentiation but contrasting responses to habitat transition, with fungal communities showing greater departure from native states. This contrast highlights the importance of considering bacterial and fungal communities jointly when evaluating rhizosphere reorganization during the introduction and ex situ conservation of endangered plants. Full article