Abstract:【Objective】Adding organic waste materials into soils significantly affects microbial characteristics, however, the responses of bacterial and fungal diversity, community compositions and their interactions to the addition of different types of organic materials in urban green soils remain poorly understood.【Method】Using mesh bag method, six types of organic materials including green waste (GW), green waste compost (GWC), biogas residue (BR), biogas residue compost (BRC), peat (PT) and biochar (BC) were selected to investigate the effects of organic materials addition on soil properties, microbial communities and co-occurrence network in urban green soils through a 16-month in situ experiment.【Result】The addition of organic materials greatly increased soil electrical conductivity, soil organic carbon, and soil total nitrogen content by 12.7%-49.0%, 34.1%-87.0%, and 4.2%-14.7%, respectively. Soil bacterial alpha (?) diversity did not change among all the treatments, while soil fungal ? diversity was obviously increased after organic materials addition, which was mainly regulated by soil electrical conductivity. The dominant fungi were Ascomycota in urban green soils. Fungal communities in GW and GWC treatments obviously differed from other treatments, which was significantly influenced by soil pH and microbial biomass carbon. In contrast, Proteobacteria, Acidobacteria, Chloroflexi and Fimicutes were abundant in urban green soils. Bacterial communities in BR and BRC treatments were distinctly separated from other treatments, which was primarily driven by the aromaticity index of organic materials. Further analysis of occurrence-network revealed six main ecological clusters. The relative abundances of microbe in each module were different among all the treatments and were significantly correlated with soil nutrients and aromaticity index of organic material. Specifically, the highest relative abundance of bacteria community in module 2, 3 and 4 was observed in BR and BRC treatments, which was positively correlated with dissolved organic carbon, microbial biomass carbon, and soil total nitrogen, indicating that addition of biogas residue and biogas residue compost might enhance soil nutrient availability and subsequently facilitate microbial activity.【Conclusion】This study concludes that adding different types of organic materials can regulate urban green soil microbial community composition and interaction patterns by influencing soil physicochemical properties, thereby altering soil carbon cycling. Organic materials with low aromaticity index, which are more easily decomposed by microorganisms, may accelerate soil carbon cycling, whereas organic materials with high aromaticity index may favor carbon retention in soils. These findings hold significant implications for accurately assessing the resource utilization of urban organic wastes and the improvement of microbial diversity and ecological function in green space soils.

Abstract:【Objective】?Biological nitrogen fixation?, which converts inert nitrogen into plant-available nitrogen, is a critical process for maintaining the soil nitrogen cycle and supporting the productivity of agroecosystems. However, the effect of atmospheric CO2 on biological nitrogen fixation in paddy fields remains poorly understood. Thus, this study aims to elucidate the microbial-driven mechanism of biological nitrogen fixation in paddy soils affected by elevated atmospheric CO2. The findings of this study will provide a scientific basis for the optimization of nitrogen cycling in paddy fields and sustainable nitrogen management in agriculture under climate change scenarios.【Method】In this study, we investigated the microbial-driven mechanism of biological nitrogen fixation in paddy fields by elevated atmospheric CO2 concentration. Two treatments, CK (ambient CO2 concentration) and EC (elevated ambient CO2 concentration by 200 μmol·mol?1) were set up by using an open-top chamber (OTC)-based platform for the automated control of CO2 concentration. Soil physicochemical properties, nitrogen fixation potential (NFP), and the abundance and community composition of nitrogen-fixing bacteria (nifH gene) of paddy soils were analyzed by microcosmic cultivation, real-time quantitative PCR, and high-throughput sequencing.【Result】The results showed that across the whole rice plant growth period and compared with CK, EC treatment significantly increased the microbial biomass nitrogen (MBN) content by 3.3% and significantly decreased the NH4+?N content by 11.6%. Also, the NFP and nifH gene abundance were significantly increased by EC treatment. At the maturity stage, the community structure of the nifH gene in the EC treatment changed significantly compared with CK. In addition, the TN content was positively correlated with NFP, which was regulated by soil MBN content, SOC content, and nifH gene abundance.【Conclusion】This study reveals that elevated atmospheric CO2 concentration increased soil MBN content and nifH gene abundance, enhanced NFP, and increased the nitrogen content of paddy soils.

Abstract:【Objective】Cover crops are very important for regulating soil structure and enhancing soil organic carbon. Cover crops can improve soil pore structure by creating biopores through root penetration and subsequent decomposition. However, the effects of different cover crops on organic carbon accumulation and microbial communities in biopore sheaths remain unclear. 【Method】A field experiment was conducted in a typical Shajiang black soil, including four winter cover crop treatments (fallow, alfalfa, rapeseed, and a mixture of radish + hairy vetch) in rotation with summer maize. Soil organic carbon (SOC) and total nitrogen (TN) contents in the biopore sheaths of the 20–40 cm soil layer under different treatments were determined, while bacterial and fungal community structures were analyzed via high-throughput sequencing. 【Result】The results showed that, compared with bulk soil, SOC content in the biopore sheaths increased significantly by 33.4% under the alfalfa treatment, while TN content increased significantly by 24.6% and 18.5% under the alfalfa and radish + hairy vetch treatments, respectively. However, no significant differences in SOC and TN contents of the biopore sheath were observed among different cover crops. The microbial community structure varies significantly with the interaction between cover crop species and soil habitats. The bacterial α-diversity indices and niche breadth indices in biopore sheaths were significantly higher than those in bulk soil, particularly in the radish + hairy vetch treatment, whereas no significant differences were observed in fungal communities between the two soil compartments. Furthermore, microbial communities within biopore sheaths exhibited a shift toward copiotrophic taxa compared with bulk soil. The relative abundance of Pseudomonas and Bacillus was higher in alfalfa-derived biopore sheaths than in other treatments. Correlation analysis indicated that the relative abundance of core microbial taxa involved in carbon decomposition and transformation was significantly positively correlated with SOC content. 【Conclusion】In summary, SOC and TN contents in the biopore sheaths under the alfalfa treatment significantly increased. SOC content may regulate microbial community structures within biopore sheaths by influencing bacterial α-diversity indices, niche breadth indices, and the relative abundance of core microbial taxa.

Abstract:【Objective】Phosphorus solubilizing bacterial communities in the rhizosphere are critical functional components in soil phosphorus cycling. Their abundance, community composition, and diversity determine the activity of soil alkaline phosphomonoesterase (ALP) and phosphorus availability. Thus, this study aimed to explore the impact of different bio-fertilization regimes on phosphorus-solubilizing bacterial communities in red soil and maize productivity. 【Method】Based on a long-term (11-year) bio-fertilization experiment at the Yingtan Red Soil Ecological Experiment Station of the Chinese Academy of Sciences, four treatments were selected: chemical fertilizer + organic fertilizer (FO), FO + phosphate-solubilizing bacteria (FOP), FO + nematodes (FON), and FO + phosphate-solubilizing bacteria + nematodes (FOPN). Quantitative real-time PCR (qPCR) and high-throughput sequencing technologies were employed to elucidate the mechanisms through which biological amendments affect rhizosphere phosphorus solubilizing bacterial communities, ALP activity, and maize productivity. 【Results】(1) Compared with the FO treatment, bio-fertilization treatments (FOP, FON, FOPN) significantly improved soil fertility and maize yield, with the combined inoculation treatment (FOPN) showing the most pronounced effects. Soil organic carbon (SOC), total nitrogen (TN), available nitrogen (AN), available phosphorus (AP), and maize yield increased by 8.08%, 24.2%, 30.5%, 20.2%, and 39.7%, respectively. (2) Bio-fertilization significantly increased the abundance of rhizosphere phosphorus solubilizing bacteria, showing notable interactive effects, while the Shannon index remained consistently lower than that in the FO treatment. The abundance of phosphorus-solubilizing bacteria exhibited significant positive correlations with TN and AN. (3) AN, phosphorus solubilizing bacterial abundance and ALP activity were identified as the key drivers of maize yield. Structural equation modeling revealed that AN not only directly promoted maize yield but also indirectly enhanced yield by increasing phosphorus-solubilizing bacterial abundance and ALP activity. 【Conclusion】Bio-fertilization significantly increased phosphorus solubilizing bacterial abundance, suggesting that microbial population dynamics may regulate phosphorus uptake in maize. These amendments enhanced upland red soil fertility by indirectly promoting phosphorus solubilizing bacterial abundance and ALP activity, thereby facilitating organic phosphorus mineralization and maize growth.

Abstract:Effective soil layer thickness is a decisive indicator for evaluating soil health and productivity, and accurate depiction of the spatial distribution pattern of effective soil layer thickness and its response mechanism to land use change and surface matrix type is of great significance for the sustainable protection of soil resources. In this paper, we selected the black soil area in the eastern part of Inner Mongolia as the study area, and based on the surface matrix survey data and soil-landscape modeling, we carried out the digital mapping and spatial pattern analysis of effective soil layer thickness in this area, identified the main controlling factors of spatial variability of effective soil layer thickness through SHAP analysis, and ascertained the differential distribution pattern of effective soil layer thickness under different land use types and surface matrix zoning. The results showed that the regression model of effective soil thickness based on Cubist had good performance (R2=0.5,RMSE=43.8), and the generated spatial distribution map could accurately reveal its spatial pattern. SHAP analysis revealed that topographic and climatic factors were the main controlling factors determining the spatial variability of the effective soil thickness, which was specifically reflected in the fact that the high elevation areas within the same watershed were affected by the erosion, and the soil layer was thinner; while the monthly average soil thickness was lower than the monthly average soil thickness, and the monthly average soil thickness was lower than the monthly average soil thickness, which was lower than the monthly average soil thickness. The effect of mean monthly temperature extremes on the effective soil layer thickness was positive. Both surface substrate zoning and land use types have important constraints on the spatial characteristics of the effective soil layer thickness, with the overall soil layer thickness in the residual slope deposit area being greater than that in the slope floodplain and slope deposit areas, and the soil layer thickness in cropland being significantly lower than that in woodland and grassland due to soil disturbance by high-intensity cultivation. The mean values of effective soil layer thickness in different surface substrate zones were in the order of residual slope deposits>slope flood deposits>slope deposits. This paper provides a methodological reference for the spatial modeling and characterization of effective soil layer thickness, and the results of the study can provide a data basis for identifying the background conditions of regional natural resources and their response mechanisms to human interactions.

Abstract:The growth and evolution of biofilms in porous media involve complex coupled physicochemical and biological processes. Their pronounced multi-scale characteristics, heterogeneity of the media, and uncertainties in model parameterization have led to fundamental divergences in the theoretical frameworks of numerical models across different scales. This poses significant challenges for the accurate characterization and prediction of biofilm dynamics. In recent years, advances in computational techniques have driven substantial progress in pore-scale, continuum-scale, and cross-scale coupled numerical modeling and simulation of biofilm growth. However, considerable bottlenecks remain in model development, validation, and utilization. These include difficulties in characterizing three-dimensional microscopic pore structures, the complexity of constructing biofilm growth dynamics models, the lack of quantitative standards for cross-scale multiprocess coupling strategies, and the scarcity of experimental data required for model parameterization. Based on the mechanisms of biofilm growth dynamics in porous media, this paper reviews the research progress of pore-scale, continuum-scale, and multi-scale coupling numerical models, analyzes the theoretical foundations, numerical algorithms, application cases, applicability, and limitations of biofilm growth models at different scales. It also summarizes the application potential of three-dimensional imaging technologies, outlines the emerging trends in mechanistic representation of the complete biofilm growth processes, and explores the optimization pathways for cross-scale coupling modeling strategies. This review provides a theoretical basis for the selection and improvement of biofilm growth models, and offers technical support for the engineering application of soil microbial technologies in environmental pollution control and ecological restoration.

Abstract:【Objective】This study aimed to clarify the effects of organic-inorganic regulating material mulching on the pore structure of saline-alkali topsoil and select suitable mulching materials for crop seed germination.【Method】Four experimental treatments were set up, namely CK (native soil), JX1 (composted cow dung + (a mixture of HA, CaO, MgO, SiO?, and Na?SeO?)), JX2 (spent substrate + (a mixture of HA, CaO, MgO, SiO?, and Na?SeO?)), and JX3 (composted straw + (a mixture of HA, CaO, MgO, SiO?, and Na?SeO?)). A field operation involving digging V-shaped ditches→sowing→applying amendments→rolling was adopted. Soil structure and its pore characteristics were analyzed using micro-computed tomography (micro-CT) scanning, combined with field experiments and mathematical statistical analysis.【Result】The results showed that all treatments reduced soil bulk density and improved soil water capability and saturated hydraulic conductivity. Specifically, the saturated hydraulic conductivity of JX2 and JX3 was 2.4 times that of CK, and their soil water capability increased by 17.8%–19.5%. In terms of pore structure, different mulching material significantly affected the quantity and distribution characteristics of soil pores: The JX2 and JX3 showed significantly increased total porosity and connected porosity, while JX1 had lower total porosity; JX3 was dominated by macropores with fewer micropores, whereas JX2 had a more balanced pore size distribution. Comparison of pore structure parameters revealed that JX2 and JX3 had similar values of fractal dimension, anisotropy, and circularity ratio, but the Euler number of JX2 was significantly lower than that of JX3. This indicated that both treatments enhanced the complexity and stability of the pore structure, and JX2 had better pore connectivity. These pore structure optimizations significantly improved the microenvironment for seed germination, thereby increasing the emergence rate and improving the seedling growth traits of foxtail millet, with JX2 showing particularly notable effects.【Conclusion】In conclusion, Organic-inorganic amendment mulching can enhance soil structural performance by optimizing the pore characteristics of saline-alkali soil and create a suitable soil microenvironment for crop seed germination. Among the tested materials, the spent mushroom substrate residue-based (JX2) and straw-based (JX3) regulating materials showed showed the most significant effects.effects, These combinations are effective technical approaches for efficiently regulating the microenvironment of coastal saline-alkali soil and breaking surface soil compaction.

Abstract:【Objective】 Straw return is vital for improving soil structure, controlling erosion, and mitigating degradation. Nevertheless, the low straw decomposition efficiency under natural conditions greatly limits its widespread application. As a critical measure to promote straw decomposition, investigating the impacts of straw returning combined with decomposition agents on soil erosion resistance of medium-low yield sloping farmland, as well as the underlying mechanisms, holds significant importance for applying soil and water loss control measures that integrate the resource utilization of agricultural waste.【Methods】 A field in-situ monitoring experiment was conducted under the condition of full straw return. With no decomposition agent application as the control, four straw decomposing agents were co-applied with straw at rate of 1, 2, 3, and 4 kg·hm-2 and designed based on the viable bacterial count of the decomposer. The differences in soil erosion resistance and their dominant influencing factors under varying decomposer application rates were clarified.【Results】 The application of straw decomposition agent significantly promoted straw decomposition efficiency and improved soil structure. The straw decomposition amount and efficiency increased significantly with the increase in the application rate of the decomposition agent. Also, application of decompositing agent significantly reduced soil silt and clay contents, while significantly increasing soil sand content, saturated water content, field capacity, and organic matter content. Moreover, the soil erosion resistance was significantly improved with the application of straw decomposition agent. Compared to the control, the comprehensive soil resistance index (CSRI) increased by 43.24% ~ 360.77%. In addition, the results of PLS-SEM showed that the increase of CSRI was mainly governed by the direct binding and consolidation of residual straw (path coefficient 0.43) and the indirect effect of straw decomposition on the increase in soil organic matter content (path coefficient 0.40).【Conclusion】 Straw return combined with straw decomposition agents significantly increased soil erosion resistance of medium-low yield purple sloping farmland. Moreover, the direct effects of residual straw in enhancing soil erosion resistance slightly outweigh its indirect effects in increasing soil organic matter content via decomposition. However, a significant increase in CSRI was only detected when the application rate exceeded 3 kg·hm-2. This indicates that effective enhancement of erosion resistance requires a threshold application rate exceeding 3 kg·hm-2 for decompositing agents. These findings provide scientific guidance for the sustainable utilization of medium- low-yield purple soil sloping farmland and the green and high-quality development of the Yangtze River Economic Belt.

Abstract:【Objective】Rapid and accurate estimation of soil organic matter (SOM) is crucial for assessing soil fertility, guiding sustainable agricultural management, and supporting carbon accounting at regional and global scales. SOM is a key indicator of soil quality, influencing nutrient cycling, microbial activity, crop productivity, and soil carbon sequestration potential. While reliable, traditional chemical analysis methods are costly, time-consuming, and destructive, making them unsuitable for large-scale or repeated monitoring. Visible and near-infrared (Vis-NIR) spectroscopy provides a rapid, non-destructive, and environmentally friendly alternative for SOM assessment. However, the effectiveness of Vis-NIR spectroscopy is often limited by spectral noise, baseline drift, and low sensitivity to absorption features associated with organic components. Therefore, developing advanced spectral transformation and modeling strategies that can enhance weak spectral signals and extract effective features related to SOM is essential. This study aims to construct a collaborative modeling framework combining fractional-order derivative (FOD) transformation and spectral indices to improve the interpretability and predictive accuracy of Vis-NIR spectral data from typical black soil regions in Northeast China.【Methods】A total of 227 soil samples were collected from representative farmland in the black soil region, an important grain-producing area in Northeast China. The reflectance spectra and SOM content were obtained in the laboratory. The spectral data were processed with FOD ranging from 0 to 2.0 (increment by 0.1 at each step). Two-dimensional (2D) and three-dimensional (3D) spectral indices were calculated to explore the interaction information between different wavelength combinations. The correlation between each spectral index and SOM content was analyzed to determine the most sensitive index. Two machine learning algorithms—random forest (RF) and Cubist—were used to construct prediction models. The input datasets were divided into two categories: (1) FOD-transformed reflectance (FOD dataset); and (2) spectral indices that were most strongly correlated with SOM (index dataset). Four models were thus constructed: FOD-RF, Index-RF, FOD-Cubist, and Index-Cubist. Ten-fold cross-validation was used to evaluate the performance of the model, and the determination coefficient (R2) and root mean square error (RMSE) were used as evaluation indexes. In addition, this study also analyzes the importance of model characteristics to determine the key wavelength or exponential combination that is helpful for SOM prediction.【Results】FOD transform significantly improved the spectral interpretability and enhanced the detection of weak organic absorption characteristics in the Vis-NIR band. The Cubist model with the 0.3-order derivative spectrum exhibited the best performance and provided a validation R2 of 0.74. The RF model performs best at higher derivatives (1.6-1.9), and the R2 value remains between 0.63 and 0.65. In addition, the correlation between 3D spectral index and SOM is stronger than that of 2D index, and 3D spectral index improves the interpretability of features. The characteristic importance analysis showed that the most sensitive spectral regions predicted by SOM were located within 1410-1880 nm and 2200-2350 nm, corresponding to the overtone and combined vibration of C-H, N-H and O-H functional groups.【Conclusion】The combination of FOD preprocessing and spectral index provides a robust, flexible and scalable framework for estimating SOM using Vis-NIR spectroscopy. This study emphasizes a promising direction in the field of intelligent soil remote sensing monitoring and information technology, and provides methodological progress for digital soil mapping, precise nutrient management and sustainable land management. Its application potential is not only limited to the prediction of SOM, but also extended to a wider range of soil property assessment, which provides a theoretical and technical basis for the construction of intelligent soil information system to support the sustainable development of agriculture in major grain producing areas such as northeast China.

Abstract:A healthy soil is the foundation for ensuring food security and serves as a core pillar for achieving agricultural green development. However, current intensive agricultural systems are primarily focused on maximizing crop yields, relying heavily on high-yielding crop varieties and external inputs such as synthetic fertilizers and pesticides. This overreliance often overlooks the impact of crops and field management practices on soil health, leading to various forms of soil degradation that negatively affect crop productivity and food quality. Drawing on the ecological concept of plant-soil feedback (PSF), this paper proposes a new systematic research paradigm that places soil health as the key to the co-improvement of farmland quality and crop productivity. Future sustainable agriculture urgently requires the development of system-based strategies and solutions grounded in PSF theory, integrating aboveground crop management with belowground soil processes in a tightly coupled manner. By elucidating the reciprocal interactions among different components of the soil ecosystem, we can develop soil health management technologies based on positive plant-soil feedback, thereby enhancing the synergy between productivity and other soil multifunctionalities. Specifically, at the individual plant level, modern molecular breeding and functional genomics can be leveraged to modify root architecture, root exudate composition, and signal transduction properties in a targeted way. This enables the precise recruitment of beneficial microbes and suppression of pathogens, triggering cascade amplification effects that reinforce positive feedback loops and mitigate negative ones. At the field management level, integrated strategies such as crop-microbiome holobiont breeding, optimized nutrient management, conservation tillage, and diversified cropping systems can promote beneficial interactions between crops and soils. These approaches reduce dependence on external inputs, improve internal system efficiency, and ultimately achieve the co-enhancement of crop yield and soil health.

Abstract:【Objective】The plough layer of fluvo-aquic soil is shallow, while the subsoil is hard and compacted, exhibiting significant structural obstacles. Tillage and straw return are key measures for improving soil structure; however, the mechanism through which the combination of these agricultural practices affects soil structure remains elusive. 【Method】Undisturbed soil columns (20 cm height × 10 cm diameter) were collected from a fluvo-aquic soil experimental site at the Shangqiu Station of the national field Agro-ecosystem experimental network. The samples represented plots under rotary tillage (RT), deep ploughing (DP), and biennial deep ploughing (BDP), with and without straw returning. X-ray computed tomography (XCT) scanning, ImageJ software, and machine learning techniques were employed to perform three-dimensional reconstruction and visualization of the soil pore structure. The effects of different tillage methods and straw treatments on macroporosity, pore size distribution, pore morphology, network characteristics, saturated hydraulic conductivity, and air permeability were quantitatively analyzed. 【Result】Without straw return, deep ploughing and biennial deep ploughing increased macroporosity by 31.5% and 5.7%, respectively, compared to rotary tillage. With straw return, deep ploughing significantly increased macroporosity by 92.9% and 68.4% compared to rotary tillage and biennial deep ploughing, respectively (P < 0.05). Furthermore, the hydraulic radius increased significantly by 53.8% and 42.9%, respectively. Compactness increased significantly by 1.5 and 2.9 times, and global connectivity increased significantly by 12 times. Both saturated hydraulic conductivity and air conductivity were significantly enhanced (P < 0.05). 【Conclusion】 Deep ploughing increased the hydraulic radius of soil pores, improved connectivity, and enhanced pore network complexity, thereby constructing a relatively favorable soil pore morphology and network structure. This enhanced hydraulic and air conductivity, significantly reducing the structural obstacles in fluvo-aquic soil.

Abstract:【Objective】Soil resilience refers to the ability of soil to restore its original properties and functions after being disturbed by anthropogenic or climate change. It is an important ecological indicator for achieving the sustainable utilization of soil resources. This paper aims to construct a soil resilience evaluation system suitable for large-scale applications and assess the spatial distribution characteristics of soil resilience in China. 【Method】Based on existing research results, this study refines the logic of index construction, determines four dimensions: soil properties, climatic factors, topographic influences, and biological characteristics, and sets a total of nine specific indicators. The Analytic Hierarchy Process (AHP) is used to determine the weights of the indicators, and weighted superposition analysis is conducted to form a national spatial distribution map of soil resilience. 【Result】The results show that soil resilience in China presents a spatial pattern that gradually increases from West to East and from North to South. Nationwide, soils with high and relatively high resilience account for 25% and 39%, respectively, mainly concentrated in South and Southwest China. The areas with relatively low resilience include the Gansu and Xinjiang regions and the Loess Plateau Area. 【Conclusion】The research provides technical support and decision-making basis for establishing the evaluation of specific soil functions at the macroscopic scale in China at the theoretical and methodological level.

Abstract:【Objective】The argillic horizon is a subsurface secondary layer formed by the accumulation of soil clay particles, and its thickness exerts a crucial regulatory effect on soil processes and vegetation growth in Alfisols. Understanding its spatial distribution is critical for effective land management, particularly in agriculturally important regions such as Northeast China. However, there is still limited knowledge of the spatial variability in argillic horizon thickness, and predictive studies on this topic are scarce. Traditional understanding has largely relied on extensive field surveys combined with geostatistical methods, which are often resource-intensive and may not be efficient over large regions. This study aims to develop a robust predictive model to map the spatial distribution of argillic horizon thickness across the three northeastern provinces of China by integrating limited soil profile observations with a rich set of environmental covariates. 【Method】A total of 311 soil profile samples with argillic horizons were collected in Northeast China. These samples incorporated data from recent field surveys and historical soil records. Consistent with the SCORPAN framework, 71 environmental covariates were selected to correspond to relief, climate, organism, and soil factors. Dual feature selection was conducted via Pearson correlation analysis and the Boruta algorithm. The quantile regression forest (QRF) model was then adopted for spatial modeling, cross-validation, and uncertainty estimation. Rigorous evaluation of model performance and uncertainty estimation was conducted through 50 repetitions of 10-fold cross-validation, and accumulated local effects (ALE) plots were generated to interpret the relationship between key predictors and the target variable. 【Result】The average results from 50 iterations showed that the model achieved a coefficient of determination (R2) of 0.32, a root mean square error (RMSE) of 24.34 cm, and a mean absolute error (MAE) of 19.47 cm. This performance is significantly superior to that of most regional and national scale soil thickness prediction studies (R2 = 0.11–0.41). The prediction interval coverage percentage (PICP) was 86.2%, which is close to the predefined 90% prediction interval (PI), indicating high reliability of the uncertainty estimation. Soil and climate factors were generally more influential than organism and relief factors, with soil thickness (ST) identified as the most critical driving factor. The spatial prediction results indicated a distinct decreasing trend in argillic horizon thickness from the southwest to the northeast. The western and southwestern regions of the study area exhibited the thickest argillic horizons (mostly over 80 cm, with some regions ranging from 100 to 125 cm), while the northern, eastern, and southeastern regions had thinner ones (mostly 20–35 cm, with some regions below 20 cm). High prediction uncertainty was concentrated in mountainous and hilly regions with sparse soil survey points. 【Conclusion】This study confirms the feasibility of mapping argillic horizon thickness using a machine learning approach combined with environmental covariates, even in large, complex landscapes with limited soil observations. Future research could focus on integrating proxies for parent material and pedogenic age to enhance model accuracy, as well as exploring the spatial prediction of other argillic horizon properties (e.g., upper boundary and compactness). This study not only addresses the gap in argillic horizon thickness prediction in Northeast China, but also offers valuable insights for optimizing regional land management strategies.

Abstract:【Objective】Poly(butylene adipate-co-terephthalate) (PBAT) serves as a crucial alternative to conventional plastic mulch films. However, the presence of aromatic chains renders PBAT more recalcitrant to biodegradation compared to other biodegradable plastics (e.g., polylactic acid). Moreover, there are limited microbial resources exhibiting efficient PBAT degradation capabilities.【Method】This study employed a soil-compost enrichment approach to screen high-efficiency PBAT-degrading microbial strains. Microbial consortia were enriched at 60 ℃ under thermophilic composting conditions using PBAT as the sole carbon source, yielding six candidate strains (designated B1-B6). Degradation efficacy was comprehensively evaluated through mass loss, surface morphology analysis, and water contact angle measurements.【Result】Strain B3 demonstrated superior PBAT degradation efficiency, achieving a 17.85%±11.22% mass loss within 7 days, exceeding currently reported values for PBAT-degrading microorganisms. Atomic force microscopy (AFM) analysis revealed significant surface modification across all treatment groups, with B3-exposed PBAT exhibiting the most pronounced surface roughness (Ra = 44.84±26.48 nm). Concurrent physicochemical characterization showed a 15.6° reduction in water contact angle, collectively indicating substantial polymer matrix alteration. Taxonomic identification through 16S rRNA gene sequencing classified strain B3 as?Parageobacillus toebii.?In addition, characterization of the degradation performance of the mixed microbial consortium (designated as MIX) showed that MIX achieved a PBAT degradation rate of 12.48%±1.11%. Although the impact on surface roughness of PBAT was relatively minor, MIX induced the most significant changes in water contact angle, indicating a pronounced degradation effect. High-throughput 16S rRNA sequencing analysis revealed that, at the species level, the dominant strain within the MIX consortium was Parageobacillus toebii, accounting for 98.50% of the population. Other minor constituents included Aeribacillus pallidus (1.45%), unclassified_g_Lactobacillus (0.01%), unclassified_c_Bacilli (0.02%), unclassified_k_norank_d_Bacteria (0.01%), and unclassified_g_Clostridium_sensu_stricto_1 (<0.01%). These findings suggest that the PBAT degradation capability of the MIX consortium is primarily attributed to Parageobacillus toebii. Through whole genome sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) gene function annotation, it was identified that strain B3 possesses genes encoding enzymes relevant to PBAT degradation, including carboxylesterase, arylesterase, long-chain acyl-CoA synthetase, aldehyde dehydrogenase, alcohol dehydrogenase, and catechol 2,3-dioxygenase. Based on the above results, the potential degradation pathway of PBAT microplastics by the degrading microbes could be inferred as follows: (1) Initial hydrolysis: PBAT ester bonds are first cleaved by carboxylesterases, releasing intermediate products such as terephthalic acid and adipic acid. (2) Aliphatic chain metabolism: Adipic acid is activated into its CoA derivative by long-chain fatty acid-CoA ligase and subsequently undergoes β-oxidation catalyzed by acyl-CoA dehydrogenase to form acetyl-CoA. Short-chain aldehyde/alcohol byproducts generated during aliphatic chain metabolism are further degraded by aldehyde dehydrogenase and alcohol dehydrogenase. (3) Aromatic ring degradation and ring-cleavage: Terephthalic acid undergoes hydroxylation to form catechol, which is then cleaved by dioxygenases, producing intermediates that enter the tricarboxylic acid cycle.【Conclusion】This study successfully isolated Parageobacillus toebii B3 as a high-performance PBAT degrader through multi-parametric characterization (mass loss, surface topography, and hydrophilicity changes). The findings provide both theoretical foundations and practical microbial resources for controlling biodegradable microplastic pollution.

Abstract:【Objective】Thermal desorption technology is widely applied in the remediation of petroleum-contaminated soil. However, the significant differences in the thermal desorption characteristics due to different types of clay mineral, significantly impact the setting of process parameters and the efficiency of thermal desorption. Thus, this study aims to clarify the differences in thermal desorption mechanisms among various petroleum-contaminated clay minerals and to guide the determination of application parameters for thermal desorption engineering.【Method】In this study, contaminated soil with typical clay minerals including montmorillonite, chlorite and kaolinite were prepared to investigate the thermal desorption kinetic properties, and characterize their microstructures to explore the differences in thermal desorption and the influencing factors. 【Result】The results showed that the thermal desorption of three contaminated soil could be divided into three stages. Phase I (30 ℃-110 ℃), in this phase, montmorillonite and chlorite exhibited a three-dimensional diffusion desorption mechanism, while kaolinite followed a first-order kinetic desorption mechanism. The activation energies (Ea) were 58.64, 124.96 , and 75.22 kJ mol-1, respectively. Phases II (110 ℃-370 ℃) and III (370 ℃-520 ℃) followed a first-order kinetic mechanism. 【Conclusion】The physicochemical properties and microstructure of clay minerals are the main parameters accounting for the differences in their thermal desorption characteristics. Montmorillonite mainly relied on azeotropic stripping, diversion diffusion, catalytic cracking, and interlayer structure adsorption, which promoted the thermal desorption of petroleum hydrocarbons. The influencing mechanism of chlorite involved physical barrier and catalytic cracking, showing an inhibitory effect at temperatures <200 ℃. However, thermal desorption of petroleum hydrocarbons was promoted when the temperature was >200 ℃. The influencing mechanism of kaolinite was mainly chemical adsorption, which generally inhibited the thermal desorption of petroleum hydrocarbons. This study provides theoretical guidance for determining the thermal desorption process parameters of petroleum-contaminated soils containing different types of clay minerals.

Abstract:【Objective】This study aimed to investigate the synergistic effects of different water and fertilizer treatments on the physicochemical properties, bacterial community structure, and ion transport function of saline-alkali maize fields, thereby providing a theoretical basis for their targeted improvement. 【Method】A field experiment was conducted in saline-alkaline land in Pingluo County, Ningxia. A split-plot design was used with two irrigation levels as main plots: conventional irrigation (w1, 6 000 m3hm-2) and water-saving irrigation (w2, 4 800 m3hm-2)， and four fertilization modes as sub-plots: f1 (nitrogen fertilizer alone), f2 (nitrogen with controlled-release fertilizer), f3 (nitrogen with organic fertilizer), and f4 (controlled-release fertilizer with organic fertilizer). Soil physicochemical properties were measured. Bacterial community structure was analyzed by 16S rRNA high-throughput sequencing, and the abundance of ion transporter genes was predicted using PICRUSt2 software. 【Result】Water-saving irrigation w2 exhibits no significant difference in its impact on soil physicochemical properties compared to conventional irrigation w1. Compared with w2f1 treatment, the w2f3 treatment significantly increased the contents of soil organic matter (SOM), total nitrogen, alkaline hydrolyzable nitrogen, available phosphorus, available potassium, and Ca2+ (P<0.05), while significantly decreasing pH, electrical conductivity, and Na+ content (P<0.05). The water-fertilizer interaction had highly significant effects on the contents of sodium, magnesium, potassium, and calcium ions (P<0.01). Microbial analysis showed that the w2f4 treatment significantly increased the Simpson diversity index and Pielou evenness index (P<0.05). At the phylum level, w2f3 and w2f4 significantly increased the relative abundance of Proteobacteria and Actinobacteria, while decreasing the relative abundance of Acidobacteria (P<0.05). At the genus level, Kaistobacter and Lysobacter were the dominant genera, and their abundance was significantly increased by the w2f3 treatment (P<0.05). Linear discriminant analysis effect size analysis identified 32 biomarker species across five phyla, with w2f3 significantly enriching Proteobacteria and Bacteroidota. Prediction of ion transporter genes indicated that the w2f3 treatment simultaneously activated the magnesium transporter gene CorA and the Na+/H+ antiporter gene nhaA. The ecological dominance of Proteobacteria was positively regulated by KefB and CorA. Mantel test confirmed that SOM and pH were the core environmental factors driving the evolution of the microbial community structure.【Conclusion】Under water-saving irrigation, the combined application of nitrogen fertilisers with organic fertilisers (w2f3) achieves systematic restoration of ecological functions in saline-alkali soils by synergistically enhancing soil fertility, optimising bacterial community structures, and activating ion homeostasis networks. This provides both theoretical and technical underpinnings for the efficient remediation of saline-alkali land.

Abstract:【Objective】Litter quality is a key factor regulating the intensity and direction of the soil priming effect. However, it remains unclear whether inputs of litter from different organs of the same plant or litter with different carbon to nitrogen ratios (C/N) from the same organ differentially impact soil priming effect, as well as the underlying mechanisms.【Method】To address this gap, 13C-labeled seedlings of Phoebe bournei were used as study materials. Through fertilized and non-fertilized treatments, leaf, stem, and root tissues with low and high C/N ratios were obtained to investigate the effects of litter inputs with different C/N ratios on soil priming. Soil microbial biomass, enzyme activity, and soil available nitrogen contents (NH4+-N and NO3--N) were measured concurrently to elucidate the underlying mechanisms.【Result】After 180 days of incubation, the addition of high and low C/N ratio leaf litter and low C/N ratio root litter inhibited the mineralization of soil organic carbon (SOC) by about 11.09%, 9.05% and 8.07%, respectively, inducing a significant negative priming effect. However, the other treatments did not cause significant priming effects. The influence of different C/N ratios in the same organ of Phoebe bournei on soil priming effect was primarily observed within the first 8 days of incubation, with high C/N ratio litter inducing a stronger negative priming effect than low C/N ratio litter. The reason is that high C/N ratio litter input caused microbial nitrogen (N) immobilization, reducing soil available N content, which led to N limitation and suppressed microbial activity, thereby decreasing SOC decomposition. In the later stages of incubation, the effects of different C/N ratio litter on soil microbial biomass carbon and carbon metabolism-related enzyme activities were not significant, so the influence of C/N ratio on soil priming gradually diminished. Among different plant organs, leaf litter induced a stronger negative priming effect than root litter. Specifically, the negative priming effect induced by leaf addition weakened over time, while root addition continuously induced a negative priming effect. Stem addition caused a priming effect that fluctuated between positive and negative, but the cumulative effect offset, resulting in no significant change in SOC decomposition.【Conclusion】The impact of Phoebe bournei litter input on soil priming effect varied significantly among organs, whereas the influence of litter C/N ratio on soil priming effect was mainly concentrated in the early stages of litter decomposition. The main mechanism by which leaf litter induced a negative priming effect was through reducing soil available nitrogen, which inhibited microbial activity, thereby decreasing SOC decomposition. In contrast, the negative priming effect induced by low C/N ratio roots was because their high lignin content and low bioavailability, causing C limitation for microorganisms during decomposition, leading to reduced SOC decomposition.

Abstract:【Objective】Soil eukaryotes are key indicator organisms for soil health in ecosystems, and changes in their diversity and community structure can effectively reflect the evolution of soil quality. In high-throughput sequencing-based studies on eukaryotic diversity, the selection of amplification primers directly affects the number of sequences of detected taxa, thereby determining the accuracy of biodiversity assessment. However, the impact of primer selection on the assessment of soil eukaryotic diversity remains timidly explored.【Method】 This study focused on soils from seven typical urban land use types in Ningbo City. Amplification was only conducted for two pairs of widely used 18S-rRNA gene V4 region primers (NF1F_18Sr2bR, TAReuk454FWD1F_TAReukREV3R). The study systematically compared the effects of different primers on the assessment of soil eukaryotic community composition and diversity, and analyzed the differences between two bioinformatic methods: Amplicon sequence variants (ASVs) and operational taxonomic units (OTUs). 【Result】That the proportion of amplification in eukaryotes for the NF1F_18Sr2bR primer was significantly higher than that of TAReuk454FWD1F_TAReukREV3R. Different primers exhibited a preference for specific soil eukaryotic taxonomic groups. Specifically, at the ASVs level, the NF1F_18Sr2bR primer preferred fungi, protozoa, nematoda, arthropoda, and annelida; at the OTUs level, the TAReuk454FWD1F_TAReukREV3R primer preferred protozoa and arthropoda, while the NF1F_18Sr2bR primer preferred nematoda, and annelida. Among the primers, NF1F_18Sr2bR was more appropriate for detecting rare species. The rare species of fungi, nematoda, and annelida amplified by this primer accounted for 12.09%, 38.31%, and 58.33% of their total sequences, respectively. In contrast, TAReuk454FWD1F_TAReukREV3R was more suitable for detecting shared species, as it detected 804 shared species OTUs across different land use types, which was higher than that detected by the other primer. Both primer selection and analytical methods collectively determine the differences in α-diversity assessment, but they do not determine the variations in β-diversity or the effects of environmental factors on community structure. In terms of α-diversity, for both primer pairs, the differences in α-diversity among different land uses were greater at the ASV level than at the OTU level. With respect to β-diversity, the explanatory power of the OTUs level for community diversity was higher than that of the ASVs level. 【Conclusion】This study revealed the critical impact of primer selection on the assessment of soil eukaryotic diversity. In future studies, primers and analytical methods should be selected appropriately based on target taxa and research objectives to ensure the accuracy of community structure and diversity assessment.

Abstract:【Objective】Soil gross nitrogen (N) transformation processes are fundamental and critical components of terrestrial N cycling. However, the mechanisms controlling gross N transformation rates and their controlling factors across soils with contrasting properties and land uses remain underexplored.【Method】Seven typical soils from three major ecosystems in China were selected: forest (Changsha, Linzhi, Chongqing), grassland (Duolun, Bayanbulak), and upland (Shangzhuang, Quzhou). A short-term incubation experiment was conducted using the?1?N isotope dilution technique combined with a numerical N tracing model. Ten key gross N transformation processes were quantified. 【Result】 Mineralization, immobilization, and autotrophic nitrification were identified as the dominant gross N transformation pathways. No significant differences in gross transformation rates were found among land use types. The means (±S.D.) of gross mineralization rates were 1.40±1.31, 2.07±1.46, and 1.83±0.01 mg·kg?1·d?1 for forest, grassland, and upland soils; corresponding to gross immobilization rates of 4.24±3.04, 6.93±3.79, and 5.54±2.00 mg·kg?1·d?1, and gross nitrification rates of 1.47±1.30, 3.75±1.86, and 5.26±2.52 mg·kg?1·d?1, respectively. Significant differences were observed between individual soils in most gross N transformation rates, indicating spatial heterogeneity in soil N supply and retention capacity. Correlation analysis showed that gross mineralization rates were positively correlated with soil organic carbon and negatively correlated with bulk density, whereas gross nitrification rates were positively correlated with soil salinity. 【Conclusion】These results demonstrate that soil properties and environmental factors jointly regulate the gross N transformation process. Under the context of global change, a multi-scale and multi-factor integrative framework, explicitly accounting for land use type, soil characteristics, and environmental conditions, is essential for improving the accuracy of ecosystem N dynamics modeling and predicting nitrogen loss risks.

Abstract:【Objective】This study aimed to investigate the effects of equal replacement of chemical fertilizer by organic fertilizer on rice microbial community and yield. 【Method】 A long-term field experiment was conducted in Liaoning from 2019 to 2023. In this experiment, two rice cultivars, Shendao47 (SD47) and Shendao505 (SD505), were grown in the field with four fertilization treatments at same N, P, K rate: CF (100% chemical fertilizer), OR10 (10% organic fertilizer + 90% chemical fertilizer), OR20 (20% organic fertilizer + 80% chemical fertilizer), OR30 (30% organic fertilizer + 70% chemical fertilizer). 【Results】The results revealed the following: (1) Organic fertilizer substitution increased rice yield mainly by enhancing effective panicles, grain filling rate, and 1000-grain weight, with OR20 treatment achieving the highest yield; (2) Organic fertilizer substitution significantly improved soil fertility by increasing organic matter, total nitrogen, and available nutrient content (alkali-hydrolyzable nitrogen, available phosphorus, and available potassium) in plow layer (0-20 cm); (3) Organic fertilizer substitution significantly enhanced the activity of urease, protease, sucrase, and nitrate reductase in both rhizosphere and bulk soil; (4) Organic fertilizer substitution significantly increased the Chao1 index (richness) and Shannon index (diversity) of bacterial communities in the rhizosphere, whereas its effect on bulk soil bacterial diversity was not statistically significant; (5) At the phylum level, organic fertilizer substitution improved the relative abundance of carbon and nitrogen cycling bacterial phyla such as Proteobacteria, Bacteroidetes, reduced the abundance of oligotrophic bacterial phyla such as Acidobacteria, and optimized the bacterial community structure in bulk and rhizosphere soil; (6) Functional prediction analysis indicated that organic fertilizer treatments enhanced transcription and carbohydrate transport and metabolism in bulk soil, and strengthened metabolism pathways such as amino acid transport and metabolism, inorganic ion transport and metabolism, and lipid transport and metabolism in rhizosphere soil.【Conclusion】In conclusion, under equivalent nutrient input, partial substitution of chemical fertilizer with organic fertilizer could improve the soil microenvironment, enhance key enzyme activities, and optimize the structure and function of soil microbial communities. These changes synergistically promote soil nutrient availability and supply capacity, ultimately increasing rice yield. This practice represents a sustainable fertilization strategy suitable for paddy fields in Northeast China.

Abstract:【Objective】Under the global context of climate change and anthropogenic impacts, soil salinization has become increasingly severe. However, traditional salinization monitoring suffers from being time-consuming, labor-intensive, and costly. Hyperspectral-based salinization monitoring often relies on single mathematical transformations and one-dimensional spectral information, while also exhibiting poor model interpretability. Research utilizing combined spectral transformations to construct spectral indices for salinization estimation urgently requires in-depth exploration. Thus, this study aims to fully exploit spectral information, enhance data sensitivity, and establish a high-precision, interpretable salinization inversion model based on spectral indices.【Method】Dongying City was selected as the study area, where hyperspectral datasets were collected through field surveys, and soil samples were analyzed in the laboratory for salinity determination. The samples were divided into training and testing sets in a 7:3 ratio based on salinity gradients. Spectral data were preprocessed using Savitzky-Golay (S-G) filtering and Multiplicative Scatter Correction (MSC). Four spectral transformations were applied: Reflectance (R), Reciprocal (1/R), Logarithm of Reciprocal (log(1/R)), and Continuum Removal (CR). The Fractional Order Derivative (FOD) transformation was subsequently performed on each form. Ten types of two-dimensional spectral indices were constructed from the combined transformed data at each derivative order. Optimal band combinations and differential orders were identified by assessing correlation coefficients with soil salt content (SSC). Using these spectral indices as features and measured salinity as the dependent variable, four machine learning models—Partial Least Squares Regression (PLSR), Convolutional Neural Network (CNN), eXtreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. The hyperparameters of all models were optimized using the Bayesian Optimization (BO) algorithm, which iteratively fitted a probabilistic surrogate model to guide the search for hyperparameters that minimize cross-validation error. Each model was trained and tuned via ten-fold cross-validation. Performance was evaluated using the Coefficient of Determination (R2), Root Mean Square Error (RMSE), and Residual Prediction Deviation (RPD). The best-performing model was further interpreted using SHapley Additive exPlanations (SHAP) to identify influential spectral features. 【Result】Results demonstrated that:(1) FOD effectively enhances spectral sensitivity by highlighting gradient information during spectral curve variations; (2) Mathematical transformations combined with FOD significantly improve correlations between spectral data and SSC; (3) The 2-order NDI index after CR treatment achieved the highest absolute correlation coefficient (|r|=0.91) with SSC; (4) The CR-FOD-XGBoost model delivered optimal accuracy (testing set: R2=0.94, RMSE=0.85 g·kg?1, RPD=4.33); (5) In the optimal model, GDI1 contributed most significantly while DI clusters adjacent to zero contributed minimally. 【Conclusion】Collectively, this study demonstrates that combining spectral transformations to construct indices with Bayesian-optimized XGBoost modeling effectively improves soil salinity inversion accuracy, providing scientific foundations for salinization control and ecological sustainability. Future research should focus on enhancing spectral sensitivity responsiveness to further improve model performance, thereby advancing theoretical frameworks for sustainable land-use and environmental conservation strategies.

Abstract:【Objective】Phosphorus-solubilizing bacteria (PSB) are ubiquitous in heavy metal-contaminated soils; however, their impacts on soil heavy metals and crop growth remain inadequately understood. 【Method】This study investigated the mechanisms and efficacy of Bacillus sp. PSB32, a Cd- and Pb-tolerant PSB strain isolated from the maize rhizosphere in the Yunnan Plateau, in removing aqueous Cd and Pb and influencing maize (Zea mays L.) growth in contaminated soils.【Result】Under Cd and Pb stress, strain PSB32 primarily removed Cd via intracellular accumulation(43.7%) and surface precipitation(43.2%), with biosorption playing a secondary role (13.0%). In contrast, Pb removal was dominated by surface adsorption (53.2%), followed by surface precipitation (28.8%) and intracellular accumulation (18.0%). Scanning electron microscopy (SEM) revealed the formation of granular precipitates on the bacterial cell surface, which were identified by X-ray diffraction (XRD) as Cd?(PO?)?, Pb?(PO?)?Cl (Pyromorphite), and Pb?(PO?)?OH. Fourier transform infrared (FTIR) spectroscopy confirmed the involvement of functional groups (e.g., -COOH, -OH, -NH?) and anionic groups (e.g., PO?3?, SO?2?) in the surface complexation of Cd and Pb. In the pot experiments, the amendment of PSB32 across the three differentially contaminated soils (contaminated farmland, tailings, and slag) led to a consistent increase of 5.90%-9.43% in the residual fraction of Cd, alongside a decrease of 7.20%-18.8% in the reducible fraction of Pb. Concurrently, the soil available phosphorus content was enhanced by 3.00%-18.7%, which contributed to a substantial promotion of maize biomass, ranging from 25.7% to 82.2%. Notably, PSB32 also increased the Cd content in maize shoots by 61.9% and 32.9% in the farmland and tailings soils, respectively, and significantly enhanced the accumulation of Cd and Pb in the roots by 365% and 35.3% in the slag soil.【Conclusion】In conclusion, Bacillus sp. PSB32 demonstrates a dual ecological function: effectively removing aqueous Cd and Pb through multiple mechanisms, and enhancing plant tolerance in contaminated soils by altering metal speciation and improving phosphorus nutrition. This strain presents a promising microbial resource for the bioremediation of heavy metal-contaminated soils.

Abstract:As global agriculture evolves alongside the increasing demand for environmental protection, green intelligent fertilizers have emerged as a novel approach to enhancing crop productivity and resource use efficiency. This paper reviews the core concepts and development status of green intelligent fertilizers, exploring the principles of intelligent regulation within plant-microbe-environment interactions and the design and application strategies based on the rhizobiont theory. Green intelligent fertilizers operate by maximizing the biological potential of crops and microorganisms to regulate the integrated plant-microbe-soil system, thereby promoting plant growth and minimizing environmental impact. Looking ahead, breakthroughs in material innovation, process optimization, and intelligent fertilizer formulation will enable intelligent fertilizers to drive agricultural green transformation, providing critical support for global food security and environmental sustainability.

Abstract:Heavy metal contamination in agricultural soils in China is severe, posing a significant threat to the safety of agricultural products. The development of long-lasting and stable in-situ passivation materials has become a current research hotspot for the safe utilization of contaminated farmland. Layered double hydroxides (LDHs) possess unique advantages such as large specific surface area, strong ion-exchange capacity, tunable structure, and super-stable mineralization, offering a new pathway to overcome the limitations of traditional materials. This article systematically reviews the research progress of LDHs in the in-situ passivation of heavy metals in farmland soils from three perspectives: mechanisms of action, material design, and stability evaluation. Firstly, it analyzes the mechanisms by which LDHs synergistically passivate heavy metals through multiple pathways, including isomorphous substitution, ion exchange, adsorption–precipitation, and redox–precipitation. Secondly, it summarizes the effectiveness of both pure LDHs and their composite materials in the in-situ passivation of heavy metals in farmland soils, and discusses the “molecular engineering” design achieved by regulating layer cations, functionalizing interlayer guests, and composite design to enhance targeting capability. Finally, the long-term stability of their passivation effects is evaluated from chemical, physical, and biological perspectives, revealing their potential to resist environmental interference. The article concludes by analyzing current challenges in LDH research and outlining future research directions, aiming to provide insights for the targeted design, precise application, long-term effectiveness, and safety evaluation of LDHs in the in-situ passivation of heavy metals in farmland soils.

Abstract:【Objective】This study aimed to explore the effects of the coupling of different biochar application depths and cropping patterns on the soil carbon pool and crop yield. 【Method】A long-term stationary experiment established in 2019 was adopted, with cropping pattern as the main plot and biochar application method as the subplot. Three cropping patterns were designed: soybean-maize rotation (SM), continuous soybean cropping (S), and continuous maize cropping (M). Three treatments were set up: biochar mixed application at 0-20 cm (B1), biochar mixed application at 0-40 cm (B2), and no biochar application (CK). Soil samples were collected from the 0-20 cm and 20-40 cm soil layers at the crop maturity stage in 2023, and the soil carbon fractions, humus components, and crop yield were determined. 【Result】The results showed that: the contents of soil carbon fractions (e.g., soil organic matter (SOM) and microbial biomass carbon (MBC)) in the rotation system were significantly higher than those in continuous cropping systems, and the SOM content under continuous soybean cropping was significantly higher than that under continuous maize cropping. The application of biochar at 4 500 kg?hm-2 had no significant effect on SOM content in the 0-20 cm soil layer, but it increased the activity of MBC in the 0-20 cm soil layer (by 11.3%-33.7%), optimized humus properties (humic acid (HA) content increased by 6.7%-25.7% while fulvic acid (FA) content decreased by 0.4%-22.5%). This treatment also improved crop yield (soybean yield increased by 24.2%-32.4% and maize yield increased by 13.0%-24.3%). Under the synergistic effect of rotation and biochar application, MBC content increased by 22.8%-33.7%, dissolved organic carbon (DOC) content increased by 17.6%-31.1%, readily oxidizable organic carbon (ROC) content increased by 14.9%-26.6%, HA content increased by 14.5%, FA content increased by 11.8%-15.5%, and the humus quality index (PQ) increased by 11.7%-17.4%.【Conclusion】The coupling of biochar application and crop rotation is beneficial for improving the soil carbon pool, enhancing carbon activity, optimizing humus properties, and increasing crop yield. This practice is expected to play an important role in future agricultural production and soil environment improvement.

Abstract:【Objective】Determining the patterns of regulatory factors of soil extracellular enzyme activity along elevational gradients is critical for understanding microbial nutrient limitation and metabolic processes. This contributes to predicting the responses of soil biogeochemical cycles to global change. However, knowledge of the elevational patterns in soil extracellular enzyme activity and their stoichiometry, as well as their drivers, remains limited. 【Method】Soil samples (0-10 cm) were collected from different elevation gradients on Jinzhongshan Mountain in Guangxi, China. These samples were used to investigate the elevational patterns of soil physical and chemical properties, extracellular enzyme activities, and microbial nutrient limitations. Also, the major factors influencing microbial extracellular enzyme activities and their stoichiometry were evaluated. 【Result】 The results indicate that (1) soil water content (SWC), soil nutrient content, stoichiometric ratios, and microbial biomass content increased with increasing elevation. However, soil bulk density (BD), pH, and available phosphorus (AP) content decreased with increasing elevation. (2) The activities of carbon and nitrogen degradation-related enzymes, including β-glucosidase (BG), N-acetylamino glucosidase (NAG), and leucine aminopeptidase (LAP), exhibited no clear pattern with increasing elevational gradient. In contrast, acid phosphatase (ACP) activity initially increased, then decreased along with elevation, presenting a unimodal pattern. Vector analysis of ecoenzyme activities revealed that vector lengths were larger at middle and high elevations (1 429-1 691 m), suggesting an enhanced carbon limitation for soil microorganisms. Additionally, all vector angles were greater than 45°, indicating a widespread phosphorus limitation for soil microbes in the study region. (3) Compared with soil enzyme activity data at the global scale and in Chinese regions, soil enzyme activities related to carbon, nitrogen, and phosphorus cycling in Jinzhongshan, which is located in the transition zone from the eastern humid region to the western semi-humid and semi-arid region, were generally low. This suggested that soil microorganisms in this area were subject to relatively greater N and P limitations. Furthermore, compared to soils in humid regions, the activities of C-, N-, and P-cycling enzymes were lower, whereas the activities of enzymes associated with C and P cycling were relatively higher when compared with arid regions. (4) Mantel test results indicated that soil extracellular enzyme activity and their stoichiometry were significantly correlated with SWC, NO3--N, and microbial biomass nitrogen (MBN). Redundancy analysis (RDA) revealed that NO3--N and microbial biomass phosphorus (MBP) were the key factors driving variations in soil extracellular enzyme activities, whereas soil enzyme stoichiometry was primarily regulated by NO3--N, total phosphorus (TP), C:N, and MBP. (5) Partial least squares path modeling (PLS-PM) demonstrated that soil physical properties and microbial biomass directly influenced soil extracellular enzyme activities, whereas soil physicochemical properties together with microbial biomass exerted direct effects on enzyme stoichiometry.【Conclusion】Elevation affected extracellular enzyme activities mainly through regulating soil physical properties and microbial biomass, but indirectly modulated enzyme stoichiometry via altering soil physicochemical properties and microbial biomass. These findings contribute to enhancing the mechanistic understanding of how soil extracellular enzyme activities and their stoichiometric patterns respond to elevation gradients in mountain forest ecosystems under global climate change.

Abstract:【Objective】Elevated near-surface ozone (O3) concentrations have been shown to reduce methane (CH4) emissions from rice paddies. However, the underlying mechanisms regulating soil CH4 production remain poorly understood. Thus, this study aimed to decipher the mechanisms regulating soil CH4 production at different rice growth stages and identify the main controlling factors.【Method】In this study, a widely cultivated rice cultivar (Nanjing 9108) in the Yangtze River Delta was used to investigate the effects of elevated O3 on methane production processes. An open-top chamber (OTC) system was employed to simulate elevated ozone conditions, including ambient air (NF) and ambient air supplemented with O3 (NF40 + 40 nmol·mol-1 O3). Rhizosphere soils were collected at the typical growth stages of rice (the filling stage and the maturity stage) and subjected to microcosm incubation experiments. Root morphological traits, soil carbon components, microbial abundance, and methanogenic archaeal community composition were simultaneously analyzed to elucidate the regulatory mechanisms of O3 on CH4 production. 【Results】The results showed that elevated O3 reduced specific root length (SRL) and specific root area (SRA) during the filling stage of rice, while enhancing soil organic carbon stability during the maturity stage of rice. This simultaneously altered the community composition of methanogens, characterized by an increase in the relative abundance of hydrogenotrophic methanogens and a decrease in the relative abundance of acetoclastic methanogens. O3 elevation reduced CH4 production rates in paddy soils by 38.1%–46.8%, with decreased acetoclastic methanogenesis rates by 66.6%–68.1%. Conversely, CH4 production rates via hydrogenotrophic methanogenesis increased by 6.1%–24.7%.【Conclusion】This study provides a process-based understanding of how elevated O3 regulates methane production in rice soils through coupled changes in plant root traits, soil carbon stabilization, and methanogenic community structure, offering critical insights for predicting CH4 emissions from agricultural ecosystems under future O3 pollution scenarios.