Objective This study aims to scientifically delineate land use functional zones in Anhui Province， identify the key driving factors of landscape ecological risk， and reveal the spatiotemporal evolution characteristics and spatial conflict patterns of ecological risk， providing scientific support for regional ecological security and territorial space planning. Methods Taking Anhui Province as the study area， a land use functional zoning scheme was developed by integrating the morphological spatial pattern analysis （MSPA）， Conefor， and minimum cumulative resistance （MCR） models and applying the resistance threshold method. On this basis， This study combines the XGBoost model with the SHAP interpretation method to quantitatively analyze the effects of topographic conditions， climatic factors， and socio-economic factors on landscape ecological risks. Results 1）According to land use functions， Anhui Province can be divided into three core areas， among which the ecological protection core area accounts for 30.96%， the agricultural production core area accounts for 35.52%， and the construction and development core area accounts for 33.52%. Spatially， the three areas are respectively concentrated in the southern Anhui region， the northern Anhui region， and the urban agglomeration in central Anhui. 2） From 2000 to 2020， the overall landscape ecological risk in the region has been continuously intensifying， with the proportion of areas with high and very high risks increasing from 16.95% to 32.81%. In terms of spatial distribution， low-risk zones largely coincided with ecological protection zones， while high-risk zones were concentrated in construction development zones. 3） The analysis of influencing factors showed that topographic factors exerted the greatest influence on the provincial risk pattern. Climatic factors were the dominant factors in ecological protection and construction development zones， whereas socio-economic factors had the most significant influence on risk in agricultural production zones. 4） Ecological risk conflicts within the province were significant， with relatively high- and high-conflict zones accounting for 30.78%， mainly distributed in cities such as Anqing and Hefei. Conclusion Landscape ecological risk in Anhui Province shows an intensifying trend. The province is influenced by topographic factors， while different zones are driven by climatic and socio-economic factors， and high-risk zones are concentrated in construction development core zones. It is recommended to implement differentiated management strategies based on functional zoning， focusing on mitigating spatial conflicts in areas such as Anqing and Hefei to improve regional ecological security. The findings provide a scientific basis for the synergistic governance of territorial space planning and ecological risk.

Objective This study aims to construct a gully erosion susceptibility assessment model in order to provide an important scientific basis for early warning of gully erosion occurrence and its precise management in the black soil region of Northeast China. Methods Kedong County in Heilongjiang Province， a typical thick-layer black soil region， was selected as the study area. Erosion gullies were extracted based on 0.4 m high-resolution remote sensing images. Redundant variables were eliminated using the variance inflation factor （VIF）. Four machine learning models covering linear， nonlinear， and ensemble learning architectures-logistic regression （LR）， support vector machine （SVM）， random forest （RF）， and extreme gradient boosting （XGBoost）-were compared. The SHAP （Shapley Additive exPlanations） interpretability model was introduced to quantify the contribution of each influencing factor to gully erosion susceptibility. Results 1） XGBoost demonstrated the best predictive capability for gully erosion susceptibility （training set AUC=0.81， test set AUC=0.75）， followed by the SVM and RF （test set AUC=0.74）， while LR showed the weakest predictive capability （AUC=0.67）. 2） The gully erosion susceptibility predicted by the four models all exhibited a spatial distribution pattern of "low in the periphery and high in the center" at the county scale， but there were significant differences in the susceptibility levels. The RF model predicted the largest proportion of high gully erosion susceptibility， accounting for 45.0%. The gully erosion susceptibility predicted by the SVM and XGBoost models in the study area was predominantly moderate and very low levels， accounting for 56.2% and 59.2%， respectively. In contrast， the LR prediction results indicated that low gully erosion susceptibility was dominant， covering 39.4% of the study area. 3） SHAP analysis revealed that the digital elevation model （DEM） was the dominant factor influencing gully erosion susceptibility （SHAP value=0.55）， exhibiting a significant positive effect. The stream power index （SPI） had the second strongest positive driving effect on gully erosion susceptibility （SHAP value=0.30）， while the normalized difference vegetation index （NDVI） showed a clear negative effect on gully erosion susceptibility （SHAP value=0.37）. Conclusion In the thick-layer black soil region of Kedong County， significant differences are observed in the gully erosion susceptibility levels evaluated by the four machine learning models. The integration of the XGBoost model with the SHAP method enhances the interpretability of machine learning models in predicting gully erosion susceptibility. Moreover， gully erosion susceptibility is jointly driven by the coupled effects of "terrain-dominated control， vegetation regulation， and confluence hydrodynamics triggering". These findings deepen the understanding of gully erosion occurrence and provide theoretical guidance for optimizing gully erosion control measures in black soil regions.

Objective This study aims to clarify the spatiotemporal evolution patterns， obstacle factors， and cultivated land improvement zoning in the Loess Plateau of northern Shaanxi from 1990 to 2020， and to optimize the regional allocation of cultivated land resources and achieve the strategy of "grain security in the land". Methods Taking Yulin City as the study area， the evaluation indicator system for cultivated land quality mainly covered five aspects： climatic conditions， soil nutrients， cultivated land management， site conditions， and physicochemical properties. The spatial autocorrelation model and the obstacle degree model were introduced to analyze the spatiotemporal evolution characteristics and core restrictive factors of cultivated land quality， and based on this， the improvement zones were scientifically delineated. Results 1） From 1990 to 2020， the cultivated land quality index in Yulin City showed an upward trend （rising from 0.52 to 0.55）， with a spatial distribution pattern of "higher in the east and lower in the west， and higher in the south and lower in the north". 2） The spatial heterogeneity was significant. The high-high-clustering-type cultivated land was distributed in Suide County， Wubu County， and other loess hilly-gully regions， while low-low-clustering-type cultivated land was concentrated in Dingbian County， Jingbian County， and other sandy grassland areas. 3） The diagnosis of obstacle factors indicated that accumulated temperature was the primary factor restricting cultivated land quality in Yulin City. Based on the dominant obstacle factor types， the city was divided into 22 regional types， including accumulated temperature zone， average patch area-pH zone， and organic carbon zone， with differentiated improvement plans proposed for key zones. Conclusion The research findings can provide a scientific basis for cultivated land quality protection and high-quality agricultural development in the northern Shaanxi Loess Plateau.

Objective This study investigates the effects and mechanisms of biochar application on the accumulation of total soil organic carbon （SOC） and key organic carbon fractions such as microbial necromass carbon （MNC） in paddy soils. Methods A field experiment was conducted to analyze the changes in SOC fractions， such as MNC and enzyme activities， five years after a one-time application of maize straw biochar at rates of 20 t/hm² （M20）， 30 t/hm² （M30）， and 40 t/hm² （M40）. Results Compared with the control （no biochar application）， biochar treatments increased the contents of SOC， particulate organic carbon （POC）， and mineral-associated organic carbon （MAOC） by 19.4%-45.0%， 36.3%-65.3%， and 13.4%-47.2%， respectively， whereas dissolved organic carbon （DOC） and microbial biomass carbon （MBC） decreased by 9.8%v29.2%， and 19.5%-29.1%， respectively. Biochar treatments had no significant effects on the contents of biomarkers such as mannosamine， glucosamine， muramic acid， and galactosamine， nor on fungal necromass carbon （FNC） and bacterial necromass carbon （BNC）. However， biochar treatments significantly reduced the contribution rates of FNC， BNC， and MNC to SOC by 16.6%-32.4%， 16.7%-27.2%， and 17.0%-30.8%， respectively. The M30 treatment significantly decreased the activities of polyphenol oxidase （PHOX）， peroxidase （PERO）， α-glucosidase （AG）， β-D-cellobiohydrolase （CB）， and β-xylosidase （XYL） by 19.8%， 24.7%， 32.7%， 34.2%， and 33.7%， respectively. Correlation analysis indicated that the contribution rate of MNC to SOC was significantly negatively correlated with pH， POC， and MAOC， and positively correlated with MBC and some hydrolytic enzyme activities. Random forest model prediction showed that MAOC and pH were the main driving factors determining the contribution of MNC to SOC. Conclusion Biochar application enhances the accumulation and stability of SOC mainly by promoting the accumulation of POC and MAOC rather than MNC. The results provide a theoretical reference for improving soil carbon sequestration in paddy soils through biochar application.

Objective This study aims to examine whether and how conservation tillage improves the climate adaptability of grain production， revealing its heterogeneous effects from a dual-dimensional perspective of proactive response and passive adaptation. Methods Based on panel data from 44 sample counties in Heilongjiang Province， China， from 2012 to 2022， a dual-dimensional evaluation framework was established incorporating proactive response and passive adaptation. The Tobit models， system generalized method of moments （GMM）， double machine learning， and spatial Durbin models were employed to empirically test the impacts of conservation tillage on climate adaptability. Results 1） From 2012 to 2022， the climate adaptability of grain production in Heilongjiang Province exhibited an overall evolution pattern of first declining and then rising， with 2017 as a key turning point. Spatially， the pattern evolved from a scattered distribution of high-value areas in the early stage to a distinct east-west differentiation， with high-value areas in the east and low-value areas in the west. 2） Conservation tillage had a significantly positive effect on proactive response， but no significant effect on passive adaptation. The system GMM results showed that the first-order lag term of climate adaptability was significantly positive， indicating that the adaptability improvement showed evident path dependence and dynamic accumulation characteristics. Spatial analysis further demonstrated that the direct and indirect effects of conservation tillage on proactive response were 0.119 and 0.711， respectively， with indirect effect playing a dominant role， indicating a significant spatial spillover effect. 3） The effect of conservation tillage on improving proactive response was more pronounced in regions with higher levels of economic development and flatter terrain. Conclusion Conservation tillage can significantly improve the climate adaptability of grain production， mainly by strengthening proactive response， and exhibits evident path dependence and spatial spillover characteristics. The research findings provide a basis for optimizing agricultural climate adaptation policies from a dual-dimensional perspective and for enhancing the resilience of grain production systems.

Objective This study aims to achieve efficient utilization and value transformation of the space under photovoltaic panels in rocky desertification areas， and to reveal the effects of different "medicinal herb-liana" utilization models on improving soil nutrients and enzyme activities， thereby selecting a model that can efficiently utilize the space under panels while having socioeconomic value. Methods Based on a near-natural indoor simulation test site， composite utilization models of Polygonum multiflorum with various lianas were established. Drawing from soil data in both dry and rainy seasons， one-way ANOVA， nonlinear regression， and redundancy analysis were employed to systematically analyze the temporal variation trends of total soil nutrients and available nutrients under different utilization models， thereby further clarifying the correlation characteristics between soil physicochemical properties and enzyme activity. Results 1） The model of P. multiflorum with Lonicera japonica exhibited a stable nutrient accumulation effect； the model of P. multiflorum with Puerarialobata showed strong seasonal fluctuations， with a net depletion of nutrient content throughout the year； the model of P. multi-florum with Wisteria showed an initial increase followed by a decrease in nutrients. In comparison， the control group exhibited continuous nutrient depletion. 2） The seasonal dynamics of available nutrients showed significant species specificity. The L. japonica model achieved accumulation of available phosphorus and potassium in both dry and rainy seasons. In addition， despite an explosive increase of 4.02 mg/kg in alkali-hydrolyzable nitrogen in the Wisteria model during the dry season， this increase was rapidly lost during the rainy season. 3） Organic carbon and available phosphorus served as key factors driving enzyme activity variation， with explanatory rates of 71.8% （dry season） and 83.5% （rainy season）， respectively. The L. japonica model alleviated carbon and phosphorus limitations through the accumulation of organic carbon， resulting in a steady increase in both soil nutrients and enzyme activity， whereas the Wisteria model presented a state of high enzyme activity but low nutrient content. Conclusion The "medicinal herb-liana" composite utilization model plays an important role in enhancing the stability of the soil biochemical system and nutrient cycling efficiency in the area under photovoltaic panels. The composite utilization model of P. multiflorum with L. japonica exhibits the best adaptation potential and ecological benefits. The research results can provide a theoretical basis and practical guidance for under-panel economic deve-lopment and sustainable soil ecological management of photovoltaic power stations in rocky desertification areas.

Objective This study aims to investigate the effects of different vegetation restoration models on runoff and sediment reduction in dry-hot valleys and to analyze their underlying mechanisms， thereby providing a scientific basis for functional vegetation restoration for soil and water conservation in these areas. Methods Taking the Yuanmou dry-hot valley in Yunnan Province as the study area， an in-situ monitoring experiment was conducted from 2019 to 2022. Bare land was used as the control， and vegetation restoration models including cultivated land， shrub-grassland， tree-shrub-grassland， naturally restored land 1 and naturally restored land 2 were established. The runoff and sediment reduction benefits under different vegetation restoration models were compared， and the influence mechanisms of rainfall， soil， and vegetation factors on soil loss and runoff under different models were explored. Results Compared with bare land， runoff decreased by 64.25%， 89.08%， 91.81%， 87.20% and 84.79%， and soil loss decreased by 92.16%， 99.45%， 99.92%， 99.37% and 97.26% in cultivated land， shrub-grassland， tree-shrub-grassland， naturally restored land 1， and naturally restored land 2， respectively. The effectiveness of runoff and sediment reduction followed the order： tree-shrub-grassland > shrub-grassland > naturally restored land 1 > naturally restored land 2 > cultivated land > bare land. Rainfall erosivity was the major driving factor of runoff， with a total effect ranging from 21.90% to 70.73%， while runoff was the primary driving factor of soil loss， with a total effect ranging from 26.94% to 97.81%. In bare land and intensively disturbed cultivated land， the water and sediment processes were mainly dominated by rainfall factors （rainfall erosivity）. In contrast， under restoration models such as shrub-grassland and tree-shrub-grassland， the system shifted to being dominated by "surface hydrological processes"， where vegetation and soil factors fundamentally reduced the occurrence of runoff and soil loss by curbing runoff volume. Conclusion The tree-shrub-grass model combining Bombax ceiba， Bauhinia purpurea， Heteropogon contortus， and Bothriochloa pertusa was the most effective in reducing runoff and sediment. This model achieves significant soil and water conservation benefits by jointly regulating soil and vegetation factors to suppress the generation of runoff and soil loss.

Objective This study investigates the response characteristics of water storage at gully heads to rainfall in the black soil region of Northeast China， reveals the variation patterns of water storage at gully heads before and after rainfall， and establishes a quantitative prediction method for its changes before and after rainfall. Methods Four gully heads with similar developmental stages and scales in three study areas （Jiusan， Binxian and Jiutai） were selected as research objects. Differences in soil hydraulic parameters， decay coefficients of water storage， and variation patterns of water storage before and after rainfall were investigated through transient water release and imbibition method （TRIM）， numerical fitting， and prediction model construction. Results Obvious hysteresis effects were observed in soil-water characteristic curves （SWCC） of soils at gully heads， with the intensity ranking as gully 1 ≈ gully 2 < gully 3 < gully 4. After rainfall， water storage decayed exponentially over time， showing rapid decline in the initial stage and slower decline in the later stage. The decay coefficient （K_d） of water storage decreased progressively with increasing soil depth. Model simulations showed that water storage changes at 85.7 % of the monitoring sites were best predicted using 1 h maximum rainfall intensity （I_{1 h}） as the rainfall input parameter， whereas 14.3 % of the sites were better simulated using 2 h average maximum continuous rainfall intensity （I_{2 h}） as input. Therefore， in predicting soil water storage changes， I_{1 h} could be selected as the rainfall input parameter for sites with good infiltration performance， such as gully heads or severely eroded sites. However， I_{2 h} should be selected as the rainfall input parameter for sites with poor infiltration performance or strong water redistribution. Conclusion The evolution of water storage at gully heads after rainfall in the black soil region of Northeast China can be effectively characterized using exponential decay patterns and short-duration rainfall indices. The constructed model can accurately and quantitatively predict short-duration water storage changes at gully heads at the event scale， which provides methodological support for prediction and early warning of gully erosion processes.

Objective This study aims to investigate the co-developmental relationship between the overlying soil and the underlying strongly weathered bedrock layer， thereby providing fundamental data for the quantitative prediction of subsurface rock-soil structures in karst areas. Methods In the Mulian small watershed of Huanjiang， Guangxi， intelligent photogrammetry technology was employed， using a 3 m high standard leveling staff as a reference， to investigate 68 rock-soil profiles， each 5 m in width， across four different geomorphic positions： upper slope， middle slope， lower slope， and depression （17 profiles per position）. Through image characterization in AutoCAD and vectorization processing using ArcGIS-Fragstats， structural indicators of the rock-soil profiles were obtained and compared， including equivalent thickness （T）， number of patches （NP）， shape index （SHAPE）， perimeter-to-thickness ratio （PTR）， fractal dimension （FRAC）， and coefficient of variation of thickness （CV）. Results 1） The equivalent thickness of the soil layer and the strongly weathered bedrock layer increased non-uniformly from the upper slope to the depression. The soil thickness on the upper slope was less than 25 cm， while the thickness of the strongly weathered bedrock layer in the depression ranged from 110 cm to 250 cm. 2） The number of patches （NP>4） and the shape index （SHAPE） on the middle slope were significantly higher than those at other slope positions， exhibiting fragmented and interlocked rock-soil mosaic characteristics. The number of trees and shrubs and the maximum root depth were significantly positively correlated with the thickness of the soil and the strongly weathered bedrock layer （r=0.86， r=0.65）， and increasing woody vegetation effectively reduced the spatial variability of soil thickness. 3） A linear model indicated that the thickness of the strongly weathered bedrock layer was approximately 69% of the soil layer thickness. The complex characteristics of the concealed subsurface structure could be effectively predicted through easily measurable surface indicators， such as soil thickness （T） and woody stem density （Sd）. Conclusion Quantitative research at the rock-soil profile scale reveals differences in structural characteristics among various geomorphic positions， providing a scientific basis for precise zonal management of geomorphic positions in karst ecological restoration.

Objective This study aims to reveal the differences in infiltration processes of soda saline-alkali soils with different degrees and their influencing factors， and to evaluate the applicability of different infiltration models in simulating the infiltration process of soda saline-alkali soils. Methods Using the one-dimensional vertical constant-head single-ring infiltration method， field in-situ infiltration experiments were conducted to study the characteristics of infiltration process parameters in soda saline-alkali soils with different degrees， analyze the effects of salinization-alkalization indicators on the infiltration process， and evaluate the applicability of different prediction models. Results 1） As pH increased from 9.31 to 10.35， exchangeable sodium percent （ESP） rose from 1.09% to 65.82%， and sodium adsorption ratio （SAR） increased from 1.24 to 115.71， the stable infiltration rates of the five tested soils decreased by 41.81% to 99.59% compared with the initial infiltration rates. Among them， the Suaeda salsa land with the highest degree of salinization and alkalization showed the largest decrease， with a stable infiltration rate of only 0.13 mm/h. 2） Correlation analysis indicated that the stable infiltration rate was significantly negatively correlated with ESP and pH （p<0.01）， and significantly negatively correlated with exchangeable Na⁺ （p<0.05）. The average infiltration rate was significantly negatively correlated with ESP， exchangeable Na⁺， SAR， pH， and salt content at different levels. 3） Based on the coefficient of determination （R²） of the models and the correlation with the saline-alkali indicators of soda saline-alkali soils with different degrees， the simulation performance of the Horton infiltration model was superior to that of the general empirical model when SAR<108.60， salt content （SC）<10 568.64 mg/kg， and electrical conductivity （EC）<1.70 mS/cm. When the degree of salinization and alkalization exceeded this range， the general empirical model performed better. Conclusion The degree of soda salinization and alkalization is a key factor constraining soil infiltration capacity. The applicability of infiltration models for soils with different degrees of salinization and alkalization can be optimized based on thresholds of typical saline-alkali indicators. These findings provide a theoretical basis and methodological support for simulating water movement and managing irrigation and drainage in soda saline-alkali soil regions.