Search Results (93)

Gravity erosion is one of the main physical processes of soil erosion and sediment sources in catchments, and its spatiotemporal patterns and driving mechanisms are seriously understudied, mainly due to the the great difficulties in monitoring and quantifying. This study obtained gravity erosion amounts by runoff scouring experiments on the field slope of the hilly–gully region of the Chinese Loess Plateau. The terrain point cloud before and after gravity erosion was obtained based on the TLS, SfM and the fusion of single-scan TLS and SfM, and then the gravity erosion was estimated by four terrain change detection algorithms (DoD, C2C, C2M and M3C2). Results showed that the M3C2 algorithm plus fused data had the highest quantization accuracy among all the algorithms and data sources, with a relative error of 14.71%. The fused data combined with M3C2 algorithm performed much better than other algorithms and data sources for the different gravity erosion magnitudes (mean relative error < 17.00%). The DoD algorithm plus TLS data were preferable for collapse areas, while the M3C2 algorithm plus TLS was suitable for the alcove area. This study provides a useful reference for the monitor and quantitative research of gravity erosion in complex topographic areas. Full article

Information on the effects of differences in root and soil properties on Saturated hydraulic conductivity (K_s) is crucial for estimating rainfall infiltration and evaluating sustainable ecological development. This study selected typical grass shrub composite plots widely distributed in hilly and gully areas of the Loess Plateau: Caragana korshinskii, Caragana korshinskii and Agropyron cristatum (fibrous root), and Caragana korshinskii and Artemisia gmelinii (taproot). Samples were collected at different distances from the base of the shrub (0 cm, 50 cm), with a sampling depth of 0–30 cm. The constant head method is used to measure the K_s. The K_s decreased with increasing soil depth. Due to the influence of shrub growth, there was significant spatial heterogeneity in the distribution of K_s at different positions from the base of the shrub. Compared to the sample location situated 50 cm from the base of the shrub, it was observed that in a single shrub plot, the K_s at the base were higher, while in a grass shrub composite plot, the K_s at the base were lower. Root length density, >0.25 mm aggregates, and organic matter were the main driving factors affecting K_s. The empirical equation established by using principal component analysis to reduce the dimensions of these three factors and calculate the comprehensive score was more accurate than the empirical equation established by previous researchers, who considered only root or soil properties. Root length density and organic matter had significant indirect effects on K_s, reaching 52.87% and 78.19% of the direct effects, respectively. Overall, the composite plot of taproot herbaceous and shrub (Caragana korshinskii and Artemisia gmelinii) had the highest K_s, which was 82.98 cm·d⁻¹. The ability of taproot herbaceous plants to improve K_s was higher than that of fibrous root herbaceous plants. The research results have certain significance in revealing the influence mechanism of the grass shrub composite on K_s. Full article

This study takes the Jinfoping Small Watershed in the Loess Hilly Region as the research area. Through field investigation and laboratory analysis, combined with methods such as spatial autocorrelation analysis, the ordinary least squares method (OLS), and the geographically weighted regression model (GWR), it deeply explores the spatial distribution characteristics and driving factors of Formicidae in the study area. The research results are as follows: (1) Spatial autocorrelation analysis indicates that the distribution of Formicidae is significantly regulated by spatial dependence and has significant spatial autocorrelation (global Moran’s I = 0.332; p < 0.01). (2) The spatial visualization analysis of the GWR model reveals that soil physical and chemical properties and topographic factors have local influences on the spatial distribution of Formicidae. Available phosphorus (AP) and slope (SLP) were significantly positively correlated with the number of ants. Hydrogen peroxidase (HP) and topographic relief (TR) were significantly negatively correlated with the number of ants. This study reveals the spatial distribution pattern of Formicidae in the Loess Hilly Region and its complex relationship with environmental factors, and clarifies the importance of considering spatial heterogeneity when analyzing ecosystem processes. The research results provide a scientific basis for the protection and management of soil ecosystems, and also offer new methods and ideas for future related research. Full article

Soil erosion is a major environmental concern, especially in sensitive ecosystems like the Loess Plateau of China, where certain geological and climatic circumstances exacerbate the erosion process. Terracing and mulching are popular soil erosion management strategies in this region. However, their combined effects under varied rainfall intensities are poorly understood. The purpose of this study is to assess the performance of various terracing–mulch combinations in reducing water erosion under different rainfall intensities. The experimental layout included a control plot (C), non-terraced mulch applications (NTr-M), fish-scale pits with mulch (FSPs-M), zig terraces with mulch (ZTr-M), level bench terraces with mulch (LBTr-M), and trench terraces with mulch (TTr-M). Controlled artificial rainfall experiments were carried out under different intensities, and runoff and soil loss data were collected to evaluate the effects of the combinations. The event-based WEPP simulations, calibrated for the Loess Plateau, demonstrated strong predictive accuracy, as evidenced by the high correlation coefficients (R² = 0.97 for runoff; R² = 0.86 for soil loss) and Nash–Sutcliffe efficiency (NSE = 0.93 for runoff; NSE = 0.89 for soil loss), confirming their reliability in simulating erosion processes when compared to measured values. Our results revealed significant differences (p < 0.05) in mean runoff and soil loss among the treatments, ranked in the order LBTr-M < TTr-M < ZTr-M < FSPs-M < NTr-M < C. Incremental response analysis also revealed that the control plot (C) was the most sensitive to changes in rainfall intensity, followed by FSPs-M and NTr-M. In contrast, LBTr-M was found to be the most stable strategy. These findings highlight the importance of optimizing micro-relief construction and mulch application to enhance erosion control and support the recommendation of LBTr-M, TTr-M, and ZTr-M as effective strategies. Conversely, FSPs-M and NTr-M proved less effective under higher rainfall intensities. These findings emphasize the need to optimize micro-relief construction and mulch application for erosion management, as well as suggest that such strategies could be applied to the Loess Plateau and other erosion-prone regions worldwide with similar climatic and topographic conditions. Full article

The dynamics of vegetation changes and phenology serve as key indicators of interannual changes in vegetation productivity. Monitoring the changes in the Nanling grassland ecosystem using the remote sensing vegetation index is crucial for the rational development, utilization, and protection of these grassland resources. Grasslands in the hilly areas of southern China’s middle and low mountains have a high restoration efficiency due to the favorable combination of water and temperature conditions. However, the dynamic adaptation process of grassland restoration under the combined effects of climate change and human activities remains unclear. The aim of this study was to conduct continuous phenological monitoring of the Nanling grassland ecosystem, and evaluate its seasonal characteristics, trends, and the thresholds for grassland changes. The Normalized Difference Phenology Index (NDPI) values of Nanling Mountains’ grasslands from 2000 to 2021 was calculated using MOD09A1 images from the Google Earth Engine (GEE) platform. The Savitzky–Golay filter and Mann–Kendall test were applied for time series smoothing and trend analysis, and growing seasons were extracted annually using Seasonal Trend Decomposition and LOESS. A segmented regression method was then employed to detect the thresholds for grassland ecosystem restoration based on phenology and grassland cover percentage. The results showed that (1) the NDPI values increased significantly (p < 0.01) across all grassland patches, particularly in the southeast, with a notable rise from 2010 to 2014, and following an eastern to western to central trend mutation sequence. (2) the annual lower and upper NDPI thresholds of the grasslands were 0.005~0.167 and 0.572~0.727, which mainly occurred in January–March and June–September, respectively. (3) Most of the time series in the same periods showed increasing trends, with the growing season length varying from 188 to 247 days. (4) The overall potential productivity of the Nanling grassland improved. (5) The restoration of the mountain grasslands was significantly associated with the grassland coverage and mean NDPI values, with a key threshold identified at a mean NDPI value of 0.5 for 2.1% grassland coverage. This study indicates that to ensure the sustainable development and conservation of grassland ecosystems, targeted management strategies should be implemented, particularly in regions where human factors significantly influence grassland productivity fluctuations. Full article

With the rapid urbanization in China, traditional villages are undergoing simultaneous construction and destruction, making it crucial to scientifically balance the protection and development of these villages. The Loess Hilly Area of Northern Shaanxi, one of the most severely eroded regions in the world, was chosen as the study area. Socio-economic, land use, and natural ecological data from 152 traditional villages in this area were analyzed. First, an evaluation model was developed to assess the comprehensive level of protection and development in these villages. Next, a coupling coordination model and spatial autocorrelation model were employed to measure the coordination level and spatial distribution of protection and development. Finally, a coordination influence model was combined with a geographically weighted regression model to reveal the driving mechanisms promoting the coupling coordination between protection and development. The results indicate that (1) the protection and development levels of traditional villages in the study area exhibit contrasting patterns of “high in the east and low in the west” and “high in the west and low in the east”, respectively; (2) nearly half of the regions show a low level of coordination between protection and development, with a few counties and districts in the east achieving better coordination; and (3) the spatial variation in the coupling of protection and development is influenced by regional economic capacity, social development, resource endowment, and policy inclination, with various factors influencing the coordination in different ways. This study helps to further elucidate the relationship between the protection and development of traditional villages and provides valuable references for the protection and development of traditional villages in other ecologically fragile areas. Full article

The Loess Plateau, with a fragile ecological environment, is one of the most serious water- and soil-eroded regions in the world, which has been improved by large-scale projects involving returning farmland to forest and grassland. This work is mainly aimed at exploring a more reasonable and efficient ecological forest restoration mode and revealing synergistic restoration mechanisms. This study sampled typical Loess Plateau areas and designed the restoration modes for pure forests of Armeniaca sibirica L. (AR), Amygdalus davidiana (Carrière) de Vos ex Henry. (AM), Medicago sativa L. (MS), and mixed forests of apricot–peach–alfalfa (AR&AM&MS), using abandoned land (AL) as a control treatment. The effects of these modes on the physical and chemical properties and enzyme activities of various soils were investigated in detail. Moreover, the soil microbial diversity and community structure, functional gene diversity, and differences in the restoration modes were deeply analyzed by meta-genomic sequencing technology, and the inherent driving correlation and mechanisms among these indicators were discussed. The results showed that the soil water content and porosity of the AR, AM, and AR&AM&MS treatments increased significantly, while the bulk density decreased significantly, compared with AL. Moreover, the total carbon, total nitrogen, nitrate nitrogen, total phosphorus, available phosphorus, total potassium, and available potassium contents of the AR&AM&MS restoration mode increased significantly. Compared to CK, there was no significant change in the catalase content of pure forest and mixed forest; however, the contents of urease, phosphatase, sucrase, B-glycanase, and N-acetylglucosaminidase in the restoration mode of the mixed forest all increased significantly. The species diversity index of the restoration modes is similar, and the dominant bacteria in soil microorganisms include Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, and Gemmatimonadetes. The mixed forest restoration mode had the highest microbial abundance. The functional gene diversity of the different restoration modes was also similar, including kegg genes, eggNOG genes, and carbohydrate enzymes. The functional genes of the mixed forest restoration mode were the most abundant, and their restoration mechanism was related to the coupling effect of soil–forest grass. After evaluation, the restoration mode of mixed forest was superior to that of pure forest or pure grass. This is attributed to the fact that the mode can improve soil structure, retain soil moisture, enhance soil enzyme activity, optimize soil microbial community structure, and improve microbial diversity and functional gene activity. This provides key data for the restoration of fragile ecological areas, and the promotion of sustainable management of forests and grass in hilly areas of the Loess Plateau. Full article

Soil erosion has become an increasingly serious issue, drawing global attention. As one of the countries facing severe soil erosion in the world, China confronts significant ecological challenges. Against this backdrop, the country places great emphasis on soil conservation efforts, considering them a crucial component of ecological civilization construction. This study focuses on the carbon sink benefits of comprehensive soil conservation management in the loess hilly region and sandy slopes, using the Xiaonanshan Mountain small watershed in Youyu County, Shanxi Province, as a typical case for in-depth analysis. In terms of research methodology, an integrated monitoring approach combining fundamental data, measured data, and remote sensing data was developed. A comprehensive survey of the Xiaonanshan Mountain small watershed was conducted to categorize plant carbon pools and soil carbon pools, establish baseline scenarios, and utilize methods such as inverse distance spatial interpolation, sample calculation, and feature extraction to estimate forest carbon storage across different years and determine changes in soil and vegetation carbon storage. Simultaneously, data collection and preprocessing were carried out, including the gathering of fundamental data, field data collection, and internal data preprocessing. On this basis, a vegetation carbon storage model was constructed, and an assessment of soil carbon pool storage was conducted. The research results indicate that from 2002 to 2024, the continuous implementation of various soil conservation measures over 22 years has led to a significant increase in carbon storage within the Xiaonanshan Mountain small watershed. The vegetation carbon density of the entire small watershed increased from 14.66 t C/ha to 27.02 t C/ha, and the soil carbon density rose from 28.92 t C/ha to 32.48 t C/ha. The net carbon sink amount was 18,422.20 t C (corresponding to 67,548.08 t CO₂e in terms of carbon dioxide equivalent). Populus simonii and Pinus sylvestris var. mongholica significantly contribute to the carbon sink; however, due to partial degradation of Populus simonii, its net carbon sink amount is less than that of Pinus sylvestris var. mongholica. Additionally, the carbon sink capacity of the small watershed exhibits spatial differences influenced by conservation measures, with high carbon density areas primarily concentrated within the range of Populus simonii, while low carbon density areas are mainly found in shrub zones. The increase in carbon storage within the small watershed is primarily attributed to the contributions of vegetation and soil carbon storage, indicating that comprehensive soil erosion management has a significant carbon accumulation effect; moreover, the annual growth rate of vegetation carbon storage exceeds that of soil carbon storage, with the proportion of soil carbon storage increasing year by year. Furthermore, the vegetation carbon sink, soil carbon sink, and total carbon sink of the small watershed were separately calculated. In terms of benefit analysis, the Xiaonanshan Mountain small watershed offers ecological benefits such as increased forest coverage, carbon fixation and oxygen release, and biodiversity conservation; from an economic perspective, the value of carbon trading is substantial, promoting soil conservation and rural revitalization, with the total value of timber reaching 7.6 million yuan, of which the value of standing timber constitutes the largest proportion; social benefits include the improvement of environmental landscapes, stimulation of ecological tourism, and attraction of investment, with the Xiaonanshan Mountain Ecological Park receiving numerous visitors and generating significant tourism revenue. This research provides a theoretical basis and data foundation for comprehensive soil conservation management in project areas or small watersheds within the loess hilly and sandy slope regions, offering technical and methodological support for other soil conservation carbon sink projects in the area. Full article

The hilly and gully region of the Loess Plateau represents one of China’s most ecologically vulnerable landscapes, characterized by severe soil erosion, intensive land use, and pronounced disturbances to the structure and functionality of ecosystem services. Taking Zichang City as a case study, this research integrates grid-scale analysis with the InVEST-PLUS model and bivariate spatial autocorrelation techniques to examine the spatiotemporal dynamics and inter-relations of four critical ecosystem services—carbon storage, water yield, biodiversity, and soil retention—under varying land use intensity scenarios from 1990 to 2035. The findings indicate that (1) between 1990 and 2020, land use intensity in Zichang City steadily declined, exhibiting a spatial distribution pattern typified by central-area clustering and gradual peripheral transitions. (2) Across three development scenarios, the spatial distribution of the four ecosystem services aligned with the patterns observed in 2020, with central areas showing pronounced fluctuations, whereas peripheral regions experienced relatively minor changes. Specifically, from 1990 to 2020, the proportion of low-carbon storage areas increased by 2.89%, and high water yield areas expanded by 9.45%, while the shares of low habitat quality and low soil retention areas decreased by 5.59% and 6.25%, respectively. (3) A significant spatial autocorrelation was observed between land use intensity and the four ecosystem services, with widespread cold and hot spots reflecting dynamic spatial clustering patterns. These results offer valuable insights for optimizing land use strategies, improving ecosystem service performance, and advancing ecological conservation and sustainable development initiatives. Full article

The terrain in the loess hilly area of western Henan is fragmented, with steep slopes and weak soil erosion resistance. The substantial soil erosion in this region results in plenty of problems, including decreased soil productivity and ecological degradation. These problems significantly hinder the social and economic development in the region. Soil conservation planning and ecological development require accurate soil erosion surveys. However, the studies of spatio-temporal patterns, evolution, and the driving force of soil erosion in this region are insufficient. Therefore, based on a multi-stage, unequal probability, systematic area sampling method and field investigation, the soil erosion of the loess hilly area of western Henan was quantitatively evaluated by the Chinese Soil Loss Equation (CSLE) in 2022. The impact forces of soil erosion were analyzed by means of a geographic detector and multiple linear regression analysis, and the key driving factors of the spatio-temporal evolution of soil erosion in this region were revealed. The results were as follows. (1) The average soil erosion rate of the loess hilly area in western Henan in 2022 was 5.94 t⋅ha⁻¹⋅a⁻¹, with a percentage of soil erosion area of 29.10%. (2) High soil erosion rates mainly appeared in the west of Shangjie, Xingyang, and Jiyuan, which are related to the development of production and construction projects in these areas. The areas with a high percentage of soil erosion area were in the north (Xinan and Yima), west (Lushi), and southeast (Songxian and Ruyang) of the study area. Moreover, areas with the most erosion were found in forest land, cultivated land, and areas with a slope above 25°. (3) At the landscape level, the number and density of patches of all land types, except orchard land, increased significantly, and the boundary perimeter, landscape pattern segmentation, and degree of fragmentation increased. (4) The geographical detector and multiple linear regression analysis indicated that the driving forces of soil erosion are mainly topographic and climatic (slope length, elevation, precipitation, and temperature). Soil erosion was significantly influenced by the density of landscape patches. These maps and factors influencing soil erosion can serve as valuable sources of information for regional soil conservation plans and ecological environment improvements. Full article

Afforestation in the transitional zone between the loess hilly area and the Mu Us Sandy Land of China has reshaped the landscape and greatly affected eco-hydrological processes. Plantations are crucial for regulating local net rainfall inputs, thus making it necessary to quantify the closure loss of plantation species in drought and semi-arid areas. To quantify and model the canopy interception of these plantations, we conducted rainfall redistribution measurement experiments. Based on this, we used the modified Gash model to simulate their interception losses, and the model applicability across varying rainfall types was further compared and verified. Herein, Caragana korshinskii, Salix psammophila, and Pinus sylvestris plantations in the Kuye River mountain tract were chosen to measure the precipitation distribution from May to October (growing season). The applicability of a modified Gash model for different stands was then evaluated using the assessed data. The results showed that the canopy interception characteristics of each typical plantation were throughfall, interception, and stemflow. The relative error of canopy interception of C. korshinskii simulated by the modified Gash model was 8.79%. The relative error of simulated canopy interception of S. psammophila was 4.19%. The relative error of canopy interception simulation of P. sylvestris was 13.28%, and the modified Gash model had good applicability in the Kuye River Basin. The modified Gash model has the greatest sensitivity to rainfall intensity among the parameters of the C. korshinskii and S. psammophila forest. The sensitivity of P. sylvestris in the modified Gash model is that the canopy cover has the greatest influence, followed by the mean rainfall intensity. Our results provide a scientific basis for the rational use of water resources and vegetation restoration in the transitional zone between the loess hilly region and the Mu Us Sandy Land. This study is of import for the restoration and sustainability of fragile ecosystems in the region. Full article

The selection of suitable tree species and the reasonable allocation of planting areas are important measures for improving soil quality. To evaluate the soil quality (SQ) and its driving factors of Pinus tabuliformis forests in loess hilly areas where forestry ecological projects, such as returning farmland to forest (grass), have been implemented, this study selected P. tabuliformis forests with different restoration years (1a, 6a, 11a, 18a, and 22a) in Wuqi County and used grassland before afforestation (PRG) and abandoned grassland (AG) with 22 years as controls. In this study, soil physicochemical indices, soil fauna indices, and herbaceous plant indices obtained via principal component analysis were used to establish a soil quality evaluation model via the fuzzy comprehensive evaluation method to comprehensively evaluate SQ. Structural equation modeling (SEM) was used to identify the key factors affecting the SQ of P. tabuliformis forests. The goal was to create a model that could effectively evaluate the SQ while considering all relevant factors. The findings of the study showed that: (1) by performing a principal component analysis on the 27 indicator factors, the first six principal components had eigenvalues > 1, and the cumulative contribution rate was 90.028%, effectively encompassing the information of the original variables. (2) The highest soil quality index (SQI) was 0.592 (p < 0.05) in the restored 6a P. tabuliformis forest, whereas the lowest SQI was 0.323 in the restored 1a P. tabuliformis forest. As the number of years of restoration increased, the SQ of the P. tabuliformis plantation forest progressively approached that of the long-term abandoned grassland, with only a 1.8% difference after 22 years of restoration. The SQI of the P. tabuliformis woodland in restored 6a was 83% higher than that of 1a, and following 6a of restoration, the SQI showed a decreasing trend with increasing restoration years. Nevertheless, the SQI increased by >52% compared with the early stage of restoration (1a) and by 31% compared with the grassland before afforestation (PRG). (3) SEM revealed that the SQ of P. tabuliformis forest land was mainly driven by soil physical and herbaceous plant indicators, and soil fauna indicators and restoration years had a negative effect on the evolution of SQ in P. tabuliformis forests. The driving factors of P. tabuliformis forests of different restoration years were different, and with the increase in restoration years, the effects of soil fauna and herbaceous plant indicators on the SQ of P. tabuliformis plantation forests showed an overall upward trend. Full article

The Loess Plateau is an important source of particulate matter pollution in North China. In order to establish and repair shelterbelts and improve their function of inhibiting wind erosion and dust, four typical shelterbelts (Populus simonii, Pinus tabulaeformis Carr., Pinus tabulaeformis Carr. × Populus simonii and Caragana korshinskii Kom.) were selected to investigate the inhibition rate of soil wind-erosion and the reduction rates of PM₁, PM_2.5 and PM₁₀ by stand type, stand structure and soil properties. A sample plot survey and semi-fixed observation method were used to measure wind speed and particulate matter concentration and to calculate wind protection effect, sand transport rate, vertical flux of particulate matter, wind-erosion inhibition rate and particulate matter reduction rate. The results showed that the Pinus tabulaeformis Carr. forest and Caragana korshinskii Kom. forest had the best windproofing effect, at 2 m (82.9% ± 23.8%) and 0.5 m (54.4% ± 21.5%), respectively. The distribution curve of the sediment flux of shelterbelts is a logarithmic function. The wind-erosion inhibition rate and PM₁ reduction rate of the Pinus tabulaeformis Carr. forest were significantly greater than those of other stand types (p < 0.05). The generalized linear mixed model (GLMM) shows that the DBH variation coefficient (CV) can effectively explain the reduction rate of PM₁. It is suggested that policies be enacted to add or replace Pinus tabulaeformis Carr. forest in polluted areas to prevent wind erosion and dust. Full article

The unique geographic environment, diverse ecosystems, and complex landforms of the Qinghai–Tibet Plateau make accurate land cover classification a significant challenge in plateau earth sciences. Given advancements in machine learning and satellite remote sensing technology, this study investigates whether emerging ensemble learning classifiers and submeter-level stereoscopic images can significantly improve land cover classification accuracy in the complex terrain of the Qinghai–Tibet Plateau. This study utilizes multitemporal submeter-level GF-7 stereoscopic images to evaluate the accuracy of 11 typical ensemble learning classifiers (representing bagging, boosting, stacking, and voting strategies) and 3 classification datasets (single-temporal, multitemporal, and feature-optimized datasets) for land cover classification in the loess hilly area of the Eastern Qinghai–Tibet Plateau. The results indicate that compared to traditional single strong classifiers (such as CART, SVM, and MLPC), ensemble learning classifiers can improve land cover classification accuracy by 5% to 9%. The classification accuracy differences among the 11 ensemble learning classifiers are generally within 1% to 3%, with HistGBoost, LightGBM, and AdaBoost-DT achieving a classification accuracy comparable to CNNs, with the highest overall classification accuracy (OA) exceeding 93.3%. All ensemble learning classifiers achieved better classification accuracy using multitemporal datasets, with the classification accuracy differences among the three classification datasets generally within 1% to 3%. Feature selection and feature importance evaluation show that spectral bands (e.g., the summer near-infrared (NIR-S) band), topographic factors (e.g., the digital elevation model (DEM)), and spectral indices (e.g., the summer resident ratio index (RRI-S)) significantly contribute to the accuracy of each ensemble learning classifier. Using feature-optimized datasets, ensemble classifiers can improve classification efficiency. This study preliminarily confirms that GF-7 images are suitable for land cover classification in complex terrains and that using ensemble learning classifiers and multitemporal datasets can improve classification accuracy. Full article

Combined organic and inorganic fertilization can improve soil fertility in coal mine reclamation areas. However, the contribution of the bacterial community (especially its occurrence patterns) to soil physicochemical properties and enzyme activity needs further evaluation. The objective of this research was to clarify the bacterial community diversity, composition, and intraspecific interactions in response to combined organic and inorganic fertilizer application in coal mine reclamation areas in the Loess Hilly Region, China. Maize rhizosphere soil samples were collected under four fertilization regimes (CK, no fertilization control; NPK, compound inorganic fertilizer; M, organic fertilizer; and NPKM, combined organic and inorganic fertilization) in a 10-year field experiment in Gujiao city, Shanxi Province. Bacterial communities were characterized using high-throughput sequencing of the 16S rRNA gene V3–V4 region. A cross-treatment Spearman correlation network was constructed to explore the bacterial co-occurrence patterns. Compared with CK, NPK, M, and NPKM decreased the pH by 0.59%, 2.27%, and 0.12%; increased the soil organic carbon by 11.25%, 11.69%, and 27.05%; and significantly decreased the bacterial Shannon diversity by 3.68%, 0.14%, and 3.54%, respectively. Compared with CK, NPKM significantly increased sucrase, urease, and alkaline phosphatase activities (p < 0.05). Critically, oligotrophic Acidobacteria were significantly more abundant in CK than in the other treatments. Gemmatimonadetes were more abundant in NPK and M, and Actinobacteria, Bacteroidota, and Patescibacteria were more abundant in NPKM. In addition, network analysis revealed that the keystone taxa in the different fertilization treatments belonged to different network modules and were significantly correlated with soil nutrient content and enzyme activity. Simultaneously, the Actinobacteria enriched in NPKM formed specific clusters through strong symbiosis, and there were significant positive correlations among sucrase, urease, and alkaline phosphatase. In summary, long-term combined organic and inorganic fertilization improved maize rhizosphere soil fertility by regulating enzyme activity, bacterial community composition, and bacterial species interactions in coal mine reclamation areas in the Loess Hilly Region. Full article