Sustainable Land Management Research Articles

Adoption of sustainable land and water management practices and their impact on crop productivity among smallholder farmers in sub-Saharan Africa

Adoption of sustainable land and water management practices and their impact on crop productivity among smallholder farmers in sub-Saharan Africa

Dynamic impacts of urban expansion on vegetation growth in urban environments: A sustainable land management framework

Dynamic impacts of urban expansion on vegetation growth in urban environments: A sustainable land management framework

Assessment of land degradation neutrality to guide Sustainable Land Management practices in Ethiopia

Assessment of land degradation neutrality to guide Sustainable Land Management practices in Ethiopia

Assessment of soil erosion dynamics and implications for sustainable land management: A case study using the RUSLE model

Assessment of soil erosion dynamics and implications for sustainable land management: A case study using the RUSLE model

Effects of artificial waterpoints on woody species composition and structure in semi-arid communal rangelands, northern Namibia

The provision of artificial water resources for livestock in communal rangelands in arid environments is a major driver of land degradation. This study examined the impact of waterpoints on woody plant species composition and structure in the Omuntele communal rangeland, Namibia. Fieldwork was conducted during the dry season at three waterpoints within the rangeland. The study employed a randomised block design, with quadrats placed at 50 m intervals radiating from each waterpoint. Results show the effects of distance from waterpoints on species richness, abundance, diversity, and evenness of woody species. The results further reveal variations in woody plant structural attributes across distance from waterpoints. Pearson’s correlation indicated complex relationships between woody vegetation composition and structure, suggesting an interplay between vegetation structural attributes, richness, diversity, and evenness. The findings improved our understanding of ecological dynamics in rangeland ecosystems, particularly concerning how structural variations affect ecological functions. For example, alterations in vegetation structure may have an impact on it’s grazing and browsing value for livestock, and forest resource availability to the local communities. They may also influence biodiversity within the area due to habitat change. These revelations are essential for developing sustainable land management strategies that meet the requirements of communities and their livestock.

Mapping the Research Landscape of Land Use and Land Cover Change: A Bibliometric Analysis

The Land Use and Land Cover (LULC) change is a crucial phenomenon in environmental science, reflecting the interplay between human activities and natural ecosystems. This bibliometric review examines research trends, thematic focus, and methodologies in LULC studies published between 1993 and 2023 through a systematic search criteria and PRISMA framework. Data were retrieved from Scopus and Web of Science and filtered for peer-reviewed journal articles, yielding 2,655 records. Analysis using R Bibliometrix and VOSviewer revealed a significant surge in the LULC studies after 2000, particularly from 2011 to 2020, aligned with advances in GIS and remote sensing tools. The results showed that leading journals are ‘Environmental Monitoring and Assessment’ in Scopus and ‘Ecological Indicators’ in Web of Science (WoS). The most relevant author is Burkhard Benjamin, who appears in both databases. The key themes include climate change, biodiversity loss, and sustainable land management, highlighting the growing interdisciplinary nature of LULC research. Emerging topics encompass urbanization, climate impacts, and ecosystem services, and spatially explicit modeling approaches, such as cellular automata, have gained prominence recently. The collaborative networks indicate China, notably Beijing Normal University and the Chinese Academy of Sciences, as leading contributors. Despite major progress, gaps remain in integrating interdisciplinary perspectives and systematic classifications of LULC trends. This review underscores the importance of bibliometric analysis in guiding future LULC research and calls for stronger collaborations and policy-oriented frameworks to address global challenges. Bridging technological innovations, with socio-environmental considerations, is essential in fostering resilience in land management practices.

Classification of grassland community types and palatable pastures in semi-arid savannah grasslands of Kenya using multispectral Sentinel-2 imagery

Semi-arid grassland ecosystems are crucial for biodiversity, carbon sequestration, and animal fodder; however, they are increasingly threatened by overgrazing degradation and climate variability. Understanding their spatial distribution and palatability is essential for sustainable land management and maintenance of pastoralist livelihoods. This study aimed to map grassland communities and assess their palatability in semi-arid Kenya using Multiple Endmember Spectral Mixture Analysis (MESMA) and Sentinel-2 satellite imagery, integrating species abundance with forage quality metrics. Sentinel-2 imagery was processed using MESMA to classify the fractional cover of four key grass species (Cynodon, Setaria, Themeda, and Kunthii) along with non-grass land cover types (bare ground, forests, shrubs, and water). An iterative endmember selection method optimized the classification, achieving a root mean square error (RMSE) of 23.5% and a 6% improvement in the overall accuracy compared to the unoptimized models. Palatability was assessed based on literature-derived chemical analyses and pastoralists’ perceptions of the forage quality. In the study area, medium and low-palatable species (Setaria and Kunthii) predominated lowland and midland areas, whereas highly palatable Cynodon was found in small, scattered areas across varied elevations. Mixed-grass communities were found in the central areas. The optimized MESMA model effectively identified overgrazed areas and areas vulnerable to degradation by observing grass palatability with grazing pressure from wildlife and livestock. The MESMA model utilized Sentinel-2 imagery and successfully characterized grassland communities’ spatial distribution and palatability in the study area. These findings provide actionable insights for sustainable grazing management and land protection, assisting pastoralists in identifying optimal grazing areas and enabling land managers to implement targeted restoration measures.

Enhancing biomass production in multifunctional agroforestry: A review of strategies and benefits

The decline in the global forest area has increased the demand for timber and forest products, necessitating sustainable forestry practices. Agroforestry integrates trees with crops and livestock, offering multifunctional benefits including soil improvement, biodiversity conservation and climate change mitigation. This review explores agroforestry’s diverse roles, emphasizing biomass production enhancement through optimized planting methods, nutrient management and water conservation. It highlights the environmental, economic and social benefits of agroforestry while addressing sustainable land use. Agroforestry enhances soil quality through improved nutrient cycling and biodiversity. Researchers indicated that agroforestry practices reduce the soil temperature (3.37-9.25 %) and increase the soil moisture considerably (10-20 %). They also reduce the soil erosion by 50 % thus stabilizing soil structure. An increase in soil organic carbon (40 %), nitrogen storage (13 %) and accessible nitrogen and phosphorus (46 % and 11 %) availability was also reported by many. In pest management, it considerably reduces flies (38 %), pollen beetles (57 %), wheat stem sawflies (37 %) and aphid damage by 13 % while increasing farm income. Agroforestry represents a viable strategy for sustainable land management, food security and ecological restoration. Tailored models can improve economic returns, environmental sustainability and climate resilience. Further research should refine best practices and integrate advanced technologies to maximize the benefits.

Mitigating Erosion and Enhancing Sediment Retention: A Modeling Approach to Sustainable Land Management

Abstract Soil erosion poses a critical threat to global ecosystems, water resources, and agricultural productivity. This study assesses how Sustainable Land Management (SLM) mitigates sediment export and improves climate resilience using the InVEST Sediment Delivery Ratio (SDR) model across 12 Moroccan basins, representative of Mediterranean and arid environments. Our results identify significant hotspots in northern basins, where steep slopes and annual rainfall exceeding 500 mm drive erosion rates up to 14,700 tons per year, contributing substantially to downstream sediment transport. Conversely, arid basins exhibit lower erosion rates due to reduced precipitation and gentler slopes but struggle with sediment retention, with efficiencies below 50%. SLM interventions, such as a 25% increase in soil organic matter in agricultural lands, reduced sediment export by over 25% in northern basins and decreased sediment loss by more than 1 ton per hectare annually in vulnerable agricultural areas. These measures were especially effective in forested and terraced landscapes, enhancing sediment retention and minimizing impacts on reservoirs and water systems. This study underscores the dynamic nature of erosion and sediment transport under varying environmental and management conditions. By integrating high-resolution spatial data with scenario-based modeling, it provides a transferable framework for implementing SLM practices in erosion-prone regions. The findings emphasize the necessity of adaptive management to address soil erosion and inform sustainable land-use planning globally. Graphical Abstract This Graphical Abstract visually summarizes the study’s key findings on the role of Sustainable Land Management (SLM) in mitigating soil erosion and sediment export. The diagram outlines the methodology and key variables influencing erosion processes, using the Sediment Delivery Ratio (SDR) model to assess the impacts of SLM interventions. The left section of the figure highlights the study area in Morocco, covering 102 sub-basins across 12 hydrological basins, where erosion processes were analyzed. It illustrates a comparison between the current scenario and an SLM scenario, where agricultural lands experience a 25% increase in soil organic matter. In the central section, key environmental factors—land use, rainfall, soil erodibility (K Factor), and slope—are depicted as primary variables influencing sediment dynamics. These factors interact with SDR outputs, affecting soil loss, sediment export, and deposition patterns. The SDR model application (bottom-left) integrates these variables to simulate erosion processes, generating spatial outputs such as RUSLE, sediment export, sediment deposition, avoided export, and avoided erosion. The results demonstrate the differences between the current scenario and the SLM intervention, emphasizing the potential of improved land management practices. On the right side, statistical analysis results highlight the relationships between precipitation, slope, soil erodibility, and sediment transport across the study basins. The conclusion box presents the main findings: A 25% increase in soil organic matter reduces sediment loss by > 1 ton/ha annually. Scenario-based modeling provides a transferable framework for SLM applications. SLM significantly decreases soil erosion and sediment export, enhancing climate resilience. This graphical representation provides a clear and concise visual synthesis of the study, facilitating a better understanding of erosion processes and SLM effectiveness in mitigating land degradation.

Observing the Landscape and Lifescape of the Jeneberang Hulu Watershed: Interactions Between Development and Local Communities

Abstract The evolving understanding of the relationship between humans and the environment has led to the concept of landscape-lifescape, emphasizing the integration of biophysical and human elements in sustainable land management. This study analyzes the dynamics of landscape and lifescape in the Jeneberang Hulu Watershed, Gowa Regency, South Sulawesi Province, Indonesia, focusing on the influence of stakeholder interactions on rural community livelihoods. Utilizing Geographic Information Systems (GIS), structured interviews, and focus group discussions (FGDs), the study identifies significant connections between landscape changes and livelihood capitals: social, economic, natural, human, and physical. Results indicate that 60 % of lifescape conditions are moderate, 20 % are low, and 20 % are high. Natural capital has transitioned from vegetated community land to residential land as the area develops into a tourist destination, impacting economic capital by shifting livelihoods toward tourism services. Physical capital, such as road access and housing, is relatively strong, while health conditions are satisfactory. However, education, skills, and access to savings and credit remain challenges. Social capital is robust, characterized by strong harmony and kinship. The study highlights the need for better coordination among stakeholders to enhance community practices in land management, enabling villagers to optimize livelihood capitals for sustainable living.

Unveiling the Potential of Agricultural Soil Loss Mitigation in Poland: Assessing Conservation Management and Support Practices

This study aims to evaluate soil erosion mitigation strategies in Poland’s agricultural landscapes by applying the Revised Soil Loss Equation (RUSLE) model to identify high-risk areas where excessive soil loss adversely affects agricultural sustainability and productivity. Scenario assessments were conducted to evaluate the effectiveness of specific conservation practices—contour farming, reduced tillage, and cover crops—by simulating changes in the C-factor (cover-management factor) and P-factor (support practices factor) within the RUSLE framework. The research revealed heightened soil erosion rates during the summer months, particularly in regions with steep slopes and loess formations. Analysis indicated that annual soil loss from arable lands in Poland totals approximately 4.65 Mt yr−1 and that contour farming, reduced tillage, and cover crops could collectively reduce this amount by up to 47%, with the highest reduction observed during the summer period. These findings highlighted the urgent need for stakeholders to adopt sustainable land management strategies. By quantifying the impact of these management practices on soil erosion rates, the study provided insights into the effectiveness of soil conservation measures in reducing erosion risks within Poland’s agricultural landscapes. This study emphasizes the importance of adopting sustainable land management strategies to preserve soil integrity and maintain agricultural productivity in Poland.

Profile of Urban and Peri-Urban Agriculture in Rio de Janeiro State: Case Study

Objective: This study investigates the profile of urban, peri-urban, and potential agricultural producers in the State of Rio de Janeiro, classifying them according to social, management, and environmental aspects using frequency analysis and Spearman correlation. Theoretical framework: The study draws on concepts of urban and peri-urban agriculture, sustainability, urban planning, and public policies to analyze producer profiles and political challenges. Method: Quantitative and exploratory interviews were conducted with 159 producers across 29 municipalities. Data were analyzed through frequency distributions and Spearman correlation. Results and Discussion: Producers are predominantly men over 50 years old, with primary or secondary education, cultivating small plots (<500 m²), favoring organic fertilization and alternative pest control methods, but with little technical support. Key challenges include lack of assistance and resources. Despite its potential for food security and local development, urban agriculture remains hindered by the absence of effective policies. The sample may not fully represent the state's diversity. Research implications: The study supports the formulation of public policies for urban agriculture, contributing to productive inclusion, food security, and sustainable urban land use. Originality/Value: By covering producers in 29 municipalities and employing statistical classification methods, this study advances beyond localized approaches, providing valuable insights for the planning of public policies related to urban agriculture and sustainable land management.

Analysis of Land Use Impact on Land Surface Temperature Changes in the Ultramafic Rock Mining Area Awang Bangkal Barat Village, South Kalimantan Province, Indonesia

The study aims to analyze land use changes in the area to determine whether these changes impact environmental quality. The conversion of vegetated land into residential areas has led to an increase in surface temperature. Surface temperature refers to the temperature of objects on the Earth's surface. Based on image analysis from 2000 to 2023, the researchers classified the land into five categories: vegetated land, built-up land, mining land, open land, and water bodies. The results indicate significant changes in both land use and land surface temperature (LST) across different land use categories in Awang Bangkal Barat Village, with some areas experiencing an increase while others showed a decrease. The classification of land use and surface temperature was derived from satellite data processing using Landsat 7 for the years 2000 to 2010 and Landsat 8 for the period from 2015 to 2023. Land cover classification was conducted through on-screen digitization, and surface temperature values were extracted from the thermal bands of Landsat imagery. The study found that built-up areas and mining lands showed higher LST values, indicating the effect of urbanization and mining activities on increasing surface temperatures. Conversely, vegetated areas generally exhibited lower LST, emphasizing the importance of maintaining vegetation to regulate local climate. This research highlights the need for sustainable land management practices to mitigate the negative environmental impacts associated with land use changes. By providing a comprehensive analysis of land use patterns and their correlation with LST, the findings offer valuable insights for policymakers in planning urban development while considering environmental sustainability. The integration of long-term satellite data allows for better monitoring and understanding of the dynamics between land use and surface temperature changes over time.

Five Decades of Transformation Due to Human-Environment Stressors: Land Cover, Vegetation, and Land Surface Temperature Change Analysis in the Largest Wetland Ecosystem in Bangladesh

Abstract Chalan Beel, the largest wetland in Bangladesh, plays a crucial role in maintaining ecological balance and supporting local community livelihoods. This vital ecosystem has undergone significant landscape transformations over the past five decades due to increasing anthropogenic pressures. This is the first study that examines spatiotemporal changes in land cover, Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST) in the Chalan Beel wetland ecosystem from 1973 to 2023 using remote sensing (RS) and Geographic Information System (GIS). Landsat imagery was utilized, and an unsupervised classification was performed to categorize land cover into five major classes: developed land, farmland, high vegetation, water, and wetland. The results reveal a clear trend of increasing anthropogenic activities, particularly the expansion of farmlands and developed areas, alongside a decline in high vegetation and wetlands, with the most pronounced changes occurring between 2013 and 2023. Accuracy assessments yielded overall accuracies of 72.5% (1973), 73.8% (1980), 75.0% (1993), 73.8% (2003), 72.5% (2013), and 77.5% (2023). NDVI analysis indicates declining vegetation health from 1973 to 2023, while LST trends reflect a consistent rise in surface temperatures from 1993 to 2023. These findings highlight intensified land use pressures driven by population growth and economic activities. The study provides critical insights into the environmental dynamics of Chalan Beel, emphasizing the urgent need for sustainable land management and wetland conservation strategies. It contributes to evidence-based policymaking and supports global efforts to achieve Sustainable Development Goal 6, Target 6, which is related to protecting and conserving resources like mountains, forests, wetlands, rivers, aquifers, and lakes throughout the globe, including Bangladesh. Graphical Abstract This graphical abstract provides a comprehensive, step-by-step visual summary of the spatiotemporal assessment of Chalan Beel, Bangladesh’s largest wetland ecosystem, from 1973 to 2023. It illustrates the methodological flow from satellite image retrieval and preprocessing through land cover classification, NDVI, and LST computation using ArcGIS Pro 3.1. The workflow highlights the use of thermal and spectral bands to derive key environmental indicators. On the left, land cover change maps reveal a sharp increase in developed and farmland areas, alongside a decline in high vegetation and wetlands. The NDVI trend chart shows a progressive decrease in vegetation health, while the LST trend graph confirms a steady rise in surface temperatures. These results demonstrate clear signs of ecological stress driven by increased anthropogenic activities. Combining time-series maps, diagrams, and classification outputs creates a visually intuitive abstract. It effectively communicates how landscape transformations and environmental degradation interrelate over the last five decades. This visual summary is an essential bridge between technical methodology and actionable insights, reinforcing the urgency of adopting sustainable land management and wetland conservation policies in Chalan Beel of Bangladesh.

A Comprehensive Evaluation of Land Reclamation Effectiveness in Mining Areas: An Integrated Assessment of Soil, Vegetation, and Ecological Conditions

Land reclamation is crucial for restoring ecosystems in mining areas, improving land use efficiency, and promoting sustainable regional development. Traditional single-indicator assessments fail to capture the full complexity of reclamation, highlighting the need for a more comprehensive evaluation approach. This study combines field-measured and remote sensing data to develop multiple evaluation indices, creating a comprehensive framework to assess reclamation effectiveness. A soil quality index based on the Minimum Data Set (SQIMDS) was developed to analyze spatial variations in soil quality, efficiently capturing key soil attributes. Remote sensing data were used to calculate the Dump Reclamation Disturbance Index (DRDI) and the Enhanced Coal Dust Index (ECDI) to evaluate vegetation recovery and ecological improvements. The Comprehensive Evaluation Quality Index (CEQI) was introduced, synthesizing soil, vegetation, and ecological conditions for a holistic assessment. Key findings include significant soil quality improvement over time, with MDS effectively capturing variations; vegetation recovery increased with reclamation duration, though regional disparities were observed; ecological conditions steadily improved, as evidenced by a decline in ECDI values and reduced contamination; and the CEQI reflected overall improvements in reclamation effectiveness. This study offers a practical framework for coal mining land reclamation, providing scientific support for decision-making and guiding effective reclamation strategies for ecological restoration and sustainable land management.

A soil organic carbon mapping method based on transfer learning without the use of exogenous data

Accurate and cost-effective mapping of soil organic carbon (SOC) is critical for understanding carbon dynamics and informing sustainable land management. Although deep learning-based methods have demonstrated strong potential in digital soil mapping, they typically require large amounts of data. However, the availability of site-level SOC observations is often limited, which poses a challenge for model performance. To address this, we propose a novel transfer learning approach based on a Convolutional Neural Network (CNN) model that does not rely on exogenous data. Specifically, when predicting SOC for a given soil layer, the model is first pre-trained on data from all layers and then fine-tuned using data from the target layer. This design enables more efficient use of limited site data. Experimental results show that the proposed transfer model consistently outperforms other machine learning models, including the Random Forest (RF), standard CNN, and Multi-Task CNN (MTCNN) models. The transfer model achieves a coefficient of determination (R2) of 0.374 and a root mean square error (RMSE) of 2.937%, indicating superior performance. These findings highlight the effectiveness of the proposed approach for digital soil mapping under data-scarce conditions and underscore its potential as a robust tool for accurate SOC estimation.

Topographical Discrepancy in Heavy Metal Pollution and Risk Assessment from Cornfields in the Licheng District, China

Heavy metal pollution refers to the presence of excessive levels of heavy metal elements in soil beyond their natural background concentrations, posing serious threats to human health and ecological systems. Several factors are involved in the contamination disparity in agriculture soils from various terrains, demanding extra care. An examination of the topographical HM dispersions in farmland soils from the Licheng District was conducted to reveal spatial changes in pollution levels and sources and to establish an empirical framework to develop targeted remediation strategies and promote sustainable land management practices. Cd and As had over-standard rates of more than 50% in the low-lying area, whereas the HMs in the high-lying area had over-standard rates of more than 50%. Also, the rates of HMs in high terrain were higher than in low terrain. Using the single-factor pollution index, only low-lying Cu, Ni, Pb, and Hg contamination levels were clean in low-lying and high-lying areas. The overall decline in HM pollution occurred from high to low terrain, triggered by soil physicochemical properties and human interventions. Meanwhile, strong anthropogenic influence fell in high terrain for pollution. Nevertheless, low levels of HM-integrated contamination prevailed in both topographies. Natural and anthropogenic processes gave rise to environmental pollution, such as soil formation, fertilization, metal smelting, and traffic emissions. Overall, the district held a low risk for HMs. The results highlight that strong anthropogenic interventions resulted in increased HM contamination, in addition to natural processes. It is possible to further reduce HM pollution and risk by promoting scientific agricultural techniques, new energy vehicles, and cleaner production.

Assessment of climate change impacts and land cover dynamics in the Upper Sakarya Basin, Türkiye using the Collect Earth approach

Abstract Long-term monitoring and evaluation of climate change effects in a basin help identify trends, assess ecosystem resilience, and guide adaptive management for sustainable resource use and conservation. The Upper Sakarya Basin (USB), which has the ability to represent semiarid areas of Turkey due to its climate and environmental conditions and land use integrity, was selected as the study area. The study focused on Land Cover and Land Use Transformations, soil moisture, evapotranspiration, Normalized Difference Vegetation Cover (NDVI), Net Primary Production (NPP), water deficit criteria in the basin for a 20-year period (2000–2020) in order to support adaptive management and conservation strategies and to evaluate the effects of climate change on ecosystem dynamics, water balance and vegetation health. As a field monitoring and evaluation method, Collect Earth (CE), which is a sample-based visual interpretation method, was selected because it can better explain the complex structure of land cover types and provides the opportunity to easily access and interpret many graphical data through the GEE code editor. In the context of Land Use, Land-use Change and Forestry (LULUCF), it was observed that the increase in Forestland was due to afforestation activities in Grassland. Although this situation was observed in NDVI observations, it was not evaluated as a net gain area compared to the past situation of Forestland in terms of the ecosystem and the services they provide. It was determined that the conversion to Settlement in the basin was rapid and large in area. As an indicator of vegetation productivity, it was determined that the areas with decreasing trend in NPP were Forestland and Settlement. According to water deficit data, it was determined that water deficit was high in regions where intensive agriculture was carried out in the basin. Evapotranspiration value was continuously increasing for the basin in general, while soil moisture was on a decreasing trend. These findings emphasize the vulnerability of the basin to climate change and emphasize the need for sustainable land and water management strategies. It is recommended that decision makers at the basin scale develop policies based on these findings and evaluate interventions within the framework of a balancing approach against land degradation.

Spatiotemporal Patterns of Agriculture Expansion Intensity and Land-Use/Cover Changes in the Mixed Urban-Rural Upper Kafue River Basin of Zambia (1989–2019)

Understanding land-use and land-cover (LULC) changes is essential for sustainable land management, particularly in regions experiencing rapid urbanization and agricultural expansion. This study analyzes the LULC dynamics in the Upper Kafue River Basin, Zambia, from 1989 to 2019, using remote-sensing data, Geographic Information Systems (GISs), and advanced analytical techniques such as intensity analysis and directional gradient analysis. The findings indicate a notable decline in forest cover, primarily driven by agricultural expansion, while built-up areas increased, reflecting urban growth. Forest-to-agriculture conversion emerged as the dominant driver of change, with significant transitions also occurring across multiple land categories. The results highlight a dynamic and complex landscape shaped by overlapping socio-economic and environmental pressures, emphasizing the need for targeted policy interventions to mitigate environmental degradation. These insights provide valuable guidance for policymakers and land managers seeking to balance development with conservation in Zambia and similar regions.

Land Use Types Drive the Distinct Patterns of Bacterial and Fungal Communities in Soils from the Semi-arid Area

Land types and ways of utilization significantly influence soil microbial communities in arid and semi-arid regions, which are vital for nutrient cycling and ecosystem functionality. In this study, the soil bacterial and fungal communities of five land types, including natural grasslands, farmlands, artificial grasslands, uncultivated lands, and riverbeds in the semi-arid lower reaches of the Heihe River, China, were investigated. Farmlands exhibited the highest bacterial Chao1 richness and Shannon diversity, while uncultivated soils had the lowest bacterial Chao1 richness. Fungal diversity was highest in uncultivated soils compared to farmlands. Principal coordinate analysis (PCoA) showed distinct microbial community structures across land types, with Actinobacteria, Proteobacteria, Firmicutes, and Chloroflexi dominating bacterial communities, and Ascomycota and Basidiomycota dominating fungal communities. Life history strategies revealed distinct patterns between bacterial and fungal communities within farmland soils and artificial grassland soils. Microbial community assembly in natural grasslands was primarily deterministic, with limited stochastic influence, while farmlands exhibited mixed assembly processes. Co-occurrence network analysis showed more stable and cooperative microbial networks in natural grasslands, while farmland networks were more competitive and reliant on key species. These findings provide important insights into the role of land use in shaping microbial diversity and ecosystem function, offering guidance for sustainable land management in semi-arid oasis regions.