Soil Erosion Research Articles

Globally increased cropland soil exposure to climate extremes in recent decades

Soil quality is fundamental to nutrient-rich food production and the sustainability of terrestrial ecosystems. However, inappropriate agricultural practices often lead to persistent soil exposure to air and sunlight, which increases soil organic matter losses and erosion risks, particularly under climate extremes. Here, we provide a satellite-based mapping of daily soil exposure occurrence across global croplands from 2001 to 2022 and evaluate the associated degradation risks caused by extreme climate events. We find that while 57% of global croplands experienced a reduction in soil exposure duration in the past two decades, 86% are increasingly subjected to climate extremes. The areas exposed to increasing climate extremes tend to have higher soil organic carbon levels, indicating an intensified degradation risk of global nutrient-rich cropland soils. Our study offers spatio-temporally explicit insights into global cropland soil exposure and its vulnerability to climate extremes, providing evidence to support improvements in sustainable agriculture practices.

Spatiotemporal dynamics of soil erosion in the Daqing river basin: a comparative analysis of mountains and plains

Soil erosion has been significantly exacerbated by climate change and urbanization, posing serious threats to environmental protection and sustainable development. In this study, soil erosion in the Daqing River Basin from 2000 to 2022 was assessed using the revised universal soil loss equation (RUSLE) model, which incorporates data from digital elevation model (DEM), normalized vegetation index (NDVI), and land-use sources, and the spatiotemporal evolution of soil erosion was subsequently analyzed. The impacts of natural and anthropogenic factors on erosion and their interactions with soil erosion were analyzed via random forest and partial least squares-structural equation modeling (PLS-SEM). The results revealed that soil erosion in the Daqing River Basin averaged 159 t/(km2·a) from 2000 to 2022, with averages of 386 t/(km2·a) in the mountains and 1.1 t/(km2·a) in the plains. The erosion intensity increased from southeast to northwest, with higher levels in mountains than in plains. The soil erosion level initially improved but then deteriorated sharply after a significant turning point in 2015. Natural factors, particularly precipitation, were the largest drivers of soil erosion throughout the Daqing River Basin, whereas anthropogenic factors had the greater impact on erosion in plains than in mountains. There was strong synergy among various anthropogenic factors throughout the basin. In the mountains, anthropogenic factors were antagonistic to vegetation coverage, whereas in the plains, they were synergistic with vegetation coverage and meteorological factors.

Influence of soil porosity on hydraulic properties in dike failure induced by overtopping

Coastal dike failures can lead to severe disasters. However, the impact of soil porosity on hydraulic properties during sea-dike failure induced by overtopping has not been adequately studied. This research develops a numerical simulation method to model sea-dike failure and analyze the influence of soil porosity on hydraulic properties during dike failure. A sediment scour model for bedload and suspended load is employed to simulate soil erosion during dike breaching. The Reynolds-averaged Navier–Stokes equations are used to characterize the hydrodynamic properties of breach flow. The results indicate that the breach process of cohesionless dikes can be generally categorized into three stages: lateral erosion of the dike crest, downstream slope erosion, and vertical erosion of the dike crest. The denser the dike, the less susceptible it is to failure, and the longer the breach duration, the larger the residual dike body. The variation in porosity does not affect the dike breach duration or the time of peak flow arrival, but it does influence the peak flow magnitude. The relationship between dike porosity and peak flow rate exhibits a significant positive linear correlation. This research enhances the understanding of the sea-dike failure process and contributes to disaster prevention and mitigation in coastal areas.

Assessing the impact of eucalyptus trees on soil chemical properties in rice fields

Eucalyptus trees around rice fields can provide benefits like acting as windbreaks, reducing soil erosion, and improving drainage, but they may also compete for water and light and release chemicals that inhibit crop growth. Proper management is essential to balance these effects. The current study was undertaken to explore the effects of eucalyptus trees along boundaries on the chemical composition of rice field’s soil. In the northern region of Bangladesh, in the Bogra district, surface soils were collected from rice fields. Inductively coupled plasma mass spectrometry (ICP-MS) technique was used to analyze these samples. The pH of most soil samples was less than 7.0, suggesting a slight acidity. Furthermore, the sub-surface soil samples (214.4, 174.3, and 159.3 µS/cm) had slightly higher electrical conductivity (E.C.) values than the surface soil samples (10.3, 178.3, and 154.3 µS/cm). Significant variations in soil chemical properties such as organic matter content, soil moisture, availability of phosphorus, sulphur, sodium, calcium, potassium, magnesium, copper, zinc, manganese, and iron were observed across different distances from eucalyptus boundaries. These variations reflect the influence of eucalyptus trees on soil characteristics. A considerable portion of nickel, copper, and zinc was detected in the strongly bound residual phase, while arsenic, cadmium, and lead were bound to carbonate and exchangeable fractions. This research indicates that planting eucalyptus trees could potentially enhance soil fertility in agricultural fields, particularly in areas with concentrated agriculture near industrial zones. The novelty of this research lies in identifying the positive impacts of eucalyptus boundary plantations on soil properties in rice fields.

Identification of Priority Areas for the Control of Soil Erosion and the Influence of Terrain Factors Using RUSLE and GIS in the Caeté River Basin, Brazilian Amazon

Soil erosion poses a significant global environmental challenge, causing land degradation, deforestation, river siltation, and reduced agricultural productivity. Although the Revised Universal Soil Loss Equation (RUSLE) has been widely applied in Brazil, its use in the tropical river basins of the Amazon remains limited. This study aimed to apply a GIS-integrated RUSLE model and compare its soil loss estimates with multiple linear regression (MLR) models based on terrain attributes, aiming to identify priority areas and key geomorphometric drivers of soil erosion in a tropical Amazonian river basin. A digital elevation model based on Shuttle Radar Topography Mission (SRTM) data, land use and land cover (LULC) maps, and rainfall and soil data were applied to the GIS-integrated RUSLE model; we then defined six risk classes—slight (0–2.5 t ha−1 yr−1), slight–moderate (2.5–5), moderate (5–10), moderate–high (10–15), high (15–25), and very high (>25)—and identified priority zones as those in the top two risk classes. The Caeté River Basin (CRB) was classified into six erosion risk categories: low (81.14%), low to moderate (2.97%), moderate (11.88%), moderate to high (0.93%), high (0.03%), and very high (3.05%). The CRB predominantly exhibited a low erosion risk, with higher erosion rates linked to intense rainfall, gentle slopes covered by Arenosols, and human activities. The average annual soil loss was estimated at 2.0 t ha−1 yr−1, with a total loss of 1005.44 t ha−1 yr−1. Additionally, geomorphological and multiple linear regression (MLR) analyses identified seven key variables influencing soil erosion: the convergence index, closed depressions, the topographic wetness index, the channel network distance, and the local curvature, upslope curvature, and local downslope curvature. These variables collectively explained 26% of the variability in soil loss (R2 = 0.26), highlighting the significant role of terrain characteristics in erosion processes. These findings indicate that soil erosion control efforts should focus primarily on areas with Arenosols and regions experiencing increased anthropogenic activity, where the erosion risks are higher. The identification of priority erosion areas enables the development of targeted conservation strategies, particularly for Arenosols and regions under anthropogenic pressure, where the soil losses exceed the tolerance threshold of 10.48 t ha−1 yr−1. These findings directly support the formulation of local environmental policies aimed at mitigating soil degradation by stabilizing vulnerable soils, regulating high-impact land uses, and promoting sustainable practices in critical zones. The GIS-RUSLE framework is supported by consistent rainfall data, as verified by a double mass curve analysis (R2 ranging from 0.64 to 0.77), and offers a replicable methodology for soil conservation planning in tropical basins with similar erosion drivers. This approach offers a science-based foundation to guide soil conservation planning in tropical basins. While effective in identifying erosion-prone areas, it should be complemented in future studies by dynamic models and temporal analyses to better capture the complex erosion processes and land use change impacts in the Amazon.

Soil Erosion in Important Agricultural Areas of Haidong City, Qinghai Province, China

Haidong City is located in the eastern region of the Tibetan Plateau and the upper reaches of the Yellow River, which is an important agricultural area in Qinghai Province. Surface soil erosion in this area not only reduces soil quality, but also leads to the pollution of the Yellow River water and the increase of sand transport.The soil erosion status of Haidong City in 2022 was assessed using the modified soil loss equation (RUSLE model), combined with landsat8 OLI imagery, DEM, rainfall and land use data, and RS and GIS techniques. The results show that soil erosion in Haidong City is dominated by slight and mild erosion, with an area of 7,835 km2 and 2,735 km2 respectively.Among the districts (counties), Ledu District and Mutual aid County have the largest area of strong erosion, with an area of 633 km2 and 144 km2 respectively; Ping'an District and Minhe County have a smaller area of strong erosion, with an area of 11 km2 and 30 km2 respectively.Between the different land-use types. grassland erosion area was the largest, with an area of 7449km2, accounting for 59.83%. The results of the above study can provide a scientific basis for soil degradation management in the region to meet the challenges of fragile ecological environment and increasing land use.

A Systematic Review on the Influence of Drainage Systems on the Environment

Environmental research has become increasingly important due to the human impact on ecosystems, with a particular need to study how different drainage systems affect water quality. Improperly functioning drainage can result in significant losses of biogenic substances, soil erosion, eutrophication, and declining biological capacity. This study addresses the existing knowledge gap by consolidating and critically analyzing the recent scientific literature on controlled and free draining types over forty years (1986–2024) using the Web of Science and Scopus databases. The objective of this systematic review is to collect and summarize information on various drainage systems, their advantages and disadvantages, and their effect on environmental water quality. A review of 144 selected papers from the past four decades indicates that the installation, use, and upgrading of drainage systems remains a subject of extensive debate within the scientific community, particularly regarding their impact on the leaching of biogenic substances into open water bodies. The results obtained from this study indicate that nitrogen (N) (found in 54 papers) and phosphorus (P) (found in 48 papers) are the primary biogenic elements affecting aquatic ecosystems and eutrophication processes. Also, compared to mathematical tools (found in 42 articles), there is a lack of application of AI tools for modeling and predicting the impact of drainage systems on water quality and climate change. Consequently, ongoing research in this area is crucial, offering researchers, practitioners, and wild society with significant insights into the overall effect of drainage on the environment, opportunities for improvement and unexplored research directions for drainage systems.

Suitability Analysis of Crops for Sloping Farmland in Arid Sandy Regions with Traditional Farming Methods

Global agricultural systems are predominantly concentrated in regions characterized by fertile soils, abundant precipitation, and gentle slopes. However, a significant proportion of farmland is situated in areas with poor soil quality, arid conditions, and steep slopes. In such challenging environments, particularly sandy-arid sloping farmlands, selecting native crops that are well-adapted to local conditions is critical for sustainable agricultural practices. This study categorizes local crops in arid regions into four distinct types: tall-stem monocotyledonous plants (represented by maize, Zea mays L.), short-stem monocotyledonous plants (represented by millet, Setaria italica), tap-rooted dicotyledonous plants (represented by soybean, Glycine max (L.) Merr.), and tuberous dicotyledonous plants (represented by potato, Solanum tuberosum L.). A quantitative evaluation framework was developed using five key indices: nitrogen fixation, anti-wind erosion, roots reinforcement, anti-water erosion, and water conservation. These indices were used to calculate the suitability index values for each crop type. The findings revealed that in sandy-arid sloping farmland regions, maize and millet emerged as the most suitable crops for cultivation, followed by soybean, while potato was identified as the least suitable. Maize exhibited high values across all five indices, particularly demonstrating exceptional performance in nitrogen fixation. Additionally, the study demonstrated that traditional farming practices are highly effective in sloping farmlands, since they not only promote crop growth but also mitigate soil erosion. This research offers insights into agricultural management in regions affected by drought, soil erosion, and steep terrain. The results highlight the feasibility of employing traditional farming methods to cultivate maize in such challenging environments, providing practical guidance for sustainable agricultural development.

Impacts of Intensive Management Practices on the Long-Term Sustainability of Soil and Water Conservation Functions in Bamboo Forests: A Mechanistic Review from Silvicultural Perspectives

Bamboo forest ecosystems are an important component of the Earth’s terrestrial ecosystems and play an important role in addressing the global timber crisis as well as climate change. Bamboo is a typical shallow-rooted, fast-growing clonal plant species whose developed rhizome system and high canopy closure play an important role in soil and water conservation. The function of soil and water conservation services of bamboo forests can intuitively reflect the regional regulation of precipitation, the redistribution function of precipitation, and the function of soil fixation, which is one of the crucial ecological service functions in regional ecosystems. Bamboo forests are divided into monopodial bamboo forests, sympodial bamboo forests, and mixed bamboo forests, which are mainly distributed in tropical and subtropical mountainous areas. The region’s variable climate, abundant precipitation, and high potential risk of soil erosion, in conjunction with the frequent operation of bamboo forests and frequent occurrence of extreme weather events, have the potential to adversely affect the ecosystem function of bamboo forests. Presently, bamboo forests are primarily managed through the cultivation of bamboo, with the objective of enhancing productivity. Extensive research has been conducted on the long-term maintenance of bamboo forest productivity. However, there is a paucity of research on the mechanisms of management measures for ecosystem stability and the development of adaptive management technology systems suitable for soil and water conservation, carbon sequestration and sink enhancement, and biodiversity conservation. This paper is predicated on the biological characteristics of bamboo and, thus, aims to compile the extant research progress on the following subjects: the role of rainfall redistribution in bamboo forest canopies, the role of deadfall interception, and the mechanism of soil fixation mechanics of the root system. It also synthesizes the current status of research on the impact of traditional management measures on the soil and water conservation function of bamboo forests. Finally, it discusses the problems of current research and the direction of future development.

Stability of Slope and Concrete Structure Under Cyclic Load Coupling and Its Application in Ecological Risk Prevention and Control

This paper focuses on the stability issues of geological and engineering structures and conducts research from two perspectives: the mechanism of slope landslides under micro-seismic action and the cyclic failure behavior of concrete materials. In terms of slope stability, through the combination of model tests and theories, the cumulative effect of circulating micro-seismic waves on the internal damage of slopes was revealed. This research finds that the coupling of micro-vibration stress and static stress significantly intensifies the stress concentration on the slope, promotes the development of potential sliding surfaces and the extension of joints, and provides a scientific basis for the prediction of landslide disasters. This helps protect mountain ecosystems and reduce soil erosion and vegetation destruction. The number of cyclic loads has a power function attenuation relationship with the compressive strength of concrete. After 1200 cycles, the strength drops to 20.5 MPa (loss rate 48.8%), and the number of cracks increases from 2.7 per mm3 to 34.7 per mm3 (an increase of 11.8 times). Damage evolution is divided into three stages: linear growth, accelerated expansion, and critical failure. The influence of load amplitude on the number of cracks shows a threshold effect. A high amplitude (>0.5 g) significantly stimulates the propagation of intergranular cracks in the mortar matrix, and the proportion of intergranular cracks increases from 12% to 65%. Grey correlation analysis shows that the number of cycles dominates the strength attenuation (correlation degree 0.87), and the load amplitude regulates the crack initiation efficiency more significantly (correlation degree 0.91). These research results can optimize the design of concrete structures, enhance the durability of the project, and indirectly reduce the resource consumption and environmental burden caused by structural damage. Both studies are supported by numerical simulation and experimental verification, providing theoretical support for disaster prevention and control and sustainable engineering practices and contributing to ecological environment risk management and the development of green building materials.

Description of representative “in-situ” soil profiles in northwestern Tunisia

Soil profiling is important for understanding soil evolution in space and time and its ability to deliver ecosystem services. It reflects the soil's physical, chemical, and biological, along with its management history. As a fundamental step in assessing soil health, it helps determine the soil’s potential for the provision of ecosystem services and its suitability for various agricultural and land-use applications. Soil profiling allows for the classification of soil types across different regions, contributing to soil mapping and enabling informed decisions for sustainable soil and land management. This study describes and classifies four soil profiles in Tunisia using the WRB classification system. The main areas of the WRB soil classification are soil Reference Soil Groups (RSG) mainly defined by diagnostic horizons, and qualifiers used to provide additional information about the soil's characteristics. The four soil profiles analyzed are Luvisol, Cambisol, Vertisol, and Fluvisol each exhibiting distinct physical, chemical, and morphological properties. Luvisol in Cap Negro (northern coast) is moderately fertile but vulnerable to erosion, necessitating protection measures. Cambisol in Oued Zarga (northern continental area) supports field crops but faces threats such as soil compaction and erosion, which can be mitigated by reduced tillage and providing soil cover after the harvest. Vertisol in Béja (northern continental area), characterized by high clay shrink-swell activity, is cultivated with winter cereals, where appropriate tillage and irrigation practices help manage soil stability. Lastly, Fluvisol in Oued Meliz (north-western continental area) benefits from high fertility due to alluvial deposits but requires careful water management to erosion. By providing detailed soil classification and management insights, this study contributes to deepen our understanding on soil classification, sustainable land use planning in Tunisia.

Loess Plateau Cropland: Evolution and Ecological Impacts over Four Millennia

The Loess Plateau (LP), the cradle of Chinese civilization, has a long history of agricultural activities closely linked to ecological changes. This study addresses a fundamental question: what was the maximum sustainable cropland area threshold for the LP prior to modern soil and water conservation measures? To answer this, we analyzed the historical data to investigate changes in the cropland area and their ecological impacts over the past 4000 years, with the specific aim of examining the long-term interactions between land exploitation and the ecosystem that defined sustainable thresholds. Three key stages of cropland area development were identified: slow growth (2000–500 BC), a fluctuating phase (500 BC–1000 AD), and rapid expansion (1000–2000 AD). During the slow-growth and rapid-expansion stages, the cropland areas were estimated at 34.9 ± 23.4 and 117.9 ± 34.1 thousand km2, with growth rates of 2.9 and 8.7 thousand km2/100 years, respectively, while the fluctuating period stabilized at 62.1 ± 18.1 thousand km2. Population growth was the primary driver of cropland expansion (56.9%), followed by agricultural technology and policy adjustments (27%) and climate change (16.1%). Particularly over the past 1000 years, climate deterioration and a population surge due to the abolition of the poll tax accelerated cropland expansion, resulting in deforestation, intensified soil erosion specific to the LP, and frequent flooding of the lower Yellow River (YR). In contrast, during the fluctuating period, rapid social development did not lead to major ecological issues, suggesting that moderate cropland expansion can balance social development and ecological sustainability. Based on the historical conditions, without modern soil and water conservation measures, this study determined that the upper limit of the cropland area during the fluctuating period (80.2 thousand km2) is the maximum sustainable cropland area for the LP, establishing a scientific basis to guide future land-use strategies. Especially in the face of population pressure and climate deterioration, developing agriculture and adjusting policies to increase grain production will be essential to balance the ecological risks and maintenance of food security while remaining within this threshold. These findings offer insights into the agricultural history and ecological management of the LP and can serve as a reference for similar studies of other regions.

Correction: Assessment of Morphology and Soil Erosion Risk in Agrarian Watershed of Jharkhand India Using RUSLE, GIS and MCDA‑AHP

Correction: Assessment of Morphology and Soil Erosion Risk in Agrarian Watershed of Jharkhand India Using RUSLE, GIS and MCDA‑AHP

Operational and Cost Assessment of Mechanizing Soil Removal Between Peach Trees Planted on Raised Berms

Armillaria root rot (ARR) is a fungal disease caused by Desarmillaria caespitosa and the leading cause of peach tree decline in the Southeastern U.S. It affects the roots and lower stems of trees, leading to the decay of the tree’s root system. Planting peach trees shallow on berms and excavating soil around the root collar after two years can extend the economic life of infected trees. However, berms pose operational challenges, including elevation changes, soil erosion from water flow, and herbicide and fertilizer runoff, thereby reducing orchard management efficiency. This study aimed to develop a tractor-mounted rotary tillage method to flatten the area between peach trees planted on berms, improving safety and reducing runoff. A custom paddle wheel attachment (20.3 cm height, 30.5 cm length) was retrofitted to an existing mechanical orchard weed management implement equipped with a hydraulic rotary head. A hydraulic flow meter, two pressure transducers, and an RTK-GPS receiver were integrated with a wireless data acquisition system to monitor the paddle wheel rotational speed and tractor ground speed during field trials. The effects of three paddle wheel speeds (132, 177, and 204 RPM) and three tractor ground speeds (1.65, 2.255, and 3.08 km/h) were evaluated in two orchards with Cecil sandy loam soil (bulk density: 1.93 g/cm3; slope: 2–6%). The paddle wheel speed had a greater influence on the torque and power requirements than the tractor ground speed. The combination of a 177 RPM paddle speed and 3 km/h tractor speed resulted in the smoothest soil surface with minimum torque demand, indicating this setting as optimal for flattening berms in similar soil conditions. Future research will include optimizing the paddle wheel structure and equipping the berm leveling machine with tree detection sensors to control the rotary head position.

Suitability Evaluation of Ecological Restoration Relying on Water Resources in an Agro-Pastoral Transition Zone: A Case Study of Zhangbei, Zhangjiakou, Northern China

(1) Background: Ecological restoration is crucial to improve ecological functions and optimize its security patterns. The Zhangbei of Zhangjiakou, a typical agro-pastoral transition zone, was studied as an example to conduct ecological restoration suitability evaluation in northern China. (2) Methods: suitability of ecological restoration in Zhangbei was assessed by both single factor analysis and comprehensive factor analysis, which were based on the data of regional water resources, ecosystem service function, and ecosystem sensitivity obtained from a high-precision environmental survey. (3) Results and conclusions: The results show that in Zhangbei County, areas classified as important and extremely important for ecosystem service functions account for 50.32%, ecologically sensitive and highly sensitive areas represent 5.95%, and regions designated as important and extremely important for ecological protection cover 52.70%. Furthermore, ecological restoration of Zhangbei was divided into four ecological restoration zones: agro-forest–wetland ecological restoration and soil erosion control zone, agro-forest–wetland ecological restoration and water conservation zone, forest–grassland soil erosion and soil–water conservation zone, and mountain forest conservation and biodiversity maintenance zone. The study can be a scientific case study for local ecosystem restoration and conservation. In the future, this study will further explore multi-source data fusion, the establishment of a multi-scale evaluation system, and the trade-off analysis between conservation and development.

Multiscale Two-Stream Fusion Network for Benggang Classification in Multi-Source Images

Benggangs, a type of soil erosion widely distributed in the hilly and mountainous regions of South China, pose significant challenges to land management and ecological conservation. Accurate identification and assessment of their location and scale are essential for effective Benggang control. With advancements in technology, deep learning has emerged as a critical tool for Benggang classification. However, selecting suitable feature extraction and fusion methods for multi-source image data remains a significant challenge. This study proposes a Benggang classification method based on multiscale features and a two-stream fusion network (MS-TSFN). Key features of targeted Benggang areas, such as slope, aspect, curvature, hill shade, and edge, were extracted from Digital Orthophotography Map (DOM) and Digital Surface Model (DSM) data collected by drones. The two-stream fusion network, with ResNeSt as the backbone, extracted multiscale features from multi-source images and an attention-based feature fusion block was developed to explore complementary associations among features and achieve deep fusion of information across data types. A decision fusion block was employed for global prediction to classify areas as Benggang or non-Benggang. Experimental comparisons of different data inputs and network models revealed that the proposed method outperformed current state-of-the-art approaches in extracting spatial features and textures of Benggangs. The best results were obtained using a combination of DOM data, Canny edge detection, and DSM features in multi-source images. Specifically, the proposed model achieved an accuracy of 92.76%, a precision of 85.00%, a recall of 77.27%, and an F1-score of 0.8059, demonstrating its adaptability and high identification accuracy under complex terrain conditions.

Assessment of soil erosion and sediment transport index in the Awash River Basin, Ethiopia: an application of the USLE model and GIS techniques

In the fight against soil erosion, Ethiopia has a formidable obstacle. The Awash River Basin issue is addressed in this paper. Soil loss and the sediment transport index (STI) in the Awash River Basin were predicted using GIS and the Universal Soil Loss Equation (USLE) Model. Using the Universal Soil Loss Equation (USLE) in conjunction with Geographic Information System (GIS) and remote sensing technologies, this study evaluates the spatial distribution and intensity of soil erosion in the basin. The result of annual average soil loss shows a significant range from 0–31,049,739 t/h/y after analyzing of various soil, DEM, topographical and meteorological data, obtained from USGS and EMA. The broader implications of this finding are highlights the significant capacity of land management potential in study area. The result of sediment transport index which computed based on flow accumulation and slope gradients, ranges from 0–247,097. The finding stipulates that considerable increment of soil loss and sedimentation in the study area, and promote for implementing reforestation and contour farming, to mitigate potential erosion’s impact. Hence, sustainable erosion mitigation strategies in the upper part of the basin should to be considered. Furthermore, this study emphasizes how important land use patterns, erodibility of soil, and erosivity of rainfall are associate in exacerbating of erosion. This information is significant for conservation and the development of sustainable agricultural frameworks. In portions of the study Basin that are prone to soil loss and sediment deposition, sustainable erosion management measures according to topography and current land use types are strongly recommended.

Study on Class Imbalance in Land Use Classification for Soil Erosion in Dry–Hot Valley Regions

The inherent spatial heterogeneity of land types often leads to a class imbalance in remote sensing-based classification, reducing the accuracy of minority class detection. Consequently, current land use datasets are often inadequate for the specific needs of soil erosion studies. In response to the need for soil conservation in dry–hot valley regions, this study integrated multi-source remote sensing imagery and constructed three high-precision imbalanced sample datasets on the Google Earth Engine (GEE) platform to perform land use classification. The degree of class imbalance was quantified using the imbalance ratio (IR), and the impact of sample imbalance on the classification accuracy of different land use types in a typical dry–hot valley was analyzed. The results show that (1) Feature selection significantly improved both classification accuracy and computational efficiency. The period from February to April each year, between 2018 and 2023, was identified as the optimal time window for land use classification in dry–hot valleys. (2) Constructing composite images over longer time scales enhanced classification performance: using a 2020 annual composite image combined with a Gradient Tree Boosting classifier yielded the highest accuracy, indicating that longer temporal synthesis improves classification results. (3) The effect of class imbalance on classification accuracy varied by land type: woodland (the majority class) was least affected by imbalance, whereas minority classes such as cultivated land, garden plantations, and grassland were highly sensitive to imbalance. In imbalanced scenarios, minority classes are prone to omission errors, leading to notable accuracy declines; producer’s accuracy (PA) decreased by 46%, 42%, and 25% for cultivated land, garden plantations, and grassland, respectively, as IR increased (with PA dropping faster than user’s accuracy, UA). Cultivated land was especially sensitive and frequently overlooked under high imbalance conditions compared to gardens and grasslands. Despite overall accuracy improving with higher IR, the accuracy of these minority classes dropped significantly, underscoring the importance of addressing the class imbalance in land use classification for erosion-prone areas.

Mineral protection rather than aggregate stability improved soil organic carbon contents at high altitudes of Yulong Mountain in southwest China

Abstract Alpine regions sequester large vulnerable and unprotected soil organic carbon (SOC), determining its extreme sensitivity to global change and pivotal role in the carbon cycle. However, there is ongoing debate regarding how SOC storage and its stabilizing mechanism vary along altitudinal gradients. Here, we examined the SOC contents of soil aggregate and density fractions, and their interactions with climate, biology and soil properties along elevation (2100-3900 m) of western Yulong Mountain in southwest China. Results showed that SOC contents in bulk soils and heavy fractions significantly increased with elevated altitudes, whereas no changes in aggregates. The increasing Fe/Al oxides with altitudes might be responsible for such significant variations. While soil C-enzyme activities had strong effects on increasing SOC in macroaggregates (> 250 μm), aggregate stability (indicated by mean weight diameter and soil erodibility) mainly reduced SOC in microaggregates, silt and clay (< 250 μm). The structural equation models further showed that 57-91% of variations in SOC contents could be explained by environmental variables, with the Fe/Al oxides showing the strongest positive associations with SOC contents in bulk soils, light and heavy fractions. Taken together, our results emphasized positive impacts of mineral protection on the SOC stabilization at high altitudes. This not only offers novel insights into predicting soil C stability in alpine regions but also provides practical significance for soil C pool management across various altitudes.

Topographic and Edaphic Factors Shaping Floral Diversity Patterns and Vegetation Structure of Treeline Ecotones in Kumaun Himalaya

ABSTRACTTreeline ecotones are ecologically sensitive ecosystems that are increasingly vulnerable to recent global warming and land degradation processes such as soil erosion, nutrient depletion, and organic matter loss. However, little is known about how floral diversity in treeline ecotones responds to changing environmental factors, particularly in the high Himalayan treeline ecotones. The present study examined the potential effects of topographic and edaphic factors on the vegetation structure of treeline ecotones of two mountain summits in Kumaun Himalaya. Using line transects, plots, and quadrats, we recorded 96 plant species from 72 genera and 36 families. Jaccard similarity coefficients revealed varying degrees of similarity in species composition between different aspects and elevations. Beta diversity analysis indicated nestedness as a dominant driver of community composition. Vegetation assessments showed shifts in tree density (ranging from 12.50 to 227.50 individuals per hectare), basal area (ranging from 0.138 to 9.855 square meters per hectare), and dispersion patterns along the elevational gradient. The dominant tree species across all treeline ecotone plots was Rhododendron arboreum. Regeneration was evident, with 69% of trees in smaller girth classes, indicating active recruitment. In addition to vegetation distribution, this study analysed soil characteristics across the treeline ecotones to assess potential land degradation trends. Soil temperature, pH, moisture, and water holding capacity decreased with elevation. South and east aspects had higher temperatures, pH, and phosphorus, while north and west aspects had higher moisture, organic carbon, and nitrogen. Results indicate that decreasing soil moisture, increasing bulk density, and declining total organic carbon at higher elevations and exposed aspects are indicative of degradation processes that may impact long‐term vegetation stability. The significant relationships between soil parameters and species distribution highlight the importance of understanding degradation dynamics in shaping floristic patterns. Non‐metric multidimensional scaling (NMDS) showed distinct clusters of treeline plots based on environmental variables (stress value: 0.17), while canonical correspondence analysis (CCA) demonstrated strong species‐environment correlations, explaining 83.08% of the total inertia. Given the observed soil degradation trends, conservation strategies should prioritize soil stabilization, erosion control, and nutrient depletion to mitigate the risks of ecosystem degradation. This research provides key insights into ecosystem resilience and serves as a foundation for monitoring treeline ecotones under changing environmental conditions.