Search Results (478)

To investigate the spatiotemporal evolution characteristics and primary driving factors of Gross Primary Productivity (GPP) on the Qinghai-Tibet Plateau, we employed an enhanced MODIS-PSN model. Utilizing the fifth-generation global climate reanalysis dataset (ECMWF ERA5), we generated GPP remote sensing products by integrating six natural factors. Through correlation analysis and geographical detector modeling, we quantitatively analyzed the spatiotemporal dynamics and key drivers of vegetation GPP across the Qinghai-Tibet Plateau from 2001 to 2022. The results demonstrate that GPP changes across the Qinghai-Tibet Plateau display pronounced spatial heterogeneity. The humid northeastern and southeastern regions exhibit significantly positive change rates, primarily distributed across wetland and forest ecosystems, with a maximum mean annual change rate of 12.40 gC/m²/year. In contrast, the central and southern regions display a decreasing trend, with the minimum change rate reaching −1.61 gC/m²/year, predominantly concentrated in alpine grasslands and desert areas. Vegetation GPP on the Qinghai-Tibet Plateau shows significant correlations with temperature, vapor pressure deficit (VPD), evapotranspiration (ET), leaf area index (LAI), precipitation, and radiation. Among the factors analyzed, LAI demonstrates the strongest explanatory power for spatial variations in vegetation GPP across the Qinghai-Tibet Plateau. The dominant factors influencing vegetation GPP on the Qinghai-Tibet Plateau are LAI, ET, and precipitation. The pairwise interactions between these factors exhibit linear enhancement effects, demonstrating synergistic multifactor interactions. This study systematically analyzed the response mechanisms and variations of vegetation GPP to multiple driving factors across the Qinghai-Tibet Plateau from a spatial heterogeneity perspective. The findings provide both a critical theoretical framework and practical insights for better understanding ecosystem response dynamics and drought conditions on the plateau. Full article

Understanding alpine plants’ survival and reproduction is crucial for their conservation in climate change. Based on 423 valid distribution points, this study utilizes the MaxEnt model to predict the potential habitat and distribution dynamics of Leontopodium nanum under both current and future climate scenarios, while clarifying the key factors that influence its distribution. The primary ecological drivers of distribution are altitude (2886.08 m–5576.14 m) and the mean temperature of the driest quarter (−6.60–1.55 °C). Currently, the suitable habitat area is approximately 520.28 × 10⁴ km², covering about 3.5% of the global land area, concentrated mainly in the Tibetan Plateau, with smaller regions across East and South Asia. Under future climate scenarios, low-emission (SSP126), suitable areas are projected to expand during the 2050s and 2070s. High-emission (SSP585), suitable areas may decrease by 50%, with a 66.07% reduction in highly suitable areas by the 2070s. The greatest losses are expected in the south-eastern Tibetan Plateau. Regarding dynamic habitat changes, by the 2050s, newly suitable areas will account for 51.09% of the current habitat, while 68.26% of existing habitat will become unsuitable. By the 2070s, newly suitable areas will rise to 71.86% of the current total, but the loss of existing areas will exceed these gains, particularly under the high-emission scenario. The centroid of suitable habitats is expected to shift northward, with migration distances ranging from 23.94 km to 342.42 km. The most significant shift is anticipated under the SSP126 scenario by the 2070s. This study offers valuable insights into the distribution dynamics of L. nanum and other alpine species under the context of climate change. From a conservation perspective, it is recommended to prioritize the protection and restoration of vegetation in key habitat patches or potential migration corridors, restrict overgrazing and infrastructure development, and maintain genetic diversity and dispersal capacity through assisted migration and population genetic monitoring when necessary. These measures aim to provide a robust scientific foundation for the comprehensive conservation and sustainable management of the grassland ecosystem on the Qinghai–Tibet Plateau. Full article

The ecosystem services (ESs) of forests are the benefits that people derive from forest ecosystems. Their precise recognition is important for differentiating and determining the optimal principles of multifunctional forest management. The aim of this study is to identify some important ESs based on a site classification system at the lowest level—i.e., forest stands, at the forest owner level—as a tool for differentiated management. ESs were assessed within the Czech Republic and are expressed in units in accordance with the very sophisticated Forest Site Classification System. (1) Biomass production: The vertical differentiation of ecological conditions given by vegetation tiers, which reflect the influence of altitude, exposure, and climate, provides a basic overview of biomass production; the highest value is in the fourth vegetation tier, i.e., the Fageta abietis community. Forest stands are able to reach a stock of up to 900–1200 m³·ha⁻¹. The lowest production is found in the eighth vegetation tier, i.e., the Piceeta community, with a wood volume of 150–280 m³·ha⁻¹. (2) Soil conservation function: Geological bedrock, soil characteristics, and the geomorphological shape of the terrain determine which habitats serve a soil conservation function according to forest type sets. (3) The hydricity of the site, depending on the soil type, determines the hydric-water protection function of forest stands. Currently, protective forests occupy 53,629 ha in the Czech Republic; however, two subcategories of protective forests—exceptionally unfavorable locations and natural alpine spruce communities below the forest line—potentially account for 87,578 ha and 15,277 ha, respectively. Forests with an increased soil protection function—a subcategory of special-purpose forests—occupy 133,699 ha. The potential area of soil protection forests could be up to 188,997 ha. Water resource protection zones of the first degree—another subcategory of special-purpose forests—occupy 8092 ha, and there is potentially 289,973 ha of forests serving a water protection function (specifically, a water management function) in the Czech Republic. A separate subcategory of water protection with a bank protection function accounts for 80,529 ha. A completely new approach is presented for practical use by forest owners: based on the characteristics of the habitat, they can obtain information about the fulfillment of the habitat’s ecosystem services and, thus, have basic information for the determination of forest categories and the principles of differentiated management. Full article

Amidst the intensification of global climate change and the increasing impacts of human activities, ecosystem patterns and processes have undergone substantial transformations. The distribution and evolutionary dynamics of mountain ecosystems have become a focal point in ecological research. The Surkhan River Basin is located in the transitional zone between the arid inland regions of Central Asia and the mountain systems, where its unique physical and geographical conditions have shaped distinct patterns of vertical zonation. Utilizing Landsat imagery, this study applies a hierarchical classification approach to derive land cover classifications within the Surkhan River Basin. By integrating the NDVI (normalized difference vegetation index) and DEM (digital elevation model (30 m SRTM)), an “NDVI-DEM-Land Cover” scatterplot is constructed to analyze zonation characteristics from 1980 to 2020. The 2020 results indicate that the elevation boundary between the temperate desert and mountain grassland zones is 1100 m, while the boundary between the alpine cushion vegetation zone and the ice/snow zone is 3770 m. Furthermore, leveraging DEM and LST (land surface temperature) data, a potential energy analysis model is employed to quantify potential energy differentials between adjacent zones, enabling the identification of ecological transition areas. The potential energy analysis further refines the transition zone characteristics, indicating that the transition zone between the temperate desert and mountain grassland zones spans 1078–1139 m with a boundary at 1110 m, while the transition between the alpine cushion vegetation and ice/snow zones spans 3729–3824 m with a boundary at 3768 m. Cross-validation with scatterplot results confirms that the scatterplot analysis effectively delineates stable zonation boundaries with strong spatiotemporal consistency. Moreover, the potential energy analysis offers deeper insights into ecological transition zones, providing refined boundary identification. The integration of these two approaches addresses the dimensional limitations of traditional vertical zonation studies, offering a transferable methodological framework for mountain ecosystem research. Full article

To clarify the ecological mechanisms underlying the succession of artificial grasslands to native alpine meadows and systematically reveal the patterns of ecological restoration in artificial grasslands in the Qinghai–Tibet Plateau, this study provides a theoretical basis for alpine meadow ecological restoration. In this study, artificial grassland and degraded grassland (CK) with different restoration years (20 years, 16 years, 14 years, and 2 years) in the Qinghai–Tibet Plateau were taken as research objects. We focused on the tillering characteristics, patch number, community structure evolution, and soil properties of the dominant species, C. alatauensis, and systematically explored the ecological restoration law by comparing and analyzing ecological indicators in different restoration years. The results showed the following: (1) With the extension of restoration years, the asexual reproduction ability of C. alatauensis was enhanced, the patches became large, and aboveground/underground biomass significantly accumulated. (2) Community structure optimization meant that the coverage and biomass of Cyperaceae plants increased with restoration age, while those of Poaceae plants decreased. The diversity of four species in 20A of restored grasslands showed significant increases (10.71–19.18%) compared to 2A of restored grasslands. (3) Soil improvement effect: The contents of soil organic carbon (SOC), total phosphorus (TP), nitrate nitrogen (NN), and available phosphorus (AP) increased significantly with the restoration years (in 20A, the SOC content in the 0–10 cm soil layer increased by 57.5% compared with CK), and the soil pH gradually approached neutrality. (4) In artificial grasslands with different restoration ages (20A, 16A, and 14A), significant or highly significant correlations existed between C. alatauensis tiller characteristics and community and soil properties. In conclusion, C. alatauensis in artificial grasslands drives population enhancement, community succession, and soil improvement through patch expansion. Full article

Fractional Vegetation Cover (FVC) is a crucial indicator describing vegetation conditions and provides essential data for ecosystem health assessments. However, due to the low and sparse vegetation in alpine meadows, it is challenging to obtain pure vegetation pixels from Sentinel-2 imagery, resulting in errors in the FVC estimation using traditional pixel dichotomy models. This study integrated Sentinel-2 imagery with unmanned aerial vehicle (UAV) data and utilized the pixel dichotomy model together with four machine learning algorithms, namely Random Forest (RF), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Deep Neural Network (DNN), to estimate FVC in an alpine meadow region. First, FVC was preliminarily estimated using the pixel dichotomy model combined with nine vegetation indices applied to Sentinel-2 imagery. The performance of these estimates was evaluated against reference FVC values derived from centimeter-level UAV data. Subsequently, four machine learning models were employed for an accurate FVC inversion, using the estimated FVC values and UAV-derived reference FVC as inputs, following feature importance ranking and model parameter optimization. The results showed that: (1) Machine learning algorithms based on Sentinel-2 and UAV imagery effectively improved the accuracy of FVC estimation in alpine meadows. The DNN-based FVC estimation performed best, with a coefficient of determination of 0.82 and a root mean square error (RMSE) of 0.09. (2) In vegetation coverage estimation based on the pixel dichotomy model, different vegetation indices demonstrated varying performances across areas with different FVC levels. The GNDVI-based FVC achieved a higher accuracy (RMSE = 0.08) in high-vegetation coverage areas (FVC > 0.7), while the NIRv-based FVC and the SR-based FVC performed better (RMSE = 0.10) in low-vegetation coverage areas (FVC < 0.4). The method provided in this study can significantly enhance FVC estimation accuracy with limited fieldwork, contributing to alpine meadow monitoring on the Qinghai–Tibet Plateau. Full article

The Alpine Periglacial Weathering Zone (APWZ) is a critical transitional belt between alpine vegetation and glaciers, and a highly sensitive region to climate change. Its dynamic variations profoundly reflect the surface environment’s response to climatic shifts. Taking Gongga Mountain as the study area, this study utilizes summer Landsat imagery from 1986 to 2024 and constructs a remote sensing method based on NDVI and NDSI indices using the Otsu thresholding algorithm on the Google Earth Engine platform to automatically extract the positions of the upper limit of vegetation and the snowline. Results show that over the past four decades, the APWZ in Gongga Mountain has exhibited a continuous upward shift, with the mean elevation rising from 4101 m to 4575 m. The upper limit of vegetation advanced at an average rate of 17.43 m/a, significantly faster than the snowline shift (3.9 m/a). The APWZ also experienced substantial areal shrinkage, with an average annual reduction of approximately 13.84 km², highlighting the differential responses of various surface cover types to warming. Spatially, the most pronounced changes occurred in high-elevation zones (4200–4700 m), moderate slopes (25–33°), and sun-facing aspects (east, southeast, and south slopes), reflecting a typical climate–topography coupled driving mechanism. In the upper APWZ, glacier retreat has intensified weathering and increased debris accumulation, while the newly formed vegetation zone in the lower APWZ remains structurally fragile and unstable. Under extreme climatic disturbances, this setting is prone to triggering chain-type hazards such as landslides and debris flows. These findings enhance our capacity to monitor alpine ecological boundary changes and identify associated disaster risks, providing scientific support for managing climate-sensitive mountainous regions. Full article

Belowground buds play a vital role in the clonal propagation and structural regulation of perennial herbaceous plants, especially in alpine environments, where vegetative renewal depends heavily on bud bank dynamics. However, the interactive effects of nitrogen addition and phenological stages on bud development and aboveground branching remain poorly understood. In this study, we examined the responses of rhizome buds, tiller buds, and aboveground tiller types of Kentucky bluegrass to six nitrogen levels (0, 6, 9, 12, 15, and 18 g/m²) across five growth stages on the Qinghai–Tibet Plateau. The results showed that moderate nitrogen input (N2, 9 g/m²) significantly enhanced total bud density, particularly at the heading and maturity stages, indicating a threshold response. Aboveground reproductive tiller density peaked at N2 (9 g/m²), while vegetative and total tiller densities plateaued beyond N3 (12 g/hm²), suggesting a diminishing marginal effect of nitrogen on aboveground tiller density. Furthermore, bud density showed stage-specific correlations with tiller types: vegetative tillers were primarily influenced at the heading stage, and reproductive tillers were mainly influenced at the mature stage, with weakened associations in senescence. These findings highlight the phenological specificity and non-linear response of clonal grass regeneration to nitrogen input and provide a theoretical basis for optimizing nutrient management in cold alpine grasslands. Full article

As a crucial ecological barrier in China, the Greater Khingan Mountains play a vital role in global ecological security. Investigating the spatiotemporal variations in fractional vegetation cover (FVC) and the driving mechanisms behind its spatial differentiation is essential. This study introduced a KNDVI-XGeoML framework integrating the Kernel NDVI and explainable geospatial machine learning to analyze the FVC dynamics and the mechanisms driving their spatial differentiation in China’s Greater Khingan Mountains, based on which targeted ecological management strategies were proposed. The key findings reveal that (1) from 2001 to 2022, FVC showed an increasing trend, confirming the effectiveness of ecological restoration. (2) The XGeoML model successfully revealed nonlinear relationships and threshold effects between driving factors and FVC. In addition, both single-factor importance and inter-factor interaction analyses consistently showed that landform factors dominated the spatial distribution of FVC. (3) Regional heterogeneity emerged—human activities drove the northern alpine zones, while landform factors governed other areas. (4) The natural-environment-dominated zones and human-activity-dominated zones were established, and management strategies were proposed: restricting tourism in low-altitude zones, optimizing the cold-resistant vegetation at high elevations, and improving the southern soil conditions to support ecological barrier construction. The innovation lies in merging nonlinear vegetation indices with interpretable machine learning, overcoming the traditional limitations in terms of saturation effects and analyses of spatial heterogeneity. This approach enhances our understanding of high-latitude vegetation dynamics, offering a methodological advancement for precision ecological management. The spatial zoning strategy based on dominant drivers provides actionable insights for maintaining this critical ecological barrier, particularly under climate change pressures. The framework demonstrates strong potential for extrapolation to other ecologically sensitive regions requiring data-driven conservation planning. Full article

Although the topic of trampling of alpine vegetation has been addressed by many authors in recent years, many unanswered questions still remain. The generalization of vegetation response patterns to trampling would be valuable, especially for problematic alpine areas, which are unsuitable for large hiking loads. Such an area is the limestone Belianske Tatras, which has been closed to tourists since 1978. Only one trail has been accessible in the area since 1993 as a one-way trail, and since 2008 it has been used as an educational two-way trail. Since there is renewed discussion about making the Belianske Tatras accessible to tourists, we sought answers to the following questions: (1) regenerated communities are more resistant to trampling than the native ones; (2) individual species in different communities react to trampling in the same way; and (3) some species can disappear or become extinct after being trampled. We conducted research in the form of an experiment according to the standard Cole and Bayfield protocol. We trampled three plant communities in 2008, treating them as native, and in 2022, treating them as regenerated. The regenerated communities appeared to be more resistant, although this came at the expense of some species disappearing or becoming extinct as a delayed response. Re-opening the area could be considered. Full article

Research on the supply–demand relationships of ecosystem services (ESs) in alpine pastoral regions remains relatively scarce, yet it is crucial for regional ecological management and sustainable development. This study focuses on the Sanjiangyuan Region, a typical alpine pastoral area and significant ecological barrier, to quantitatively assess the supply–demand dynamics of key ESs and their spatial heterogeneity from 2000 to 2020. It further aims to elucidate the underlying driving mechanisms, thereby providing a scientific basis for optimizing regional ecological management. Four key ES indicators were selected: water yield (WY), grass yield (GY), soil conservation (SC), and habitat quality (HQ). ES supply and demand were quantified using an integrated approach incorporating the InVEST model, the Revised Universal Soil Loss Equation (RUSLE), and spatial analysis techniques. Building on this, the spatial patterns and temporal evolution characteristics of ES supply–demand relationships were analyzed. Subsequently, the Geographic Detector Model (GDM) and Geographically and Temporally Weighted Regression (GTWR) model were employed to identify key drivers influencing changes in the comprehensive ES supply–demand ratio. The results revealed the following: (1) Spatial Patterns: Overall ES supply capacity exhibited a spatial differentiation characterized by “higher values in the southeast and lower values in the northwest.” Areas of high ES demand were primarily concentrated in the densely populated eastern region. WY, SC, and HQ generally exhibited a surplus state, whereas GY showed supply falling short of demand in the densely populated eastern areas. (2) Temporal Dynamics: Between 2000 and 2020, the supply–demand ratios of WY and SC displayed a fluctuating downward trend. The HQ ratio remained relatively stable, while the GY ratio showed a significant and continuous upward trend, indicating positive outcomes from regional grass–livestock balance policies. (3) Driving Mechanisms: Climate and natural factors were the dominant drivers of changes in the ES supply–demand ratio. Analysis using the Geographical Detector’s q-statistic identified fractional vegetation cover (FVC, q = 0.72), annual precipitation (PR, q = 0.63), and human disturbance intensity (HD, q = 0.38) as the top three most influential factors. This study systematically reveals the spatial heterogeneity characteristics, dynamic evolution patterns, and core driving mechanisms of ES supply and demand in an alpine pastoral region, addressing a significant research gap. The findings not only provide a reference for ES supply–demand assessment in similar regions regarding indicator selection and methodology but also offer direct scientific support for precisely identifying priority areas for ecological conservation and restoration, optimizing grass–livestock balance management, and enhancing ecosystem sustainability within the Sanjiangyuan Region. Full article

The rhizosphere serves as a critical interface for plant–soil–microorganism interactions. Rhizosphere soil refers to the soil directly adhering to root surfaces, while non-rhizosphere soil denotes the surrounding soil not in direct contact with roots. This study investigated the characteristics of soil microbial community structure, diversity, and enzyme activity dynamics in both rhizosphere and non-rhizosphere soils of Salix cupularis (shrub) across different restoration periods (4, 8, 16, and 24 years) in alpine sandy lands on the eastern Qinghai–Tibet Plateau, with unrestored sandy land as control (CK), while analyzing relationships between soil properties and microbial characteristics. Results demonstrated that with increasing restoration duration, activities of sucrase, urease, alkaline phosphatase, and catalase in Salix cupularis rhizosphere showed increasing trends across periods, with rhizosphere enzyme activities consistently exceeding non-rhizosphere levels. Bacterial Chao1 and Shannon indices followed similar patterns to enzyme activities, revealing statistically significant differences between rhizosphere and non-rhizosphere soils after 8 and 24 years of restoration, respectively. Dominant bacterial phyla ranked by relative abundance were Actinobacteria > Proteobacteria > Acidobacteria > Chloroflexi > Gemmatimonadetes. The relative abundance of Actinobacteria exhibited highly significant positive correlations with carbon, nitrogen, phosphorus, and enzyme activity indicators, indicating that Salix cupularis restoration promoted improvements in soil physicochemical properties and nutrient accumulation, thereby enhancing bacterial community diversity and increasing Actinobacteria abundance. These findings provide fundamental data for restoration ecology and microbial ecology in alpine ecosystems, offering a scientific basis for optimizing ecological restoration processes and improving recovery efficiency in alpine sandy ecosystems. Full article

The Qinghai–Tibet Plateau is a key region for biodiversity conservation, where alpine grasslands are ecologically important. While previous studies have mainly addressed vegetation, ecosystem processes, and soil microbes, phyllosphere microorganisms are essential for nutrient cycling, plant health, and stress tolerance. However, their communities remain poorly understood compared to those in soil. The relative influence of host identity and environmental conditions on shaping phyllosphere microbial diversity and community assembly remains uncertain. In this study, we characterized phyllosphere bacterial and fungal communities of the phyllosphere at two alpine steppe sites with similar vegetation but climatic conditions: the Qilian Mountains (QLM) and the Qinghai Lake region (LQS). At both sites, Cyanobacteriota and Ascomycota were the predominant bacterial and fungal taxa, respectively. Microbial α-diversity did not differ significantly between the two regions, implying that host-associated mechanisms may stabilize within-site diversity. In contrast, β-diversity exhibited clear spatial differentiation. In QLM, bacterial β-diversity was significantly correlated with mean annual precipitation, while fungal α- and β-diversity were associated with soil nutrient levels (including nitrate, ammonium, available potassium, and phosphorus) and vegetation coverage. At LQS, the β-diversity of both bacterial and fungal communities was strongly influenced by soil electrical conductivity, and fungal communities were further shaped by vegetation cover. Community assembly processes were predominantly stochastic at both sites, although deterministic patterns were more pronounced in QLM. Variability in moisture availability contributed to random bacterial assembly at LQS, while increased environmental heterogeneity promoted deterministic assembly in fungal communities. The elevated diversity of microbes and plants in QLM also reinforced deterministic processes. Overall, our findings support a host–environment interaction hypothesis, indicating that host factors primarily govern α-diversity, while climatic and soil-related variables have stronger effects on β-diversity and microbial assembly dynamics. These insights advance our understanding of how phyllosphere microbial communities may respond to environmental change in alpine ecosystems. Full article

Vegetation change profoundly influences ecosystem sustainability and human activities, with solar radiation serving as a primary driver. However, the effects of surface radiative forcing (SRF) and related factors on vegetation dynamics remain poorly understood. The Tibetan Plateau, a climate-sensitive region, offers a unique context to investigate these relationships. This study analyzes the association between vegetation greening and SRF on the Tibetan Plateau from 1982 to 2021. Using forecast albedo (FAL) and surface solar radiation downwards (SSRD), we calculated SRF and explored its correlation with the Normalized Difference Vegetation Index (NDVI) and land cover data. The results indicate a gradual increase in growing-season NDVI, suggesting vegetation greening. Both FAL and SSRD exhibit decreasing trends, yet neither shows a statistically significant correlation with NDVI. The correlations between FAL/SSRD and NDVI weaken with increasing altitude, declining by 0.035 × 10⁻¹ per 500 m and 0.021 × 10⁻¹ per 500 m, respectively. Among vegetation types, FAL correlates most strongly with shrubland NDVI and weakest with forest NDVI, while SSRD demonstrates the highest correlation with grassland NDVI and lowest with forest NDVI. The impact of SRF on NDVI changes is evident in 52.881% of the plateau, showing a positive correlation between SRF and ΔNDVI, compared to 39.589% for SSRD and ΔNDVI. This research enhances the understanding of vegetation responses to FAL, SSRD, and SRF, providing a scientific basis for ecological conservation and climate adaptation strategies, and also emphasizes radiation–vegetation feedback, providing guidance for conservation strategies in other alpine ecosystems globally, such as the Andes and Alps, where elevation gradients and vegetation-type-specific responses to radiative forcing may similarly govern ecological outcomes. Full article

Assessing cropland soil quality and identifying limiting indicators are crucial in guiding sustainable agricultural practices, particularly in fragile agricultural ecosystems. However, a unified understanding of key limiting indicators and the controlling factors of soil quality remains lacking due to the dual demands of environmental protection and agricultural production. To address this gap, 621 soil samples were collected across the “One River and Its Two Tributaries” agricultural region on the Tibetan Plateau. Twenty-four soil physicochemical indicators and eight environmental parameters were analyzed to evaluate soil quality and identify the key limiting factors. Meanwhile, the random forest model, correlation analysis, and the structural equation model were used to determine the factors influencing limiting indicator. The results showed that (1) croplands had a mean soil quality index (SQI) of 0.66 with obvious spatial heterogeneity, where eastern, northern, and southern regions exhibited higher SQI values than western and central valley areas. (2) Soil organic matter (SOM) was identified as the primary limiting indicator, with its limiting degree increasing with soil depth. (3) Total nitrogen is the strongest statistical predictor of SOM content in this region, while soil pH negatively impacted SOM. Environmental factors, including fertilizer amount, altitude, and normalized difference vegetation index, positively influenced SOM, whereas temperature and precipitation negatively affected it. (4) The structural equation model revealed effective intervention pathways for addressing SOM deficiency, highlighting targeted measures such as optimizing nitrogen management and increasing organic fertilizer application, particularly in relative lower-altitude areas. This study provides a unified perspective for managing soil quality and offers a potentially replicable framework for similar alpine ecosystems worldwide. Full article