Search Results (247)

Coastal wetlands represent significant sources of greenhouse gases (GHGs) and serve as crucial ecological interfaces between terrestrial and marine environments, substantially contributing to global biogeochemical cycles. However, GHG emission fluxes are strongly influenced by complex anthropogenic activities, yet their underlying microbial mechanisms remain poorly understood. This study investigated seven representative human-impacted sites within the Yellow River Delta. Employing a combined approach of in vitro microcosm cultivation, molecular biology, and multivariate statistical analysis, we investigated the integrated mechanisms controlling nitrous oxide (N₂O) and methane (CH₄) fluxes, with consideration of soil depth, environmental factors, microbial communities, and functional microbes. The results indicated that significant differences in GHG fluxes among different anthropogenic activities and soil depths (p < 0.05). Surface soil N₂O fluxes were positive within sewage irrigation areas (20.98–35.08 mg N₂O-N m⁻² h⁻¹) and tourism development areas (12.52–23.87 mg N₂O-N m⁻² h⁻¹), while mariculture areas displayed negative fluxes. CH₄ fluxes were positive exclusively in natural areas (surface soil: 25.02–55.54 mg CH₄-C m⁻² h⁻¹; deep soil: 8.38–356.68 mg CH₄-C m⁻² h⁻¹), while other areas predominantly showed negative values (surface soil: −130.98–44.32 mg CH₄-C m⁻² h⁻¹; deep soil: −106.16–65.24 mg CH₄-C m⁻² h⁻¹). Furthermore, a structural equations model highlighted the pivotal role of key functional microbes in soil carbon–nitrogen cycling (e.g., nirK, nosZII, and SRB) involved in soil carbon–nitrogen cycling in negatively regulating N₂O and CH₄ fluxes. The study also revealed distinct microbial responses across diverse habitats, underscoring the significant role of Proteobacteria in wetland soil. This research enhances our understanding of GHG dynamics in coastal wetlands and provides scientific evidence and potential regulatory pathways for enhancing soil biological mitigation functions and achieving carbon neutrality and sustainability within wetland ecosystems. Full article

Urban sprawl refers to the undesirable expansion of cities and the irrational exploitation of land resources. This study takes the Yellow River Basin as the research domain and measures the urban sprawl index of 73 prefecture-level cities in the basin from 2000 to 2020. Utilizing DMSP/OLS, NPP/VIIRS nighttime light data, and LandScan population data, the research applies the Theil index to examine urban sprawl levels and spatial heterogeneity among the upper, middle and lower reaches of the basin, as well as within individual cities. The results show that: (1) between 2000 and 2020, urban sprawl levels in the 73 prefecture-level cities within the Yellow River Basin demonstrated a consistent downward trend, with a spatial decrease observed from west to east; (2) the overall Theil index revealed regional disparities that gradually lessened over the years, with differences within the basin being significantly greater than those between its upper, middle, and lower sections; and (3) in terms of spatial heterogeneity, multiple prefecture-level cities in Qinghai Province, at the source of the basin, are primarily located in the “high high cluster” region, whereas the “low low cluster” is largely concentrated in the eastern downstream areas of the Yellow River. Sanmenxia City, located in the middle reaches, was long term the “high low cluster” zone, while the “low high cluster” zone was concentrated in Xining, Lanzhou, and Baotou cities in the upper reaches. Investigating urban sprawl in the Yellow River Basin contributes to advancing the sustainable development of the basin in a profound manner. Full article

Addressing national goals for ecological conservation in the Yellow River Basin, this study focuses on its Henan segment (HYRB). We developed a VOR-SQ assessment framework by augmenting the classic Vitality–Organization–Resilience model with ecosystem services and an enhanced ecological quality indicator. Using multi-source remote sensing and statistical data, we examine the spatiotemporal evolution of ecosystem health in the HYRB from 2000 to 2020. The XGBoost-SHAP algorithm was applied to identify nonlinear drivers and threshold effects. Key findings indicate (1) a persistent “high west, low east” health gradient with an overall declining trend; western mountains remain healthy, while eastern plains, urban, and intensive agricultural areas show degradation. (2) Natural factors—evapotranspiration (ET), elevation, NDVI, and slope—dominate health dynamics, with critical thresholds (~1153 mm, ~457 m, ~0.76, ~10.5°, respectively) beyond which their impacts shift markedly. (3) Anthropogenic factors (GDP, population/road density) contribute less globally but cause strong local negative disturbances in plains. For instance, road density > 434 km/km² or population density > 159 persons/km² reverses their effects from positive to negative. Accordingly, we propose tailored strategies: western conservation, central farmland optimization, and eastern development control. By coupling the VOR-SQ framework with XGBoost-SHAP, this study offers a robust diagnostic tool for ecosystem health and adaptive governance in fragile socio-ecological systems. Full article

Rapid urbanization has led to severe landscape fragmentation and ecosystem degradation in the Gansu Section of the Yellow River Basin (GSYRB). Focusing on this region, this study identified the spatial distribution of key ecological elements; consequently, an integrated “source–corridor–pinch point” ecological network was constructed. The findings aim to optimize the regional ecological security pattern. Ultimately, this study provides a scientific basis for the sustainable development of the study area and similar regions. This study revealed ecological trends based on four periods of land use data (1993–2023). We identified ecological source areas through MSPA and ecosystem service evaluations, and constructed resistance surfaces using spatial PCA. By applying circuit theory, we extracted ecological corridors—incorporating width attributes—and identified pinch points, thereby establishing a comprehensive ecological network. The results show that: (1) Over the past 30 years, construction land area expanded significantly, while cultivated land and water body areas contracted, and grassland and forest areas increased slowly. (2) Both the landscape fragmentation index and connectivity index exhibited a downward trend, while the landscape diversity index decreased first and then increased, indicating a systemic transformation in the landscape pattern. (3) A total of 260 ecological source areas, 694 ecological corridors (linear pathways connecting ecological source areas), and 371 ecological pinch points (critical bottleneck sections within corridors where connectivity is most vulnerable to disruption) were identified, forming an overall network structure with uneven spatial distribution. The ecological network spatial pattern constructed in this study based on ecosystem service assessment and circuit theory can effectively identify key ecological elements and their spatial heterogeneity characteristics, providing scientific reference for optimizing regional ecological security patterns and biodiversity conservation. Full article

As a major water conservation region and ecological security barrier in China, the Three-River Source Region (TRSR) of the Qinghai–Tibet Plateau (QTP) is underlain by extensive permafrost. However, how permafrost degradation alters regional water conservation, particularly the existence of critical thresholds and time-lagged responses, remains insufficiently understood. To clarify these issues, spatiotemporal variations in water conservation (1990–2020) were quantified, and their nonlinear, lagged, and spatially heterogeneous responses to active layer thickness (ALT) were assessed. Using multi-source remote sensing and in situ observations from 1990 to 2020, spatiotemporal variations in water conservation were quantified with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, and responses to permafrost degradation were examined by integrating Sen’s slope, GeoDetector, geographically weighted regression (GWR), and structural equation modeling (SEM) methods. The results showed that water conservation increased overall during 1990–2020 and exhibited a pronounced southeast–northwest gradient (higher in the southeast and lower in the northwest); the rates of change in the Lancang, Yellow, and Yangtze headwaters were 63.5, 56.5, and 31.0 mm a⁻¹, respectively. GeoDetector results indicate that precipitation was the dominant control on the spatial heterogeneity of water conservation (q = 0.704), and its interaction with active layer thickness (ALT) further increased explanatory power (q = 0.736). ALT also interacted with vegetation (q = 0.224) and topography (q = 0.157), suggesting that permafrost effects are modulated by vegetation condition and topographic setting in addition to water inputs. Piecewise regression identified a potential threshold at ALT = 1.77 m, indicating a shift in the ALT–water conservation relationship across this threshold. A 5–7-year lag in the response of water conservation to ALT was also detected, particularly apparent in continuous permafrost zones. Overall, water conservation exhibits a clear southeast–northwest gradient and a delayed response to ALT changes. In addition, the response exhibits clear spatial clustering, with the strongest sensitivity observed in areas with ice-rich permafrost overlain by alpine meadow, and a potential ALT breakpoint further suggests nonlinear permafrost–water conservation coupling. Full article

TENS constitutes a critical ecological barrier on the southeastern margin of the Qinghai–Tibet Plateau, providing essential services such as water conservation and biodiversity protection and helping to safeguard water security in the upper reaches of the Yangtze and Yellow Rivers. Thus, elucidating its vulnerability dynamics is paramount for regional security. Integrating multi-source spatiotemporal data with an interpretable XGBoost–SHAP framework, we quantified interannual variation in vulnerability and the nonlinear threshold responses of key drivers. The results showed pronounced nonlinear phase changes in vulnerability, with 47.96% of the area experiencing abrupt shifts. Notably, 37.89% of TENS reversed from decreasing to increasing vulnerability. TENS underwent an intensive transition during 2010–2015. Interannual variability was dominated by the coupled influence of human disturbance, soil moisture, and atmospheric water, accounting for nearly 60% of the variation, and showed distinct thresholds. Grazing intensity < 0.90 SU/ha was a moderate disturbance, reducing vulnerability, but it became a stressor above this level. Soil moisture showed an inflection point at 79 mm, while vapor pressure deficit (VPD) < 0.39 kPa enhanced resilience, revising the view of VPD as solely a stress factor. Different ecosystems exhibited distinct driving mechanisms. Grasslands were controlled by shallow soil moisture and grazing, forests by hydrothermal balance, and wetlands by low-intensity anthropogenic disturbance (NTL as a proxy; e.g., tourism development or urban expansion). These findings highlight the risk of abrupt shifts in vulnerability regimes (turning points and trend reversals) and support management that emphasizes quality improvement and threshold-based risk management. Full article

Satellite precipitation products (SPPs) generally exhibit varying accuracy and error characteristics, which influence their applicability in hydrological modeling. Based on gauge-observed precipitation and streamflow data, as well as runoff simulations from the SWAT model, this study evaluates the data accuracy, hydrological utility, and error propagation characteristics of eight SPPs derived from the GSMaP, IMERG, and PERSIANN algorithms in the Yellow River Source Region (YRSR), an alpine mountainous watershed. Results show that for estimating precipitation amounts and detecting precipitation events, post-processed GSMaP_Gauge (GGauge) performs best, followed by IMERG Final run data. These two datasets present good substitutability for gauge-based observations and demonstrate considerable potential in streamflow modeling. Specifically, after parameter recalibration, the performance of GGauge is comparable to that of gauge-derived simulations. Most propagation ratios of systematic bias (γ_RB) exceed one, while the ratios of random error (γ_ubRMSE) are below 1, indicating that, through hydrological simulation, systematic bias in precipitation data is more likely to be amplified, whereas random error is generally suppressed. Additionally, γ_ubRMSE exhibits more pronounced autocorrelation than γ_RB, with hotspots in the central region and cold spots in the western part of the YRSR, which is highly related to the basin slope. The statistical features and spatial patterns of error propagation indices help to identify zones that are sensitive to precipitation errors in the study area and highlight the need for targeted strategies to address different types of data error in the modification of SPPs for hydrological application. Full article

Vegetation drought is a critical manifestation of ecosystem vulnerability in high-altitude, water-limited regions under climate change. The Yellow River Water Conservation Area (YRWC), as the core water source of the Yellow River Basin, is highly sensitive to variations in hydrothermal conditions. In this study, a Temperature–Vegetation–Precipitation Drought Index (TVPDI) was constructed to characterize the spatio-temporal dynamics of vegetation drought in the YRWC for 2003, 2012, and 2019. The XGBoost–SHAP framework was further employed to quantitatively analyze the nonlinear response characteristics and relative contributions of key factors within the TVPDI framework. Scenario-based spatial simulations of vegetation drought for 2035 are then conducted based on the GeoSOS-FLUS model. The results indicate that vegetation drought in the YRWC exhibits a relatively stable spatial pattern, with drought severity gradually intensifying from southeast to northwest and moderate drought as the dominant type. Precipitation is the key variable of TVPDI, followed by land surface temperature, while NDVI mainly plays a nonlinear regulatory role. Among external factors, atmospheric moisture conditions show relatively higher explanatory relevance, whereas topographic and human activity factors exert comparatively weaker influences. Scenario-based simulation results suggest that vegetation drought may be alleviated under low-emission pathways, whereas high-emission scenarios substantially exacerbate drought severity and associated risks. This study presents an interpretable, index-based analytical framework combined with scenario-based spatial simulation for characterizing vegetation drought in the YRWC, thereby providing scientific support for ecological management and climate adaptation strategies in the Yellow River Basin. Full article

This study systematically evaluated the response mechanisms of water and sediment processes in the Kuye River Basin to climate change and human activities from 2023 to 2053 by integrating multi-source climate scenarios (CMIP5 models), land-use change projections (based on the Markov chain model), and a distributed hydrological model (SWAT model). The results indicate that under the RCP8.5 high-emission scenario, annual precipitation in the basin shows a non-significant increasing trend but with intensified interannual variability. Spatially, precipitation exhibits a pattern of increasing from northwest to southeast, with a marked decadal transition occurring around 2043. Land-use structure undergoes significant transformation, with construction land projected to account for 30.54% of the total basin area by 2050, while grassland and cropland continue to decline. Water and sediment processes display distinct phased characteristics: a fluctuating adjustment phase (2023–2033), a relatively stable phase (2034–2043), and a sharp growth phase (2044–2053). Parameter sensitivity analysis identifies the curve number (CN2) and soil bulk density (SOL_BD) as key regulatory parameters, revealing the synergistic mechanism by which land-use changes amplify climatic effects through alterations in surface properties. Based on the findings, an adaptive watershed management framework is proposed, encompassing dynamic water resource regulation, spatial zoning, targeted erosion control, and iterative scientific management. Particular emphasis is placed on addressing hydrological transition risks around 2043 and promoting low-impact development practices in high-erosion areas. This study provides a scientific basis for the integrated management of water and soil resources in the context of ecological conservation and high-quality development in the Yellow River Basin. The methodology developed herein offers a valuable reference for predicting water and sediment processes and implementing adaptive management in similar semi-arid basins. Full article

Under intensifying climate change and anthropogenic pressures, extreme low-flow events increasingly jeopardize water security in the Yellow River water supply region. This study develops the Inter-basin Multi-source Water Joint Allocation and Interconnected Routes Regulation System (IMWA-IRRS) to optimize spatiotemporal allocation of multi-source water and simulate topological relationships in complex water networks. The model integrates system dynamics simulation with multi-objective optimization, validated through multi-criteria calibration using three performance indicators: correlation coefficient (R), Nash-Sutcliffe Efficiency (E_ns), and percent bias (PBIAS). Application results demonstrated exceptional predictive performance in the study area: Monthly runoff simulations at four hydrological stations yielded R > 0.98 and E_ns > 0.98 between simulated and observed data during both calibration and validation periods, with |PBIAS| < 10%; human-impacted runoff simulations at four hydrological stations achieved R > 0.8 between simulated and observed values, accompanied by PBIAS within ±10%; sectoral water consumption across the Yellow River Basin exhibited PBIAS < 5%, while source-specific water supply simulations maintained PBIAS generally within 10%. Comparative analysis revealed the IMWA-IRRS model achieves simulation performance comparable to the WEAP model for natural runoff, human-impacted runoff, water consumption, and water supply dynamics in the Yellow River Basin. The 2035 water allocation scheme for Yellow River water supply region projects total water supply of 59.691 billion m³ with an unmet water demand of 3.462 billion m³ under 75% low-flow conditions and 58.746 billion m³ with 4.407 billion m³ unmet demand under 95% low-flow conditions. Limited coverage of the South-to-North Water Diversion Project’s Middle and Eastern Routes constrains water supply security, necessitating future expansion of their service areas to leverage inter-route complementarity while implementing demand-side management strategies. Collectively, the IMWA-IRRS model provides a robust decision-support tool for refined water resources management in complex inter-basin diversion systems. Full article

Soil erosion undermines the sustainable development of land—a vital resource for human survival. Research into the spatiotemporal dynamics of soil erosion is therefore crucial for formulating effective soil and water conservation strategies and advancing ecological protection efforts. In the domain of soil erosion research, the Universal Soil Loss Equation and Revised Universal Soil Loss Equation (USLE/RUSLE) model represent the dominant approach for quantifying soil erosion volumes. While this methodology yields reliable outcomes, it fails to incorporate an assessment of the relative significance of the factors embedded within the model. This study selected the Henan section of the Yellow River Basin as the research area, using monthly remote sensing data from 2010 to 2025 as the main data source. Taking into account factors such as rainfall, slope, elevation, vegetation coverage, and hydrological conservation measures, the RUSLE model was used to calculate and combine Geographic Information System (GIS) geographic detectors for quantitative analysis of soil erosion factors. The results showed the following: (1) The average soil erosion modulus in the study area from 2010 to 2025 was mainly micro and mild erosion. (2) Soil erosion exhibits a certain periodicity, with a year of significant soil erosion occurring every 3–4 years. The overall trend of soil erosion is a decrease. (3) Geographic detector analysis shows that slope has the greatest impact on soil erosion, with larger slopes leading to more severe soil erosion. The influence of each factor ranges from large to small as slope > water conservation measures > rainfall > vegetation coverage > elevation. (4) The interaction between factors can enhance the influence on soil erosion, and the interaction between vegetation cover factors and other factors significantly increases the influence; after interacting with various factors, the slope factor will significantly increase the influence of soil erosion. The research results can provide technical support and decision-making basis for ecological protection in the Yellow River Basin, such as through soil and water conservation, returning farmland to forests, and slope greening; The dominant factors and obvious interaction factors in the research area can provide a scientific basis for subsequent scholars to optimize the parameters of regional models. Full article

Constructing ecological networks (ENs) is an effective measure to mitigate the conflict between urban development and ecological conservation. However, existing simulating methods lack adequate consideration of human ecological demands and the spatial scale differences between these demands and natural ecological processes. This might lead to issues such as incomplete ecological process cycles or structural mismatches being overlooked during ENs simulations. To address these gaps, this study proposed an urban multi-scale nested ENs simulating framework that integrates human ecological demands with natural ecological processes. The framework first simulated an ENs focused on natural ecological process cycles at a global scale (GS). Then, it simulated an ENs centered on human ecological needs within the core urban areas at local scale (LS). Finally, it nested these multi-scale ENs by using cross-scale ecological supply sources as connecting points. This framework was applied to simulate spatio-temporal pattern changes in ENs of Jinan City, a core city in downstream of the Yellow River in China, aiming to mitigate cross-scale ecological conflicts between human–nature interactions under the background of urbanization. The study’s findings revealed that the area of demand sources increased by 8.56 times over 20 years. the area of cross-scale supply sources decreased by 15 km² relative to 2000, and the deterioration in connectivity was more pronounced in GS compared to LS, with a decline of approximately 13.8%. These changes indicate the presence of incomplete ecological process cycles and structural mismatches across the multi-scale boundaries within the study area, which have been worsening annually. We recommend optimizing Jinan City’s multi-scale ecological network through three key strategies: rectifying internal structural mismatches, protecting core ecological areas, and aligning regional ecological demands. Implementing these strategies could significantly improve the network structure, reduce cross-scale mismatches, and enhance ecological connectivity by about 9%. This study highlights the importance of addressing structural mismatches and promoting complete ecological cycles in urban multi-scale ENs simulating, providing valuable insights for formulating urban multi-scale ecological conservation and restoration policies. Full article

The Jianggang sand ridges (JSR) in the southwestern Yellow Sea are a radiating tidal sand ridge system that plays crucial roles in ecological preservation, coastal protection, and terrestrial resource supply. Clay and silt fractions constitute important sediment components of the Jianggang sand ridges. In this study, the Sr-Nd isotopes of clay fractions and the Pb isotopes of K-feldspar in the silt fractions, along with their elemental geochemistry, are investigated to reveal the provenance and transport patterns of clay-size and silt-size sediments in the study areas. The results show that in both the clay-size sediments and the K-feldspar of the silt-size sediments, Ba exhibits the highest content, with the ranges of 432.24 μg/g to 531.05 μg/g and 398.02 μg/g to 2822.36 μg/g, respectively. In contrast, Lu shows the lowest abundance (<0.5 μg/g and <0.1 μg/g, respectively). The ⁸⁷Sr/⁸⁶Sr and ε_Nd(0) values of the clay fraction vary from 0.7158 to 0.7265 and from −14.65 to −10.92, respectively. The ²⁰⁶Pb/²⁰⁴Pb, ²⁰⁷Pb/²⁰⁴Pb, and ²⁰⁸Pb/²⁰⁴Pb of K-feldspar in silt fraction are 17.959~18.429, 15.450~15.689, and 38.066~38.551, respectively. Through the MixSIAR model, it is suggested that the Yangtze River Mouth is the dominant contributor to clay-size sediments in both the onshore and offshore sand ridges (53.9 ± 8.8% and 51.9 ± 8.4%, respectively), followed by the Modern Yellow River Mouth and the Old Yellow River Delta (sum of contributions: <36%). For the silt fraction, the primary sediment sources of the onshore and offshore sand ridges are the Yangtze River Mouth (46.8 ± 5.5%) and the Old Yellow River Delta (42.4 ± 5.3%), while the Modern Yellow River contributes less than 16%. The Northern Chinese Deserts and the Korean rivers make only minor contributions to both fractions. Elemental and isotopic tracers indicate that the silt-size and clay-size sediments derived from the Modern Yellow River are transported southward along the Jiangsu coast by the Subei Coastal Current. Meanwhile, the silt fraction from the Yangtze River Mouth is carried northward along the coast under the influence of the Subei Coastal Current, whereas the clay fraction of it has another longer path, which moves through the central Yellow Sea and migrates southward along the Jiangsu coast to the Jianggang sand ridges under the influence of the Yellow Sea Warm Current. This study enriches the geochemical dataset of the southern Yellow Sea. Full article

The rapid economic and urban development in the Yellow River Delta Efficient Ecological Economic Zone (YRDEEZ) has intensified land use changes and aggravated ecological patch fragmentation. Constructing ecological networks (ENs) can reconnect fragmented patches and enhance ecosystem services. This study simulated land use patterns for 2040 under three scenarios: Natural Development (NDS), Ecological Protection (EPS), and Urban Development (UDS). Results indicated a consistent decline in agricultural land and an expansion of urban land across all scenarios, with the most pronounced urban growth under UDS (6.79%) and the largest ecological land area under EPS (5178.96 km²). Since 2000, the number of EN sources and corridors had decreased, with sources mainly concentrated along coastal areas. The source and corridor under UDS exhibited the highest area ratio (20.08%), while NDS showed the lowest (18.72%), with UDS demonstrating the strongest resilience. Through community detection, the UDS EN was divided into five ecological clusters, encompassing 127 intra-cluster corridors (2285.95 km) and 34 inter-cluster corridors (1171.32 km), among which the cluster near the Yellow River estuary was determined to be the most critical (Level 1). These findings will provide valuable insights for managing landscape fragmentation and biological habitat protection in YRDEEZ. Meanwhile, the multi-scenario simulations of ENs could play an important role in constructing ecological security patterns and protecting ecosystems. Full article

This study takes the source region of the Yellow River from 2000 to 2024 as the research area, and integrates multi-source remote sensing, long-term meteorological observation, and land use data from 2000 to 2024. Using GIS spatial analysis, the standard ellipse model, and a geographic detector, this study systematically depicts the spatio-temporal heterogeneity and multi-scale evolution trend of soil and water conservation services, and then quantifies the spatial differentiation of the contribution rate of climate fluctuation, land use transformation, and human activity intensity to service change. The results showed the following: (1) The land use pattern in the source region of the Yellow River showed a one-way transformation of “grassland dominated, forest land increased alone, and the rest decreased”. The net increase in forest land 204.3 km² was all from the transformation of grassland. The vegetation coverage increased by 9.9%, and the low-value area of soil and water conservation services in the northwest continued to expand. (2) The overall moving distance of the center of gravity of soil and water conservation service capacity is not significant compared with the spatial scale of the source area of the Yellow River. The standard deviation ellipse of each year also did not show systematic and large changes in area, shape, or direction. (3) Annual mean temperature (Q = 0.590) and vegetation coverage (Q = 0.527) are the most influential single factors, while the interaction between annual mean temperature and precipitation (bidirectional enhancement) is the most stable synergistic driving combination. The single-factor Q values of topography and human activities were <0.10. (4) Climate and economic factors are the key factors driving the spatial differentiation of soil and water conservation service capacity, and the role of each driving factor has an optimal range to reduce the risk of soil erosion. The optimal range of population density is 7~9 person/km², the optimal range of average GDP is 11,900~14,100 yuan/km², the optimal range of annual average temperature is 1.71~3.47 °C, the optimal range of annual precipitation is 682~730 mm, the optimal range of vegetation coverage is 81.7~100%, and the optimal range of altitude is 3390~3740 m. The optimal range of slope is 18.3~24.3°. The optimal range of soil moisture is 26.7~29.4%. The optimal range of grazing intensity is 0.352~0.652. The study proposes countermeasures such as strict control of development in high-value areas of soil and water conservation services and key ecological restoration in low-value areas, the establishment of breeding bases and catchment areas in low-precipitation areas to cope with climate change, the optimization of grazing strategies, so as to provide scientific support for the stability of alpine grassland ecosystem services, and the high-quality development of the Yellow River Basin. Full article