Spatiotemporal heterogeneity of ecosystem service interactions and their drivers at different spatial scales in the Yellow River Basin

Assessing the impacts of inter-basin water transfer projects on ecosystem services in water source areas: Evidence from the Hanjiang River Basin

Inter-basin water transfer projects (IBWT) are a key strategy for alleviating regional water shortages. However, studies on the long-term effects of such projects on ecosystem services (ESs) in water source areas, as well as their spatiotemporal evolution, remain insufficient. In particular, the specific impacts of the entire project lifecycle (project initiation, dam heightening, project operation, and ecological restoration) on ESs need further exploration. This study focuses on the Middle Route of the South-to-North Water Diversion Project in China, utilizing multi-source datasets (land use and land cover, meteorological data, soil texture, digital elevation models, normalized difference vegetation index, and net primary productivity), applying the biophysical model method to examine the spatiotemporal variations in ESs across the Hanjiang River Basin over the past three decades, and investigates the impact of IBWT on the ESs of water source areas. The findings reveal: (1) During the project initiation phase (2000-2010), vegetation restoration strategies enhanced soil retention by over 60%, demonstrating that simultaneous project-ecological implementation can mitigate habitat degradation risks. (2) The dam heightening phase (2005-2010) drove spatial reconfiguration of water-energy fluxes, leading to declines in water conservation and carbon sequestration in the midstream region, while enhancing flood mitigation and climate regulation in the reservoir area, unveiling the reshaping mechanisms of dam heightening on ESs supply patterns. (3) The operation phase exhibited significant temporal heterogeneity: initial operation (2010-2015) saw a sharp decline in water conservation (>40%) and soil retention (>60%) due to hydrological disturbances, whereas sustained operation (2015-2020) restored water conservation by nearly 70% and soil retention by over 40% through ecological restoration, alongside a net increase of 14.14% in carbon sequestration, confirming the time-lag compensation effects of restoration measures and the dynamic interplay between ecological restoration and project interventions. This research presents empirical evidence supporting the sustainable management and ecological restoration of IBWT, emphasizing the need to balance spatial water allocation with ecological conservation.

Centennial-scale spatiotemporal heterogeneity of ecosystem service interactions: Implications for spatial management

Over the past century, China has experienced unprecedented land use and land cover changes (LULCC). Centennial-scale evaluation of ecosystem services (ESs) is essential for effective environmental management but remains scarce. A "Landscape Pattern-ESs-Management" framework was developed to quantify the century-scale LULCC impact on ESs and help to make future management policies. Taking Dongting Lake Region as an example, this study focused on water yield, water retention, flood regulation, water purification, soil conservation, and carbon storage. To explore the trade-offs and synergies among these ESs, we employed spearman's correlation, geographically weighted regression, and self-organizing maps clustering algorithm. The results showed that cropland expansion, at the expense of lakes and forests, was the most significant LULCC over the last century, with rapid urbanization becoming prominent after the 1980s. The area of Dongting Lake in the 2020s was less than half of that in the 1900s. While the spatial patterns and distribution of ESs remained relatively stable, their temporal evolution exhibited notable differences. Synergies were primarily observed between water yield, water retention, soil conservation and carbon storage. The boundaries of trade-offs and synergies closely aligned with the 50 m elevation contour. Notably, ESs bundles have significant scale effects. At the grid scale, the FR-WP synergy bundle decreased significantly, mainly in the lake area. At the county scale, the FR-dominated bundle declined, while the WP-dominated bundle increased. Although hilly areas constitute only 35 % of the region, they contribute over 45 % of multiple ESs and experience the most drastic LULCC and ESs bundles transitions. The shrinking of lake and hilly areas underscores the need to prioritize the two regions in future ecosystem management. This study highlights the long-term landscape dynamics under intensive human-nature interactions and provides a transferable method for historical land change detection. It also offers a scientific framework for century-scale environmental evaluation and making sustainable policies.

Spatial differences, dynamic evolution and influencing factors of the coupling and coordination relationship between health resources allocation and health service utilization in China

BACKGROUND

With the progress of economic and social development, the demand for healthcare has increased, making the rational allocation of health resources and the efficient utilization of services crucial for public health. However, mismatches between resource allocation and service utilization have led to strain on resources. This study aims to assess the spatiotemporal evolution and influencing factors of the coupling coordination between health resource allocation (HRA) and health service utilization (HSU) in China, contributing to the realization of the "Healthy China" strategy.

METHODS

Based on the panel data from 2010 to 2022, The entropy method is employed to measure the comprehensive development index of HRA and HSU. The Coupling Coordination Degree Model (CCDM) was used to measure the coupling coordination degree (CCD)of HRA and HSU. The standard deviation ellipse (SDE) and kernel density estimation (KDE) to find the gravity centers movement trends and dynamic evolution of CCD. The XGBoost-SHAP machine learning was used to explore the key factors affecting CCD.

RESULTS

(1) The comprehensive development levels of the subsystems of HRA and HSU showed an overall upward trend, but they do not rise simultaneously. (2) CCD exhibited a stable upward trend over time, with higher values in the south and east, and lower values in the north and west. (3) The spatial migration of CCD was centered in Henan Province, with shifts from northwest to southwest to northeast, and after initial fluctuations, the distribution became more concentrated, and polarization diminished. (4) CCD is primarily influenced by healthcare investment and economic development. Additionally, influencing factors exhibit regional heterogeneity: in the eastern region, URRBMI coverage positively impacts CCD; in the central region, traffic network density positively influences CCD; and in the western region, population density negatively affects CCD.

CONCLUSIONS

This study investigates the spatiotemporal evolution and influencing factors of CCD, suggesting that governments adopt differentiated strategies to enhance CCD and offering a theoretical foundation for implementing the "Healthy China" strategy.

Quantifying thresholds of key drivers for ecosystem health in large-scale river basins: A case study of the upper and middle Yellow River

Under the dual pressures of global climate change and anthropogenic activities, identifying key thresholds for ecosystem health is essential for biodiversity conservation, climate change mitigation, and regional sustainable development. Utilizing the vitality-organization-resilience-service model, this study quantifies the spatiotemporal evolution of ecosystem health in the upper and middle reaches of the Yellow River from 2000 to 2020. Extreme precipitation indices, integrated with partial least squares structural equation modeling, were employed to elucidate the mechanisms by which extreme rainfall impacts ecosystem health. The results indicate that:(1) Both ecosystem vitality and ecosystem organization increased, reflecting enhanced ecosystem stability and connectivity, with significant vegetation recovery in forest and grassland regions. (2) Ecosystem health significantly improved in 69.48 % of the regions. The improvement of ecosystem health in the midstream is primarily attributed to the extensive restoration of forest and grassland. Ecological restoration did not substantially change the ecological vulnerability of the northern desert areas, and restoration should be prioritized in the future. (3) As a primary driver of ecosystem health, moderate increases in vegetation coverage can enhance ecosystem health; the threshold values for nighttime light intensity, relative humidity, precipitation, and land use intensity are 0.6, 68.61 %, 789.92 mm, and 2.34, respectively. (4) Extreme precipitation indirectly affects ecosystem health by influencing vegetation, with a combined contribution rate of 26.10 %. The long-term impact of single extreme precipitation events is limited, and cumulative precipitation events have a greater effect on ecosystem stability. This study determines the threshold of environmental and anthropogenic factors on ecosystem health and clarifies the indirect impact of extreme precipitation on ecosystem health through vegetation, thereby providing a scientific basis for the sustainable management of large-scale vulnerable river systems.

Integrated trade-offs/synergies and interactions approach to quantifying the direct and indirect effects of environmental factors on ecosystem services

The driving mechanisms of ecosystem services (ESs) involve two aspects: the effects of environmental factors (e.g., precipitation and slope) on ESs and the effects of trade-offs/synergies on ESs. Clarifying the complex causal relationships between environmental factors and ESs is essential for decision-makers to formulate ES management. However, existing studies have focused more on identifying the main drivers of ESs without adequately exploring the direct and indirect effects of environmental factors on ESs, especially those based on the interactions between environmental factors and trade-offs/synergies on ESs. In this study, we proposed an integrated approach of trade-offs/synergies and interactions to quantify the direct and indirect effects of environmental factors on ESs by differentiating between the effects of trade-offs/synergies on ESs and the effects of environmental factors on ESs. Three typical ESs, net primary productivity (NPP), soil conservation (SC), and water yield (WY), were estimated in Sichuan Province from 2000-2020. The trade-offs/synergies between ES pairs were subsequently explored using correlation analysis and the geographically weighted regression (GWR) model. The interactions between environmental factors and ESs were verified and separated utilizing the Geodetector model and partial correlation analysis. Finally, the direct and indirect effects of environmental factors on ESs were measured through the bootstrap method. The results revealed that (1) from 2000-2020, three ESs exhibited significant spatial heterogeneity in Sichuan Province. (2) Complex trade-offs and synergies among these ESs were apparent at the provincial scale, characterized by distinct spatial heterogeneity. (3) DEM, temperature, precipitation, and relative humidity were the dominant factors affecting the spatial heterogeneity of ESs. Notably, the interactions involving environmental factors and ESs demonstrated more robust explanatory power for ESs and their trade-offs/synergies than individual drivers did. (4) DEM and temperature had significant direct and indirect effects on ESs when NPP and WY served as the mediating variables, and these mediating variables contributed significantly to the total effect. The integrated trade-offs/synergies and interactions approach deepens our understanding of ES mechanisms and provides a theoretical basis and reference for decision-making, rather than blindly pursuing the maximization of a particular service at the expense of others.

Spatiotemporal assessment of ecological quality and driving mechanisms in the Beijing metropolitan area

Climate change and human expansion are primary drivers of ecological degradation in metropolitan areas, underscoring the necessity of examining the complex interplay between environmental factors and ecological quality. This study investigates the spatial-temporal evolution of ecological quality within the Beijing Metropolitan Area (BMA) from 2000 to 2020 and proposes a comprehensive assessment framework integrating machine learning techniques and spatial heterogeneity analyses. Ecological quality is quantitatively evaluated using the Remote Sensing Ecological Index (RSEI), leveraging MODIS imagery, climate data, land use patterns, and soil characteristics. Spatial clustering patterns of ecological quality are identified through RSEI calculations and spatial autocorrelation analyses, while future trends are projected utilizing the coefficient of variation, Sen and Mann-Kendall methods, and the Hurst index. The XGBoost algorithm elucidates the multifaceted driving mechanisms, and geographically weighted regression (GWR) quantifies the spatial variability of these drivers. The application of XGBoost reveals nonlinear relationships among ecological drivers, and GWR enhances spatially explicit interpretations of these relationships. Results indicate an overall improvement in ecological quality, with the RSEI rising from 0.428 in 2000 to 0.480 in 2020, corresponding to an annual average increase of approximately 0.55%. Notable spatial variability exists, with ecological quality consistently higher in the Taihang Mountains relative to lower-altitude plains. Current ecological protection policies have effectively mitigated ecological degradation in approximately 32.35% of the study area; however, significant environmental pressures persist in urban-rural transition zones and plain regions. Topography and soil properties emerge as dominant influencing factors, while climate indirectly influences ecological quality by shaping vegetation coverage. Human activities predominantly exert negative impacts within urban expansion zones. This research offers a robust quantitative framework for regional ecological conservation, providing critical insights to inform sustainable development and environmental policy-making.

Can ecosystem services supply match local residents' perception: Linking macro-ESs and micro-individual perceptions in the Yellow River Basin

Residents' satisfaction perceptions of ecosystem services (ESs) are essential for the ecological protection and high-quality development of the Yellow River Basin (YRB). Existing studies lacks large-scale survey of local residents' satisfaction perception at urban scale within river basins, and has not effectively explored the matching relationship between the ESs supply and the perceptions of local residents. To address this gap, this study develops a database on nine ESs supply and individual perceptions of the YRB, constructs a comprehensive framework to quantify the matching of ESs supply and local residents' satisfaction perceptions, and proposes targeted strategy. The results reveal that: (1) Provisioning services are higher in cities along the river, while regulating services are higher in the south and west, both showing spatial clustering (p < 0.05). Cultural services are unevenly distributed, with higher quality of life and leisure tourism in the east and south. Provisioning and regulating services exhibit a spatial clustering (p < 0.05). (2) Residents' perceptions of provisioning services are the highest [3.86, 4.28], followed by cultural services [3.85, 3.98], and regulating services are lowest [3.53, 3.69]. Only provisioning services show significant spatial correlation (p < 0.05). (3) There are trade-offs and synergies in the ESs supply, but no significant correlation between the supply and perceptions. (4) A significant mismatch between ESs supply and local residents' perceptions in 15-24 cities, with 33.33%-71.79% of cities showing underestimation or overestimation of ESs supply. These findings provide feasible references for formulating and implementing tailored strategies for coordinated human and nature development.

Scale dependency of trade-offs/synergies analysis of ecosystem services based on Bayesian Belief Networks: A case of the Yellow River Basin

In recent years, climate change and human activities have reduced various ecosystem services (ESs). Analyzing trade-offs/synergies among ESs is crucial for ecosystem sustainability and human well-being. Many studies overlook potential scale effects by focusing on a single scale. We addressed this by evaluating ESs - grain production (GP), habitat quality (HQ), carbon sequestration (CS), soil conservation (SC), and water yield (WY) - in the Yellow River Basin (YRB) from 1990 to 2020, using Bayesian belief networks to analyze their drivers and relationships across scales. The study revealed a steady increase in GP, while both CS and SC exhibited fluctuating upward trends, and HQ and WY experienced downward trends. Significant spatial heterogeneity was observed, with GP decreasing from east to west, and WY, CS, and SC decreasing from northeast to southwest. HQ values were generally high but lower in specific downstream and upstream locations. Key factors influencing these ESs included land use, slope, population, evapotranspiration, NDVI, and precipitation. As the spatial scale expanded, the influence of these factors diminished. The relationships among ESs primarily reflected synergies. However, with the spatial scale increased, trade-offs/synergies among ESs weakened, and several relationships transitioned between trade-offs and synergies. This study offers insights for optimizing ecosystem management by understanding the scale dependency of relationships among ESs.

Study on driving factors of island ecosystem health and multi-scenario ecology simulation using ecological conservation and eco-friendly tourism for achieving sustainability

Maintaining ecosystem health on islands is essential for constructing an ecologically balanced civilization and supporting sustainable development of island tourism. This study provided a quantitative analysis of the ecosystem's evolution on Hainan Island from 2000 to 2020, meticulously investigating the interplay between biodiversity, tourism, and local economic activities on ecosystem health. Additionally, it simulated ecosystem health in 2030 across four distinct scenarios: ecological conservation, eco-friendly tourism, natural development, and economic growth. Finally, practical management suggestions were proposed for achieving multifaceted sustainable ecosystem development. The findings indicated: (1) Ecosystem health on Hainan Island exhibited an overall declining trend from 2000 to 2020, with a noticeable decrease moving from the central mountainous to the plains area. (2) Variations in ecosystem health were primarily shaped by natural geographic factors such as altitude and slope, though socio-economic factors and tourism development increasingly influenced these trends. In addition, natural environmental factors and tourism factors contributed positively to ecosystem health, while socio-economic factors had a negative effect. (3) Simulation predictions demonstrated that prioritizing ecological protection alongside promoting tourism can positively impact ecosystem health on Hainan Island, whereas exclusive emphasis on economic growth may jeopardize long-term sustainability. This study offers invaluable perspectives for conserving biodiversity, fostering socio-economic progress, and aligning ecological conservation with tourism development towards a harmonious multi-objective strategy.

Influence of climate and landscape structure on soil erosion in China's Loess Plateau: Key factor identification and spatiotemporal variability

Climate and landscape structure are widely recognized as the primary drivers of soil erosion; however, the spatiotemporal variability of their effects remains insufficiently understood, limiting our comprehension of the dynamic processes of soil erosion. To address this gap, this study analyzed soil erosion trends on the Loess Plateau from 2000 to 2018. extreme Gradient Boosting was used to identify key climatic and landscape structural factors, while a geographically and temporally weighted regression model was applied to assess the spatiotemporal variability of these influences. The results indicate a decreasing trend in soil erosion from 2000 to 2008, followed by a sharp increase from 2008 to 2018. Grassland edge density emerged as the most important factor, followed closely by grassland percentage and annual precipitation. Temporally, the positive effect of annual precipitation has been intensifying since 2010, contributing to increased erosion, while landscape structural factors progressively enhanced their hydrological regulatory roles, reflecting dynamic interactions with climate. Spatially, the direction of climatic influences remained generally stable, consistently promoting erosion, although by 2018, the effects of average annual temperature and annual sunshine duration reversed to suppress erosion in specific areas. In contrast, landscape structural influences exhibited greater spatial variability, often fluctuating or reversing depending on topography, human activity, and land use. This variability applied specifically and differentially to each metric of fragmentation and diversity, highlighting the critical importance of trade-offs in landscape management. The findings emphasize the complexity and dynamics of soil erosion in response to climate and landscape structure, suggesting implications for the development of spatially targeted soil erosion control strategies that accommodate the phases of temporal variation.

Evolution and driving mechanism of multiple ecosystem services in resource-based region of Northern China

Understanding the spatiotemporal characteristics and comprehensive service capabilities of various ecosystem services is crucial for maintaining regional ecosystem security, and clarifying the driving mechanisms of ecosystem services plays a guarantee for achieving regional sustainable development. Based on the ecological issues of Shanxi Province (SXP) in China, an assessment system covering eight targeted ecosystem services were constructed to quantitatively analyze the spatio-temporal patterns and contribution rates of driving factors. The water conservation, sand fixation, environment purification and habitat quality in the Loess Hills of western SXP have improved, with significant increase in hotspots. The comprehensive service capacity of ecosystem services in the Fenwei Basin (central SXP) has deteriorated, and the coldspots have expanded. The water conservation, carbon storage, habitat quality and recreation culture in the Yanshan-Taihang Mountains (eastern SXP) were enhanced, while product supply, carbon storage and environment purification were deteriorated. Land use is the dominant influencing factor on product supply. Water and soil conservation, sand fixation, and environment purification are dominated by climate factors. Carbon storage, habitat quality and recreation culture are influenced by underlying surface conditions. The current study provided a research paradigm, which will help the government with appropriate management policies to ensure the effectiveness of ecological protection and restoration, and offers insights for facilitating ecological sustainability and economic transformation in resource-based regions worldwide.

Identifying environmental impacts on planktonic algal proliferation and associated risks: a five-year observation study in Danjiangkou Reservoir, China

Understanding the risks of planktonic algal proliferation and its environmental causes is crucial for protecting water quality and controlling ecological risks. Reservoirs, due to the characteristics of slow flow rates and long hydraulic retention times, are more prone to eutrophication and algal proliferation. Chlorophyll-a (Chl-a) serves as an indicator of planktonic algal biomass. Exploring the intricate interactions and driving mechanisms between Chl-a and the water environment, and the potential risks of algal blooms, is crucial for ensuring the ecological safety of reservoirs and the health of water users. This study focused on the Danjiangkou Reservoir (DJKR), the core water source of the Middle Route of the South-to-North Water Diversion Project of China (MRSNWDPC). The multivariate statistical methods and structural equation modeling were used to explore the relationships between chlorophyll-a (Chl-a) contents and water quality factors and understand the driving mechanisms affecting Chl-a variations. The Copula function and Bayesian theory were combined to analyze the risk of changes in Chl-a concentrations at Taocha (TC) station, which is the core water source intake point of the MRSNWDPC. The results showed that the factors driving planktonic algal proliferation were spatially heterogeneous. The main factors affecting Chl-a concentrations in Dan Reservoir (DR) were water physicochemical factors (water temperature, dissolved oxygen, pH value, and turbidity) with a total contribution rate of 60.18%, whereas those in Han Reservoir (HR) were nutrient factors (total nitrogen, total phosphorus, and ammonia nitrogen) with a total contribution rate of 73.58%. In TC, the main factors were water physicochemical factors (turbidity, pH, and water temperature) and nutrient factors (total phosphorus) with total contribution rates of 39.76% and 45.78%, respectively. When Chl-a concentrations in other areas of the DJKR ranged from the minimum to the uppermost quartile, the probabilities that Chl-a concentrations at the TC station exceeded 3.4 μg/L (the benchmark value of Chl-a for lakes in the central-eastern lake area of China) owing to the influence of these areas were all less than 10%. Thus, the risk of planktonic algal proliferation at the MRSNWDPC intake point is low. This study developed an integrated framework to investigate spatiotemporal changes in algal proliferation and their driving factors in reservoirs, which can be used to support water quality management in mega hydro projects.

Prediction of As and Cd dissolution in various soils under flooding condition

Although the mobility of arsenic (As) and cadmium (Cd) in soils during the flooding-drainage process has been intensively studied, predicting their dissolution among various soils still remains a challenge. After comprehensively monitoring multiple parameters related to As and Cd dissolution in 8 soils for a 60-day anaerobic incubation, the redundancy analysis (RDA) and structural equation model (SEM) were employed to identify the key factors and influencing pathways controlling the dynamic release of As and Cd. Results showed that pH alone explained 90.5 % Cd dissolution, while the dissolved-Fe(II) and 5 M-HCl extractable Fe(II) jointly only explained 50.6 % As dissolution. After data normalization, the ratio of Fe(II) to 5 M-HCl extracted total Fe (i.e. FetotII/Fetot) significantly improved the correlation to R2 = 0.824 (p < 0.001) with a fixed slope of 0.393 among the 8 soils. Our results highlight the crucial role played by the reduction degree of total iron contents in determining both the reduction and dissolution of As during flooding. In contrast, dissolved-Fe(II) was too vulnerable to soil properties to be a stable indicator of As dissolution. Therefore, we propose to replace the dissolved-Fe(II) with this novel ratio as the key index to quantitatively assess the kinetic change of As solubility potential across various soils under flooding conditions.

Challenges for sustainable development goal of land degradation neutrality in drylands: Evidence from the Northern Slope of the Tianshan Mountains, China

The SDG 15.3.1 target of Land Degradation Neutrality (LDN) only has 15 years from conception (in 2015) to realization (in 2030). Therefore, investigating the effectiveness and challenges of LDN has become a priority, especially in drylands, where fragile ecosystems intersect with multiple disturbances. In this study, solutions are proposed and validated based on the challenges of LDN. We chose the Northern Slope of the Tianshan Mountains as a case study and set baselines in 2005 and 2010. The region and degree of land change (including degraded, stable, and improved) were depicted at the pixel scale (100 × 100 m), and LDN realization was assessed at the regional scale (including administrative districts and 5000 × 5000 m grids). The results showed a significant disparity between the two baselines. The number of areas that realized the LDN target was rare, regardless of the scale of the administrative districts or grids. Chord plots, Spearman's correlation, and curve estimation were employed to reveal the relationship between LDN and seven natural or socioeconomic factors. We found that substantial degradation was closely related to the expansion of unused, urban, and mining land and reduction in water, glaciers, and forests. Further evidence suggests that agricultural development both positively and negatively affects LDN, whereas urbanization and mining activities are undesirable for LDN. Notably, the adverse effects of glacier melting require additional attention. Therefore, we consider the easy-to-achieve and hard-to-achieve baselines as the mandatory and desirable targets of LDN, respectively, and focus further efforts in three aspects: preventing agricultural exploitation from occupying ecological resources, defining reasonable zones for urbanization and mining, and reducing greenhouse gas emissions to mitigate warming. Overall, this study is expected to be a beneficial addition to existing LDN theoretical systems and serve as a case validation of the challenges of LDN in drylands.

Exploring future ecosystem service changes and key contributing factors from a "past-future-action" perspective: A case study of the Yellow River Basin

Understanding the impacts of climate change and human activities on ecosystem services (ESs) and taking actions to adapt to and mitigate their negative impacts are of great benefit to sustainable regional development. In this paper, we integrate the System Dynamics Model (SD), the Future Land Use Simulation (FLUS) model, the Integrated Valuation and Trade-offs of ESs (InVEST) model, and the Structural Equation Model (SEM). We select three scenarios, SSP1-1.9, SSP2-4.5, and SSP5-8.5, from the Coupled Model Intercomparison Project 6 (CMIP6) to forecast future changes under these scenarios in the Yellow River Basin (YRB) by 2030. We predict future changes in water yield (WY), carbon storage (CS), soil retention (SR), and habitat quality (HQ) in the YRB. The results show that: (1) Under the SSP1-1.9 scenario, ecological land types such as forests, grasslands, and water bodies are protected and restored to a certain extent; under the SSP2-4.5 scenario, the degree of land spatial development occupies an intermediate state among the three scenarios; and under the SSP5-8.5 scenario, there is an obvious increase in the artificialization of the watershed's land use. (2) Under scenario SSP1-1.9, there is a comprehensive approach to sustainable development that significantly improves all ESs in the watershed, while the SSP5-8.5 and SSP2-4.5 scenarios demonstrate an increase in trade-offs between WY, HQ, and CS, especially in the downstream area. (3) Anthropogenic factors having more significant impacts in the SSP5-8.5 scenario. In this paper, we not only summarize the differences in trade-offs among various ESs but also provide an in-depth analysis of the key factors affecting future ESs, providing new ideas and insights for the sustainable development of ES in the future. In summary, we propose a prioritized development pathway for the future, a reduction of trade-offs between ESs, and an improved capacity to respond to challenges.