The Coupling of Human-Water Interactions Governs Ecosystem Service Values in China's Inland River Basins: A Case Study from the Heihe River Basin

The Coupling of Human-Water Interactions Governs Ecosystem Service Values in China's Inland River Basins: A Case Study from the Heihe River Basin | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Coupling of Human-Water Interactions Governs Ecosystem Service Values in China's Inland River Basins: A Case Study from the Heihe River Basin Rujun Yang, Jieru Yu, Jing Sun, Hongbo Lv, Jun Zhang, Xiaomei Sun, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7866466/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The spatio-temporal evolution of ecosystem service value (ESV) in inland watersheds is governed by the dynamic interplay of human and water systems, a process primarily mediated by land use/cover change (LUCC); investigating this process is therefore vital for informing resource allocation and policy. This study analyzed LUCC and ESV dynamics over a 33-year timeframe (1990–2023) in the Heihe River Basin, China, utilizing remote sensing imagery from four distinct periods, as well as the land use dynamic degree and equivalent factor methods. The results indicate that grassland, desert, and bare land are the dominant land use types, with the continuous expansion of construction land. Cropland and desert area fluctuated, forestland declined, and grassland and water recovered in phases, forming a gradient from downstream desertification to upstream oasis ecosystems. The total ESV increased from CNY 144.09 billion to CNY 150.44 billion, exhibiting a "declining–rising" trend. Grassland and water were the primary contributors to ESV changes, while cropland and water exhibited stable growth in the ESV. Regulating services, particularly hydrological regulation, dominated the ESV structure. Significant spatial heterogeneity existed: high-value areas clustered in upstream counties (Qilian, Sunan) and were characterized by abundant forest, grassland, and water; low-value areas occurred in downstream counties (Ejina Banner, Jinta) and were dominated by desert and bare land. Spatially, the ESV evolved through phases of "natural continuity–interference fragmentation–local recovery", driven by LUCC dynamics. Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Hydrology land use/land cover change ecosystem service value Heihe River Basin spatio-temporal variation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Ecosystem services refer to the life-supporting products and benefits directly or indirectly derived from the structure, processes, and functions of ecosystems [1] . The ecosystem service value (ESV) quantifies these services in monetary terms. This enables the quantitative assessment of an ecosystem's potential service capacity and the economic value provided by ecosystem services to human society, reflecting the contributions to human well-being [2] . Therefore, ESV assessment has become a vital tool for measuring the impact of human activities on natural capital and for balancing development and conservation objectives. Land is a crucial carrier for various ecosystems on Earth. Land use/land cover change (LUCC) causes alterations in ecosystem types, area, and spatial patterns, subsequently affecting ecosystem service functions and their value. In recent decades, global population growth, accompanied by rapid urbanization and cropland expansion, has led to the degradation of natural ecosystems and the loss of associated services, particularly in grasslands, forests, and wetlands [3] . To effectively protect ecosystems and enhance their service provision, it is essential to investigate the mechanisms driving the ESV response to land use changes and identify driving patterns. To date, domestic and international scholars have extensively explored ESV research at the global, national, and watershed/regional scales. Valuation methods such as the equivalent factor method (based on ESV per unit area) and the functional value method (based on the price per unit service function) have been used to explain the service value characteristics of different ecosystems in various regions [4–6] . Presently, economic valuation primarily follows the ESV assessment model established by Costanza et al. [7] . For example, Liang Zheng et al. [8] used Costanza's method to estimate ten ESVs within 1km and 2km ranges of the Yangtze River Basin in 2017. To adapt the analysis to China's specific conditions, Xie Gaodi et al. [1] developed a unit area ESV table based on this model, which has been widely applied. For instance, Zhang Baiting et al. [9] analyzed the spatio-temporal evolution of ESV in the Qilian Mountains region from 1990 to 2020 using correction coefficients, laying a foundation for local land management and ecological restoration policies. Li Lan et al. [10] combined land use transfer matrices (2000–2018) with the equivalent factor method to assess ESV changes and their sensitivity in Qinghai Province over nearly 20 years, deeply exploring the underlying driving forces, management implications, and influencing factors. In watershed ESV research, Li Yue et al. [11] comprehensively used methods such as the equivalent factor method, sensitivity analysis, spatial autocorrelation analysis, optimal-parameter-based geographical detector, and spatial regression models to reveal and understand the spatial differentiation and driving mechanisms of ESV in multi-scale contexts in the Mawei River Basin. Lan Zicheng et al. [12] assessed ESV in the Minjiang River Basin, analyzing its change trends and trade-off/synergy relationships. Current research on watershed ESV is relatively scarce, and studies on the Heihe River Basin are outdated. Therefore, this study investigates LUCC changes and ESV changes in the Heihe River Basin from 1990 to 2023. The Heihe River Basin is the second-largest inland basin in northwest China. Its unique natural environment, locational conditions, and economic development model have led to severe conflicts over water and soil resources, increasingly serious land degradation, and a series of ecological problems. This study aims to systematically analyze the spatio-temporal patterns of LUCC changes within the basin, scientifically evaluate the gains and losses in ESV accompanying LUCC, and reveal the relationship between ESV and LUCC, thus providing decision-making support for achieving sustainable socio-economic development in the basin and establishing a solid scientific foundation for sound policy systems, such as watershed ecological compensation. Results LUCC from 1990 to 2023 After reclassifying the land use types in the Heihe River Basin, the area and spatial distribution of each land use type in 1990, 2000, 2010, and 2023 were determined (Fig. 1 .). The dominant land use types in the basin are desert, bare land, and grassland. Desert area was the largest, accounting for 56.99% in 2010 before declining to 50.78% in 2023 after ecological restoration, reflecting the process of desertification and control in arid regions. Bare land area increased continuously, from 15.81% in 1990 to 17.57% in 2023, closely related to the combined effects of surface vegetation destruction and wind erosion. As an ecological transition zone, grassland area showed a "decline–recovery" pattern, accounting for 21.70% in 1990, decreasing to 17.22% in 2010 due to overgrazing and reclamation, and recovering to 21.32% after 2010 with the implementation of the "Cropland-to-Grassland Conversion Project", though still not fully restored to the initial level. Construction land area increased significantly from 1990 to 2023. Water area decreased from 269,300 hectares in 1990 to 250,800 hectares in 2010 and then increased to 343,900 hectares in 2023. Figure 1 . reveals a significant north–south gradient: in the northern Alxa Plateau, influenced by an arid climate and the Mongolian high-pressure system, desert and bare land cover over 80%, forming a concentrated area of sandy land centered on the Badain Jaran Desert. The southern Qilian Mountains–Hexi Corridor transition zone, influenced by mountain precipitation and oasis agriculture, has a relatively high proportion of grassland, forming a belt-like oasis ecosystem along the main stream of the Heihe River. This differentiation essentially results from the combined effects of precipitation and human activity intensity. The land use dynamic degree changes in the Heihe River Basin from 1990 to 2023 are shown in Fig. 2 . The land use dynamic degree is a key indicator measuring regional land development intensity, the extent of land use change, and rate differences. During 1990–2023, the comprehensive land use dynamic degree in the Heihe River Basin showed a clear upward trajectory. From 1990 to 2000, the comprehensive land use dynamic degree was 0.02%, rising to 0.49% in 2010–2023. This trend demonstrates that after implementing ecological restoration projects, the land use pattern entered a more active phase of change, with significantly increased intensity. The single dynamic degree for construction land showed continuous growth, closely reflecting the acceleration of urbanization and industrialization in the basin, with an expanding urban scale. The dynamic degree for cropland showed an initial increase, followed by a decrease: 1.68% during 2000–2010 (relatively rapid growth), but − 0.13% during 2010–2023 (slight decrease). This shift stems from two aspects: cropland protection policies promoting an initial increase and, later, accelerated urban expansion occupying some cropland, leading to a decline, reflecting the tension between cropland protection and urban development needs. The dynamic degree of forestland showed little overall change, indicating insignificant but slightly declining trends. Forest resources face significant pressure, whether from excessive human development or environmental changes, necessitating strengthened protection measures. The dynamic degrees for grassland and water both showed significant recovery trends after 2010. The single land use dynamic degrees for grassland and water increased by 1.83% and 2.27%, respectively. These positive changes have benefited from ecological restoration projects, such as "Returning Cropland to Grassland" and wetland protection, which specifically targeted the restoration and protection of grassland and aquatic ecosystems, leading to more dynamic changes and enhanced ecological functions, representing important achievements in the basin's ecological construction. Overall, the land use pattern of the Heihe River Basin underwent complex but traceable changes from 1990 to 2023 under the intertwined influence of human activities and ecological engineering. Analysis of Spatio-Temporal Variation in Ecosystem Service Value Analysis of Temporal Variation in ESV The ESV of the Heihe River Basin experienced "declining–rising" fluctuations from 1990 to 2023, increasing from CNY 144.09 billion to CNY 150.44 billion, a growth of 4.41% (Fig. 3 .). From 1990 to 2010, ESV decreased continuously from CNY 144.086 billion to CNY 128.64 billion, a decrease of 10.72%. From a land use perspective, the reduction in grassland area was the dominant driving factor in reducing the overall ESV. The period 2010–2023 was a phase of ESV recovery, increasing from CNY 128.64 billion to CNY 150.44 billion, a growth of 16.95%. During this stage, grassland and water became the core contributors to ESV growth, with ecological contribution rates of 51.79% and 38.92%, respectively. This indicates that the effectiveness of ecological restoration projects became apparent, strengthening the ecological functions of grassland and water and driving rapid ESV recovery. Among land types, grassland exhibited the most significant fluctuation in ESV. From 1990 to 2010, influenced by excessive human use, grassland ESV declined from CNY 72.94 billion to CNY 57.91 billion, a decrease of 20.60%. From 2010 to 2023, grassland ESV recovered to CNY 71.68 billion. However, grassland ESV in 2023 was still 1.72% lower than in 1990, indicating that, despite restoration, the accumulated effects of earlier damage persist, and recovery is a long-term process requiring continued protection and restoration efforts. Although cropland's baseline ESV contribution was not high, it showed a stable and continuous growth trend, increasing by 21.05%—from CNY 3.33 billion in 1990 to CNY 4.03 billion in 2023. Water ESV first decreased and then increased, declining from CNY 29.94 billion in 1990 to CNY 27.88 billion in 2010 (a decrease of 6.87%) and then growing rapidly from 2010 to 2023, increasing from CNY 27.88 billion to CNY 38.23 billion (a growth of 37.13%). Overall, water body ESV increased by 27.71% from 1990 to 2023. In summary, ESV changes in the Heihe River Basin from 1990 to 2023 resulted from the combined effects of land use transformation and ecological engineering interventions. The fluctuation of grassland and the growth of cropland and water reflect the trajectory of the basin's ecosystem from being under pressure to undergoing restoration. Future efforts should focus on the long-term recovery of grasslands and consolidating the achievements in cropland and water ecological construction, optimizing land use structure, and intensifying ecological restoration to continuously enhance the ESV of the Heihe River Basin and ensure regional ecological security and sustainable development. Changes across different ESV categories varied in the Heihe River Basin from 1990 to 2023 Fig. 4 ., Table 1 ). From 1990 to 2023, the values of provisioning services, regulating services, supporting services, and cultural services all showed fluctuating upward trends. They are ranked in the following order in terms of value proportion: regulating services > supporting services > provisioning services > cultural services. Regulating services accounted for about 68% and supporting services for about 20%. Both had significantly higher value than the other two service types, dominating the basin's ESV, primarily due to their higher stability. Provisioning and cultural services had relatively low ESVs, only about 12%, mainly because their stability is lower than that of regulating and supporting services. Among individual ESV types, hydrological regulation within regulating services had the largest ESV proportion throughout the study period, with an ecological contribution rate as high as 78.88%, although with large fluctuations. From 1990 to 2010, hydrological regulation’s ESV decreased from CNY 43.15 billion to CNY 38.99 billion and then rebounded to CNY 48.58 billion in 2023. Despite fluctuating proportions over different periods, its dominant position remained stable in the long term. This stems from the scarcity of water resources in the basin. Hydrological regulation, associated with wetland and water ecosystems, plays a key role in water conservation, runoff regulation, and drought mitigation, forming the cornerstone of basin ecological security. Climate regulation had the second-highest ESV proportion, decreasing from CNY 27.95 billion in 1990 to CNY 24.01 billion in 2010 and then rebounding to CNY 27.71 billion in 2023. Its ecological contribution rate over 1990–2023 was 3.52%; during 2000–2010, its contribution rate reached 25.99%, becoming the highest contributing individual service in that period. During this stage, enhanced climate regulation capacity resulted from vegetation recovery and water area changes, reflecting the ecosystem's phased response to climate change and highlighting the supporting role of climate regulation services in ESV during specific periods. Food production, raw material production, water supply, and nutrient cycling maintenance had low ESV proportions and relatively small ecological contribution rates. Table 1 ESV and ecological contribution rate in the Heihe River Basin, 1990–2023. Ecosystem Service Value (Billion CNY) Ecological Contribution Rate (%) 1990 2000 2010 2023 1990–2000 2000–2010 2010–2023 1990–2023 Cropland 3.33 3.51 4.01 4.03 14.32% 3.29% 0.26% 5.92% Forestland 20.58 20.52 20.37 19.95 4.67% 0.86% 1.58% 5.35% Grassland 72.94 72.41 57.91 71.68 41.58% 81.11% 51.79% 10.59% Water 29.94 29.45 27.88 38.23 38.66% 8.76% 38.92% 70.12% Desert 16.42 16.43 17.48 15.57 0.72% 5.84% 7.16% 7.19% Bare land 0.88 0.88 0.91 0.98 0.04% 0.13% 0.28% 0.83% Food production 2.71 2.73 2.58 2.88 2.61% 1.06% 1.36% 2.43% Material production 3.55 3.55 3.22 3.58 0.01% 2.28% 1.64% 0.37% Water supply 3.85 3.81 3.49 4.39 4.51% 2.18% 4.10% 7.77% Gas regulation 12.01 11.97 10.69 11.99 3.71% 8.84% 5.98% 0.26% Climate regulation 27.95 27.79 24.01 27.71 16.67% 25.99% 16.96% 3.52% Environmental purification 14.73 14.66 13.63 14.80 7.31% 7.09% 5.39% 1.09% Hydrological regulation 43.15 42.70 38.99 48.58 48.02% 25.52% 43.98% 78.88% Soil conservation 14.66 14.63 13.09 14.67 3.41% 10.54% 7.22% 0.10% Nutrient cycling maintenance 1.13 1.13 1.02 1.14 0.05% 0.75% 0.53% 0.11% Biodiversity 13.91 13.83 12.25 14.11 9.11% 10.84% 8.52% 2.83% Aesthetic landscape 6.43 6.39 5.67 6.61 4.59% 4.91% 4.31% 2.65% Total 144.09 143.20 128.64 150.44 - - - - Analysis of Spatial Variation in ESV The GIS grid scale method, based on grid point units, serves as a data carrier and basic evaluation unit for indicator factors. It can intuitively reflect the spatial distribution of ESV for description and visualization. When applying this method for spatial simulation of ESV in the Heihe River Basin, a 5km×5km grid sample was established in ArcGIS. The ESV of different land use types was superimposed and calculated within each grid cell to obtain the ESV per grid. Natural break classification (Jenks) was used for interpolation analysis. As shown in Fig. 5 ., the ESV of the Heihe River Basin from 1990 to 2023 exhibited relatively stable spatial characteristics in the midstream and significant fluctuations in the upstream and downstream. The spatial distribution of ESV was strongly correlated with the spatial land use pattern. Medium–high-ESV areas were mainly distributed in Qilian County and Sunan County in the upstream, as well as regions traversed by water bodies. The upstream area is dominated by forests, grasslands, and wetlands, with strong ecological functions such as water conservation and biodiversity maintenance, and water bodies have higher ESV than other land types. Low-value areas were concentrated downstream in Ejina Banner and Jinta County, where sandy land, gobi, and bare land predominate, resulting in lower ESV. From 1990 to 2000, the mid-upper basin formed a continuous high-value zone composed of forests, wetlands, and oases, while downstream desert was mainly low-value, with natural ecosystems dominating the service value pattern. By 2010, land reclamation, wetland shrinkage, and water resource imbalances had exacerbated the fragmentation of high-value areas, leading to continuous degradation of ecosystem service functions. By 2023, ecological regulation policies had driven the partial recovery of downstream oases and midstream wetlands. However, water resource fluctuations further intensified the fragmentation of high-value areas. Overall, the spatial evolution exhibited a phased pattern of "natural dominance–interference contraction–degraded fragmentation–local recovery", with the core logic being the interactive coupling of the "human–water–ecosystem" system. Discussion Research indicates that land use change is a primary driver of ESV gains and losses, significantly influencing its spatial variation. This finding aligns with the research of Changyan Wu et al. [18] on the impact of LUCC and optimization on ESV in Jiangsu Province. Alterations in land use exert varying degrees of impact on the structure and function of ecosystems, consequently affecting the diverse services ecosystems provide for humans’ societal development and well-being. This ultimately leads to changes in ESV, with the effects being more pronounced at the regional scale [19] . The analysis of LUCC and ESV variation within the Heihe River Basin from 1990 to 2023 revealed that LUCC is the principal factor driving ESV changes, exerting substantial influence on its increase or decrease. This conclusion is consistent with the research findings of Zhang Baiting et al. [9] on ESV in the Qilian Mountain region. During the study period, the ESV of the Heihe River Basin initially declined before rising, increasing from CNY 144.089 billion to CNY 150.443 billion, a rise of CNY 6.354 billion. This trajectory differs from the findings of Shang Haiyang et al. [20] regarding ESV in the Shiyang River Basin. The discrepancy is primarily attributable to early ecological degradation in the Heihe Basin caused by urbanization and cropland expansion. Subsequently, ESV increased due to the successful intervention of ecological restoration projects, such as grazing exclusion and grassland recovery and wetland conservation. This pattern reflects the typical trajectory of ESV recovery in the northwest arid region of China. Changes in the area of grassland and water were the largest contributing factors to ESV variation in the Heihe River Basin. This conclusion contrasts with the findings of Gao Mengmeng et al. [21] for the Yellow River Basin, where cropland and forestland changes were dominant. This difference stems from the Heihe Basin's primary landscape being desert and grassland, whereas forest and cropland cover a larger proportion in the Yellow River Basin. The reduction in the area of forestland, grassland, and desert land led to a decrease in the service value of gas regulation and climate regulation within the Heihe River Basin ecosystem. Regulating services constitute the primary ecosystem service function in the Heihe Basin, with climate regulation and hydrological regulation representing the largest proportions. This result is consistent with the research of Ma Chao et al. [22] on ESV in the middle reaches of the Heihe River within Gaotai County, Zhangye City. The changes in ESV within the Heihe River Basin confirm the core principle of "water determines ecology", which is characteristic of inland river systems in arid regions. Its initial decline–recovery pattern and responsiveness to ecological policies, coupled with a structural contribution dominated by grassland and water and distinct spatial differentiation, collectively form a distinctive model differentiating the Heihe River Basin from other river basins. Fundamentally, the “human–water–ecosystem” coupling mechanism revealed here establishes a distinct management framework for arid basins, where water-centric strategies must drive ecosystem policies. Conclusions Based on land use data and the equivalent factor method per unit area, this study analyzed land use structure changes and the spatio-temporal evolution of ESV in the Heihe River Basin from 1990 to 2023. The main conclusions are as follows: From 1990 to 2023, grassland, desert, and bare land were the dominant land use types in the Heihe River Basin. Construction land expanded continuously due to urbanization. Forest land area decreased, and cultivated land and desert area showed an initial increase followed by a decrease. Grassland and water underwent phased recovery through ecological restoration, forming a spatial gradient differentiating between downstream desertification and the upstream Qilian Mountains–oasis belt. The total ESV of the Heihe River Basin increased from CNY 144.086 billion in 1990 to CNY 150.443 billion in 2023, exhibiting a "declining–rising" trend. Grassland and water bodies were the primary contributors to the overall ESV change, while cultivated land and water bodies showed stable ESV growth. The ESV structure was dominated by regulating services, with hydrological regulation contributing the most, highlighting the central role of water resources in this arid inland river basin. ESV showed significant spatial heterogeneity from 1990 to 2023, characterized by an "upstream high–downstream low" pattern: high-value areas were concentrated upstream in the forest, grassland, and water-body-dense regions of Qilian County and Sunan County; low-value areas were distributed downstream in Ejina Banner and Jinta County, where desert and bare land accounted for more than 80%. The spatial evolution underwent a phased process of "natural continuity–interference fragmentation–local recovery". Methods An Overview of the Study Area The Heihe River originates from the northern foothills of the Qilian Mountains, flowing through Qinghai Province, Gansu Province, and Inner Mongolia Autonomous Region, and finally draining into Juyan Lake. The section above Yingluoxia is the upstream, including Qilian County in Qinghai Province. The section from Yingluoxia to Zhengyixia is the midstream, encompassing Sunan Yugur Autonomous County, Shandan County, Minle County, Ganzhou District, Gaotai County, Linze County, Jiayuguan City, and Suzhou District. The section below Zhengyixia is the downstream, including Ejina Banner and Jinta County [13] . This study takes the boundaries of these 11 counties/districts as the research area (Fig. 6 .). Located between 97°E–103°E and 38°N–43°N, the basin is approximately 928 km long, with a total area of about 15.7067 million hectares. Precipitation decreases from upstream to downstream, with an average annual precipitation of 1719.80 mm and evaporation as high as 2000–3000 mm. The Heihe River Basin features coexisting cold and arid zones. The upstream Qilian Mountain area has high mountains and deep valleys with large elevation differences, where glaciers and permafrost are widely distributed, serving as the main source of Heihe River runoff. The midstream Hexi Corridor consists of contiguous oases formed by alluvial plains, relying on river water for irrigated agriculture but facing problems of water resource over-extraction. The downstream Alxa High Plain is dominated by the Gobi Desert, with Juyan Lake as the terminal lake, maintained by ecological water supplementation and surrounded by ecologically sensitive wetlands. Data Sources The DEM data used in this study were sourced from the National Cryosphere Desert Data Center/National Service Center for Special Environmental Observation Stations ( https://www.ncdc.ac.cn ). Land use data for 1990, 2000, 2010, and 2023 were obtained from the Resources and Environmental Sciences Data Platform, Chinese Academy of Sciences ( http://www.resdc.cn ). These 30 m resolution datasets were generated through systematic manual visual interpretation of Landsat TM/ETM imagery as the primary data source, with interpretation accuracy exceeding 90%, validated through random sampling with > 1,000 reference points. Referring to the National Land Use Status Classification Standard (GB/T21010-2017), the land use characteristics of the Heihe River Basin, and Xie Gaodi et al.'s (2015) ecosystem classification system, land use types were reclassified into 7 categories using ArcGIS 10.8: cropland, forestland, grassland, water, construction land, desert, and bare land. Using statistical yearbooks from 1991 to 2024, including the China Statistical Yearbook, Gansu Statistical Yearbook (renamed Gansu Development Yearbook after 2010), Qinghai Statistical Yearbook, Inner Mongolia Yearbook, and county/city/district statistical yearbooks, the sown area and grain yields of three main food crops (wheat, corn, and soybeans) in the study area were obtained. The average grain yield per unit area was calculated at 26746.04 kg/ha. Data on the net profit from grain production came from the National Compilation of Cost-Benefit Data for Agricultural Products, giving an average grain price of 2.05 CNY/kg. LUCC Analysis Method The land use dynamic degree indicates the quantitative change in land types over a period; it can be divided into the single land use dynamic degree and the comprehensive land use dynamic degree. The single land use dynamic degree is the rate of change in a specific land type within a region over a given period. The comprehensive land use dynamic degree indicates the overall rate of LUCC in a region [14] . The formulas are as follows: $$\:\begin{array}{c}V=\left(\frac{{U}_{j}-{U}_{i}}{{U}_{i}}\right)\times\:\frac{1}{T}\times\:100\% \left(1\right)\end{array}$$ $$\:\begin{array}{c}LC=\frac{\sum\:_{k=1}^{n}\varDelta\:{LU}_{k-g}}{2\sum\:_{k=1}^{n}{LU}_{k}}\times\:\frac{1}{T}\times\:100\% \left(2\right)\end{array}$$ where \(\:V\) is the single land use dynamic degree (%); \(\:{U}_{i}\) and \(\:{U}_{j}\) are the areas (ha) of a specific land use type at the beginning and end of the study period, respectively; \(\:LC\) is the comprehensive land use dynamic degree (༅); \(\:L{U}_{k}\) is the area (ha) of the k-th land use type at the beginning of the study period; \(\:\varDelta\:{LU}_{k-g}\) is the absolute value (ha) of the area converted from the k-th land type to the g-th land type during the study period; and \(\:T\) is the time interval (year) of the land use data. Ecosystem Service Value Accounting This study primarily refers to Xie Gaodi et al.'s equivalent values for ecosystem services per unit area in China [1] and previous research results [15–16] , combined with the actual land use situation in the Heihe River Basin. Desert and bare land were assigned the values for desert and bare land from the Chinese ESV equivalent table, respectively. Cropland was assigned the average value for dryland and paddy land, forestland was assigned the average value for coniferous, broadleaf, and shrub forests; grassland was assigned the average value for grassland, shrub-grass, and meadow; and water was assigned the average value for wetlands, water systems, and glaciers and snow cover. The value coefficient for construction land was assumed to be 0. This resulted in the final ESV equivalent table per unit area for the Heihe River Basin (Table 1 ). Furthermore, considering the status of socio-economic development in the study area, the economic value created by grain production per unit area was used for correction. Based on the principle that "the economic value coefficient of one standard equivalent of ecosystem services is 1/7 of the economic value of food production per unit area of farmland", the formula is $$\:\begin{array}{c}{E}_{a}=\frac{1}{7}\times\:\sum\:_{i=1}^{n}\frac{{m}_{i}{P}_{i}{q}_{i}}{M}\times\:\frac{R}{{R}_{0}} \left(3\right)\end{array}$$ where \(\:{E}_{a}\) is the economic value of one standard equivalent of ecosystem services (CNY/ha); i is one of the main crop types; \(\:{m}_{i}\) is the area of the i-th grain crop (ha); \(\:{P}_{i}\) is the calculated average price of the i-th grain crop (CNY/kg); \(\:{q}_{i}\) is the yield per unit area of the i-th grain crop (kg/ha); \(\:M\) is the total area of grain crops (ha); \(\:n\) is the number of grain crop types; \(\:R\) is the average yield per unit area of grain crops in the study area (kg/ha); and \(\:{R}_{0}\) is the national average yield per unit area of grain crops (kg/ha). To enhance the comparability of ESV across years, the average value over the study periods was used as the standard. The standard equivalent coefficient for the Heihe River Basin from 1990 to 2023 was 1775 CNY/ha. Referring to previous studies, based on the Heihe River Basin unit area ESV equivalent table and the value of one standard unit ESV equivalent factor, the ESV coefficients for different land use types in the Heihe River Basin were calculated using the following formulas (Table 2 ), which largely reflect the actual situation in the basin. The formulas are $$\:\begin{array}{c}V{C}_{k}=V\times\:{C}_{k} \left(4\right)\end{array}$$ $$\:\begin{array}{c}ESV=\sum\:_{k=1}^{n}{A}_{k}V{C}_{k} \left(5\right)\end{array}$$ where \(\:V{C}_{k}\) is the equivalent coefficient of ESV per unit area for the k-th land use type (CNY/ha); \(\:{C}_{k}\) is the ESV coefficient (equivalent factor) per unit area for the k-th land use type; \(\:V\) is the monetary value of a single ESV equivalent factor in the Heihe River Basin; ESV is the total ESV of the Heihe River Basin (CNY); and \(\:{A}_{k}\) is the area of the k-th land use type (ha). Table 2 Ecosystem service value (ESV) per unit area (CNY·hm⁻²·yr⁻¹) for different land use types in the Heihe River Basin. Ecosystem Service Type Cropland Forestland Grassland Water Desert Bare Land First category Second category eq. value eq. value eq. value eq. value eq. value eq. value Provisioning Services Food production 0.85 1508.77 0.23 408.26 0.23 408.26 0.44 775.09 0.01 17.75 0.00 0.00 Material production 0.40 710.01 0.54 958.51 0.34 603.51 0.24 431.92 0.03 53.25 0.00 0.00 Water supply 0.02 35.50 0.28 497.01 0.19 337.26 4.35 7715.45 0.02 35.50 0.00 0.00 Regulating Services Gas regulation 0.67 1189.27 1.76 3124.05 1.21 2147.78 0.95 1686.28 0.11 195.25 0.02 35.50 Climate regulation 0.36 639.01 5.27 9354.39 3.19 5662.34 2.14 3804.47 0.10 177.50 0.00 0.00 Environmental purification 0.10 177.50 1.57 2786.79 1.05 1863.78 3.10 5508.50 0.31 550.26 0.10 177.50 Hydrological regulation 0.27 479.26 3.81 6762.85 2.34 4153.56 44.53 79047.86 0.21 372.76 0.03 53.25 Supporting Services Soil conservation 1.03 1828.28 2.14 3798.56 1.47 2609.29 1.08 1917.03 0.13 230.75 0.02 35.50 Nutrient cycling maintenance 0.12 213.00 0.16 284.00 0.11 195.25 0.08 147.92 0.01 17.75 0.00 0.00 Biodiversity 0.13 230.75 1.95 3461.30 1.34 2378.54 3.48 6171.18 0.12 213.00 0.02 35.50 Cultural Services Aesthetic landscape 0.06 106.50 0.86 1526.52 0.59 1047.27 2.24 3970.14 0.05 88.75 0.01 17.75 Total 4.01 7117.86 18.57 32962.25 12.06 21406.82 62.63 111175.84 1.10 1952.53 0.20 355.01 Ecological Contribution Rate The ecological contribution rate is the percentage of ESV change for a specific land type within a given period relative to the total ESV change [17] , and it is used to identify the main contributing factors affecting ESV change. The formula is $$\:{C}_{i}=\frac{\left|\varDelta\:{ESV}_{i}\right|}{\sum\:_{i=1}^{n}\left|\varDelta\:{ESV}_{i}\right|}\times\:100\%$$ where \(\:{C}_{i}\) is the ecological contribution rate (%) of the i-th land use type and \(\:\varDelta\:{ESV}_{i}\) is the change in ESV of the i-th land use type (CNY). Declarations Author contributions statement Conceptualization, R.Y. and J.Y.; Methodology, R.Y.; Software, R.Y.; Validation, R.Y., J.Y., J.S., H.L. and J.Z.; Formal Analysis, R.Y. and J.Y.; Investigation, R.Y. and J.Y.; Resources, J.Y. and J.S.; Data Curation, R.Y.; Writing – Original Draft Preparation, R.Y.; Writing – Review & Editing, R.Y. and J.Y.; Visualization, R.Y.; Supervision, R.Y. and J.Y.; Project Administration, R.Y.; Funding Acqui-sition, J.Y. and J.S. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Natural Science Foundation Project of Gansu Province (23JRRA1413); Dingxi Science and Technology Plan Project (DX2024AZ03). Conflicts of Interest: No conflict of interest exists in this submitted manuscript, and this manuscript is approved by all authors for publication. Data availability The data and materials used and/or analyzed during the current study are available from the corresponding author on reasonable request. References 1. Xie, G.D.; Zhang, C.X.; Zhang, L.M.; Chen, W.H.; Li, S.M. Improvement of the ecosystem service value method based on unit area value equivalent factor. [J]. Journal of Natural Resources . 2015, 30 ,1243–1254. 2. Yang, R.F.; Ren, F.; Xu, W. X.; Ma, X.Y.; Zhang, H.W.; He, W.W. China's ecosystem service value in 1992–2018: Pattern and anthropogenic driving factors detection using Bayesian spatiotemporal hierarchy model. [J]. Journal of Environmental Management .2022, 302 ,114089–114089. 3. Brander, L.M.; de Groot, R.; Schaegner, J. P.; Guisado-Goni, V.; van't Hoff, V.; Solomonides, S.; McVittie, A.; Eppink, F.; Sposato, M.; Do, L.; Ghermandi, A.; Sinclair, M.; Thomas, R. Economic values for ecosystem services: A global synthesis and way forward. [J]. Ecosystem Services .2024, 66 ,101606. 4. Akhtar, M.; Zhao, Yuan.y.; Gao, G.L.; Gulzar, Q.; Hussain, A.; Samie, A. Assessment of ecosystem services value in response to prevailing and future land use/cover changes in Lahore, [J]. Regional Sustainability .2020, 1 ,37–47. 5. Li, L.; Wang, X.Y.; Luo, L.; Ji, X.Y.; Zhao, Y.; Zhao, Y.C.; Nabil B. Review of ecosystem service value assessment methods. [J]. Chinese Journal of Ecology. 2018, 37 ,1233–1245. 6. Yin, N.; Wang, S.; Liu, Y.X. Ecosystem service value assessment: Research progress and prospects. [J]. Chinese Journal of Ecology. 2021, 40 ,233–244. 7. Costanza, R.; d'Arge, R.; de Groot, R.; Farber, S.; Grasso, M.; Hannon, B.; Limburg, K.; Naeem, S.; O'Neill, R. V.; Paruelo, J.; Raskin, R.G.; Sutton, P.; Van Den Belt, M.The value of the world's ecosystem services and natural capital. Nature 1997, 387 , 253–260. 8. Zheng, L.; Liu, H.; Huang Y.F.; Yin, S.J.; Jin, G. Assessment and analysis of ecosystem services value along the Yangtze River under the background of the Yangtze River protection strategy. [J]. Journal of Geographical Sciences. 2020, 30 ,553–568. 9. Zhang, B.T.; Li, Z. X.; Feng, Q.; Lu, Z.X.; Zhang, B.J.; Cheng, W.J. Evolution of ecosystem service values in Qilian Mountains based on land-use change from 1990 to 2020༎[J]. Acta Ecologica Sinica. 2024, 44 ,4187–4202༎ 10. Li, L.; Zhao, Y.L.; Li, X.; Ni, W.K.; Zhao, K.Y.; He, Z.G.; Abuarab, M.E.; Elbeltagi, A.; Ahmed, A. Temporal Dynamics of Ecosystem Service Value in Qinghai Province (2000–2018): Trends, Drivers, and Implications. [J]. Sustainability 2025, 17 ,1458. 11. Li, Y.; Liu, J.L.; Bai, X.Y.; Feng, X.; Qiu L. Multi-scale spatial differentiation of ecosystem service value in the water conservation area of the upper Yangtze River: Pattern, Process, and Driving Forces. [J]. Acta Ecologica Sinica. 2025, 45 ,3062–3078. 12. Lan, Z.C.; Jia, L.; Cheng, Y. Ecosystem service value assessment and trade-off/synergy relationships in the Minjiang River Basin. [J]. Acta Ecologica Sinica. 2020, 40 ,3909–3920. 13. Ma, H.L. Evolution of landscape ecological risk and its relationship with terrain gradient in the Heihe River Basin in recent 40 years. MA thesis, Lanzhou Jiaotong University, Lanzhou Chins, 20210525. 14. Qiu, H.H.; Hu, B.Q.; Zhang, Z. Impacts of land use change on ecosystem service value based on SDGs report–Taking Guangxi as an example - ScienceDirect. [J]. Ecological Indicators. 2021, 133. 15. Li, G.C.; Wu, Y.; Qiu, B.; Li, Y.L.; Ning, L.L.; Wang, H.; Liu, L.; Jin, M. Study on dynamic changes in land use and ecosystem service value in the Huaihe River ecological economic belt based on multi-scenario simulations. [J]. Frontiers in Environmental Science. 2025, 13 ,1617829. 16. Yao, Z.Q.; Shi, Chen.; Huang, Y.L. Exploring the threshold of human activity impact on urban ecosystem service value: a case study of Hefei, China. [J]. Scientific Reports. 2025, 15 ,24118–24118. 17. Du, M.H.; Fu, J.X.; Guo, W.J. Spatiotemporal variation characteristics of ecosystem service value of Mountains-Rivers-Forests-Farmlands-Lakes-Grasslands in the Fenhe River Basin. [J]. Journal of Hainan Normal University (Natural Science). 2023, 36 ,80–88. 18. Wu, Y.C.; Chen, B.W.; Huang, X.J.; Wei, Z.Q. Effect of land-use change and optimization on the ecosystem service values of Jiangsu province, China. [J]. Ecological Indicators .2020,117 19. Polasky, S.; Nelson, E.; Pennington, D.; Johnson, K.A. The Impact of Land-Use Change on Ecosystem Services, Biodiversity and Returns to Landowners: A Case Study in the State of Minnesota. [J]. Environmental and Resource Economics. 2011, 48 ,219–242. 20. Shang, H.Y.; Liu, L.J. Evolution of ecosystem service value and research on coordinated development of ecology and economy in the Shiyang River Basin over the past 20 years. [J]. Ecological Science. 2024, 43 ,10–20. 21. Gao, M.M.; Yang, N.; Wang, Y.; Liu, Q.; Li, X.L.; Zhi, E.Q. Spatiotemporal variation characteristics of ecosystem service value in the Yellow River Basin. [J]. Geological Bulletin of China. 2025, 44 , 353–363. 22. Ma, C.; Wang, H.W.; Ma, X.F.; Chen, Y.; Zhou, X. Estimation of ecosystem service value in the middle reaches of the Heihe River Basin in Gaotai County, Zhangye City. [J]. Wetland Science . 2021, 19 , 762–766. Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":42972762,"visible":true,"origin":"","legend":"\u003cp\u003eSpatio-temporal distribution of land use/land cover change in the Heihe River Basin for each year.\u003c/p\u003e","description":"","filename":"image1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7866466/v1/59b10f3bbf11ec46c8c83cea.jpg"},{"id":95321533,"identity":"3828c8f6-9229-4af2-9e5b-5e530b5d3ff3","added_by":"auto","created_at":"2025-11-06 16:49:20","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":6549202,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in land use dynamic degrees for different periods in the Heihe River Basin.\u003c/p\u003e","description":"","filename":"image2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7866466/v1/b41d0c5412efef2f38fd3a0e.jpg"},{"id":95321541,"identity":"ce8d5ca8-f277-47f9-90b8-e6a087ca463b","added_by":"auto","created_at":"2025-11-06 16:49:21","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":5660927,"visible":true,"origin":"","legend":"\u003cp\u003eESV by land type and total ESV in the Heihe River Basin, 1990-2023.\u003c/p\u003e","description":"","filename":"image3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7866466/v1/75490903dd025afd17f7678f.jpg"},{"id":95321534,"identity":"5e6340d7-ed97-482b-b82d-209e901a9267","added_by":"auto","created_at":"2025-11-06 16:49:20","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":8432702,"visible":true,"origin":"","legend":"\u003cp\u003eIndividual ESV and ESV by category in the Heihe River Basin, 1990-2023.\u003c/p\u003e","description":"","filename":"image4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7866466/v1/3186a90693e0ceb1b218854f.jpg"},{"id":95321545,"identity":"261badcb-97e4-4a84-864a-884fae621d74","added_by":"auto","created_at":"2025-11-06 16:49:21","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":14216953,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of ESV in the Heihe River Basin, 1990-2023.\u003c/p\u003e","description":"","filename":"image5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7866466/v1/d4bb4ecd4243ec733c0b9e3c.jpg"},{"id":95321550,"identity":"438ad4bd-ba1f-47dd-a735-205256c2a1c8","added_by":"auto","created_at":"2025-11-06 16:49:21","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":49190692,"visible":true,"origin":"","legend":"\u003cp\u003eLocation and scope of the study area.\u003c/p\u003e","description":"","filename":"image6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7866466/v1/fa977a28a07d61c9ddeac22f.jpg"},{"id":108182396,"identity":"513d6f61-b75f-4487-93e1-845d0056f993","added_by":"auto","created_at":"2026-04-30 08:59:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":127472519,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7866466/v1/c2f5ae5c-3e46-400c-927b-4e47059417d6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Coupling of Human-Water Interactions Governs Ecosystem Service Values in China's Inland River Basins: A Case Study from the Heihe River Basin","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eEcosystem services refer to the life-supporting products and benefits directly or indirectly derived from the structure, processes, and functions of ecosystems\u003csup\u003e[1]\u003c/sup\u003e. The ecosystem service value (ESV) quantifies these services in monetary terms. This enables the quantitative assessment of an ecosystem's potential service capacity and the economic value provided by ecosystem services to human society, reflecting the contributions to human well-being\u003csup\u003e[2]\u003c/sup\u003e. Therefore, ESV assessment has become a vital tool for measuring the impact of human activities on natural capital and for balancing development and conservation objectives. Land is a crucial carrier for various ecosystems on Earth. Land use/land cover change (LUCC) causes alterations in ecosystem types, area, and spatial patterns, subsequently affecting ecosystem service functions and their value. In recent decades, global population growth, accompanied by rapid urbanization and cropland expansion, has led to the degradation of natural ecosystems and the loss of associated services, particularly in grasslands, forests, and wetlands\u003csup\u003e[3]\u003c/sup\u003e. To effectively protect ecosystems and enhance their service provision, it is essential to investigate the mechanisms driving the ESV response to land use changes and identify driving patterns.\u003c/p\u003e\u003cp\u003eTo date, domestic and international scholars have extensively explored ESV research at the global, national, and watershed/regional scales. Valuation methods such as the equivalent factor method (based on ESV per unit area) and the functional value method (based on the price per unit service function) have been used to explain the service value characteristics of different ecosystems in various regions\u003csup\u003e[4\u0026ndash;6]\u003c/sup\u003e. Presently, economic valuation primarily follows the ESV assessment model established by Costanza et al. \u003csup\u003e[7]\u003c/sup\u003e. For example, Liang Zheng et al. \u003csup\u003e[8]\u003c/sup\u003e used Costanza's method to estimate ten ESVs within 1km and 2km ranges of the Yangtze River Basin in 2017. To adapt the analysis to China's specific conditions, Xie Gaodi et al. \u003csup\u003e[1]\u003c/sup\u003e developed a unit area ESV table based on this model, which has been widely applied. For instance, Zhang Baiting et al. \u003csup\u003e[9]\u003c/sup\u003e analyzed the spatio-temporal evolution of ESV in the Qilian Mountains region from 1990 to 2020 using correction coefficients, laying a foundation for local land management and ecological restoration policies. Li Lan et al. \u003csup\u003e[10]\u003c/sup\u003e combined land use transfer matrices (2000\u0026ndash;2018) with the equivalent factor method to assess ESV changes and their sensitivity in Qinghai Province over nearly 20 years, deeply exploring the underlying driving forces, management implications, and influencing factors. In watershed ESV research, Li Yue et al. \u003csup\u003e[11]\u003c/sup\u003e comprehensively used methods such as the equivalent factor method, sensitivity analysis, spatial autocorrelation analysis, optimal-parameter-based geographical detector, and spatial regression models to reveal and understand the spatial differentiation and driving mechanisms of ESV in multi-scale contexts in the Mawei River Basin. Lan Zicheng et al. \u003csup\u003e[12]\u003c/sup\u003e assessed ESV in the Minjiang River Basin, analyzing its change trends and trade-off/synergy relationships. Current research on watershed ESV is relatively scarce, and studies on the Heihe River Basin are outdated. Therefore, this study investigates LUCC changes and ESV changes in the Heihe River Basin from 1990 to 2023.\u003c/p\u003e\u003cp\u003eThe Heihe River Basin is the second-largest inland basin in northwest China. Its unique natural environment, locational conditions, and economic development model have led to severe conflicts over water and soil resources, increasingly serious land degradation, and a series of ecological problems. This study aims to systematically analyze the spatio-temporal patterns of LUCC changes within the basin, scientifically evaluate the gains and losses in ESV accompanying LUCC, and reveal the relationship between ESV and LUCC, thus providing decision-making support for achieving sustainable socio-economic development in the basin and establishing a solid scientific foundation for sound policy systems, such as watershed ecological compensation.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eLUCC from 1990 to 2023\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAfter reclassifying the land use types in the Heihe River Basin, the area and spatial distribution of each land use type in 1990, 2000, 2010, and 2023 were determined (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.). The dominant land use types in the basin are desert, bare land, and grassland. Desert area was the largest, accounting for 56.99% in 2010 before declining to 50.78% in 2023 after ecological restoration, reflecting the process of desertification and control in arid regions. Bare land area increased continuously, from 15.81% in 1990 to 17.57% in 2023, closely related to the combined effects of surface vegetation destruction and wind erosion. As an ecological transition zone, grassland area showed a \"decline\u0026ndash;recovery\" pattern, accounting for 21.70% in 1990, decreasing to 17.22% in 2010 due to overgrazing and reclamation, and recovering to 21.32% after 2010 with the implementation of the \"Cropland-to-Grassland Conversion Project\", though still not fully restored to the initial level. Construction land area increased significantly from 1990 to 2023. Water area decreased from 269,300 hectares in 1990 to 250,800 hectares in 2010 and then increased to 343,900 hectares in 2023. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. reveals a significant north\u0026ndash;south gradient: in the northern Alxa Plateau, influenced by an arid climate and the Mongolian high-pressure system, desert and bare land cover over 80%, forming a concentrated area of sandy land centered on the Badain Jaran Desert. The southern Qilian Mountains\u0026ndash;Hexi Corridor transition zone, influenced by mountain precipitation and oasis agriculture, has a relatively high proportion of grassland, forming a belt-like oasis ecosystem along the main stream of the Heihe River. This differentiation essentially results from the combined effects of precipitation and human activity intensity.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe land use dynamic degree changes in the Heihe River Basin from 1990 to 2023 are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The land use dynamic degree is a key indicator measuring regional land development intensity, the extent of land use change, and rate differences. During 1990\u0026ndash;2023, the comprehensive land use dynamic degree in the Heihe River Basin showed a clear upward trajectory. From 1990 to 2000, the comprehensive land use dynamic degree was 0.02%, rising to 0.49% in 2010\u0026ndash;2023. This trend demonstrates that after implementing ecological restoration projects, the land use pattern entered a more active phase of change, with significantly increased intensity. The single dynamic degree for construction land showed continuous growth, closely reflecting the acceleration of urbanization and industrialization in the basin, with an expanding urban scale. The dynamic degree for cropland showed an initial increase, followed by a decrease: 1.68% during 2000\u0026ndash;2010 (relatively rapid growth), but \u0026minus;\u0026thinsp;0.13% during 2010\u0026ndash;2023 (slight decrease). This shift stems from two aspects: cropland protection policies promoting an initial increase and, later, accelerated urban expansion occupying some cropland, leading to a decline, reflecting the tension between cropland protection and urban development needs. The dynamic degree of forestland showed little overall change, indicating insignificant but slightly declining trends. Forest resources face significant pressure, whether from excessive human development or environmental changes, necessitating strengthened protection measures. The dynamic degrees for grassland and water both showed significant recovery trends after 2010. The single land use dynamic degrees for grassland and water increased by 1.83% and 2.27%, respectively. These positive changes have benefited from ecological restoration projects, such as \"Returning Cropland to Grassland\" and wetland protection, which specifically targeted the restoration and protection of grassland and aquatic ecosystems, leading to more dynamic changes and enhanced ecological functions, representing important achievements in the basin's ecological construction. Overall, the land use pattern of the Heihe River Basin underwent complex but traceable changes from 1990 to 2023 under the intertwined influence of human activities and ecological engineering.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAnalysis of Spatio-Temporal Variation in Ecosystem Service Value\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eAnalysis of Temporal Variation in ESV\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe ESV of the Heihe River Basin experienced \"declining\u0026ndash;rising\" fluctuations from 1990 to 2023, increasing from CNY 144.09\u0026nbsp;billion to CNY 150.44\u0026nbsp;billion, a growth of 4.41% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.). From 1990 to 2010, ESV decreased continuously from CNY 144.086\u0026nbsp;billion to CNY 128.64\u0026nbsp;billion, a decrease of 10.72%. From a land use perspective, the reduction in grassland area was the dominant driving factor in reducing the overall ESV. The period 2010\u0026ndash;2023 was a phase of ESV recovery, increasing from CNY 128.64\u0026nbsp;billion to CNY 150.44\u0026nbsp;billion, a growth of 16.95%. During this stage, grassland and water became the core contributors to ESV growth, with ecological contribution rates of 51.79% and 38.92%, respectively. This indicates that the effectiveness of ecological restoration projects became apparent, strengthening the ecological functions of grassland and water and driving rapid ESV recovery. Among land types, grassland exhibited the most significant fluctuation in ESV. From 1990 to 2010, influenced by excessive human use, grassland ESV declined from CNY 72.94\u0026nbsp;billion to CNY 57.91\u0026nbsp;billion, a decrease of 20.60%. From 2010 to 2023, grassland ESV recovered to CNY 71.68\u0026nbsp;billion. However, grassland ESV in 2023 was still 1.72% lower than in 1990, indicating that, despite restoration, the accumulated effects of earlier damage persist, and recovery is a long-term process requiring continued protection and restoration efforts. Although cropland's baseline ESV contribution was not high, it showed a stable and continuous growth trend, increasing by 21.05%\u0026mdash;from CNY 3.33\u0026nbsp;billion in 1990 to CNY 4.03\u0026nbsp;billion in 2023. Water ESV first decreased and then increased, declining from CNY 29.94\u0026nbsp;billion in 1990 to CNY 27.88\u0026nbsp;billion in 2010 (a decrease of 6.87%) and then growing rapidly from 2010 to 2023, increasing from CNY 27.88\u0026nbsp;billion to CNY 38.23\u0026nbsp;billion (a growth of 37.13%). Overall, water body ESV increased by 27.71% from 1990 to 2023.\u003c/p\u003e\u003cp\u003eIn summary, ESV changes in the Heihe River Basin from 1990 to 2023 resulted from the combined effects of land use transformation and ecological engineering interventions. The fluctuation of grassland and the growth of cropland and water reflect the trajectory of the basin's ecosystem from being under pressure to undergoing restoration. Future efforts should focus on the long-term recovery of grasslands and consolidating the achievements in cropland and water ecological construction, optimizing land use structure, and intensifying ecological restoration to continuously enhance the ESV of the Heihe River Basin and ensure regional ecological security and sustainable development.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eChanges across different ESV categories varied in the Heihe River Basin from 1990 to 2023 Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e., Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). From 1990 to 2023, the values of provisioning services, regulating services, supporting services, and cultural services all showed fluctuating upward trends. They are ranked in the following order in terms of value proportion: regulating services\u0026thinsp;\u0026gt;\u0026thinsp;supporting services\u0026thinsp;\u0026gt;\u0026thinsp;provisioning services\u0026thinsp;\u0026gt;\u0026thinsp;cultural services. Regulating services accounted for about 68% and supporting services for about 20%. Both had significantly higher value than the other two service types, dominating the basin's ESV, primarily due to their higher stability. Provisioning and cultural services had relatively low ESVs, only about 12%, mainly because their stability is lower than that of regulating and supporting services. Among individual ESV types, hydrological regulation within regulating services had the largest ESV proportion throughout the study period, with an ecological contribution rate as high as 78.88%, although with large fluctuations. From 1990 to 2010, hydrological regulation\u0026rsquo;s ESV decreased from CNY 43.15\u0026nbsp;billion to CNY 38.99\u0026nbsp;billion and then rebounded to CNY 48.58\u0026nbsp;billion in 2023. Despite fluctuating proportions over different periods, its dominant position remained stable in the long term. This stems from the scarcity of water resources in the basin. Hydrological regulation, associated with wetland and water ecosystems, plays a key role in water conservation, runoff regulation, and drought mitigation, forming the cornerstone of basin ecological security. Climate regulation had the second-highest ESV proportion, decreasing from CNY 27.95\u0026nbsp;billion in 1990 to CNY 24.01\u0026nbsp;billion in 2010 and then rebounding to CNY 27.71\u0026nbsp;billion in 2023. Its ecological contribution rate over 1990\u0026ndash;2023 was 3.52%; during 2000\u0026ndash;2010, its contribution rate reached 25.99%, becoming the highest contributing individual service in that period. During this stage, enhanced climate regulation capacity resulted from vegetation recovery and water area changes, reflecting the ecosystem's phased response to climate change and highlighting the supporting role of climate regulation services in ESV during specific periods. Food production, raw material production, water supply, and nutrient cycling maintenance had low ESV proportions and relatively small ecological contribution rates.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eESV and ecological contribution rate in the Heihe River Basin, 1990\u0026ndash;2023.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eEcosystem Service Value (Billion CNY)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eEcological Contribution Rate (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1990\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2000\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2010\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1990\u0026ndash;2000\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2000\u0026ndash;2010\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2010\u0026ndash;2023\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1990\u0026ndash;2023\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCropland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e14.32%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.29%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.26%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5.92%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eForestland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.67%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.58%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5.35%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGrassland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e72.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e72.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e71.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41.58%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e81.11%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e51.79%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e10.59%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e38.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e38.66%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.76%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e38.92%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e70.12%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDesert\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.72%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.84%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7.16%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e7.19%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBare land\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.04%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.13%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.28%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.83%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFood production\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.61%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.06%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.36%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2.43%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaterial production\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.01%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.28%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.64%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.37%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater supply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.51%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.18%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e7.77%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGas regulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.71%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.84%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.26%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClimate regulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e27.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16.67%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e25.99%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e16.96%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.52%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnvironmental purification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.31%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.09%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e5.39%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.09%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHydrological regulation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e42.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e48.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e48.02%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e25.52%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e43.98%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e78.88%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSoil conservation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.41%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10.54%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7.22%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.10%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNutrient cycling maintenance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.05%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.75%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.53%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.11%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiodiversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.11%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10.84%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e8.52%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2.83%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAesthetic landscape\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.59%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.91%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.31%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2.65%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e144.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e143.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e128.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e150.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAnalysis of Spatial Variation in ESV\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe GIS grid scale method, based on grid point units, serves as a data carrier and basic evaluation unit for indicator factors. It can intuitively reflect the spatial distribution of ESV for description and visualization. When applying this method for spatial simulation of ESV in the Heihe River Basin, a 5km\u0026times;5km grid sample was established in ArcGIS. The ESV of different land use types was superimposed and calculated within each grid cell to obtain the ESV per grid. Natural break classification (Jenks) was used for interpolation analysis. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e., the ESV of the Heihe River Basin from 1990 to 2023 exhibited relatively stable spatial characteristics in the midstream and significant fluctuations in the upstream and downstream. The spatial distribution of ESV was strongly correlated with the spatial land use pattern. Medium\u0026ndash;high-ESV areas were mainly distributed in Qilian County and Sunan County in the upstream, as well as regions traversed by water bodies. The upstream area is dominated by forests, grasslands, and wetlands, with strong ecological functions such as water conservation and biodiversity maintenance, and water bodies have higher ESV than other land types. Low-value areas were concentrated downstream in Ejina Banner and Jinta County, where sandy land, gobi, and bare land predominate, resulting in lower ESV. From 1990 to 2000, the mid-upper basin formed a continuous high-value zone composed of forests, wetlands, and oases, while downstream desert was mainly low-value, with natural ecosystems dominating the service value pattern. By 2010, land reclamation, wetland shrinkage, and water resource imbalances had exacerbated the fragmentation of high-value areas, leading to continuous degradation of ecosystem service functions. By 2023, ecological regulation policies had driven the partial recovery of downstream oases and midstream wetlands. However, water resource fluctuations further intensified the fragmentation of high-value areas. Overall, the spatial evolution exhibited a phased pattern of \"natural dominance\u0026ndash;interference contraction\u0026ndash;degraded fragmentation\u0026ndash;local recovery\", with the core logic being the interactive coupling of the \"human\u0026ndash;water\u0026ndash;ecosystem\" system.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eResearch indicates that land use change is a primary driver of ESV gains and losses, significantly influencing its spatial variation. This finding aligns with the research of Changyan Wu et al.\u003csup\u003e[18]\u003c/sup\u003e on the impact of LUCC and optimization on ESV in Jiangsu Province. Alterations in land use exert varying degrees of impact on the structure and function of ecosystems, consequently affecting the diverse services ecosystems provide for humans\u0026rsquo; societal development and well-being. This ultimately leads to changes in ESV, with the effects being more pronounced at the regional scale\u003csup\u003e[19]\u003c/sup\u003e. The analysis of LUCC and ESV variation within the Heihe River Basin from 1990 to 2023 revealed that LUCC is the principal factor driving ESV changes, exerting substantial influence on its increase or decrease. This conclusion is consistent with the research findings of Zhang Baiting et al.\u003csup\u003e[9]\u003c/sup\u003e on ESV in the Qilian Mountain region. During the study period, the ESV of the Heihe River Basin initially declined before rising, increasing from CNY 144.089\u0026nbsp;billion to CNY 150.443\u0026nbsp;billion, a rise of CNY 6.354\u0026nbsp;billion. This trajectory differs from the findings of Shang Haiyang et al.\u003csup\u003e[20]\u003c/sup\u003e regarding ESV in the Shiyang River Basin. The discrepancy is primarily attributable to early ecological degradation in the Heihe Basin caused by urbanization and cropland expansion. Subsequently, ESV increased due to the successful intervention of ecological restoration projects, such as grazing exclusion and grassland recovery and wetland conservation. This pattern reflects the typical trajectory of ESV recovery in the northwest arid region of China. Changes in the area of grassland and water were the largest contributing factors to ESV variation in the Heihe River Basin. This conclusion contrasts with the findings of Gao Mengmeng et al.\u003csup\u003e[21]\u003c/sup\u003e for the Yellow River Basin, where cropland and forestland changes were dominant. This difference stems from the Heihe Basin's primary landscape being desert and grassland, whereas forest and cropland cover a larger proportion in the Yellow River Basin. The reduction in the area of forestland, grassland, and desert land led to a decrease in the service value of gas regulation and climate regulation within the Heihe River Basin ecosystem. Regulating services constitute the primary ecosystem service function in the Heihe Basin, with climate regulation and hydrological regulation representing the largest proportions. This result is consistent with the research of Ma Chao et al.\u003csup\u003e[22]\u003c/sup\u003e on ESV in the middle reaches of the Heihe River within Gaotai County, Zhangye City. The changes in ESV within the Heihe River Basin confirm the core principle of \"water determines ecology\", which is characteristic of inland river systems in arid regions. Its initial decline\u0026ndash;recovery pattern and responsiveness to ecological policies, coupled with a structural contribution dominated by grassland and water and distinct spatial differentiation, collectively form a distinctive model differentiating the Heihe River Basin from other river basins. Fundamentally, the \u0026ldquo;human\u0026ndash;water\u0026ndash;ecosystem\u0026rdquo; coupling mechanism revealed here establishes a distinct management framework for arid basins, where water-centric strategies must drive ecosystem policies.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBased on land use data and the equivalent factor method per unit area, this study analyzed land use structure changes and the spatio-temporal evolution of ESV in the Heihe River Basin from 1990 to 2023. The main conclusions are as follows:\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eFrom 1990 to 2023, grassland, desert, and bare land were the dominant land use types in the Heihe River Basin. Construction land expanded continuously due to urbanization. Forest land area decreased, and cultivated land and desert area showed an initial increase followed by a decrease. Grassland and water underwent phased recovery through ecological restoration, forming a spatial gradient differentiating between downstream desertification and the upstream Qilian Mountains\u0026ndash;oasis belt.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe total ESV of the Heihe River Basin increased from CNY 144.086\u0026nbsp;billion in 1990 to CNY 150.443\u0026nbsp;billion in 2023, exhibiting a \"declining\u0026ndash;rising\" trend. Grassland and water bodies were the primary contributors to the overall ESV change, while cultivated land and water bodies showed stable ESV growth. The ESV structure was dominated by regulating services, with hydrological regulation contributing the most, highlighting the central role of water resources in this arid inland river basin.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eESV showed significant spatial heterogeneity from 1990 to 2023, characterized by an \"upstream high\u0026ndash;downstream low\" pattern: high-value areas were concentrated upstream in the forest, grassland, and water-body-dense regions of Qilian County and Sunan County; low-value areas were distributed downstream in Ejina Banner and Jinta County, where desert and bare land accounted for more than 80%. The spatial evolution underwent a phased process of \"natural continuity\u0026ndash;interference fragmentation\u0026ndash;local recovery\".\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eAn Overview of the Study Area\u003c/h2\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003eThe Heihe River originates from the northern foothills of the Qilian Mountains, flowing through Qinghai Province, Gansu Province, and Inner Mongolia Autonomous Region, and finally draining into Juyan Lake. The section above Yingluoxia is the upstream, including Qilian County in Qinghai Province. The section from Yingluoxia to Zhengyixia is the midstream, encompassing Sunan Yugur Autonomous County, Shandan County, Minle County, Ganzhou District, Gaotai County, Linze County, Jiayuguan City, and Suzhou District. The section below Zhengyixia is the downstream, including Ejina Banner and Jinta County\u003csup\u003e[13]\u003c/sup\u003e. This study takes the boundaries of these 11 counties/districts as the research area (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e.). Located between 97\u0026deg;E\u0026ndash;103\u0026deg;E and 38\u0026deg;N\u0026ndash;43\u0026deg;N, the basin is approximately 928 km long, with a total area of about 15.7067\u0026nbsp;million hectares. Precipitation decreases from upstream to downstream, with an average annual precipitation of 1719.80 mm and evaporation as high as 2000\u0026ndash;3000 mm. The Heihe River Basin features coexisting cold and arid zones. The upstream Qilian Mountain area has high mountains and deep valleys with large elevation differences, where glaciers and permafrost are widely distributed, serving as the main source of Heihe River runoff. The midstream Hexi Corridor consists of contiguous oases formed by alluvial plains, relying on river water for irrigated agriculture but facing problems of water resource over-extraction. The downstream Alxa High Plain is dominated by the Gobi Desert, with Juyan Lake as the terminal lake, maintained by ecological water supplementation and surrounded by ecologically sensitive wetlands.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003eData Sources\u003c/h2\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003eThe DEM data used in this study were sourced from the National Cryosphere Desert Data Center/National Service Center for Special Environmental Observation Stations (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncdc.ac.cn\u003c/span\u003e\u003c/span\u003e). Land use data for 1990, 2000, 2010, and 2023 were obtained from the Resources and Environmental Sciences Data Platform, Chinese Academy of Sciences (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.resdc.cn\u003c/span\u003e\u003c/span\u003e). These 30 m resolution datasets were generated through systematic manual visual interpretation of Landsat TM/ETM imagery as the primary data source, with interpretation accuracy exceeding 90%, validated through random sampling with \u0026gt;\u0026thinsp;1,000 reference points. Referring to the National Land Use Status Classification Standard (GB/T21010-2017), the land use characteristics of the Heihe River Basin, and Xie Gaodi et al.'s (2015) ecosystem classification system, land use types were reclassified into 7 categories using ArcGIS 10.8: cropland, forestland, grassland, water, construction land, desert, and bare land. Using statistical yearbooks from 1991 to 2024, including the China Statistical Yearbook, Gansu Statistical Yearbook (renamed Gansu Development Yearbook after 2010), Qinghai Statistical Yearbook, Inner Mongolia Yearbook, and county/city/district statistical yearbooks, the sown area and grain yields of three main food crops (wheat, corn, and soybeans) in the study area were obtained. The average grain yield per unit area was calculated at 26746.04 kg/ha. Data on the net profit from grain production came from the National Compilation of Cost-Benefit Data for Agricultural Products, giving an average grain price of 2.05 CNY/kg.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003eLUCC Analysis Method\u003c/h2\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003eThe land use dynamic degree indicates the quantitative change in land types over a period; it can be divided into the single land use dynamic degree and the comprehensive land use dynamic degree. The single land use dynamic degree is the rate of change in a specific land type within a region over a given period. The comprehensive land use dynamic degree indicates the overall rate of LUCC in a region\u003csup\u003e[14]\u003c/sup\u003e. The formulas are as follows:\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equa\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}V=\\left(\\frac{{U}_{j}-{U}_{i}}{{U}_{i}}\\right)\\times\\:\\frac{1}{T}\\times\\:100\\% \\left(1\\right)\\end{array}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equb\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}LC=\\frac{\\sum\\:_{k=1}^{n}\\varDelta\\:{LU}_{k-g}}{2\\sum\\:_{k=1}^{n}{LU}_{k}}\\times\\:\\frac{1}{T}\\times\\:100\\% \\left(2\\right)\\end{array}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:V\\)\u003c/span\u003e\u003c/span\u003e is the single land use dynamic degree (%); \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{U}_{i}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{U}_{j}\\)\u003c/span\u003e\u003c/span\u003e are the areas (ha) of a specific land use type at the beginning and end of the study period, respectively; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:LC\\)\u003c/span\u003e\u003c/span\u003e is the comprehensive land use dynamic degree (༅); \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:L{U}_{k}\\)\u003c/span\u003e\u003c/span\u003e is the area (ha) of the k-th land use type at the beginning of the study period; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varDelta\\:{LU}_{k-g}\\)\u003c/span\u003e\u003c/span\u003e is the absolute value (ha) of the area converted from the k-th land type to the g-th land type during the study period; and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:T\\)\u003c/span\u003e\u003c/span\u003e is the time interval (year) of the land use data.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003eEcosystem Service Value Accounting\u003c/h2\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003eThis study primarily refers to Xie Gaodi et al.'s equivalent values for ecosystem services per unit area in China\u003csup\u003e[1]\u003c/sup\u003e and previous research results\u003csup\u003e[15\u0026ndash;16]\u003c/sup\u003e, combined with the actual land use situation in the Heihe River Basin. Desert and bare land were assigned the values for desert and bare land from the Chinese ESV equivalent table, respectively. Cropland was assigned the average value for dryland and paddy land, forestland was assigned the average value for coniferous, broadleaf, and shrub forests; grassland was assigned the average value for grassland, shrub-grass, and meadow; and water was assigned the average value for wetlands, water systems, and glaciers and snow cover. The value coefficient for construction land was assumed to be 0. This resulted in the final ESV equivalent table per unit area for the Heihe River Basin (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Furthermore, considering the status of socio-economic development in the study area, the economic value created by grain production per unit area was used for correction. Based on the principle that \"the economic value coefficient of one standard equivalent of ecosystem services is 1/7 of the economic value of food production per unit area of farmland\", the formula is\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equc\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}{E}_{a}=\\frac{1}{7}\\times\\:\\sum\\:_{i=1}^{n}\\frac{{m}_{i}{P}_{i}{q}_{i}}{M}\\times\\:\\frac{R}{{R}_{0}} \\left(3\\right)\\end{array}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{a}\\)\u003c/span\u003e\u003c/span\u003e is the economic value of one standard equivalent of ecosystem services (CNY/ha); i is one of the main crop types; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{m}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the area of the i-th grain crop (ha); \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{P}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the calculated average price of the i-th grain crop (CNY/kg); \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{q}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the yield per unit area of the i-th grain crop (kg/ha); \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:M\\)\u003c/span\u003e\u003c/span\u003e is the total area of grain crops (ha); \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:n\\)\u003c/span\u003e\u003c/span\u003e is the number of grain crop types; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:R\\)\u003c/span\u003e\u003c/span\u003e is the average yield per unit area of grain crops in the study area (kg/ha); and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{R}_{0}\\)\u003c/span\u003e\u003c/span\u003e is the national average yield per unit area of grain crops (kg/ha). To enhance the comparability of ESV across years, the average value over the study periods was used as the standard. The standard equivalent coefficient for the Heihe River Basin from 1990 to 2023 was 1775 CNY/ha.\u003c/p\u003e\n\u003cp\u003eReferring to previous studies, based on the Heihe River Basin unit area ESV equivalent table and the value of one standard unit ESV equivalent factor, the ESV coefficients for different land use types in the Heihe River Basin were calculated using the following formulas (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), which largely reflect the actual situation in the basin. The formulas are\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equd\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}V{C}_{k}=V\\times\\:{C}_{k} \\left(4\\right)\\end{array}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Eque\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Eque\" class=\"mathdisplay\"\u003e$$\\:\\begin{array}{c}ESV=\\sum\\:_{k=1}^{n}{A}_{k}V{C}_{k} \\left(5\\right)\\end{array}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:V{C}_{k}\\)\u003c/span\u003e\u003c/span\u003e is the equivalent coefficient of ESV per unit area for the k-th land use type (CNY/ha); \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{k}\\)\u003c/span\u003e\u003c/span\u003e is the ESV coefficient (equivalent factor) per unit area for the k-th land use type; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:V\\)\u003c/span\u003e\u003c/span\u003e is the monetary value of a single ESV equivalent factor in the Heihe River Basin; ESV is the total ESV of the Heihe River Basin (CNY); and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{A}_{k}\\)\u003c/span\u003e\u003c/span\u003e is the area of the k-th land use type (ha).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eEcosystem service value (ESV) per unit area (CNY\u0026middot;hm⁻\u0026sup2;\u0026middot;yr⁻\u0026sup1;) for different land use types in the Heihe River Basin.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eEcosystem Service Type\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCropland\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eForestland\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eGrassland\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eWater\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDesert\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eBare Land\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFirst category\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSecond category\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eeq.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003evalue\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eeq.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003evalue\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eeq.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003evalue\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eeq.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003evalue\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eeq.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003evalue\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eeq.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003evalue\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eProvisioning Services\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFood production\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1508.77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e408.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e408.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e775.09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaterial production\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e710.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e958.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e603.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e431.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWater supply\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e497.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e337.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7715.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eRegulating Services\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGas regulation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1189.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3124.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2147.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1686.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e195.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35.50\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eClimate regulation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e639.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9354.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5662.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3804.47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e177.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEnvironmental purification\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e177.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2786.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1863.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5508.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e550.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e177.50\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHydrological regulation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e479.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6762.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4153.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e79047.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e372.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53.25\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eSupporting Services\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSoil conservation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1828.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3798.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2609.29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1917.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e230.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35.50\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNutrient cycling maintenance\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e284.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e195.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e147.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBiodiversity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e230.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3461.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2378.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6171.18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35.50\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCultural Services\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAesthetic landscape\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e106.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1526.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1047.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3970.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e88.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.75\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7117.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32962.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21406.82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e62.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e111175.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1952.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e355.01\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003eEcological Contribution Rate\u003c/h2\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003eThe ecological contribution rate is the percentage of ESV change for a specific land type within a given period relative to the total ESV change\u003csup\u003e[17]\u003c/sup\u003e, and it is used to identify the main contributing factors affecting ESV change. The formula is\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Equf\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equf\" class=\"mathdisplay\"\u003e$$\\:{C}_{i}=\\frac{\\left|\\varDelta\\:{ESV}_{i}\\right|}{\\sum\\:_{i=1}^{n}\\left|\\varDelta\\:{ESV}_{i}\\right|}\\times\\:100\\%$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the ecological contribution rate (%) of the i-th land use type and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varDelta\\:{ESV}_{i}\\)\u003c/span\u003e\u003c/span\u003e is the change in ESV of the i-th land use type (CNY).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, R.Y. and J.Y.; Methodology, R.Y.; Software, R.Y.; Validation, R.Y., J.Y., J.S., H.L. and J.Z.; Formal Analysis, R.Y. and J.Y.; Investigation, R.Y. and J.Y.; Resources, J.Y. and J.S.; Data Curation, R.Y.; Writing – Original Draft Preparation, R.Y.; Writing – Review \u0026amp; Editing, R.Y. and J.Y.; Visualization, R.Y.; Supervision, R.Y. and J.Y.; Project Administration, R.Y.; Funding Acqui-sition, J.Y. and J.S. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was funded by the Natural Science Foundation Project of Gansu Province (23JRRA1413); Dingxi Science and Technology Plan Project (DX2024AZ03).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eNo conflict of interest exists in this submitted manuscript, and this manuscript is approved by all authors for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data and materials used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e1. Xie, G.D.; Zhang, C.X.; Zhang, L.M.; Chen, W.H.; Li, S.M. Improvement of the ecosystem service value method based on unit area value equivalent factor. [J]. \u003cem\u003eJournal of Natural Resources\u003c/em\u003e. 2015, \u003cem\u003e30\u003c/em\u003e,1243\u0026ndash;1254.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e2. Yang, R.F.; Ren, F.; Xu, W. X.; Ma, X.Y.; Zhang, H.W.; He, W.W. China's ecosystem service value in 1992\u0026ndash;2018: Pattern and anthropogenic driving factors detection using Bayesian spatiotemporal hierarchy model. [J]. \u003cem\u003eJournal of Environmental Management\u003c/em\u003e.2022,\u003cem\u003e302\u003c/em\u003e,114089\u0026ndash;114089.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e3. Brander, L.M.; de Groot, R.; Schaegner, J. P.; Guisado-Goni, V.; van't Hoff, V.; Solomonides, S.; McVittie, A.; Eppink, F.; Sposato, M.; Do, L.; Ghermandi, A.; Sinclair, M.; Thomas, R. Economic values for ecosystem services: A global synthesis and way forward. [J]. \u003cem\u003eEcosystem Services\u003c/em\u003e.2024,\u003cem\u003e66\u003c/em\u003e,101606.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e4. Akhtar, M.; Zhao, Yuan.y.; Gao, G.L.; Gulzar, Q.; Hussain, A.; Samie, A. Assessment of ecosystem services value in response to prevailing and future land use/cover changes in Lahore, [J]. \u003cem\u003eRegional Sustainability\u003c/em\u003e.2020,\u003cem\u003e1\u003c/em\u003e,37\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e5. Li, L.; Wang, X.Y.; Luo, L.; Ji, X.Y.; Zhao, Y.; Zhao, Y.C.; Nabil B. Review of ecosystem service value assessment methods. [J]. \u003cem\u003eChinese Journal of Ecology.\u003c/em\u003e 2018, \u003cem\u003e37\u003c/em\u003e,1233\u0026ndash;1245.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e6. Yin, N.; Wang, S.; Liu, Y.X. Ecosystem service value assessment: Research progress and prospects. [J]. \u003cem\u003eChinese Journal of Ecology.\u003c/em\u003e 2021, \u003cem\u003e40\u003c/em\u003e,233\u0026ndash;244.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e7. Costanza, R.; d'Arge, R.; de Groot, R.; Farber, S.; Grasso, M.; Hannon, B.; Limburg, K.; Naeem, S.; O'Neill, R. V.; Paruelo, J.; Raskin, R.G.; Sutton, P.; Van Den Belt, M.The value of the world's ecosystem services and natural capital. \u003cem\u003eNature\u003c/em\u003e 1997,\u003cem\u003e387\u003c/em\u003e, 253\u0026ndash;260.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e8. Zheng, L.; Liu, H.; Huang Y.F.; Yin, S.J.; Jin, G. Assessment and analysis of ecosystem services value along the Yangtze River under the background of the Yangtze River protection strategy. [J]. \u003cem\u003eJournal of Geographical Sciences.\u003c/em\u003e2020, \u003cem\u003e30\u003c/em\u003e,553\u0026ndash;568.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e9. Zhang, B.T.; Li, Z. X.; Feng, Q.; Lu, Z.X.; Zhang, B.J.; Cheng, W.J. Evolution of ecosystem service values in Qilian Mountains based on land-use change from 1990 to 2020༎[J]. \u003cem\u003eActa Ecologica Sinica.\u003c/em\u003e 2024,\u003cem\u003e44\u003c/em\u003e,4187\u0026ndash;4202༎\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e10. Li, L.; Zhao, Y.L.; Li, X.; Ni, W.K.; Zhao, K.Y.; He, Z.G.; Abuarab, M.E.; Elbeltagi, A.; Ahmed, A. Temporal Dynamics of Ecosystem Service Value in Qinghai Province (2000\u0026ndash;2018): Trends, Drivers, and Implications. [J]. \u003cem\u003eSustainability\u003c/em\u003e 2025,\u003cem\u003e17\u003c/em\u003e,1458.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e11. Li, Y.; Liu, J.L.; Bai, X.Y.; Feng, X.; Qiu L. Multi-scale spatial differentiation of ecosystem service value in the water conservation area of the upper Yangtze River: Pattern, Process, and Driving Forces. [J]. \u003cem\u003eActa Ecologica Sinica.\u003c/em\u003e 2025, \u003cem\u003e45\u003c/em\u003e,3062\u0026ndash;3078.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e12. Lan, Z.C.; Jia, L.; Cheng, Y. Ecosystem service value assessment and trade-off/synergy relationships in the Minjiang River Basin. [J]. \u003cem\u003eActa Ecologica Sinica.\u003c/em\u003e 2020, \u003cem\u003e40\u003c/em\u003e,3909\u0026ndash;3920.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e13. Ma, H.L. Evolution of landscape ecological risk and its relationship with terrain gradient in the Heihe River Basin in recent 40 years. MA thesis, Lanzhou Jiaotong University, Lanzhou Chins, 20210525.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e14. Qiu, H.H.; Hu, B.Q.; Zhang, Z. Impacts of land use change on ecosystem service value based on SDGs report\u0026ndash;Taking Guangxi as an example - ScienceDirect. [J]. \u003cem\u003eEcological Indicators.\u003c/em\u003e 2021, 133.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e15. Li, G.C.; Wu, Y.; Qiu, B.; Li, Y.L.; Ning, L.L.; Wang, H.; Liu, L.; Jin, M. Study on dynamic changes in land use and ecosystem service value in the Huaihe River ecological economic belt based on multi-scenario simulations. [J]. \u003cem\u003eFrontiers in Environmental Science.\u003c/em\u003e2025,\u003cem\u003e13\u003c/em\u003e,1617829.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e16. Yao, Z.Q.; Shi, Chen.; Huang, Y.L. Exploring the threshold of human activity impact on urban ecosystem service value: a case study of Hefei, China. [J]. \u003cem\u003eScientific Reports.\u003c/em\u003e 2025,\u003cem\u003e15\u003c/em\u003e,24118\u0026ndash;24118.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e17. Du, M.H.; Fu, J.X.; Guo, W.J. Spatiotemporal variation characteristics of ecosystem service value of Mountains-Rivers-Forests-Farmlands-Lakes-Grasslands in the Fenhe River Basin. [J]. \u003cem\u003eJournal of Hainan Normal University (Natural Science).\u003c/em\u003e2023, \u003cem\u003e36\u003c/em\u003e,80\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e18. Wu, Y.C.; Chen, B.W.; Huang, X.J.; Wei, Z.Q. Effect of land-use change and optimization on the ecosystem service values of Jiangsu province, China. [J]. \u003cem\u003eEcological Indicators\u003c/em\u003e.2020,117\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e19. Polasky, S.; Nelson, E.; Pennington, D.; Johnson, K.A. The Impact of Land-Use Change on Ecosystem Services, Biodiversity and Returns to Landowners: A Case Study in the State of Minnesota. [J]. \u003cem\u003eEnvironmental and Resource Economics.\u003c/em\u003e2011,\u003cem\u003e48\u003c/em\u003e,219\u0026ndash;242.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e20. Shang, H.Y.; Liu, L.J. Evolution of ecosystem service value and research on coordinated development of ecology and economy in the Shiyang River Basin over the past 20 years. [J]. \u003cem\u003eEcological Science.\u003c/em\u003e2024, \u003cem\u003e43\u003c/em\u003e,10\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e21. Gao, M.M.; Yang, N.; Wang, Y.; Liu, Q.; Li, X.L.; Zhi, E.Q. Spatiotemporal variation characteristics of ecosystem service value in the Yellow River Basin. [J]. \u003cem\u003eGeological Bulletin of China.\u003c/em\u003e 2025, \u003cem\u003e44\u003c/em\u003e, 353\u0026ndash;363.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e22. Ma, C.; Wang, H.W.; Ma, X.F.; Chen, Y.; Zhou, X. Estimation of ecosystem service value in the middle reaches of the Heihe River Basin in Gaotai County, Zhangye City. [J]. \u003cem\u003eWetland Science\u003c/em\u003e. 2021, \u003cem\u003e19\u003c/em\u003e, 762\u0026ndash;766.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"land use/land cover change, ecosystem service value, Heihe River Basin, spatio-temporal variation","lastPublishedDoi":"10.21203/rs.3.rs-7866466/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7866466/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe spatio-temporal evolution of ecosystem service value (ESV) in inland watersheds is governed by the dynamic interplay of human and water systems, a process primarily mediated by land use/cover change (LUCC); investigating this process is therefore vital for informing resource allocation and policy. This study analyzed LUCC and ESV dynamics over a 33-year timeframe (1990\u0026ndash;2023) in the Heihe River Basin, China, utilizing remote sensing imagery from four distinct periods, as well as the land use dynamic degree and equivalent factor methods. The results indicate that grassland, desert, and bare land are the dominant land use types, with the continuous expansion of construction land. Cropland and desert area fluctuated, forestland declined, and grassland and water recovered in phases, forming a gradient from downstream desertification to upstream oasis ecosystems. The total ESV increased from CNY 144.09\u0026nbsp;billion to CNY 150.44\u0026nbsp;billion, exhibiting a \"declining\u0026ndash;rising\" trend. Grassland and water were the primary contributors to ESV changes, while cropland and water exhibited stable growth in the ESV. Regulating services, particularly hydrological regulation, dominated the ESV structure. Significant spatial heterogeneity existed: high-value areas clustered in upstream counties (Qilian, Sunan) and were characterized by abundant forest, grassland, and water; low-value areas occurred in downstream counties (Ejina Banner, Jinta) and were dominated by desert and bare land. Spatially, the ESV evolved through phases of \"natural continuity\u0026ndash;interference fragmentation\u0026ndash;local recovery\", driven by LUCC dynamics.\u003c/p\u003e","manuscriptTitle":"The Coupling of Human-Water Interactions Governs Ecosystem Service Values in China's Inland River Basins: A Case Study from the Heihe River Basin","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-06 16:49:16","doi":"10.21203/rs.3.rs-7866466/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8464774a-2798-4cad-9a1a-f5360a65223f","owner":[],"postedDate":"November 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57274490,"name":"Biological sciences/Ecology"},{"id":57274491,"name":"Earth and environmental sciences/Ecology"},{"id":57274492,"name":"Earth and environmental sciences/Environmental sciences"},{"id":57274493,"name":"Earth and environmental sciences/Hydrology"}],"tags":[],"updatedAt":"2026-04-29T08:40:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-06 16:49:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7866466","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7866466","identity":"rs-7866466","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}