Preamble

ARID LAND GEOGRAPHY
Vol. 48 No. 6 Jun. 2025

Ecological Management Zoning in Northwest China Based on Ecosystem Service Supply-Demand Matching
LI Zhi, SU Yang, SHU Qin
(College of Economics and Management, Xinjiang Agricultural University, Urumqi 830000, Xinjiang, China)

Abstract: Accurately identifying the spatial characteristics of ecosystem service supply and demand and delineating ecological management zones are of great significance for guiding regional ecosystem management and restoration. Focusing on the overall ecosystem of Northwest China and from the perspective of coordinated water-food development, this study quantifies the spatial matching characteristics of water production, carbon sequestration, and food supply and demand from 2000 to 2020. Ecological management zones are delineated according to the surplus conditions and sustainability features of supply-demand matching. The results indicate that: (1) The spatial matching of ecosystem service supply and demand varies across Northwest China. Water and food services show fluctuating upward trends or remain stable in terms of supply and demand, while carbon sequestration service demand grows with declining supply and supply-demand ratios, leading to gradually imbalanced matching. (2) Food production services are mostly sustainable, whereas water production and carbon sequestration services tend to be unsustainable. (3) Classified management of ecological zones should balance natural ecosystems and human well-being to enhance ecosystem service supply. The findings provide scientific references for rational allocation of basic resources and precise management of ecosystem services in Northwest China.

Keywords: ecosystem services; supply-demand matching; ecological management zoning; Northwest China

1. Introduction

Ecosystem services represent the benefits humans obtain from ecosystems and provide an important foundation for social development [1]. The supply function of ecosystem services refers to the various products and services provided by ecosystems, while human consumption of these products and services during survival and development creates demand, reflecting the flow of ecosystem services from natural systems to social domains [2]. Research on ecosystem services in the supply-demand domain is crucial for achieving sustainable use of natural capital and coordinated ecosystem service supply and demand, and ecological management zoning based on supply-demand matching can provide effective references for optimizing spatial layout and improving human well-being [3]. Dynamic matching analysis can reflect the historical evolution and future states of ecosystem service supply and demand [4]. As society continues to develop, considering both the current state and future changes of ecosystem service supply-demand matching in ecological zoning can facilitate scientific management decisions.

With ongoing social development, human demand for food, water resources, and energy continues to increase, exacerbating ecosystem vulnerability and negatively impacting water, energy, and food security [5]. Further exploring the supply-demand matching relationships among water, energy, and food is beneficial for promoting coordinated regional development and management of ecosystem services [6]. Most of Northwest China lies west of the "Hu Huanyong Line," featuring vast territory, favorable light and heat resources, and abundant traditional energy reserves, but faces increasingly prominent ecological problems such as water shortages, soil erosion, population growth, and economic development [7]. Ecological space and living well-being have been severely affected. In the "Two Screens, Three Belts, One Area, and Multiple Points" strategic pattern for ecological security, Northwest China bears an important mission [8]. Currently, scholars have explored ecological management in Northwest China at provincial, municipal, and county scales [9], but few studies have examined the region as a whole. Therefore, this research focuses on the overall Northwest China region, quantifies the supply and demand of water production, carbon sequestration, and food services from 2000 to 2020, explores the evolution characteristics and matching features of ecosystem service supply and demand, and proposes corresponding policy recommendations for ecological civilization construction in Northwest China.

Research methods for ecosystem service supply-demand relationships are continuously developing and improving. Matrix and expert experience methods based on land use can quickly assess supply-demand relationships for multiple ecosystem services [10], but are not conducive to quantitative analysis and cross-regional comparison [11]. Research has shifted toward quantitative analysis, primarily using ecological process models (such as the InVEST model) to assess ecosystem service supply and statistical methods or actual consumption to calculate demand [12]. To date, no scientifically systematic method has been established for evaluating supply and demand of various services. Ecological zoning is an important basis for territorial space optimization and plays a significant role in promoting ecosystem service coordination and human well-being improvement [13]. This study employs the InVEST model to evaluate ecosystem service supply and calculates demand based on statistical methods, providing a foundation for ecological management zoning.

2. Methods

2.1 Study Area Overview

Northwest China includes Shaanxi, Gansu, Ningxia, Qinghai, and Xinjiang, comprising 51 prefecture-level administrative regions (Fig. 1), with a total land area of 308×10⁴ km². According to the seventh national population census, the total population of Northwest China is approximately 1.04×10⁸. Influenced by unique landforms and climate conditions, Northwest China relies primarily on irrigated agriculture, mainly cultivating drought-resistant crops such as wheat, soybeans, highland barley, and corn. The Guanzhong Plain in Shaanxi, Hexi Corridor in Gansu, Ningxia, and southern Xinjiang are all important grain production areas in Northwest China [14]. As a key region for the "Western Development" strategy and "Belt and Road" construction, Northwest China also occupies an important position in China's energy strategic layout.

2.2 Data Sources

This study uses multi-source datasets to quantify and characterize the spatial distribution of ecosystem service supply and demand, including land use data, normalized difference vegetation index (NDVI), nighttime light data, and socioeconomic data (Table 1). All data were resampled to a 500 m spatial resolution and processed using the WGS_1984_Albers coordinate system in ArcGIS 10.8 for data preprocessing, spatial analysis, and statistics.

Table 1 Data sources
| Data Type | Spatial Resolution | Source |
|-----------|-------------------|--------|
| Land use data | 500 m | China Land Use Dataset (1980-2020) released by Professors Yang Jie and Huang Xin |
| NDVI | 500 m | MOD13A3 product |
| Nighttime light data | 500 m | Global NPP-VIIRS-like nighttime light data (2000-2018) |
| DEM | 500 m | GEBCO Global Land-Sea Database |
| Soil data | 1 km | World Soil Database (HWSD) from National Tibetan Plateau Science Data Center |
| Population density | 1 km | LandScan from Resource and Environment Science and Data Center |
| Socioeconomic data | - | Statistical yearbooks, water resources bulletins, China Energy Statistical Yearbook |

2.3 Quantification of Ecosystem Services

2.3.1 Water Production Service

Water Yield. The InVEST water yield module was used to assess annual water production in Northwest China, calculated as follows:

$$P(x)_i = P(x)_i$$

where $P(x)_i$ is the annual water yield in grid cell $x$ for land use type $i$; $P(x)$ is the precipitation in grid cell $x$; and $P(x)_i$ is the actual annual evapotranspiration in grid cell $x$ for land use type $i$.

Water Demand. Water demand includes agricultural production, industrial production, residential consumption, and ecological water use. Industrial water use was allocated based on secondary industry output, residential water use was distributed according to population density data, and agricultural and ecological water uses were primarily allocated based on cultivated land and green space types in the land use data. The three water use types were superimposed to obtain total water demand in Northwest China [15]. The formula is:

$$D_{agr} + D_{eco} + D_{ind} + D_{gdp} \times \text{pop} \times \text{Ac} + \text{Bd} \times Y + Z$$

where $D$ is annual water demand (m³·hm⁻²); $D_{agr}$, $D_{eco}$, $D_{ind}$, and $D_{gdp}$ are agricultural, ecological, industrial, and domestic water use (m³·hm⁻²), respectively; $Ac$ and $Bd$ are spatial distribution data for cultivated land and green space grids; $Y$ and $Z$ are water consumption per unit area for agriculture and ecology (m³·hm⁻²); $G$ is grid population density (people·hm⁻²); $U$ is domestic water consumption per 10,000 yuan GDP (m³·10,000 yuan⁻¹); and $W$ is per capita domestic water consumption (m³·person⁻¹).

2.3.2 Carbon Sequestration Service

Carbon storage refers to the total amount of carbon accumulated and stored in natural ecosystems through biochemical processes during a specific period [16]. Human production activities have led to continuously rising carbon emissions, posing increasingly severe global environmental challenges. It is necessary to balance carbon emissions with carbon storage, enhance ecosystem carbon storage capacity, reduce carbon emissions from socioeconomic systems, and achieve the "dual carbon" goals as soon as possible.

Carbon Storage. Current research primarily uses the InVEST model to calculate carbon storage as follows:

$$CS_{tot} = C_{above} + C_{below} + C_{soil} + C_{dead}$$

where $CS_{tot}$ is total carbon storage (t·hm⁻²); $C_{above}$, $C_{below}$, $C_{soil}$, and $C_{dead}$ are aboveground biomass carbon, belowground biomass carbon, soil organic carbon, and dead organic matter carbon (t·hm⁻²), respectively.

Carbon Demand. Recent studies have verified the correlation between nighttime light data and carbon emissions and widely applied nighttime light data to study spatiotemporal patterns of carbon emissions [17]. This study uses corrected nighttime light data to reflect the spatial distribution of carbon emissions, calculated as:

$$CD_j = \frac{DN_{sum}}{DN_{sum}} \times CD_j$$

where $CD_j$ is carbon storage demand in grid cell $j$ (t·hm⁻²); $DN_{sum}$ is the brightness value in grid cell $j$; and $DN_{sum}$ is the total carbon emissions in the study area (t).

2.3.3 Food Service

Food Production. Using NDVI to measure food production capacity is an important method for calculating food yield. This study uses the ratio of grid NDVI values to total NDVI values in cultivated land types as the coefficient for measuring food production, with the specific formula:

$$NDVI_{sum} = \frac{NDVI(x)}{NDVI_{sum}} \times \text{food}$$

where $NDVI_{sum}$ is food production (t·hm⁻²); $NDVI(x)$ is the NDVI value in grid cell $x$; and $NDVI_{sum}$ is the total actual food production in Northwest China (t).

Food Demand. Food demand is reflected by the product of per capita food consumption and population density [18]:

$$\text{food} = D_{pop} \times \text{food}$$

where $\text{food}$ is food service demand (t·hm⁻²); $D_{pop}$ is grid population density (people·hm⁻²); and $\text{food}$ is per capita food consumption (t·person⁻¹).

2.4 Supply-Demand Matching Analysis

2.4.1 Static Matching

The Ecosystem Service Supply-Demand Index ($SDI_x$) links ecosystem service supply and demand to reflect surplus, balance, or deficit conditions in different regions [19], calculated as:

$$SDI_x = \frac{ESS_x - ESD_x}{ESS_x + ESD_x}$$

where $ESS_x$ is the ecosystem service supply in region $x$; and $ESD_x$ is the ecosystem service demand in region $x$. Based on supply-demand matching conditions, the study area is divided into surplus zones (supply > demand), balance zones (supply = demand), and deficit zones (supply < demand).

2.4.2 Dynamic Matching

Static matching represents the matching status at a specific moment but cannot capture sustainability characteristics. Therefore, dynamic matching analysis is introduced to characterize sustainability based on the change intensity of ecosystem service supply and demand [20]:

$$\Delta ESS = \frac{ESS_b - ESS_a}{ESS_a}$$
$$\Delta ESD = \frac{ESD_b - ESD_a}{ESD_a}$$

where $\Delta ESS$ and $\Delta ESD$ represent changes in ecosystem service supply and demand, respectively; $ESS_a$ and $ESS_b$ are supply in years $a$ and $b$; and $ESD_a$ and $ESD_b$ are demand in years $a$ and $b$.

Using supply and demand change intensity as coordinate axes, space is divided into four quadrants based on the signs of $\Delta ESS$ and $\Delta ESD$, with the balance line of incremental changes as the boundary. Comparing the absolute values of $\Delta ESS$ and $\Delta ESD$ yields six types (Fig. 2):

• Sustainable types: Supply growth > demand growth (SIDI-S); Supply increase and demand decrease (SIDD-S); Supply decrease < demand decrease (SDDD-S)
• Unsustainable types: Supply growth < demand growth (SIDI-US); Supply decrease > demand decrease (SDDD-US); Supply decrease and demand increase (SDDI-US)

2.5 Ecological Management Zoning

Referencing previous studies [21], static matching indicates ecosystem service surplus or deficit, while dynamic matching indicates sustainability. Combining both yields four ecological management zones (Fig. 2):

1. Ecosystem Surplus Sustainable (S-S): Supply exceeds demand or is relatively balanced, with the supply-demand gap gradually increasing or remaining stable.
2. Ecosystem Surplus Unsustainable (S-US): Supply exceeds demand or is relatively balanced, but the supply-demand gap is gradually narrowing.
3. Ecosystem Deficit Sustainable (D-S): Supply is less than demand, but the gap is gradually narrowing.
4. Ecosystem Deficit Unsustainable (D-US): Supply is less than demand, and the gap is gradually increasing.

3. Results

3.1 Historical Evolution of Ecosystem Service Supply and Demand in Northwest China

From 2000 to 2020, ecosystem services in Northwest China showed different supply-demand trends (Table 2). To eliminate climate fluctuation impacts and better reflect current conditions, data from 2015-2020 were averaged (hereinafter the same). Overall, the supply-demand indices for all three ecosystem services were positive, indicating a relatively coordinated water-food system in Northwest China. However, the supply-demand index for carbon sequestration services declined annually, decreasing from 0.16 to 0.10 t·hm⁻².

Table 2 Evolution of supply and demand of ecosystem services in Northwest China from 2000 to 2020
| Service | 2000 | 2010 | 2020 | 2000-2020 Change |
|---------|------|------|------|------------------|
| Water yield supply (m³·hm⁻²) | 656.86 | 728.45 | 815.37 | ↑ |
| Water demand (m³·hm⁻²) | 260.78 | 271.52 | 282.17 | ↑ |
| Carbon storage (t·hm⁻²) | 39.86 | 38.45 | 39.33 | → |
| Carbon emissions (t·hm⁻²) | 0.10 | 0.13 | 0.16 | ↑ |
| Food production (t·hm⁻²) | 0.16 | 0.18 | 0.20 | ↑ |
| Food demand (t·hm⁻²) | 0.12 | 0.13 | 0.13 | → |

In terms of supply, water yield and food production showed increasing trends, with water yield rising from 656.86 to 815.37 m³·hm⁻² and food production increasing from 0.16 to 0.20 t·hm⁻². In contrast, carbon storage fluctuated, decreasing from 39.86 to 39.33 t·hm⁻². Regarding demand, water demand increased from 260.78 to 282.17 m³·hm⁻², while carbon emissions continued to rise, primarily due to local economic development and population growth, presenting potential threats to supply-demand balance.

3.2 Spatial Characteristics of Ecosystem Service Supply and Demand

3.2.1 Supply Characteristics

The spatial distribution of the three ecosystem services showed distinct differences (Fig. 3). Water yield was distributed roughly along northwest-southeast axes, decreasing from these axes outward and from mountains to basins due to geographical location, topography, and weather systems. The Sanjiangyuan area, known as the "Water Tower of China," is an important water source replenishment zone. Water yield in southern Gansu, southern Ningxia, and northern Shaanxi increased annually.

Changes in terrestrial ecosystem carbon storage are mainly caused by regional land use type changes [22]. Cultivated land, forest land, and wetlands are high-value areas for carbon storage, while glaciers, construction land, and bare land have lower carbon storage. Food production correlates with cultivated land distribution, with high-value production areas mainly located in suitable agricultural regions such as the Ningxia Plain, Weihe Plain, Hexi Corridor in Gansu, and Tarim River Basin.

3.2.2 Demand Characteristics

To some extent, regional ecosystem service demand is influenced by population density and economic development, with high values concentrated in densely populated areas with prominent social activities (Fig. 4). Water demand high-value areas are primarily distributed in Shaanxi, Ningxia, Gannan, and northwestern Xinjiang, showing a "belt-like" pattern, with particularly significant increases in central Shaanxi. During the study period, water demand in Xinjiang increased annually. With economic growth, industrial structure upgrading, and urbanization in Northwest China, carbon emissions continued to increase, showing a "high at both ends, low in the middle" distribution pattern that increased annually. High values in the east concentrated in the Ningxia Plain, Guanzhong Plain, and Loess Plateau, while western high values concentrated near the Tarim Basin and Junggar Basin. Food demand high-value distribution first decreased slightly then remained stable, particularly prominent in the Guanzhong Plain area of central Shaanxi.

3.3 Static Matching Spatial Characteristics

The supply-demand index high-value areas for water services showed a "high at both ends, low in the middle" pattern similar to water yield distribution (Fig. 5). The Sanjiangyuan area, upper Yellow River reaches, and Tianshan-Altay Mountains have abundant water resources. However, most areas in northern Gansu, northern Ningxia, and Xinjiang suffer from water imbalance, primarily because they are located in arid and semi-arid zones with low precipitation and high agricultural irrigation water demand that cannot meet basic needs.

The overall situation for carbon sequestration service supply-demand index was favorable, with the highest ratio among the three services, indicating certain carbon sink advantages in Northwest China. The spatial pattern showed roughly point and belt distributions, with large deficit areas in the central-west gradually converting to balance zones during 2015-2020. However, the deficit range expanded from 2000-2010, and the continuous growth of carbon emissions is unfavorable for carbon balance and achieving "dual carbon" goals.

Food service supply-demand index high-value areas were relatively consistent with cultivated land distribution, with high values in the Guanzhong Plain, Ningxia Plain, and irrigated areas along Xinjiang rivers. In 2000, food service supply-demand index showed low values across large areas, mainly due to limited agricultural production technology and the fragile ecological environment's inability to fully meet human living and production needs. The problem of food supply-demand imbalance in eastern regions has persisted.

3.4 Dynamic Matching Spatial Characteristics

Dynamic matching better reveals the future development of ecosystem services. For water services, central-eastern regions generally have good water resource foundations, with dynamic matching types mostly being SIDI-US, but water supply growth cannot keep pace with demand growth, potentially facing structural water shortages in the future. Southwestern Xinjiang, central Shaanxi, and northern Ningxia showed SDDI-US types, where water service supply decreases while demand increases, posing hidden risks of water resource imbalance.

For carbon sequestration services, most regions showed carbon storage growth less than carbon emission growth, indicating potential future supply-demand imbalance. However, western Xinjiang, Zhangye and Linxia in Gansu, Weinan in Shaanxi, and most of Ningxia (except Guyuan) showed SIDI-S types, where carbon storage growth exceeds carbon emission growth, representing sustainable types.

In food production services, Northwest China was dominated by SIDD-S types. Urumqi in Xinjiang and Xi'an in Shaanxi, being densely populated, showed SIDI-US types where food supply growth is less than demand growth, representing unsustainable types. Ankang, Shangluo, and Yulin in Shaanxi, Xining and Yushu in Qinghai, Lanzhou in Gansu, and Alar in Xinjiang all showed SDDD-US types, where both food supply and demand are decreasing but supply is declining faster, potentially leading to food security issues in the future.

3.5 Ecological Management Zoning

Combining static and dynamic matching identified four ecosystem service matching types as four ecological management zones (Fig. 7):

• S-S type: Scattered across all services, with Weinan in Shaanxi showing supply exceeding demand or balanced status for all three service types, indicating excellent ecosystem services. Tacheng area also showed good conditions for carbon sequestration and food services.

• S-US type: Mainly concentrated in water and carbon sequestration services. Water services primarily involve eastern Northwest China, while carbon sequestration services involve most of the region.

• D-S type: Mainly distributed in food services, as well as some water and carbon sequestration services. The supply-demand gap in these regions is gradually narrowing, potentially leading to future supply shortages.

• D-US type: This characteristic is mainly reflected in food services, where the supply-demand contradiction is intensifying. These regions require strengthened ecosystem service management and optimization.

4. Discussion

4.1 Ecosystem Service Supply-Demand Relationships and Spatial Matching

Effective ecosystem service supply-demand management strategies can achieve "win-win" outcomes for various services. Compared with previous studies, comprehensively considering both the changing trends of ecosystem service supply-demand matching and sustainability characteristics provides a more comprehensive reflection of the current status and future dynamics of ecological services in Northwest China, enabling more precise and effective ecological management strategies.

In the coordinated development of the water-food system, water resources occupy a core position. Regional coordinated management must be "water-defined and water-measured," following regional characteristics to rationally plan food industry and energy industry layouts [23]. Resource-based and structural water shortages remain important factors constraining social development and ecological improvement in Northwest China [24]. The increase in food service supply benefits from ecosystem structural adjustments and agricultural technological progress, while food demand remains relatively stable, related to local population structure and lifestyle.

For carbon sequestration services, the main reason for carbon storage changes in Northwest China from 2000-2020 was grassland degradation [25]. Construction land development and cultivated land expansion during the "Belt and Road" process have led to significant increases in carbon emissions. While promoting economic development, Northwest China must attach great importance to carbon emission reduction and ecological restoration to gradually achieve carbon cycle balance.

4.2 Management Strategies for Different Zones

To better integrate into the new development pattern, Northwest China needs to balance development and protection, comprehensively promoting coordinated green development of economy, society, and ecology around the "dual carbon" goals. Different regulatory strategies are needed for different ecological management zones:

• S-S zones: Mostly distributed along river lines or in piedmont basins near core ecological areas, these are key guarantee zones for ecosystem service supply in Northwest China. Strategies should focus on improving ecological resource utilization efficiency, accelerating the construction of a green, low-carbon circular economic system, and fostering resource-saving and environmentally friendly production and lifestyles [26].

• S-US zones: Mainly involve water services. These zones have imbalanced ecosystem supply and demand that is continuously deteriorating. It is necessary to optimize land use and industrial structures, comprehensively advance integrated protection and management projects for mountains, rivers, forests, farmlands, lakes, grasslands, sands, and ice, and establish cross-regional ecological compensation mechanisms [27].

• D-S zones: Involve food services and some water and carbon sequestration services. The supply-demand gap is gradually narrowing, potentially leading to future supply shortages. Water resource utilization efficiency should be improved, and modern water cycle systems with interconnected, mutually regulated, and spatially balanced features should be constructed [28]. Natural ecosystem carbon sinks should be enhanced to coordinate high-quality development with ecological protection.

• D-US zones: This type is mainly characterized by food services with intensifying supply-demand contradictions. Agricultural industrial layout and ecological spatial layout should be constructed according to market demands and habitat quality, and the "Three Zones and Three Lines" should be designated based on regional advantages [29].

5. Conclusions

1) Temporal trends: Water service supply and demand both showed fluctuating upward trends, with supply growth exceeding demand growth. Food service supply showed an upward trend while demand remained stable, with the supply-demand index increasing annually. Carbon demand showed an upward trend, while carbon storage and the carbon sequestration service supply-demand index both declined, affecting future carbon balance and "dual carbon" goal achievement.

2) Spatial characteristics: Under static matching, water services showed an "east-west high, middle low" pattern, with the deficit range in northern Xinjiang continuously expanding. Carbon sequestration services generally had supply exceeding demand, but deficit areas increased annually, consistent with carbon emission distribution. Food production service deficit ranges decreased, with low-value areas concentrated in the south and northwest, and high and low value areas interspersed. Under dynamic matching, food services were mostly sustainable, while carbon sequestration and water services were mostly unsustainable, facing risks of local imbalance between ecological carrying capacity and social development.

3) Municipal-scale management zoning: Water services were mostly unsustainable, making water resources a constraint factor for future sustainable development in Northwest China. Carbon sequestration services mainly involved S-US types, with scattered S-S types, requiring improved ecosystem carbon sinks to promote carbon balance. Food services were mainly sustainable, with D-US types scattered in the south, east, and north, requiring continuous protection of cultivated land safety and integrated planning of production, living, and ecological spaces.

References

[1] Costanza R, D'Arge R, De Groot R, et al. The value of the world's ecosystem services and natural capital[J]. Nature, 1997, 387(6630): 253-260.

[2] Yin D, Yu H, Shi Y, et al. Matching supply and demand for ecosystem services in the Yellow River Basin, China: A perspective of the water-energy-food nexus[J]. Journal of Cleaner Production, 2023, 384: 135469, doi: 10.1016/j.jclepro.2022.135469.

[3] Zhang Liwei, Fu Bojie. The progress in ecosystem services mapping: A review[J]. Acta Ecologica Sinica, 2014, 34(2): 316-325.

[4] Ma Lin, Liu Hao, Peng Jian, et al. A review of ecosystem services supply and demand[J]. Acta Geographica Sinica, 2017, 72(7): 1277-1289.

[5] Liu Yuting, Qin Menglin, Ouyang Huiting, et al. The optimization of territorial spatial resources allocation based on the balance of supply and demand of ecosystem services[J]. Journal of Natural Resources, 2024, 39(6): 1358-1383.

[6] Li Cheng, Zhao Jie. Research on spatiotemporal pattern and influencing factors of supply-demand matching in the Yangtze River Delta urban agglomeration[J]. Ecological Economy, 2022, 38(9): 160-169, 187.

[7] An Zhiying, Sun Caizhi, Hao Shuai. Matching relationship between supply and demand of ecosystem services from the perspective of water-energy-food nexus in northeast China[J]. Acta Ecologica Sinica, 2024, 44(10): 4170-4186.

[8] Teng Y, Chen G, Su M, et al. Ecological management zoning based on static and dynamic matching characteristics of ecosystem services supply and demand in the Guangdong-Hong Kong-Macao Greater Bay Area[J]. Journal of Cleaner Production, 2024, 448: 141599, doi: 10.1016/j.jclepro.2024.141599.

[9] Guan Qingchun, Hao Jinmin, Xu Yueqing, et al. Zoning of agroecological management based on the relationship between supply and demand of ecosystem services[J]. Resources Science, 2019, 41(7): 1359-1373.

[10] Campagne C S, Roche P, Müller F, et al. Ten years of ecosystem services matrix: Review of a (r)evolution[J]. One Ecosystem, 2020, 5: e51103, doi: 10.3897/oneeco.5.e51103.

[11] Su Boru, Liu Moucheng. Research progress in ecosystem management strategies based on ecosystem services trade-offs[J]. Journal of Natural Resources, 2023, 38(7): 1848-1862.

[12] Zhao Y, Wang N, Luo Y, et al. Quantification of ecosystem services supply-demand and the impact of demographic change on cultural services in Shenzhen, China[J]. Journal of Environmental Management, 2022, 304: 114280, doi: 10.1016/j.jenvman.2021.114280.

[13] Xiong Xinying, Meng Mei. Regionalization and optimization strategy of ecological management in Xinjiang, China based on supply-demand relationship and spatial flow of ecosystem services[J]. Chinese Journal of Applied Ecology, 2023, 34(8): 2237-2248.

[14] Xu L X, Yang D W, Wu T H, et al. An ecosystem services zoning framework for the permafrost regions of China[J]. Advances in Climate Change Research, 2019, 10(2): 92-98.

[15] Li Xiaofei, Gong Jian, Ye Jing, et al. Optimization of ecological function zoning in Gansu Province under the trade-offs and synergies of ecosystem services[J/OL]. Arid Land Geography. [2025-01-16]. http://kns.cnki.net/kcms/detail/65.1103.X.20241106.1557.001.html.

[16] Zhou Bo, Xu Yuanxi, Feng Tian. Spatial differentiation of carbon balance and optimization countermeasures in Chengdu-Chongqing urban agglomeration[J]. Resources and Environment in the Yangtze Basin, 2024, 33(8): 1650-1662.

[17] Sun R, Jin X, Han B, et al. Does scale matter? Analysis and measurement of ecosystem service supply and demand status based on ecological unit[J]. Environmental Impact Assessment Review, 2022, 95: 106785, doi: 10.1016/j.eiar.2022.106785.

[18] Liu Chunfang, Wang Weiting, Liu Licheng, et al. Supply-demand matching of county ecosystem services in northwest China: A case study of Gulang County[J]. Journal of Natural Resources, 2020, 35(9): 2177-2190.

[19] Zhao Xianchao, Peng Jingxiao, Hu Yijue, et al. Spatiotemporal pattern and influence factors of county carbon emissions in Hunan Province based on nightlight data[J]. Ecological Science, 2022, 41(1): 91-99.

[20] Ma S, Smailes M, Zheng H, et al. Who is vulnerable to ecosystem service change? Reconciling locally disaggregated ecosystem service supply and demand[J]. Ecological Economics, 2019, 157: 289-298.

[21] Ma Zeyu, Li Ning, Xin Cunlin, Tang Daobin, et al. Multi-scenario land use optimization and carbon storage assessment in northwest China[J]. Environmental Science, 2023, 44(8): 4655-4665.

[22] Chen Peng, Xiao Lie, et al. Identification of key areas for ecological restoration and division of restoration zones in Qinghai Province[J]. Journal of Soil and Water Conservation, 2024, 38(3): 252-265.

[23] Li Xiuhua, Wu Chunyuan. Coordination of water resources utilization in the five provinces of northwest China[J]. Arid Land Geography, 2022, 45(1): 9-16.

[24] Yue Wenze, Hou Li, Xia Haoxuan, et al. Territorially ecological restoration zoning and optimization strategy in Guyuan City of Ningxia, China: Based on the balance of ecosystem service supply and demand[J]. Chinese Journal of Applied Ecology, 2022, 33(1): 149-158.

[25] Zhang Chunyue, Bai Yongping, Yang Xuedi, et al. Identification of ecosystem service bundles in Ningxia Plain under multi-scenario simulation[J]. Geographical Research, 2022, 41(12): 3364-3382.

[26] Sun Caizhi, Wei Yaqiong, Zhao Liangshi. Co-evolution of water-energy-food nexus in arid areas: Take northwest China as an example[J]. Journal of Natural Resources, 2022, 37(2): 320-333.

[27] Chen Z, Yu B L, Yang C S, et al. An extended time series (2000-2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration[J]. Earth System Science Data Discussions, 2020, 13(3): 889-906.

[28] Feng Qi, Baiguangzu, Li Zongsheng, et al. Accelerating the construction of a new pattern of ecological protection in northwest China[J]. Bulletin of the Chinese Academy of Sciences, 2022, 37(10): 1457-1470.

[29] Shaanxi Provincial People's Government. Shaanxi Province land space planning (2021-2035)[EB/OL]. [2024-06-21]. http://www.shaanxi.gov.cn/zfxxgk/fdzdgknr/ghxx/gtzygh/202406/P020240622343901996974.

[30] Qinghai Provincial People's Government. Spatial planning of Qinghai Province land (2021-2035)[EB/OL]. [2024-05-27]. http://www.qinghai.gov.cn/zwgk/system/2024/05/27/030045305.shtml.