Spatial and Temporal Characteristics of Ecosystem Service Trade-Off and Synergy Relationships in the Western Sichuan Plateau, China

Abstract

Clarifying the complex relationships among ecosystem services (ESs) and the driving mechanisms of ecosystem service (ES) is essential for supporting regional ES and ecological sustainability. Although studies on ES relationships provide guidance for regional ecological management, the driving mechanisms of ES have not been adequately studied, especially in areas with complex natural environments and progressive urbanization. Combined with the data on land use, climate, NDVI, and soil data, this paper aims to explore this issue by analyzing the relationships among ESs and the driving mechanisms of ESs in the western Sichuan Plateau region of China. Firstly, the temporal and spatial distribution characteristics of five ecosystem services (food supply, water supply, habitat quality, soil conservation, and carbon storage) from 2000 to 2020 were analyzed by the InVEST model. Second, the trade-offs/synergistic relationships among ESs were analyzed using SPSS as well as the Pearson product-moment correlation coefficient method in MATLAB. Finally, the Geodetector model was further used to reveal the influencing factors of ecosystem services in the western Sichuan Plateau. The results showed that: (1) Water supply decreased in the western Sichuan Plateau from 2000 to 2020, but increased in the eastern part; habitat quality was generally good in the whole Sichuan Plateau, but decreased in some areas; carbon storage showed an overall improving trend; soil conservation showed an overall increasing and then decreasing trend, and food supply services showed an increasing trend. (2) From 2000 to 2020, food supply and other services in the western Sichuan Plateau were in a trade-off relationship; all other service pairs showed a synergistic relationship. (3) In terms of space, the relationships between ecosystem services showed spatial heterogeneity. There was a synergistic relationship between food supply and habitat quality in some areas, such as Litang County and Xinlong County, and there was a trade-off relationship between water supply and carbon storage services in some areas, such as Ruoergai County and Daocheng County, etc. (4) The Geodetector results showed that food supply and soil conservation were mainly influenced by the slope (0.682, 0.672), annual precipitation was the strongest explanation for water supply (0.967), and habitat quality and carbon storage were the most influenced by NDVI (0.876, 0.828); meanwhile, each ecosystem service was interactively influenced by multiple factors. Based on the results, we proposed ecological management recommendations for the western Sichuan Plateau, the most important one being that the western Sichuan Plateau should protect and rationally use the existing natural resources, especially the existing forest and grassland resources, and at the same time reform the agricultural structure and scientifically plan urban development, to promote the coexistence of cities and nature. We took the western Sichuan Plateau of China, where urbanization and a complex natural environment are in opposition, as an example, to explore its ecosystem services, relationships, and driving mechanisms, and then put forward suggestions on ecological management and control, providing a reference for future regional coordination between urbanization and the natural environment.

1. Introduction

Ecosystem services refer to the benefits that humans derive directly or indirectly from ecosystem products and services through the structure, functions, and processes of ecosystems, and according to the classification criteria of the Millennium Ecosystem Assessment, ecosystem services can be broadly classified into four categories: supply services, regulation services, cultural services, and support services [1]. Since human activities, socioeconomic development, and ecological management strategies in different regions can have different impacts on regional ecological environments, resulting in regional landscape heterogeneity, the relationships among ecosystem services may vary in different regions. In addition, the interactions between ecosystem services can take diverse forms at different times [2,3]. Ecosystem services exhibit trade-offs when one ecosystem service increases while others decrease, and synergistic effects when two or more ecosystem services increase or decrease simultaneously [4]. The relationship between ecosystem services can directly or indirectly affect the natural ecosystem, human well-being, and the socioeconomic sphere [5]. Therefore, identifying trade-off synergistic relationships among ecosystem services can help inform the balance between sustainable development and economic development. Many scholars have explored a large number of trade-off synergistic relationships among ecosystem services [6,7,8], mostly for water source areas and watersheds [9,10], protected areas [3,11], or local regions [12,13]. These studies have contributed to a deeper understanding of the interactions among ecosystem services. Current methods commonly used to explore the trade-off and synergistic relationships of ecosystem services include correlation analysis [14,15], spatial correlation analysis [10,16,17,18], trade-off/synergy degree model (ESTD) [19,20], and scenario simulation [21,22]. Studying the trade-offs and synergies of ecosystem services helps to deeply understand the mechanisms of action among different services and accurately analyze and compare the relationships between them to guide ecological environmental protection.

Ecosystem services (ESs) provide the basic physical environment and numerous products for humans, which has a significant impact on sustainable development [23,24]. ESs are subject to change by different factors [25,26]. Many scholars have explored the factors affecting ESs, and common methods include gray correlation degree analysis [27], ordination analysis ranking analysis [28], spatial regression models [29], etc. However, most of these studies have focused on exploring the relationship patterns between drivers and ESs over a short time period, and less on exploring drivers in conjunction with long time series ES change characteristics, which may provide more information for regional ecological sustainability. Therefore, exploring the driving mechanisms of ESs is critical to providing guidelines for policymakers to maintain and improve ES function and achieve sustainable development [30].

Our study area, the western Sichuan Plateau in China, is an important ecological barrier in the upper reaches of the Yangtze River and plays an important role in natural environmental protection in China. However, the western Sichuan Plateau faces great challenges, especially the problem of ecological sustainability, with sensitive and fragile natural ecology, relatively backward socioeconomic development, and large differences in internal geographic spatial development [31]. With the gradual development of economic construction, the contradiction between urbanization and the fragile natural environment has deepened, and ecological management is urgently needed. However, issues concerning the regional ecological status of the western Sichuan Plateau and the main driving factors affecting ESs are still unclear; thus, to maintain the important functions of ESs and promote sustainable development in regions where urbanization development is in conflict with the natural environment, it is vital to explore the changes in ESs and the driving mechanisms behind them as well as the relationships of ESs to provide a reference for future ecological management.

In this study, the InVEST model was applied to quantitatively assess five ecosystem services: water supply, carbon storage, soil conservation, habitat quality, and food supply in the western Sichuan Plateau from 2000 to 2020, to investigate the spatial and temporal variation characteristics and dynamic changes in ecosystem services in the western Sichuan Plateau from a long time series perspective. Then, the study further identified the trade-off/synergy of ecosystem services and their spatial and temporal characteristics in the western Sichuan Plateau through the Pearson product–moment correlation coefficient method and explored the driving factors of ecosystem services based on Geodetector. The specific objectives of this study are as follows: (1) to map the spatial characteristics of ESs over time; (2) to analyze the spatial and temporal characteristics of the relationships of ESs; and (3) to analyze the driving mechanisms of ESs and propose relevant measures to optimize regional ecological management.

2. Study Area and Data Sources

2.1. Overview of the Study Area

The western Sichuan Plateau region is situated in the transition zone between the Qinghai–Tibetan Plateau and the middle and lower reaches of the Yangtze River Plain, and is located in the western part of Sichuan Province, including Ganzi Tibetan Autonomous Prefecture and Aba Tibetan and Qiang Autonomous Prefecture, comprising 31 counties (Figure 1). According to the Sichuan Statistical Yearbook [32], the GDP of the western Sichuan Plateau reached CNY 82.251 billion (yuan is the basic unit of money in China) in 2020, which was 13.7 times higher than that in 2000. In 2020, the urbanization rate in the western Sichuan Plateau area was 35.49%, while in 2000, the urbanization rate was only 15.11%. However, the rapid economic growth and the development of urbanization have led to serious problems, such as the over-exploitation of natural resources, and the destruction of forests, grasslands, and habitats of animals and plants in the western Sichuan Plateau; for example, the expansion of cities and towns have aggravated land desertification in the western Sichuan Plateau [33]. The western Sichuan Plateau is rich in water resources, with many water systems such as the Jinsha River, Minjiang River, Yalong River, and Dadu River running through it, and a large amount of ice and snow meltwater also serves as an important source of water recharge. The western Sichuan Plateau is an important water conservation reserve in the upper reaches of the Yangtze River and Yellow River. The topography of the West Sichuan Plateau is complex, with large altitude differences, and is dominated by plateaus and mountains; the vegetation is mainly grassland, with a natural advantage of the green ecological substrate and a wide variety of wildlife, which has an irreplaceable role in biodiversity conservation. The western Sichuan Plateau region is an important source of natural resources and ecosystem services for Sichuan province and China and serves as an important ecological barrier in the upper reaches of the Yangtze River, but it is also a typical ecologically fragile and sensitive area in China [31,34].

2.2. Data Sources

The data used in this study mainly include land use, topographic soil, climate, socioeconomic data, and parameters required for InVEST model calculation. The land use data include five periods of 2000, 2005, 2010, 2015, and 2020 data of the western Sichuan Plateau region, from the Resource and Environment Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn 2 March 2022), all with a spatial resolution of 1 km × 1 km. The topographic data use ASTERGDEM with a spatial resolution of 30 m, from the Geospatial Data Cloud (http://www.gscloud.cn 14 March 2022). Soil data were obtained from the World Soil Database (HWSD) (http://webarchive.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/ 15 February 2022) with a spatial resolution of 1 km × 1 km. Climate data were obtained from the Resource and Environment Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn 12 March 2022), including a spatially interpolated dataset of year-by-year precipitation in China. Socioeconomic data were obtained from the Sichuan Provincial Statistical Yearbook, the China Rural Statistical Yearbook, and the statistical yearbooks of counties. Normalized difference vegetation index (NDVI) data (2000, 2020, 2010, 2015, and 2020, 30 m × 30 m) were provided by the Resource and Environment Science and Data Center (http://www.resdc.cn/ 9 March 2022). The parameters required for the InVEST model calculation mainly referred to the InVEST model evaluation manual and existing related studies [30,35]. All spatial variables in this study were projected to the Universal Transverse Mercator projection (UTM) coordinate system and unified to a spatial resolution of 30 m.

3. Research Methodology

This study first assessed the characteristics and changes of five ecosystem services (water supply, carbon storage, soil conservation, food supply, and habitat quality) in the western Sichuan Plateau of China from 2000 to 2020 through the InVEST model. Secondly, we explored the complex trade-offs and synergies between ecosystem services in the western Sichuan Plateau through Pearson correlation analysis and the product–moment correlation coefficient method. Then, we analyzed the driving mechanism of ecosystem services in the western Sichuan Plateau through Geodetector. Finally, based on our research results, we put forward ecological management and control suggestions (Figure 2).

3.1. InVEST Model

This study assessed ecosystem services based on the InVEST model, which can effectively reveal the spatial distribution and dynamic change patterns of ecosystem services and link ecosystem services to support human well-being [36]; moreover, the InVEST model can be used to assess supply services, support services, and regulation services at multiple scales. In this study, four sub-modules of the InVEST model (water supply, carbon storage, habitat quality, and soil conservation) were selected to assess ecosystem services in the western Sichuan Plateau region for multiple years from 2000 to 2020, based on the importance and representativeness of different ecosystems for human well-being and data availability in the study area.

3.1.1. Water Supply

As one of the dominant ecosystem services in the western Sichuan Plateau, the water supply has a crucial eco-strategic position. Relevant studies have shown that water content and water yield are positively correlated [34], and this study estimates water supply in the western Sichuan Plateau region based on the water yield sub-module.

$$Y\mathit{xj}=\left(1-\frac{AETxj}{Px}\right)\times Px$$

(1)

$$\frac{AE{T}_{xj}}{P_x}=\frac{1+{\omega }_x{R}_{xj}}{1+{\omega }_x{R}_{xj}+\frac{1}{R_{xj}}}$$

(2)

$${\omega }_x=Z\times \frac{AW{C}_{xj}}{P_x}+1.25$$

(3)

where Y_xj denotes the water yield of land use type j (mm); AET_xj denotes the actual evapotranspiration (mm); P_x denotes the annual precipitation of raster x (mm); and Z is the Zhang coefficient, which denotes the seasonal influence factor.

3.1.2. Carbon Storage

The carbon storage module of the InVEST model assesses the carbon sequestration capacity of terrestrial ecosystems, and the required data include land use data and carbon density data.

$$C_{total}=C_{above}+C_{below}+C_{soil}+C_{dead}$$

(4)

where C_total is the total regional carbon stock; C_above is the above-ground carbon stock; C_below is the below-ground biological carbon stock; C_soil is the soil carbon stock, and C_dead is the organic matter carbon stock. The carbon density table was modified by referring to the results obtained by Liu Chunfang and Gao Yanli [37].

3.1.3. Habitat Quality

The habitat quality submodule responds to biodiversity and the required data and parameters include land-use type, habitat sensitivity factors, and threat factors. Habitat quality values range from 0 to 1, and the closer the value is to 1, the better the habitat quality [38]. Habitat quality is calculated by the following equation:

$$Q_{xj}=H_j\left[1-\left(\frac{D_{xj}{}^z}{D_{xj}{}^z+k^z}\right)\right]$$

(5)

$$i_{rxy}=1-\left(\frac{d_{xy}}{d_{rmax}}\right) \left(\mathrm{Linear} \mathrm{decline}\right)$$

(6)

$$i_{rxy}=\mathbf{exp}\left[-\left(\frac{2.99}{d_{rmax}}{d}_{xy}\right)\right] (\mathrm{Index} \mathrm{decline})$$

(7)

where Q_xj is the habitat quality index of raster x in land use type j; H_j and D_xj are habitat suitability index and habitat degradation degree, respectively; d_xy is the distance between raster x and raster y; d_rmax is the influence range of stress factor r; k is the half-saturation constant, which is usually taken as 1/2 of the maximum habitat degradation degree value. To determine the threat, the size of parameters such as threat factors and habitat sensitivity factors were determined according to the recommended parameters of the model and related research results [21].

3.1.4. Soil Conservation

Soil conservation was assessed and calculated using the SDR submodule of the InVEST model with the following formula:

$$S{C}_x=R_x\times K_x\times L{S}_x\left(1-C_x\times P_x\right)+SD{R}_x$$

(8)

where SC_x represents the amount of annual soil conservation of grid cell x, R_x is the precipitation erosion factor, K_x is the soil erodibility, LS_x represents the slope length factor, C_x and P_x represent the vegetation cover factor and soil conservation factor, respectively; SDR_x is the sediment retention.

3.2. Food Supply

There are 31 counties in the western Sichuan Plateau, and we calculated the food supply for each of these 31 counties (Figure 1). The significant correlation between food supply and the normalized difference vegetation index (NDVI) has been used to assess food supply service per unit area [39]. Because the main mode of food supply in the western Sichuan Plateau also includes livestock, the forestland and grassland in the region can provide a certain amount of food. In most areas of the western Sichuan plateau, residents tend to herd cattle and sheep on the grassland [40], while pigs, chickens, and other livestock are in the forest [41]. Therefore, we thought that the forest land in the western Sichuan Plateau also has a greater supporting role for meat and dairy product. In this study, food supply was calculated by linking grain, oilseed, and vegetable production to the NDVI of farmland, and meat and dairy to the NDVI of forestland and grassland to calculate their total food supply per unit, as follows:

$$G_i=\frac{NDV{I}_i}{NDV{I}_{xsum}}\times G_{xsum}+\frac{NDV{I}_i}{NDV{I}_{ysum}}\times G_{ysum}$$

(9)

where Gi is the food supply of grid i of a particular county; NDVIi is the NDVI value of grid i in the county, Gxsum is the county’s gross production of grain, oilseed, and vegetables, NDVIxsum is the total NDVI value of the county’s arable land, Gysum is the county’s gross product of meat and dairy, and NDVIysum is the total NDVI value of the county’s forest and grassland.

3.3. Trade-Off and Synergy Analysis of Ecosystem Services

In this study, the changes in the relationships between five ecosystem services in the western Sichuan Plateau from 2000 to 2020 were explored by Pearson correlation analysis in SPSS. The data used for calculations in SPSS were the total values of five ecosystem services in the western Sichuan Plateau, including three years: 2000, 2010, and 2020. Each correlation coefficient represented the overall trade-off and synergy relationship between two ecosystem services in a given year.

In this study, we used the Pearson product–moment correlation coefficient method based on the MATLAB platform to conduct an image-by-image correlation analysis of the trade-off/synergy relationships of five ecosystem services in the western Sichuan Plateau from 2000 to 2020, represented the trade-off and synergy relationships based on the positive and negative relationships of the correlation coefficients [42,43], and visualized the spatial characteristics of the relationships between food supply, water supply, habitat quality, soil conservation, and carbon storage with the help of the ArcGIS platform. The pixel-by-pixel Pearson product–moment correlation analysis equation is as follows:

$$R_{xy}=\frac{{\sum }_{i=1}^n\left(x_i-\overline{x}\right)\left(y_i-\overline{y}\right)}{\sqrt{{\sum }_{i=1}^n{\left(x_i-\overline{x}\right)}^2{\sum }_{i=1}^n{\left(y_i-\overline{y}\right)}^2}}$$

(10)

where R_xy is the correlation coefficient of two ecosystem services; R > 0 indicates a synergistic relationship between two ecosystem services, vice versa indicates a trade-off relationship, and when R = 0, there is no correlation; x_i and y_i are the ith raster values of ecosystem services x and y; $\overline{x}$ and $\overline{y}$ indicate the mean values of ecosystem services x and y, respectively; n is the total number of samples. The correlation coefficients were calculated and then analyzed for significance by the t-test [21]. After passing the significance test, the ecosystem service trade-off synergistic relationships were classified into the following classes: strong trade-off (−1 to −0.7), weak trade-off (−0.7 to −0.3), no correlation (−0.3 to 0.3), weak synergy (0.3 to 0.7), and strong synergy (0.7 to 1).

3.4. Geodetector

Geodetector is a powerful tool for effectively detecting spatial heterogeneity and exploring the driving forces behind it, revealing its spatial heterogeneity and related influencing factors by quantitatively analyzing the geographical correlation between two elements in the same region and the variability of elements in different regions [44,45]. In this study, factor detection and interaction detection in the Geodetector were selected to explore the driving factors of ecosystem services in the western Sichuan Plateau and the degree of influence of interactions among the driving factors on ecosystem services, respectively. Based on the actual natural environment and socioeconomic development of the western Sichuan Plateau, annual precipitation, mean annual temperature, normalized difference vegetation index (NDVI), elevation, slope, population density, and land-use type were finally selected as the driving factors for detection, and the factors were scientifically classified by the natural breakpoint method. The factor detection equation is as follows:

$$q=1-\frac{{\sum }_{h=1}^L{N}_h{\sigma }_h^2}{N{\sigma }^2}$$

(11)

where q is the detection power value of the detection factor X. The value range of q is [0, 1], and the closer the value of q is to 1, the higher the degree of influence of the driver X on the ecosystem service Y in the study area; N and N_h are the number of samples in the whole study area and h stratification, respectively; σ_h² is the variance of the driver X within the sample, and L is the classification of each driver. The types of interaction detection mainly reveal the effects of driver interactions on the dependent variable Y, including the five types of nonlinear attenuation, single-factor nonlinear attenuation, two-factor enhancement, and independent and nonlinear enhancement [46].

4. Results

4.1. Spatial Heterogeneity Analysis of Ecosystem Services

Figure 3 reflects the spatial and changes over 20 years of ecosystem services in the western Sichuan Plateau region from 2000 to 2020. Carbon storage in the western Sichuan Plateau region was generally good between 2000 and 2020, while carbon storage in the western region improved, but the southern and northeastern regions showed a decrease in carbon storage. Soil conservation was generally poor, mostly in low-value areas, while the soil conservation value was relatively high in eastern areas, and soil conservation in some areas showed a slowly increasing trend with time, with the highest value increasing from 1.81 × 10⁵ t/km² to 2.56 × 10⁵ t/km². The western Sichuan Plateau was treacherous, mostly in high mountain valley areas, and some of the lands suffered serious desertification. However, with the promotion of measures such as sand restoration, ecological afforestation, and grass planting, the sandy land has been restored and improved. The water supply in the western Sichuan Plateau was polarized, and the water supply gradually increased from west to east, with the highest and lowest values of 167.49 m³/km² and 43.31 m³/km² in 2000, respectively, and the difference between east and west was more obvious in 2020. Low-value areas of water supply increased, and the lowest value decreased to 36.85 m³/km², but in the eastern region water supply service increased, the highest value increasing to 181.49 m³/km². The western Sichuan Plateau should take timely water conservation and flow-saving measures and make reasonable use of river systems and snowmelt water resources. Habitat quality service was good in most areas of the western Sichuan plateau, while a few areas showed lower value, and the habitat quality decreased in the north and south between 2000 and 2020. In 2000, the food supply service showed a low trend in the west and a high trend in the east, but compared with the average level of food supply in Sichuan province in the same year, it was generally a low-value area for food supply. The western Sichuan Plateau area did not easily grow crops because of the fragile soil texture, so the food supply was relatively difficult; however, the food supply service was improved in 2020, most areas’ food supply value increased, and the highest value increased to 232.25 t/km².

4.2. Analysis of Ecosystem Service Trade-Off and Synergy Relationships in the Western Sichuan Plateau

4.2.1. Changes in 20 Years of Ecosystem Service Trade-Off/Synergy Relationships

The temporal characteristics and changes in the relationships among ecosystem services in the western Sichuan Plateau were obtained by applying SPSS Pearson correlation analysis to the five ecosystem services between 2000 and 2020. As shown in

Table 1. Trade-off and synergy of ecosystem services in western Sichuan Plateau.

Ecosystem Service Relationships Year	2000	2010	2020
food supply–water supply	−0.265 **	−0.214 **	−0.180
food supply–habitat quality	−0.368 **	−0.382 **	−0.420 **
food supply–soil conservation	−0.593 **	−0.482 **	−0.391 **
food supply–carbon storage	−0.299 **	−0.311 **	−0.109
water supply–habitat quality	0.833 **	0.857 **	0.864 **
water supply–soil conservation	0.826 **	0.812 **	0.822 **
water supply–carbon storage	0.661 **	0.571 **	0.627 **
habitat quality–soil conservation	0.841 **	0.810 **	0.819 **
habitat quality–carbon storage	0.922 **	0.924 **	0.915 **
soil conservation–carbon storage	0.569 **	0.429 **	0.408 **

** indicates a significant correlation at the 0.01 level (two-tailed).

, most of the relationships among ecosystem services were significantly correlated, and the trade-off and synergy relationships of the five ecosystem services from 2000 to 2020 were relatively stable with small changes in correlation coefficients. Among them, food supply and the remaining four services all showed a trade-off relationship from 2000 to 2020, with food supply showing the strongest trade-off with soil conservation, −0.593 and −0.482 in 2000 and 2010, respectively. Food supply and habitat quality showed the strongest trade-off in 2020. Water supply showed strong synergies with habitat quality, soil conservation, and carbon storage and the most significant synergistic effect with habitat quality, with the coefficient of synergy increasing from 0.833 to 0.864 from 2000 to 2020, which was due to the high vegetation cover and habitat support in areas with high values of water supply. Habitat quality also showed strong synergistic relationships with soil conservation and carbon storage service, with correlation coefficients remaining between 0.810–0.845 and 0.910–0.925, respectively. Soil conservation and carbon storage also showed synergy, but the correlation coefficients were weaker compared to the rest of the synergistic relationships

4.2.2. Spatial Characteristics of Ecosystem Service Trade-Off/Synergy Relationships

Based on the long time-series data from 2000 to 2020, the spatial distribution of the trade-off and synergy relationships of ecosystem services was analyzed by the MATLAB platform for five services (food supply, water supply, habitat quality, soil conservation, and carbon storage) in the western Sichuan Plateau, combined with GIS to produce a spatial distribution map (Figure 4).

Food supply and water supply showed a trade-off relationship in the eastern and western parts of the Sichuan Plateau while the synergy was concentrated in Langtang, Aba, Jinchuan, Luding, Danba, Songpan, and northeastern Kangding counties. Food supply and habitat quality exhibited an interlocking distribution of trade-off and synergistic relationships in space, with a more significant trade-off and synergy relationship in the western region than in the northeastern region, in which Litang, Xinlong, southern Danba, and southern Dafu showed strong synergy relationships. The correlations between food supply and soil conservation, and food supply and carbon storage had similar spatial distribution characteristics, showing a strong spatial distribution in the west and a weak spatial distribution in the east. Strong trade-offs were mainly concentrated in Litang and Dafu counties, while food supply and carbon storage in Aba also showed a strong trade-off. The relationships between water supply and habitat quality, soil conservation, and carbon storage service had similar spatial distribution characteristics, with weak trade-offs/synergies concentrated in the northern part of the western Sichuan Plateau, while strong trade-off/synergy relationships were noted in most of the area. Water supply and habitat quality, water supply and soil conservation, and water supply and carbon storage all showed strong trade-off/synergistic relationships in large areas of Litang, Dafu, and Songpan counties. For habitat quality and soil conservation, the synergistic relationships were mainly concentrated in Ruoerge, Dacheng, Litang, and Dege. Habitat quality and carbon storage showed a strong synergy in most areas of the western Sichuan Plateau, while the trade-off was concentrated in Shiqu and Litang. The synergistic relationship between soil conservation and carbon storage was mainly concentrated in Dacheng, Litang, Dafu, and Songpan counties, while the trade-off was distributed in Ruoergai and Jiuzhaigou.

4.3. Ecosystem Service Driver Detection in the Western Sichuan Plateau

4.3.1. Analysis of Factor Detection Results

The factor detection module in Geodetector was used to explore the factors influencing ecosystem services in the western Sichuan Plateau, revealing the degree of influence on ecosystem services from both natural and anthropogenic perspectives. As shown in

Table 2. Detection results of ecosystem service factors of the western Sichuan Plateau.

Ecosystem Services	Annual Precipitation	NDVI	Mean Annual Temperature	Elevation	Slope	Population Density	Land-Use Type
food supply	0.403	0.124	0.169	0.096	0.682	0.328	0.484
water supply	0.967	0.434	0.523	0.154	0.649	0.475	0.018
habitat quality	0.008	0.876	0.026	0.537	0.234	0.009	0.822
soil conservation	0.159	0.228	0.152	0.018	0.672	0.097	0.016
carbon storage	0.652	0.828	0.032	0.318	0.372	0.097	0.016

, different ecosystem services were affected by different driving factors. The results indicated that slope had the greatest impact on food supply with a q-value of 0.682, and some areas in the western Sichuan Plateau had poor soil and were difficult to cultivate, which was not conducive to food supply. Precipitation had the most significant effect on water supply with a q-value of 0.967, while slope had an effect on water supply with a value of 0.649. The water supply improved as the slope slowed down. Habitat quality was mainly influenced by NDVI, land use type, and elevation, with q-values of 0.876, 0.822, and 0.537 respectively. The land type of the western Sichuan Plateau was mainly forest and grassland, with rich plant species and high vegetation cover, which provided a living environment for plants and animals, while some high-altitude areas had a harsh climate, which was not conducive to the survival of plants and animals. The most significant factor influencing soil conservation was the slope with a q-value of 0.672, followed by the NDVI. Vegetation can slow down soil erosion and thus promote soil conservation, while the rest of the drivers had limited influence on soil conservation with relatively low q-values. Carbon storage service was most significantly influenced by the driver NDVI with a q value of 0.828. Areas with a high NDVI index were generally areas with high vegetation cover and strong carbon sequestration capacity, so the carbon storage function was good; precipitation amount also had a significant influence on carbon storage service (0.652), and sufficient precipitation promoted the growth of forest and grass.

4.3.2. Factor Interaction Detection

As shown in

Table 3. Interaction detection results of ecosystem service factors in the western Sichuan Plateau.

Interaction Type	Food Supply	Water Supply	Habitat Quality	Soil Conservation	Carbon Storage
AP∩NDVI	0.319 **	0.969 *	0.694 **	0.109 **	0.836 **
AP∩MAT	0.434 **	0.971 *	0.049 **	0.099*	0.024 **
AP∩ELE	0.496 *	0.970 *	0.358 **	0.090 **	0.350 **
AP∩SL	0.722 *	0.968 *	0.048 **	0.614 *	0.419 **
AP∩PD	0.503 *	0.970 *	0.016 *	0.131 **	0.025 **
AP∩LU	0.511 *	0.971 *	0.700*	0.118 **	0.325 **
NDVI∩MAT	0.223 **	0.538 *	0.127 **	0.101 **	0.337 **
NDVI∩ELE	0.154 *	0.203 **	0.852 *	0.673 **	0.544 *
NDVI∩SL	0.562 *	0.078 *	0.612 **	0.829 **	0.723 **
NDVI∩PD	0.335 *	0.491 *	0.090 **	0.132 **	0.233 **
NDVI∩LU	0.496 *	0.048 *	0.863 *	0.050 **	0.397 **
MAT∩ELE	0.179 *	0.551 *	0.193 **	0.079 **	0.344 **
MAT∩SL	0.562 *	0.535 *	0.054 *	0.195 *	0.022 **
MAT∩PD	0.346 *	0.627 *	0.035 **	0.129 *	0.018*
MAT∩LU	0.492 *	0.533 *	0.401 *	0.110 **	0.095 **
ELE∩SL	0.154 *	0.180 *	0.779 **	0.705 **	0.432 *
ELE∩PD	0.168 *	0.504 *	0.148 **	0.117 **	0.133 **
ELE∩LU	0.512 *	0.178 **	0.914 *	0.066 **	0.395 **
SL∩PD	0.168 *	0.482 *	0.037 *	0.523 *	0.021 **
SL∩LU	0.724 *	0.061 *	0.840 *	0.312 **	0.491 **
PD∩LU	0.501 *	0.485 *	0.623 *	0.172 **	0.292 **

AP denotes annual precipitation, NDVI denotes normalized difference vegetation index, MAT denotes mean annual temperature, ELE denotes elevation, SL denotes slope, PD denotes population density, LU denotes land-use type, * denotes two-factor enhancement, and ** denotes non-linear enhancement.

, the interaction results indicated that most of the factors interacted with each other to produce more significant effects on ecosystem services, and the detection results of the interactions between the factors showed that the main interaction types of the factors exhibited two-factor enhancement and non-linear enhancement. In food supply, the q-values of the interaction between precipitation and its remaining factors were larger than those of the remaining factors when they acted singly on food supply, and the q-values of the interaction between land-use type, slope, and population density were significantly larger than those of the driving factors on food supply services, reaching 0.724 and 0.501, respectively. This result showed that land-use type had an important influence on crop productivity when slope or population density remained stable. The results of the factor interaction of water supply showed that the interaction of precipitation and its remaining factors had the greatest influence on water supply, with q-values greater than 0.965. The degree of influence of the annual mean temperature ∩ the remaining factors also increased, with q-values ranging from 0.533 to 0.627. In habitat quality, NDVI, elevation, and land use type explained more about habitat quality after two interactions, with q-values reaching 0.852, 0.863, and 0.914, respectively, and the q-values of the interactions with their remaining factors also increased. Soil conservation was most influenced by the combination of NDVI and slope with a q-value of 0.829, followed by elevation ∩ slope and elevation ∩ NDVI, and the degree of explanation increased after the interaction. Among the factor interactions of carbon storage service, the degree of explanation of carbon storage service after the interaction of precipitation and NDVI reached 0.836, which was more influential than when the two factors explained carbon storage alone, followed by NDVI ∩ slope, indicating that in the case of the same slope, the higher or lower NDVI had a greater influence on carbon storage. The results of factor interaction detection indicated that ecosystem services in the western Sichuan Plateau were jointly influenced by multiple factors.

5. Discussion

5.1. Ecosystem Services and Their Trade-Off/Synergy Relationships

Ecosystem services in the western Sichuan Plateau from 2000 to 2020 showed a relatively obvious spatial heterogeneity. Soil conservation and food supply mainly showed better services in the east than in the west, because from east to west, the elevation of the western Sichuan Plateau gradually increases, the terrain gradually steepens, desertification occurs in some areas, and the soil is more infertile, making it more difficult for crops to grow. However, as ecological protection was taken seriously, the local government started to promote ecological measures to improve land conditions, while optimizing agricultural production methods, resulting in a significant improvement in food supply services in 2020 compared to 2000. In terms of water supply, the eastern region had a stronger water supply capacity than the western region due to its proximity to the high precipitation area of western China, where high precipitation enhanced the water supply capacity of the eastern part of the western Sichuan Plateau to a certain extent [47]. The generally good spatial characteristics of carbon storage were due to the good natural ecological environment of the western Sichuan Plateau, but the vegetation cover in the southern and northeastern regions had been relatively reduced because of urbanization development and deforestation, resulting in a decrease in carbon storage services in the southern and northeastern regions in 2020 compared to 2000 [48].

The ecosystem services and their relationships in the western Sichuan Plateau remained unchanged from 2000 to 2020, and most of the ecosystem services showed synergistic relationships with each other, indicating that the relationships between ecosystem services on the western Sichuan Plateau were generally stable. Among them, the increase in food supply services and the trade-off between food supply and other services showed that conflicts between food supply and ecological conservation existed objectively, and the growth of human food demand led to the occupation of some forests and grassland by agricultural land, thus affecting the natural environment [49]. However, the trade-off effect has been weakened in recent years, indicating that the implementation of measures such as the ban on overgrazing, and the reforestation projects on the western Sichuan Plateau, has moderated the conflict between food supply and the natural environment.

Meanwhile, the west Sichuan Plateau is located in the transition area between the Qinghai–Tibet Plateau and the Sichuan Basin, and the differences and diversity of climate, topography, and vegetation have led to a spatially heterogeneous distribution of ecosystem services. The spatial heterogeneity of ecosystem services leads to the spatial heterogeneity of ecosystem service trade-offs and synergistic relationships [50]. There is a synergistic relationship between food supply and habitat quality in some regions of the western Sichuan Plateau, such as Litang County and Xinlong County, because grassland animal husbandry and in-forest raising were particularly developed in these regions [51,52]. In recent years, the county government and residents have paid attention to the protection and management of forests and grasslands in order to optimize the transformation of modes of animal husbandry. Forests and grasslands not only provide food and activity space for Tibetan pigs and yaks and other livestock, but also are important influencing factors of habitat quality. In addition, Litang County and Xinlong County attached importance to the implementation of returning farmland to forests and grasslands [48], which also promoted the improvement of habitat quality. In some areas, such as Ruoergai County and Daocheng County, the water supply and carbon storage services showed a trade-off relationship. This was due to the degradation of wetlands, swamps, and land desertification in Daocheng County and Ruoergai County, resulting in the decline of water supply capacity, but much of the swamp was converted into grasslands, which relatively increased the carbon storage capacity [53]. In recent years, with the implementation of wetland restoration projects, afforestation, and other measures [54], wetlands and swamp have been significantly restored.

5.2. Exploration of Driving Mechanism and Suggestions

5.2.1. Exploration of the Driving Mechanism

The goal of eco-sustainable development is primarily the sustainable use of ecosystems to meet human needs through environmental management, so it is important to fully understand the linkages between drivers and ESs in order to optimize the ecological management of the region. According to our results, the ecosystem services of the western Sichuan Plateau were influenced by multiple drivers, among which NDVI, precipitation, and slope were the main drivers of the ecosystem services of the western Sichuan Plateau, which can provide a basis for ecological control of the western Sichuan Plateau. In particular, the most significant effect of NDVI on several ecosystem services indicated that forestland and grassland played an important role in the restoration of the ecological environment. For example, areas with high vegetation cover can provide space for plants and animals to survive, so NDVI had better explanatory power for habitat quality. Second, tree canopies have good rainfall interception capacity, water supply can increase, and vegetation can reduce erosion and stabilize soil structure [55], so habitat quality, water supply, and soil conservation are synergistic.

In terms of agricultural farming, most areas in the western Sichuan plateau have basically been lifted out of poverty, but the standard of living is still relatively low due to the natural topography, slope, etc. The level of urbanization will continue to increase in the future, while urbanization will intensify the impact of human activities on land and ecosystems, resulting in significant ecosystem degradation; thus, there is a need to balance livelihood development and environmental protection.

5.2.2. Suggestions

For regions where opposition exists between urban development and the natural environment, future urban construction should be planned rationally, control over the protection of natural resources should be strengthened [56], and policymakers should try to coordinate the joint development of people’s livelihood and the ecological environment. In addition, it is necessary to enhance people’s awareness of environmental protection and laws, prohibit indiscriminate fishing, strengthen the construction of wild nature protection sites and conservation corridors, and establish or improve existing nature reserves to reduce man-made damage to the ecological environment.

Based on the results, we propose four recommendations for future ecological planning in the western Sichuan plateau region: (1) It is recommended that the western plateau of Sichuan should pay attention to the protection of forestland and grassland, and reasonably promote natural forest and grass planting projects to increase the vegetation cover in the future. (2) Rainwater storage and water conservation irrigation should be implemented in the future to maximize the rational use of precipitation and improve the utilization of water resources in the western Sichuan Plateau. (3) Scientific improvement of agricultural production methods and optimization of the agricultural structure are needed. (4) In the western Sichuan Plateau, natural resources should be used scientifically and reasonably, and local conservation should be adhered to. Policymakers should adjust ecological protection measures in a timely manner according to the actual service supply, so as to improve the natural ecology of the western Sichuan Plateau. Specifically, for example, for Litang County and Xinlong County, it is necessary to scientifically promote in-forest raising and grassland animal husbandry, establish plateau breeding demonstration sites, and then appropriately plant trees and grass to ensure the natural ecology and provide the space and food needed for animal husbandry [51,52]. For Daocheng County and Ruoergai County, the wetland and swamp restoration projects still need to be continued, and afforestation and grassland restoration should be carried out at the same time [54].

5.3. Future Outlook and Limitations

In the future, with the development of the socioeconomic sphere, there will inevitably be conflicts between rapid urbanization and the ecological environment in more regions. Therefore, for regions with a complex natural environment, it is necessary to coordinate urbanization and the natural environment to achieve sustainable development. Exploring the relationship and driving mechanism between ESs has become increasingly important in achieving coordination, because they can help policymakers formulate policies or provide a strong reference for implementing measures [30]. In China, the western Sichuan Plateau is a typical area where there is a serious opposition between urbanization and the natural environment.

The main finding of this study is that in areas dominated by agriculture and animal husbandry, such as the western Sichuan Plateau, food supply and habitat quality may show a synergistic relationship, and ESs and their relationships were greatly affected by forestland and grassland. Forestland and grassland in agricultural and pastoral areas help coordinate urbanization and the natural environment, which proves that with the rapid development of the socioeconomic sphere, the importance of forestland and grassland in coordinating social development with nature and promoting sustainable development should be recognized.

Both this study and previous studies deeply explored the regional ecological status by exploring ecosystem services and their relationships. Although some studies have begun to pay attention to the regional ESs and their relationships in areas where urbanization and the natural environment were in opposition, there were relatively few studies on agricultural and pastoral areas, which also faced the problem of how to coordinate social and economic development with nature. In China, as the ecological barrier, natural resource trove, and ecosystem service provider of Sichuan Province and China, the western Sichuan Plateau plays an extremely important role in the maintenance of regional and national ecological security. The western Sichuan Plateau is also one of the major agricultural and pastoral areas in China. At the same time, the urban construction in the western Sichuan plateau is developing rapidly, which makes the western Sichuan Plateau a typical area with a severe opposition between urbanization and the natural environment. Therefore, the study of the western Sichuan Plateau, a typical agricultural and pastoral area, can provide a reference for other agricultural and pastoral areas in the world where urbanization and nature conflict, and is conducive to promoting regional sustainability.

Previous studies have focused on exploring the changes in ecosystem services and their relationships at a single time point or over a short time. The conclusions explored at a single time point or over a short time were limited, and the suggestions based on these results were not universal. This paper was based on a 20-year interval. The characteristics of and changes in ecosystem services over the past 20 years can reflect the impact of some regional policies or measures. For example, the measures of returning farmland to forests have improved the carbon storage services in the western Sichuan Plateau in 2020 compared with 2000, mainly due to the increase in vegetation coverage. Studying the changes in ecosystem services and their driving mechanisms from the perspective of long time series can help decision-makers judge whether a policy or measure should be continued or improved, or whether a new policy or measure should be implemented.

Therefore, in the future, when exploring the regional ecological status and coordinating the relationship between urbanization and the natural environment, research should be based on the perspective of long time series, which is more conducive to decision-making aimed at promoting regional sustainable development.

The following limitations of this study could be further explored in future studies: First, in this paper, the spatial characteristics of the trade-off/synergy relationships among ecosystem services were only based on the grid metric scale. Thus, in future research, we will combine multiple spatial scales of inquiry to achieve a multi-scale understanding of the relationships among ecosystem services. Second, when using Geodetector to analyze the driving mechanisms of ecosystem services in the western Sichuan Plateau, since the Geodetector mainly analyzes the overall driving mechanism of the region, and there is a slight lack of zonal detection, we only discussed the overall driving mechanism of the western Sichuan Plateau, but not in different areas. We will try to explore the driving mechanism based on more detailed spatial scale detection in future research, so that targeted management measures can be proposed for these areas where urbanization is in conflict with the complex natural environment. Third, there are fewer anthropogenic factors than natural factors, and more suitable anthropogenic factors will be explored in the future. In future studies, the complex relationships of ecosystem services will be further explored based on ecological processes to provide a reference for decision-makers to propose more precise implementation of ecological measures.

6. Conclusions

Based on long time series of multi-source data from 2000–2020 in the western Sichuan Plateau region, this study explored the ecosystem services and their relationships in the region, and delved into the driving mechanism of ecosystem services. The results showed that the spatial heterogeneity of ecosystem services in the western Sichuan Plateau from 2000 to 2020 was significant, and the spatial distribution of some services was higher in the east than in the west, which was attributed to the implementation of environmental protection measures, such as returning farmland to forestland in the east. Over the 20-year period, food supply exhibited trade-offs with water supply, habitat quality, soil conservation, and carbon storage, while water supply, habitat quality, soil conservation, and carbon storage showed synergistic relationships with each other. The trade-off/synergistic relationships among the five ecosystem services showed significant spatial heterogeneity. In our study area, multiple drivers have significant impacts on ESs, with NDVI having the most pronounced effect. Based on our results, we provide ecological control suggestions for these areas where urbanization is in conflict with the complex natural environment, and we make four specific recommendations for the study areas in this paper. In the future, urbanization and increased human activities in more areas will inevitably conflict with the ecological environment, so for areas with complex natural environments, the relationships and driving mechanisms between ESs need to be explored for regional ecological management.