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Journal of Geographical Sciences >

2022 , Vol. 32 >Issue 6: 1059 - 1075

DOI: https://doi.org/10.1007/s11442-022-1985-6

Research article

Ecological changes and the tradeoff and synergy of ecosystem services in western China

  • NIU Linan , 1, 2 ,
  • SHAO Quanqin , 1, 2, * ,
  • NING Jia 1 ,
  • HUANG Haibo 1
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  • 1.Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 2.College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
* Shao Quanqin (1962-), PhD and Professor, specialized in ecological information. E-mail:

Niu Linan (1996-), PhD Candidate, specialized in Geographic Information System applications. E-mail:

Received date: 2022-01-14

  Accepted date: 2022-02-28

  Online published: 2022-08-25

Supported by

Strategic Priority Science and Technology Special Project of Chinese Academy of Sciences(XDA23100203)

National Key Research and Development Program of China(2017YFC0506501)

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Abstract

Since the implementation of the Development of Western Regions in 2000, a series of major ecological construction projects have been implemented, leading to a series of changes in the ecological conditions and ecological services of western China. This study calculated the amount of ecosystem services in total in the western region from 2000 to 2019, and analyzed ecological changes and the characteristics of spatio-temporal variations in ecological services. A relevant analysis method was applied to explore the tradeoff and synergy of service. It was found that the area of settlements and wetland ecosystems in the western region increased significantly from 2000 to 2015, whereas grassland showed a downward trend year by year. The vegetation fraction showed a decreasing belt-like distribution from south to north. It showed a fluctuating increase during 2000 to 2019, with inter-annual and large spatial differences. The water conservation service (WCS) had a slight downward trend from 2000 to 2019, and the main decreasing areas were distributed in southeastern Tibet, the western part of the Three Rivers Source region, and the karst rocky desertification area. The soil conservation service (SCS) showed an increasing but fluctuating trend, with the greatest increases observed in the Loess Plateau region, western Sichuan and Yunnan, northwest Tibet, and southeast Tibet. The windbreak and sand fixation service (SFS) showed a downward trend, and the sharp decline was mainly in the central and western parts of Inner Mongolia, Tibet and parts of northern Xinjiang. Ecosystem supply and WCS, and SCS were mainly synergistic, which were found in areas north of the Qinling Mountains-Huaihe River (QM-HR) line, especially in Ningxia and Inner Mongolia. Ecosystem supply was mainly tradeoffs with SFS, and it was found in the agriculture-pastoral transition zone. The synergistic degree of ecosystem services in areas subjected to ecological engineering policy was greater than that in non-engineering areas. Quantitative assessment of ecosystem service changes and their tradeoffs is helpful for scientific ecological management and maximizing ecological benefits.

Key words： ecosystem services; tradeoff and synergy; western region; Western Development Strategy

Cite this article

NIU Linan , SHAO Quanqin , NING Jia , HUANG Haibo . Ecological changes and the tradeoff and synergy of ecosystem services in western China[J]. Journal of Geographical Sciences, 2022 , 32(6) : 1059 -1075 . DOI: 10.1007/s11442-022-1985-6

1 Introduction

Ecosystem services are products and services that humans obtain directly or indirectly from the ecosystem (Chen et al., 2000; Smith et al., 2013). Protecting the ecosystem and enhancing ecological service functions are of great importance for ensuring ecological security and promoting sustainable development (Wen et al., 2020). The rapid growth of the human population and the associated socioeconomic development have had a considerable impact on the ecosystem, causing substantial change to its macro structure, and driving complex temporal and spatial changes in its service functions (Zhang et al., 2013). Ecosystem status and its service evaluation have become the research focus in China and internationally. In 2001, the United Nations launched the Millennium Ecological Assessment, which represents the first comprehensive assessment of global ecosystems (Reid et al., 2005). In China, national ecosystem status and service evaluations have also been instigated. For example, Wong et al. (2015) established a methodological system for evaluating ecosystem characteristics and ecosystem services.
The types of ecosystem service are diverse and their relationships are intricate, being either tradeoffs or synergies (Barbier et al., 2008; Li et al., 2013). Studying the tradeoff or synergy between different ecosystem services to strengthen the understanding of ecosystem services and support corresponding ecological decisions can improve the overall benefits of the ecosystem (Dai et al., 2015). Xue et al. (2015) used the InVEST model, cellular automata, and other models to dynamically analyze the balance relationship among food supply, soil conservation, and habitat quality in northeastern Iran. Zhu et al. (2020) studied the tradeoff and synergy between forage supply and ecosystem services such as windbreak and sand fixation and water conservation in key ecological function areas. Fu et al. (2016) concluded that land use has a positive effect with soil conservation service (SCS) and a negative effect with water production. However, earlier studies on ecosystem tradeoff and synergy concentrated primarily on small regional scales, and few studies have addressed the macro scale (Zhao et al., 2018). To protect and restore the ecosystem, China has initiated major ecological projects such as the Three-North Shelter Forest (TNSF) Program and the Grain for Green Project (GGP), which have had an important impact on ecosystem services (Shao et al., 2017). Analyzing and studying the tradeoff among ecosystem services in different ecological projects would have value as scientific reference for adjustment (implementation) of current (future) ecological projects.
The western region of China is an important part of the Two Screens and Three Belts ecological security strategy. The region, which is the source of many major rivers and an important area of resource reserves, is closely related to ecological security issues. However, the western region has a fragile ecological environment and poor ecosystem stability that make ecological protection and economic development difficult to coordinate (Chen et al., 2013; Li et al., 2019; Ren et al., 2019). In 1999, China proposed the strategic decision to implement the Western Development Strategy to address the backward situation in the western region of the country. In October 2000, the area of the Western Development Strategy was delineated and implementation of the plan commenced. Since the initial proposal of the Western Development Strategy, ecological environmental protection and ecological engineering construction have been regarded as the focus of western development. Many studies have investigated the ecological environment and ecosystem services in the western region. For example, Zhang et al. (2020) analyzed the dynamic changes of the normalized vegetation index of the alpine grassland on the Qinghai-Tibet Plateau over the past 30 years, reflecting the changes in the grassland ecosystem. Zhou (2019) quantitatively evaluated the effect of SCS in representative areas of the Loess Plateau. Gao et al. (2019) calculated the spatial tradeoff of ecosystem services and investigated the characteristics of differentiation. However, few studies have considered the changes in the ecological conditions of the entire western region and the characteristics of ecosystem services in the engineering area. The western region occupies an important position in China with its long-term and dense ecological construction projects. Therefore, to help formulate and manage ecological policies scientifically, this study explored the characteristics of the ecological changes in the western region, the temporal and spatial changes of ecosystem services, and the tradeoff and synergy between supply services and regulation services over the 20 years since the initiation of the Western Development Strategy.
Using meteorological, remote sensing, and soil data, this study adopted the modified soil erosion equation (RUSLE model) and the modified soil wind erosion equation (RWEQ model) to calculate the ecosystem services of western China during 2000-2019, analyze their temporal and spatial evolution, and explore the characteristics of the tradeoff and synergistic relationships between supply services and regulation services. The derived results provide scientific support for implementation/adjustment of large-scale regional-national ecological security strategies.

2 Materials and methods

2.1 Study area

The administrative region of western China, which includes Qinghai, Tibet, Ningxia, Xinjiang, Gansu, Shaanxi, Sichuan, Yunnan, Chongqing, Guangxi, Guizhou, and Inner Mongolia, is located in the middle of the Asian continent and covers a total area of 686 × 104 km2. It accounts for approximately 71.5% of the land area of China. The terrain in this region varies markedly and the climatic conditions differ substantially. Most of the region has harsh natural environmental conditions and experiences extreme weather frequently. The ecosystem has strong sensitivity and poor stability (Cheng et al., 2000), and the increased interference of climate change and unreasonable use attributable to human activities have caused serious degradation of the ecological environment and intensification of ecological vulnerability (Zhao et al., 2012).

2.2 Data sources

The data used in this study comprised meteorological, remote sensing, and land use data. Meteorological data obtained from the China Meteorological Data Net China Surface Climate Data Daily Value Dataset (V3.0) included temperature and daily rainfall data (1951-2019) with a 1-km spatial resolution. Soil data were acquired from the 1:1 million soil database of the Chinese Academy of Sciences Resources and Environment Data Center website. Terrain data comprised ground digital elevation model data with a 90-m spatial resolution derived from the Geospatial Data Cloud SRTMDEM. Normalized difference vegetation index (NDVI) raster data (2000-2019) were derived from the MODIS-NDVI, obtained at 16-d intervals with a 1-km spatial resolution. Land use/land cover data, acquired from the Earth System Science Data Sharing Platform of the Institute of Geographic Sciences and Natural Resources Research (Chinese Academy of Sciences), comprised Landsat-8 OLI, GF-2, and other remote sensing satellite data. This study used high-resolution remote sensing data, unmanned aerial vehicle data, ground survey data, and an observation technology system, in combination with the human-computer interaction interpretation method based on geoscience knowledge, to build a Chinese Land Use Database (Liu et al., 2018) with a 1-km spatial resolution for four periods: 2000, 2005, 2010, and 2015. The net primary productivity (NPP) data of vegetation (2000-2019) were provided by the United States Geological Survey MODIS-NPP product MOD17A3H dataset with a 500-m spatial resolution.

2.3 Methods

2.3.1 Fractional vegetation cover

The fractional vegetation cover (FVC) was calculated on the basis of the NDVI through pixel dichotomy (Jiapaer et al., 2011). The formula can be expressed as follows:
$F V C=\frac{\left(N D V I-N D V I_{\text {soil }}\right)}{\left(N D V I_{\max }-N D V I_{\text {soil }}\right)}$,
where NDVImax is the NDVI value of pure vegetation pixels (an NDVI value at 95% is taken as the NDVI value of pure vegetation pixels, and values higher than this value are replaced by the maximum value), and NDVIsoil is the NDVI value of bare soil pixels (an NDVI value at 5% is taken as the NDVI value of bare soil pixels, and values lower than this value are replaced by the minimum value).

2.3.2 Soil conservation service

The SCS was measured on the basis of the amount of soil conservation, which reflects the difference between the potential soil erosion modulus without vegetation cover and the actual soil erosion modulus (Qiang et al., 2017). The soil erosion modulus was calculated using the RUSLE model (Wischmeier et al., 1978). The formula can be expressed as follows:
$ S C=R \times K \times L S \times(1-C) \times P $,
where SC is the amount of soil conservation (t·ha-1·yr-1); R is the rainfall erosivity factor (MJ·mm·ha-1·h-1·yr-1), which is based on daily rainfall estimated using the semimonthly rainfall erosivity model (Zhang et al., 2002); K is the soil erodibility factor (t·h·MJ-1·mm-1), which uses the method in the EPIC model (Williams, 1990) that is amended following Zhang et al. (2008); LS is the slope length and slope factor, calculated using the method of McCool et al. (1987) and Liu et al. (1994); C is the vegetation cover factor, calculated using the method of Cai et al. (2000); and P is the water and soil conservation measure factor. Parameters LS, C, and P are all dimensionless.

2.3.3 Water conservation service

The water conservation service (WCS) was measured on the basis of the amount of water conservation. The water conservation of both forest and grassland ecosystems was estimated using the precipitation storage method (Zhao et al., 2004). The formula can be expressed as follows:
$WC=A \times {J} \times{E}$,
$J=J_{0} \times {W}$,
where WC is the amount of water conservation of the forest and grassland ecosystems (m3), A is the ecosystem area (ha), J is the flow rate rainfall (mm), Jo is annual rainfall (mm), and W is the proportion of total rainfall. According to the Qinling Mountains-Huaihe River (QM-HR) line, the country can be divided into northern and southern parts. According to the rainfall distribution, the value of parameter W was set at 0.4 in the northern region and 0.6 in the southern region. Parameter E is the coefficient of runoff reduction of the ecosystem in comparison with bare land. The value of E for forest was obtained from the literature (Wu et al., 2017), while that for grassland (Eg) was calculated on the basis of grassland vegetation coverage (fc) (Zhu et al., 2003). The characteristics of downstream water flow of high cold meadow under different vegetation coverage conditions were taken from Li et al. (2006). The WCS of wetland was based on the research results of Meng et al. (1999).
$E_{g}=-0.3187 \times { f_{c}}+0.36403$.

2.3.4 Wind prevention and sand fixation service

The wind prevention and sand fixation service (SFS) was measured on the basis of the amount of sand fixation, which is the difference between wind erosion under bare soil conditions and wind erosion under conditions of vegetation cover. The RWEQ model was used to calculate the wind erosion modulus in wind erosion areas. The formula can be expressed as follows:
$ Q_{\max }=109.8 \times\left(W F \times E F \times S C F \times K^{\prime} \times C O G\right)$,
$ s=150.71 \times\left(W F \times E F \times S C F \times K^{\prime} \times C O G\right)^{-0.3711}$,
$ S L=\frac{2 x}{s^{2}} Q_{m a x} e^{-\left(\frac{x}{s}\right)^{2}}$,
where SL is the wind erosion modulus; x is the length of the plot (m); Qmax is the maximum sand transport capacity of the wind (kg m-1); s is the length of the key plot (m); WF is the meteorological factor, for which the specific data processing and calculation process were based on the results of Gong et al. (2014a); EF and SCF are the soil erodibility factor and the soil crust factor, respectively, calculated using the method of Fryear et al. (2000); K′ is the soil roughness factor, obtained using the method of Saleh et al. (1993); and COG is a vegetation factor that includes flat and standing crop residue and the vegetation canopy. The difference between the potential soil wind erosion under bare soil conditions and the actual soil wind erosion under conditions with vegetation cover represents the amount of sand fixation. The formula can be expressed as follows:
$ S L_{s v}=S L_{s}-S L_{v}$,
where SLsv, SLs, and SLv represent the amount of sand fixation, the potential amount of wind erosion, and the actual amount of wind erosion, respectively.

2.3.5 Tradeoff and synergy analysis

Using NPP, SCS, WCS, and SFS data for the western region (2000-2019), the correlation coefficients between the two groups of ecosystem services were calculated separately using the pixel-by-pixel spatial correlation analysis method. The tradeoffs and synergies between ecosystem supply and the regulating services were measured according to the positive and negative correlation coefficients and the absolute value of the correlation coefficients, and the relationships between ecosystem services were assessed using the T-test to weight the significance of each relationship. The formula can be expressed as follows:
$ R=\frac{\sum(x-\bar{x})}{\sqrt{(x-\bar{x})^{2} \sum(y-\bar{y})^{2}}}$,
$ T=\frac{R}{\sqrt{\frac{1-R^{2}}{n-2}}}$,
where R is the correlation coefficient. If R is positive, there is a synergistic relationship between the two services; otherwise, it is a tradeoff relationship. If R is 0, there is no correlation. The greater the absolute value, the stronger the correlation, i.e., the greater the degree of synergy or tradeoff. Parameters x and y are two ecosystem service variables, and i represents the i-th year. The null hypothesis test of the T-test method of the correlation coefficient was used to determine the significance of the relationship between the ecosystem services. When |T|< T0.05,18, i.e., p > 0.05, the null hypothesis is established and the correlation result is not significant. When T0.05,18 ≤|T|< T0.01,18, i.e., 0.01 < p ≤ 0.05, the null hypothesis is rejected and the correlation result is more significant. When |T|≥ T0.01,18, i.e., p ≤ 0.01, the null hypothesis is rejected and the correlation result is extremely significant.

3 Results and analysis

3.1 Changes in ecological status

Owing to the limited availability of data on land use change and the small difference in land use change annually, this study used four phases of land use data (2000, 2005, 2010, and 2015) to reflect the changes in ecosystem structure in the western region over the past 20 years.

3.1.1 Changes in macro structure of ecosystems

It can be seen from Table 1 that the terrestrial ecosystem of the western region during 2000-2015 was dominated by grassland ecosystems, followed by desert ecosystems, and that settlement ecosystems accounted for the smallest proportion. The most obvious interannual change was in the area of the settlement ecosystems with an overall change rate of 320.43%, although the greatest increase was between 2010 and 2015. Water bodies and wetland ecosystems also increased considerably with a change rate of 38.72%. The area of grassland ecosystems declined gradually with an overall change rate of -12.60%. The area of desert ecosystems remained broadly stable, although the area of other ecosystems (comprising mainly bare land, bare rock, and gravel) increased.
Table 1 Statistics of changes in macro structure of ecosystem areas during 2000-2015 (104 km2)
Ecosystems 2000 2005 2010 2015 Change area from 2000-2015 Rate of change (%)
Cropland 66.38 67.86 68.20 70.19 3.81 5.74
Forest 112.97 116.10 115.78 115.57 2.60 2.30
Grassland 281.18 272.65 266.45 245.76 -35.42 -12.60
Water bodies and wetland 19.06 21.22 19.78 26.44 7.38 38.72
Settlement 1.37 1.57 2.12 5.76 4.39 320.43
Desert 127.63 128.36 127.59 128.68 1.05 0.82
Other ecosystems 63.15 63.08 72.15 75.65 12.50 19.79
During 2000-2015, the western region was dominated by conversion among grassland, forest, and desert (Table 2). The area of grassland decreased by 86.53 × 104 km2 through conversion to forest, desert, and other ecosystems, which accounted for 21.00%, 24.44%, and 29.59% of the reduced area, respectively. The increased area of grassland was converted mainly from forest, desert, and other ecological systems, which accounted for 24.84%, 20.34%, and 33.10% of the increased area, respectively. The area of cropland converted to water bodies and wetland was 1.09 × 104 km2, that converted to grassland was 8.38 × 104 km2, and that converted to settlement ecosystems was 2.98 × 104 km2, which represented the main source of the increase in the area of settlement ecosystems.
Table 2 Change in terrestrial ecosystem types during 2000-2015 (104 km2)
2000 2015
Cropland Forest Grassland Water bodies and wetland Settlement Desert Others
Cropland 47.74 5.83 8.38 1.09 2.98 0.26 0.09
Forest 8.35 89.31 12.69 1.53 0.31 0.27 0.42
Grassland 11.74 18.17 194.60 8.84 1.02 21.15 25.61
Water bodies and wetland 0.52 0.32 2.62 11.93 0.09 0.83 2.72
Settlement 0.19 0.04 0.09 0.05 0.97 0.03 0.004
Desert 1.44 0.36 10.39 1.74 0.35 105.82 7.52
Others 0.20 1.48 16.91 1.21 0.04 4.06 39.23

3.1.2 Changes in vegetation coverage

It can be seen from Figures 1 and 2 that vegetation coverage in the western region during 2000-2019 showed a fluctuating trend of increase (R2 = 0.6958, p < 0.01). In 2019, it increased by 2.79% in comparison with the level of coverage in 2000. Vegetation coverage was lowest (37.33%) in 2000 and reached its peak (40.54%) in 2018. The average rate of growth of vegetation coverage in the western region during 2000-2019 was 12.15%. According to regional characteristics and calculation results, five levels of change were defined: obvious deterioration (≤-15%), slight deterioration (-15% to -5%), broadly stable (-5% to 5%), slight improvement (5% to 15%), obviously improvement (≥ 15%). The area of obvious improvement in vegetation coverage, which accounted for 39.36% of the total area of the western region, is located in southern and eastern parts, i.e., primarily on the Yunnan-Guizhou and the Loess plateaus. The broadly stable area which accounted for 31.21% of the total area, is located in the west, i.e., mainly in the desert areas of the Tarim Basin. The area with obvious deterioration in vegetation coverage, which accounted for 8.5% of the total area, is located in southwestern and northern parts of the study area, i.e., mainly concentrated on the Qinghai-Tibet Plateau and certain parts of the Inner Mongolia Plateau.
Figure 1 Change in fractional vegetation cover (FVC) and its trend in western China during 2000-2019
Figure 2 Spatial distribution of fractional vegetation cover (FVC) trend change in western China during 2000-2019

3.2 Spatial and temporal changes of ecosystem services

It can be seen from Figures 3 and 4a that vegetation NPP in the western region showed a stable increasing trend (p < 0.01) during 2000-2019. The average vegetation NPP in 2000 was 230.15 gC/m2, while that in 2019 was 275.74 gC/m2, an increase of 19.81%. The area of increase is located mainly in eastern parts of the region, consistent with areas in which vegetation has improved considerably.
Figure 3 Changes of ecosystem services in western China during 2000-2019
Figure 4 Spatial change of ecosystem services in western China during 2000-2019
During 2000-2019, there was a slight downward trend in WCS per unit area (p < 0.01). There was a slight decrease in 2019 in comparison with 2000, and the areas with spatial reduction are distributed mainly in southeastern Tibet, west of the source of the Three Rivers, western parts of the Sichuan-Yunnan Forest area, the Guangxi-Guizhou-Yunnan karst rocky desertification area, the Wuling Mountain area, and eastern parts of the Qinba and Dabie mountains. The SCS per unit area fluctuated with an increasing trend (p < 0.01). In 2000, the SCS per unit area was 20.21 t/ha, while that in 2019 was 43.31 t/ha, an increase of 114.30%. The areas with spatial increase are located mainly on the Loess Plateau, the forest areas of western Sichuan and Yunnan, and northwestern, southern, and southeastern Tibet. The areas with spatial reduction are relatively scattered, but are distributed mainly in southwestern parts of the region. The SFS per unit area showed a downward trend (p < 0.01). In 2000, the SFS per unit area was 23.01 t/ha, while that in 2019 was 18.72 t/ha, a decrease of 18.64%. The areas with sharp spatial decline are located mainly in central and western parts of Inner Mongolia, Tibet, and parts of northern Xinjiang, while the areas with spatial increase are located mainly in eastern parts of the Da Hinggan area and parts of the western Qilian Mountains (Figures 3 and 4b-4d).

3.3 Ecosystem services tradeoff and synergy

3.3.1 Ecosystem supply and WCS

Ecosystem services data from 2000-2019 were used to calculate the correlation between vegetation NPP and WCS in the western region. As shown in Figure 5, most areas showed synergistic and uncorrelated relationships. The area of synergy accounted for 42.23%, of which the area with extremely significant and significant synergistic relationships accounted for 17.91%. The area with tradeoff relationships accounted for 21.34%, of which the area with extremely significant and significant tradeoff relationships accounted for 3.10%; the area of uncorrelated accounted for approximately 36.43%. Generally, areas with tradeoff relationships are distributed mainly to the south of the QM-HR line, especially in Sichuan, Chongqing, and Yunnan, whereas areas with synergistic relationships are distributed mainly to the north of the QM-HR line, especially in Ningxia and Inner Mongolia (Figure 6).
Figure 5 Spatial distribution of the relationship between ecosystem supply and water conservation service (WCS) in western China during 2000-2019
Figure 6 Areal proportion of tradeoff and synergy between ecosystem supply services and water conservation service (WCS) in western China during 2000-2019

3.3.2 Ecosystem supply and SCS

Ecosystem services data from 2000-2019 were used to calculate the correlation between vegetation NPP and SCS in the western region. As shown in Figure 7, most areas showed synergistic and uncorrelated relations. The areas with synergistic relationships accounted for 52.87%, of which areas with extremely significant and significant synergistic relationships accounted for 23.84%. The area of tradeoff relationships accounted for 12.34%, of which the area with extremely significant and significant tradeoff relationships accounted for 0.51%; the area of uncorrelated accounted for approximately 34.79%. Generally, areas with synergistic relationships are located mainly in eastern parts, and areas with tradeoff relationships are located mainly on the Qinghai-Tibet Plateau. In terms of extremes, Ningxia has the highest proportion of extremely significant synergy, and there are almost no tradeoff relationships in Inner Mongolia. Tibet has the highest proportion of tradeoff relationships, accounting for approximately one third of the total (Figure 8).
Figure 7 Spatial distribution of the relationship between ecosystem supply and soil conservation service (SCS) in western China during 2000-2019
Figure 8 Areal proportion of tradeoff and synergy between ecosystem supply services and soil conservation service (SCS) in western China during 2000-2019

3.3.3 Ecosystem supply and SFS

Ecosystem services data from 2000-2019 were used to calculate the correlation between vegetation NPP and SFS in the western region. As shown in Figure 9, most areas showed tradeoff relationships, accounting for a total area of 35.34%. Among them, areas with extremely significant and significant tradeoff relationships accounted for 8.35%. Areas with synergistic relationships accounted for 19.29%, of which the area with extremely significant and significant synergistic relationships accounted for 1.55%. In terms of spatial distribution, areas with tradeoff relationships are distributed mainly in northern arid/semiarid areas such as the farming and pastoral zone on the Inner Mongolia Plateau and Ningxia. Areas with synergistic relationships are distributed mainly in the regions with high forest coverage in northern parts of the Da Hinggan area. Among the various provinces and regions, Shaanxi has the highest proportion of tradeoff relationships, followed by Ningxia and Inner Mongolia, with tradeoff relationships accounting for 88.46% and 52.02%, respectively (Figure 10).
Figure 9 Spatial distribution of the relationship between ecosystem supply and wind prevention and sand fixation service (SFS) in western China during 2000-2019
Figure 10 Areal proportion of tradeoff and synergy between ecosystem supply services and wind prevention and sand fixation service (SFS) in western China during 2000-2019

3.3.4 Characteristics of tradeoff and synergy in ecosystem services of different ecological engineering regions

The tradeoff and synergy of ecosystem services in different ecological engineering areas are different. This study considered the main ecological engineering projects in the western region (the TNSF Program, Natural Forest Protection (NFP) Project, GGP, and Returning Grazing Land to Grassland Project (RGLGP)) to explore the characteristics of tradeoff and synergistic relationships in ecosystem services of different ecological projects. Among the ecosystem supply and SCS in different project areas, NFP has the largest area of synergistic relationships (69.87%), and the WGRG has the largest area of tradeoff relationships. Among the ecosystem supply and WCS, NFP has the largest areas of both synergistic and tradeoff relationships. Among the ecosystem supply and SFS, NFP has the largest area of tradeoff relationships. In relation to the different engineering areas shown in Figure 11, it can be seen that the ecosystem supply and both WCS and SCS have more synergy and less tradeoff, while the ecosystem supply and SFS have more tradeoff and less synergy. Calculation of the spatial average correlation coefficient revealed that the supply services and WCS of each project have synergistic relationships, and the average degree of synergy in decreasing order is as follows: TNSF (0.17) > NFP (0.16) > GGP (0.13) > WGRG (0.11); the degree of synergy in areas without engineering projects is very low (0.01). The supply services and SCS of each engineering area also have synergistic relationships, and the average degree of synergy in decreasing order is as follows: NFP (0.28) > GGP (0.22) > TNSF (0.21) > WGRG (0.16). The degree of synergy in areas without engineering projects is also much lower than that in ecological engineering areas. In addition to the WGRG, the NPP of other ecological engineering areas has a tradeoff relationship with SFS. Ecological projects, especially afforestation projects, have strengthened the synergistic relationships between NPP and both WCS and SCS. With increase of NPP, both WCS and SCS have also increased.
Figure 11 Areal proportion of tradeoff and synergy of ecosystem services in different ecological engineering areas of western China during 2000-2019

4 Discussion

The tradeoff and synergy between long-term ecosystem supply and regulation services is of great importance for ecosystem management and regional sustainable development (Gao et al., 2019). On the basis of changes in the ecological status in the western region of China and evaluation of ecosystem services, obvious regional differences were found in the effectiveness of ecological protection during implementation of the Western Development Strategy. In certain regions, the trend of ecological degradation has not been fundamentally reversed, while ecosystem functions in some other regions are out of balance. The ecological status of the Loess Plateau, southwest mountainous and hilly areas, southeastern Tibet, and eastern Inner Mongolia has improved substantially and ecosystem service functions have been steadily improving. However, grassland areas such as central Inner Mongolia and central and western parts of the Qinghai-Tibet Plateau have been affected by climate change, overgrazing, and reduction of vegetation coverage, and the decline of ecosystem services in these areas has not been fundamentally reversed. The results reflect that in the vast areas of degraded grassland, although important measures such as ecological management projects have been undertaken, the changes in some areas have not met expectations. Therefore, it is urgent that new governance strategies be adopted or existing management measures be adjusted.
The ecosystem service calculations in this study were all performed using current commonly used methods. However, the actual observational data support was inadequate and a large amount of measured data will be needed for supplementary correction (Chen et al., 2004; Tian et al., 2020). In the future, field observation work will be increased to obtain adequate measured data to support the research results. In this study, synergies were found between ecosystem supply and regulation services, WCS, and SCS. Greater synergy was found in ecosystem services in areas with ecological projects such as the TNSF, NFP, GGP, WGRG in comparison with non-engineering areas. Afforestation projects can affect the change of vegetation coverage, which can then affect ecosystem services (Wang et al., 2019) and have certain promotional effects on strengthening synergy and achieving ecological management goals. Areas with SFS decline are located mainly in the arid desert areas of Xinjiang. According to earlier studies, the amount of SFS obtained through comparison with the amount of wind erosion on extremely degraded land depends on the relative magnitude of changes in wind erosion of different ecosystem types. In areas where vegetation coverage is above (below) moderate, positive (negative) correlation was found between increased vegetation coverage and the amount of SFS. Therefore, improvement of vegetation coverage does not necessarily mean that the SFS capability is improved (Gong et al., 2014b; Zhu et al., 2020; Huang et al., 2021). Areas with a tradeoff relationship between NPP and SFS are distributed mainly in the arid and semiarid areas of the northern wind erosion area, whereas synergistic relationships are found in areas with higher forest coverage such as at the northern end of Da Hinggan. On the one hand, dry and semiarid areas have dry climatic conditions and mainly meadow and low shrub vegetation. Thus, the vegetation has low NPP, which might lead to a tradeoff relationship between NPP and SFS. On the other hand, in project areas, the relationship between NPP and SFS is mainly a tradeoff relationship, which reflects the ecological effects of different ecological restoration measures (Cao et al., 2011). The tradeoff relationship between ecosystem supply services and SFS in the western region is an aspect of ecological management that should be investigated in the future to further reduce the negative impact of human activities on ecosystem services.

5 Conclusions

This study investigated the changes in the ecological status and the tradeoff and synergy mechanisms of ecosystem services in the western region of China during 2000-2019. The major conclusions of the study are as follows.
(1) The rate of change of the settlement ecosystem in the western region was 320.43%, while the area of grassland ecosystems declined annually. The ecosystem structure change was dominated by conversion between grassland, forest, and desert.
(2) During 2000-2019, vegetation coverage showed a fluctuating upward trend. Areas with obvious improvement in vegetation were located on the Yunnan-Guizhou and Loess plateaus. Areas with obvious deterioration in vegetation were concentrated primarily on parts of the Qinghai-Tibet and Inner Mongolia plateaus. Vegetation NPP showed an obvious upward trend, the WCS had a slight downward trend, SCS had a fluctuating upward trend, and SFS had a downward trend. Generally, ecosystem services within the region have improved.
(3) The relationships between ecosystem supply services and both WCS and SCS were mainly synergistic. Areas with synergistic relationships were distributed mainly to the north of the QM-HR line, especially in Ningxia and Inner Mongolia. The ecosystem supply service and SFS in the wind erosion area generally had a tradeoff relationship.
(4) The ecosystem services of the TNSF, NFP, GGP, and WGRG regions have greater synergy than in non-engineering areas. Ultimately, ecological construction has had a positive impact on regional ecosystem services.

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