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Article

Designing a Sustainable Development Path Based on Landscape Ecological Risk and Ecosystem Service Value in Southwest China

by
Yuying Zhang
1,
Rongjin Yang
2,
Xiuhong Li
1,3,*,
Meiying Sun
2,
Le Zhang
2,
Yanrong Lu
1,
Lingyu Meng
1,
Yunzhi Liu
1 and
Chen Wang
1
1
State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
2
Chinese Research Academy of Environmental Sciences, Beijing 100012, China
3
Joint Center for Global Change Studies (JCGCS), Beijing 100875, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(4), 3648; https://doi.org/10.3390/su15043648
Submission received: 9 January 2023 / Revised: 8 February 2023 / Accepted: 14 February 2023 / Published: 16 February 2023
(This article belongs to the Section Social Ecology and Sustainability)
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Versions Notes

Abstract

:
Rapid urban expansion and economic development lead to the deterioration of ecosystems, which not only aggravates regional ecological risks but also leads to the degradation of ecosystem functions. It is of great significance to rationally divide regions and provide targeted management strategies for realizing the sustainability of regional economic development and ecological maintenance. Taking southwest China (Sichuan, Yunnan, Guizhou and Chongqing) as an example, land use data from 2000, 2010 and 2020 were used to evaluate the value of landscape ecological risk (LER) and ecosystem services, and comprehensive zoning was divided according to their spatial correlation. The socio-economic development characteristics of each zone were analyzed, and differentiated and targeted sustainable development paths were proposed. The results showed that the overall LER level of southwest China increased, and the gap of internal LER narrowed gradually. The ecosystem service value (ESV) per unit area showed an increasing trend, but the core metropolitan areas and northwest Sichuan had little change. According to the differences in population, industrial structure and land use, the low-ESV zone was densely populated, while the high-ESV zone was sparsely populated, and the population from the high-LER zone gradually migrated to the low-LER zone. The economic development of the low-ESV zone was better than that of the high-ESV zone, and secondary industry was an important driving force of regional economic development. Large-scale forestland can alleviate the LER, but the increase in cultivated land and grassland further aggravated the LER. According to the social and economic characteristics of each zone, this study put forward a differentiated development strategy for southwest China and also provided reference for the coordinated development of ecological protection and social economy in other key ecological regions.

1. Introduction

Since entering the 21st century, with the rapid growth of population and the acceleration of urbanization and industrialization, human production and living standards have been greatly improved, and the disturbance to the natural ecosystem has been continuously increased [1,2]. The drastic change in land use and the unreasonable use of land resources have seriously affected the landscape pattern and the structure and function of ecosystems, which has led to the gradual decline of ecosystem services, intensified ecological risks and seriously threatened regional sustainable development [3,4]. Faced with the fact that ecological and environmental problems are gradually intensifying, the Chinese government has proposed to take the road of “new urbanization”, emphasizing the construction of ecological civilization, strengthened protection and management of ecosystems, so as to coordinate the sustainable development of society, the economy and ecological environment. Therefore, how to choose a targeted sustainable development path to reduce regional ecological risks and maintain natural ecosystem services is of great significance to solving the contradiction between regional development and ecological protection.
Ecological risk reflects the possibility that external pressures such as human activities or natural disasters will have a negative impact on the ecosystem [5]. At the end of the 20th century, with the improvement and development of landscape ecology theory, landscape ecological risk (LER) assessment has gradually become a new research focus in ecology and geography [6,7]. Different from traditional ecological risk assessment methods, LER assessment is based on the change characteristics and succession rules of the landscape pattern and its components, revealing the spatial heterogeneity and scale effect of ecological risk and comprehensively evaluating the direct and cumulative effects of various risk factors in the landscape [8,9]. In recent years, scholars have carried out research on LER assessment in cities [10], watersheds [11], wetlands [12], coastal areas [13] and key risk control areas (such as industrial mining areas [14] and nature reserves [15]) and provided reference for ecosystem planning and management by analyzing the relationship between LER and economic development. Karimian et al. found that high-value landscape ecological risk areas in the upper reaches of the Dongjiang River Basin were mainly concentrated in the urban center, and population density was the main driving force of LER [16]. Ai et al. observed that human activities were increasingly influencing regional landscape patterns and ecosystems, with population density and distance to urban centers being the main driving factors [17]. Through land use and LER assessment, Ji et al. proposed that the ecological risk of Chaoyang County, with high forest coverage, was mainly affected by the expansion of construction land and large-scale deforestation [18]. These studies mainly focus on quantifying and evaluating the regional LER level and its socio-economic driving force but lack attention to the process and function of the ecosystem, which is difficult to support landscape ecological security and spatial planning management construction [19,20].
Ecosystem services are the benefits that human beings directly or indirectly obtain from the ecosystem, which are of great value to human well-being [21,22]. After Costanza et al. proposed the ecosystem service value (ESV) assessment method [23] and the United Nations launched the Millennium Ecosystem Assessment Project [24], the impact of human activities on ecosystem structure, process, service and human well-being has become one of the main research directions of ecosystem services. At present, a large number of studies have analyzed the impact of human activities on ecosystems from population, economic development, industrial structure, land use and other aspects [25,26,27]. Arowolo et al. argued that the increase in Nigeria’s total ESV as a result of cultivated land expansion appears to be economically beneficial, but continued loss of climate and hydrological regulation services cause significant economic losses that may be more than the gains from cultivated land development [28]. Zhou et al. analyzed the relationship between urbanization level and ecosystem services in the Beijing–Tianjin–Hebei urban agglomeration and found that land and population urbanization are the main driving forces affecting ESV [29]. Kuang et al. pointed out that the added value of primary industry had a significant impact on ESV by analyzing the relationship between ESV and socio-economic indicators in western Hunan [30]. Existing research on ecosystem services is relatively mature, mainly focusing on value evaluation and driver analysis. Most of the research contents are the value changes caused by a change in landscape type, and the impact of the landscape pattern vulnerability and fragmentation on the ecosystem has not been fully considered [31], especially in mountainous areas with fragile natural conditions and important ecosystem services [32].
In order to alleviate the negative impact of regional development and human disturbance on regional ecological sustainability, spatial zoning aiming to regulate disruptive activities has been an effective ecological protection measure [33]. In essence, zoning is a division method based on ecological characteristics or socio-economic development potential. It is an effective way to provide regional management strategies to promote sustainable development. Ecological zoning has also been an important means of ecosystem management in China. The state has issued the Technical Guidelines for Delineating National Ecological Red Lines and the Guiding Opinions on the Overall Delineation and Implementation of Three Control Lines in Territorial Space Planning, gradually forming a comprehensive management system for controlling the intensity of human activities [34,35]. However, ecological zoning is still being explored, and the division method of ecological spatial zoning has not yet formed a unified standard system [36]. Some scholars divided management areas based on a single evaluation index. Freudenberger et al. identified the priority areas of biodiversity conservation on the landscape scale by calculating the global ecosystem function index [37]. According to the order of ecological risk level from low to high, Wang et al. divided Baishuijiang Nature Reserve into a core area, buffer area and experimental area [15]. In addition, the multi-dimensional evaluation system was constructed to divide the comprehensive attribute zoning. Gong et al. integrated LER and ESV assessment methods to divide ecological function zones and designed and proposed differentiated ecological management strategies to reduce risks and enhance ecosystem services [38]. Zhang et al. zoned in combination with the spatial characteristics of LER and ecosystem services, aiming to improve the sustainable development of the Xi‘an metropolitan area [39]. Compared with single evaluation index zoning, multi-dimensional comprehensive zoning can more clearly display the combination state and coordination between the multiple systems in the region. Therefore, we conduct comprehensive zoning by combining the two evaluation systems of LER and ESV, exploring the socio-economic development differences of each zone, so as to provide scientific reference and flexible planning for realizing the regional sustainable development of LER reduction and ESV enhancement.
Southwest China is rich in ecological and biological resources. It is not only a high-value area of ecosystem services in the Yangtze River Basin, but also one of the important ecological security barriers in China [40]. However, the ecological environment in this region is fragile and sensitive, with multiple landforms and a lack of land resources, resulting in different economic development modes and ecological conditions of counties (cities or districts) in southwest China [41]. With the Western Development policy put forward by the state in 2000, the process of urbanization and industrialization in southwest China has accelerated, the rapid transformation of land use types has caused changes in the overall landscape pattern and the deterioration of regional ecosystem service function [42,43]. Therefore, differentiated and targeted sustainable development strategies should be formulated based on the ecological environment status and economic development level of different regions to alleviate the conflict between ecological protection and economic promotion.
LER and ESV are two evaluation methods of ecosystems. The purpose of LER is to measure whether landscape types have stability in structural composition and are vulnerable to human interference, focusing on the internal stability of the ecosystem. The purpose of ESV is to measure the service function provided by the ecosystem composed of different landscape types in monetary form, focusing on the external value. Therefore, this study combined LER and ESV evaluation methods and comprehensive zoned southwest counties (cities or districts) to study the characteristics of their differentiated development. Our specific goals include (1) analyzing the spatio-temporal changes in LER and ESV in southwest China between 2000 and 2020; (2) based on the assessment results of LER and ESV and the spatial relationship, the comprehensive zoning attributes were divided; (3) analyzing the differences and changes in population, GDP, industrial structure and land use in each zone, putting forward suggestions on economic promotion and ecological maintenance management in different zones and differentiated sustainable development paths. The results of this study can provide theoretical support and decision support for promoting the sustainable development of ecological protection and economic development in southwest China.

2. Study Area

Southwest China (97°20′~110°11′ E, 21°08′~34°14′ N) covers three provinces and one city, namely Sichuan Province, Yunnan Province, Guizhou Province and Chongqing Municipality (Figure 1), with a total of 438 counties (cities or districts), covering a total land area of about 1.12 million km2. The study area spans the first and second steps of China. The terrain is high in the west and low in the east and falling in a ladder shape. The landforms are mostly plateaus, mountains and hills, with altitudes of 5~7139 m [44]. There are 68 national nature reserves in the territory, covering an area of 49,467.09 km2. The protected wild animals and plants account for 38% and 70% of the national total, respectively. The region is a typical karst area with a fragile ecological environment, complex ecological types, rich biological and mineral resources, and relatively limited social and economic development [45]. In order to stimulate economic development, the government has implemented the Western Development Strategy since 2000. Since then, the strategies of Belt and Road and Yangtze River Economic Belt has further promoted the development of regional industries. In 2020, the total population of southwest China was 201.60 million, the regional GDP reached CNY 11,595.01 billion, and the per capita GDP was CNY 57,515. In the past 20 years, the landscape pattern, ecosystem and social economy of southwest China have experienced great changes. Land use and natural resource development have damaged the ecological environment to a certain extent [46]. Therefore, the rational planning, protection and exploitation of the ecological environment is a key factor in realizing economic improvement and ecological protection in southwest China.

3. Data Sources and Methodology

3.1. Data Sources

The data of the paper included land use data and socio-economic statistics for each county (city or district) unit. Among them, the administrative boundary data (2010) and DEM data of the southwest China are from the Resource and Environment Science and Data Center (https://www.resdc.cn/, (accessed on 1 February 2021)). The land use data for 2000, 2010 and 2020 were obtained from GlobeLand30 (http://www.globallandcover.com/, (accessed on 1 February 2021)) with a spatial resolution of 30 m. According to the Land Cover Remote Sensing Classification System and related research results, the ecosystems in the study area were divided into 7 types: forestland, grassland, cultivated land, wetland, water body, desert land and artificial surface. In addition, the required social and economic statistics, such as grain output, price and population, population density, industrial structure and GDP, were mainly from the China Yearbook of Agricultural Price Survey, the Sichuan Statistical Yearbook, the Yunnan Statistical Yearbook, the Guizhou Statistical Yearbook, the Chongqing Statistical Yearbook, the National Bureau of Statistics (https://data.stats.gov.cn/, (accessed on 10 March 2021)) and the government portals of each county (city or district).

3.2. Landscape Ecological Risk Assessment

In the study, counties (cities or districts) in southwest China were taken as ecological risk assessment units, with a total of 438 units. Land use type data for the 438 units were obtained using ArcGIS10.2, and landscape indexes such as patch quantity, landscape type area, total landscape area and fractal dimension were obtained using Fragstats 4.2. Based on the previous research results, the landscape disturbance index, landscape vulnerability index and landscape loss index were selected to construct the regional LER index, quantitatively describing the possible consequences of various ecosystems affected by harmful and uncertain factors [47]. The calculation formula is
L E R k = ∑ i = 1 N A k i A k R i
where L E R k is the landscape ecological risk index of the k th region; A k i is the area of the i th landscape type in the k th region; A k is the k th region’s area; R i is the landscape loss index of the i th type, which describes the ecological loss of a landscape type after being disturbed. It is comprehensively reflected by the landscape disturbance index and landscape vulnerability index [9]. The formula for R i is
R i = V i × E i
where V i is the landscape vulnerability index, reflecting the resistance of each landscape type to external disturbance. The larger the value of V i , the weaker the anti-interference and the greater the risk of the ecosystem. According to previous studies [8,18] and the actual situation of the study area, artificial surfaces such as construction land, industrial and mining land are not easy to change to other land use types, and this land use is the most stable. Therefore, the landscape vulnerability of the artificial surface is assigned as 1. The desert land is mainly composed of sand, rock and soil, which is vulnerable to human interference and environmental impact, being transformed into other land use types. It has the highest vulnerability and sensitivity, so it is assigned as 6. Ranking the vulnerability of each landscape type from low to high: artificial surface, forestland, grassland, cultivated land, wetland, water body and desert land were assigned as 1, 2, 3, 4, 5, 5 and 6, respectively [48,49]. The results after normalization are shown in Table 1.
E i is the landscape disturbance index, reflecting the degree of disturbance caused by human activities for different landscape types in the region; the formula for E i is
E i = a C i + b N i + c F i
where C i is landscape fragmentation, which describes the fragmentation of an ecosystem after disturbance; N i is landscape isolation, which refers to the spatial separation degree of patches of a certain landscape type; F i is landscape fractal dimension and describes the complexity of patch shape. The coefficients a ,   b and c represent the weights of C i ,   N i and F i , respectively, and a + b + c = 1. According to previous research, a, b and c were given weights of 0.5, 0.3 and 0.2, respectively [50,51]. The formulae for C i , N i and F i are
C i = n i A i
N i = A 2 A i n i A
F i = 2 ln P i 4 ln A i
where n i is the patches number of i th landscape type; A i is the area of i th landscape type; A represents the total area of all landscapes; P i is the perimeter of the i th landscape type. n i ,   A i ,   A and F i were calculated using Fragstats 4.2.

3.3. Ecosystem Services Value Assessment

Ecosystem services are mainly divided into supply, regulation, support and cultural and entertainment services, which create a series of environmental conditions and socio-economic benefits for human survival and development. ESV is the monetization form of products and services provided by the ecosystem to human beings. The value includes the direct use value of material products and cultural entertainment services and the indirect use value of maintaining ecological balance [52].
In 1997, Costanza et al. scientifically defined the principles and methods of ESV assessment and estimated the global ESV [23]. However, due to the scale effect, the value of ecosystem services obtained using the above methods in China has a large deviation. Xie et al. proposed the Chinese ecosystem service coefficient modification method based on the research results of Costanza [53,54]. The method states that the equivalent of an ecological service equivalent was the economic value of the food production function provided by cultivated land ecosystem per unit area, which was 1/7 of the grain output value per unit area. According to the yield, planting area and unit price of main food crops in southwest China, the ecological service equivalent in the study area in 2000, 2010 and 2020 were revised to 640.74 CNY ha−1, 1314.42 CNY ha−1 and 1748.86 CNY ha−1, respectively. Its calculation formula is as follows:
E a = 1 7 ∑ i = 1 n m i p i q i M i = 1 , 2 , … , n
where E a represents the value of food production provided by farmland ecosystem per unit area, namely the economic value of ecological service equivalent per unit area (CNY/ha); i is the main food crop type; m i is planting area of the i th crop (ha); p i is the national average price of the i th crop (CNY/kg); q i is the unit yield of the i th crop (kg/ha); M is the total planting area of main grain crops in the study area (ha).
Multiplying the equivalent weighting factors value per unit area of different ecosystems (Table 2) by Ea values, the ecosystem service coefficient of different land use types can be obtained. The formula of ESV calculation model is as follows:
E S V = ∑ i = 1 n ∑ j = 1 m e i j × E a × A j i = 1 , 2 , … , n ,   j = 1 , 2 , … , m
E S V ¯ = E S V / ∑ j = 1 m A j
where ESV is the total value of regional ecosystem services (CNY); E S V ¯ is the value of ecosystem services per unit area (CNY); e i j is the equivalent weighting factors of the i th value of ecosystem services of the j th land use type; A j is the area of the j th land use type (ha). In this model, A j can be obtained by using ArcGIS10.2 software from the land use classification results.
In addition, in order to eliminate the impact of crop price fluctuations and currency inflation on the inter-annual change in total ESV, we took the ESV in 2000 as the baseline and revised the ecological service equivalent value of each year according to the consumer price index. The revised ESV can be compared between years, which is convenient for the analysis of temporal change in the later stage.

3.4. Spatial Autocorrelation Analysis

Spatial autocorrelation analysis is an important means to explore the spatial correlation and heterogeneity between geographical elements [55]. It can distinguish the spatial heterogeneity of geographical entities by identifying the aggregation and dispersion characteristics between adjacent geographical elements. Spatial autocorrelation analysis includes global and local spatial autocorrelation analysis. In this paper, according to the bivariate spatial autocorrelation principle proposed by Anselin et al. [56], bivariate Moran’s I was calculated using GeoDa software to analyze the spatial correlation between LER and ESV. Local spatial autocorrelation analysis was used to explore the spatial aggregation and differentiation characteristics of local spatial elements. It provided a basis for the zoning of regional ecological management units.
The bivariate Global Moran’s I is defined in Equation (10):
I = n ∑ i n ∑ j n W i j Q k i Q l j n − 1 ∑ i n ∑ j n W i j
The bivariate Local Moran’s I is defined in Equation (11):
I s = Q k i ∑ j = 1 n W i j Q l j
where Q k j = X k i − X ¯ k ∂ k , Q l j = X l j − X ¯ l ∂ l ; n is the number of spatial units; X k i is the value of attribute k of spatial unit i; X l j is the value of attribute l of spatial unit j; X ¯ k and X ¯ l are the average values of attribute k and l, respectively; ∂ k and ∂ l are the variance of attributes k and l, respectively; W i j is a weight matrix to measure the adjacency between spatial elements, reflecting the spatial relation between spatial units i and j.
Moran’s I is between [−1, 1]. When Moran’s I > 0, there is a positive spatial correlation, indicating that adjacent spatial units have similar attribute values. Moran’s I = 0 indicates no correlation, and the space is random. Otherwise, there is a negative spatial correlation. When the value of Moran index I is closer to 1 or −1, it indicates that the spatial autocorrelation is stronger.

4. Results

4.1. Landscape Ecological Risk Assessment

We calculated the LER index of 438 units in the study area from 2000 to 2020. According to the natural breakpoint method, the LER in 2000 was divided into 10 grades. Based on these breakpoints, the spatial pattern of the LER in each county in 2010 and 2020 was divided, as shown in Figure 2.
As can be seen from Figure 2, the LER pattern mainly took core metropolitan areas (the Chengdu–Chongqing economic circle, the central Yunnan urban agglomeration, the central Guizhou economic zone) and the Northwest Sichuan Plateau as high-value areas and gradually decreased outward. The high-value areas of LER were mainly concentrated in the Northwest Sichuan Plateau with single landscape type and fragile ecological environment and a core urban agglomeration with frequent human construction activities. This area was sensitive to external risks or affected by human disturbance, resulting in poor anti-interference ability of the ecosystem and a high LER index. From 2000 to 2020, the LER level showed an upward trend, and the average value of the LER index increased from 0.0328 to 0.0347, an increase of 5.79%. The gap of LER level among internal units gradually decreased, and the difference between the maximum value and minimum value of the LER index decreased from 0.0384 to 0.0359, a decrease of 6.96%. Overall, the medium-low risk regions in southwest China were dominant, accounting for more than 50% of the study area, and the area was further expanding.

4.2. Ecosystem Services Valuation

The ESV per unit area was selected to represent the ecosystem service level of each county (city or district). According to the natural breakpoint method, the ESV per unit area in 2000 was divided into 10 grades. Based on these breakpoints, the ecosystem per unit area of each county in 2010 and 2020 was divided, as shown in Figure 3.
From 2000 to 2020, the ESV per unit area of 99% of the counties (cities or districts) in the study area showed an upward trend, and the average value of the ESV per unit area increased by 9591.88 CNY/ha, of which the ESV per unit area increased significantly from 2000 to 2010. From the perspective of spatial change, the ESV per unit area of southwest China increased significantly in the past 20 years. In particular, the central and western prefectures of Aba, Liangshan, Ganzi and Ya’an City in Sichuan Province and the northwestern prefectures of Diqing, Nujiang and Lijiang City in Yunnan increased significantly, with a change of more than 14,000 CNY/ha. Since the disturbance of human activities in northwest Sichuan is relatively weak, and the core metropolitan area has more artificial surface and stronger anti-disturbance ability, the ESV per unit area of these areas changes slightly.

4.3. Comprehensive Zoning and Change in Landscape Ecological Risk and Ecosystem Service Value

The bivariate LISA aggregation map drawn using GeoDa software is shown in Figure 4. The regions with significant spatial autocorrelation (p < 0.05) were divided into four types: the H–H type, in which both LER and ESV were high; the L–L type, in which there was a low level of both LER and ESV; the L–H type, in which there was a low level of LER and a high level of ESV; and the H–L type, in which there was a high level of LER and a low level of ESV.
The bivariate global Moran’s I between LER and ESV in 2000, 2010 and 2020 was −0.475, −0.460 and −0.411, respectively, showing a significant negative correlation (p < 0.05). Figure 4 shows that the local spatial correlation between LER and ESV is highly consistent. The H–H zone was scattered, mainly in Aba Prefecture of Sichuan Province, Lincang City of Yunnan Province and Qiandongnan Prefecture of Guizhou Province, etc. The type is mostly concentrated in the areas with fragile ecological structure or agricultural economy, so the LER is at a high level in the region. At the same time, it has rich forest, grassland and other resources, and the ESV is relatively high. The L–L zone was mainly concentrated around the Sichuan Basin. Most of the region is located at the edge of economically active areas, which are not closely connected with the economic core metropolitan area. The intensity of land use development is insufficient, and the regional development is relatively independent, which objectively results in low LER level. At the same time, the region mainly focuses on the development of agriculture or industry. Although the land use type is mainly forestland, the proportion of cultivated land is also high. Therefore, the ESV of this region is relatively low in southwest China. The L–H zone was distributed in southwest Sichuan, west Yunnan and southeast Guizhou. The forest coverage rate in this region is over 62%, and the mountainous area accounts for about 85%. The rugged terrain restricts the population gathering, industrial agglomeration and urban development in this region to a certain extent. The land use is less disturbed by human activities, and the degree of landscape loss is low. Therefore, it shows an obvious aggregation pattern of low LER and high ESV. The H–L zone was mainly distributed in the Sichuan Basin. This region is an important economic construction area and grain production base in the middle and west of China, and it is also the largest economic center in the southwest of China. With the rapid development of social economy, the disturbance of human activities has intensified, resulting in the dispersion and fragmentation of land use types, forming a high LER and low ESV aggregation situation.

4.4. Comprehensive Zoning Socio-Economic Development Characteristics

In order to explore the characteristics and differences of social and economic development in each zone in the past 20 years, the indicators of population, industrial structure and land use in 2000 and 2020 were selected for analysis.

4.4.1. Population Analysis

Figure 5 shows the spatial distribution difference of population quantity and population density of each zone in southwest China from 2000 to 2020. In terms of spatial distribution, the population was mainly concentrated in the low-ESV zone (H–L zone, L–L zone), and the population density level was relatively high. The high-ESV zone (H–H zone, L–H zone) was sparsely populated, and the population density of the region was low.
In terms of time changes (Table 3), from 2000 to 2020, the population of the H–H zone accounted for the smallest proportion, about 1% of southwest China. The population density decreased from 56 to 37 people/km2. The most obvious change was in population, which decreased by 27.90%. In the past 20 years, the population density and population of the L–L and L–H zones increased significantly, and the population change rate was +13.55% and +3.46%, respectively. The population density (about 485 people/km2) and population proportion (about 45%) of the H–L zone were the highest among the regions, and the population decreased by 7.26% in 20 years. The population of the high-LER zone (H–H zone, H–L zone) tended to gradually migrate to the low-LER zone (L–L zone, L–H zone).

4.4.2. GDP and Industrial Structure Analysis

The GDP of the H–L zone accounted for about 48% of that of the southwest region, which was located in the economically active region and gathers towards the core metropolitan areas. The GDP of the L–L zone and the L–H zone was about 10% of the total GDP of southwest China, and the economic development was at a medium level. The overall economic development of the H–H zone was relatively limited, only accounting for about 1% of the total GDP of the study area. In the past 20 years, the economic level of each zone improved obviously, and the economic development of the low-ESV zone was better than that of the high-ESV zone (see Figure 6).
Figure 7 shows the changes of industrial structure in different zones of southwest China from 2000–2020. In 2000, 75% of units in the H–H zone and 74% of units in the L–H zone had more than a 34% output value ratio of primary industry; a total of 61% of units in the L–L zone and 60% of the H–L-zone units had a primary industry output value ratio of less than 34%. In 2020, 75% of units in the H–H zone and 65% of units in the L–H zone had over an 18% output value ratio of primary industry; a total of 79% of units in the L–L zone and 72% of units in the H–L zone had a primary industry output value ratio of less than 18%. This showed that the primary industry accounted for a higher proportion in the high-ESV zone.
In 2000, 74% of units in the L–L zone and 73% of units in the H–L zone had an output value ratio of secondary industry higher than 30%. A total of 67% of units in the H–H zone and 75% of units in the L–H zone had below a 30% output value ratio of secondary industry. In 2020, 64% of units in the L–L zone and 87% of units in the H–L zone had a secondary industry output value ratio of over 29%; a total of 88% of units in the H–H zone and 57% of units in the L–H zone had less than a 29% output value ratio of secondary industry. This showed that the secondary industry accounted for a higher proportion in the low-ESV zone.
In 2000, the percentage of units in the H–H, L–L, L–H and H–L zones with a proportion of tertiary industry higher than 38% was 17%, 26%, 26% and 21%, respectively. In 2020, the tertiary industry developed rapidly, and the percentage of units with tertiary industry over 38% in each zone became 100%, 86%, 91% and 82%, respectively. The tertiary industry in the high-ESV zone with relatively limited economic development achieved a large proportion of growth. However, the increase in the output value ratio of tertiary industry promoted by the development of tourism and the service industry was still not enough to drive the improvement of the overall economic level of the region.

4.4.3. Land Use Analysis

Each unit was numbered, and the proportion of forestland, grassland, cultivated land, wetland, water body, desert land and artificial surface to the total area of each unit was counted. A comparison of zoning land use characteristics is presented in Figure 8.
The main types of land use in southwest China were forestland, grassland and cultivated land. The proportion of forestland in the low-LER zone was significantly higher than that in the high-LER zone. In 2000 and 2020, respectively, 74% and 75% of units in the L–L zone and 96% and 96% of units in the L–H zone had more than 43% forestland; a total of 58% and 63% of units in the H–H zone and 99% and 98% of units in the H–L zone had less than 43% forestland. For the low-LER zone, the proportion of grassland and cultivated land was significantly lower than that of the high-LER zone. In 2000 and 2020, respectively, 84% and 89% of units in the L–L zone and 85% and 86% of units in the L–H zone had less than 20% grassland; a total of 58% and 75% of units in the L–L zone and 92% and 88% of units in the L–H zone had less than 35% cultivated land. On the contrary, the high-LER zone had a higher proportion of grassland or cultivated land. In 2000 and 2020, respectively, 58% and 63% of units in the H–H zone had 20–90% of grassland and 98% and 94% of units in the H–L zone had more than 35% of cultivated land. Therefore, the low-LER zone had a high proportion of forestland and a low proportion of grassland and cultivated land. Conversely, the high-LER zone had a low proportion of forestland and a high proportion of grassland or cultivated land.
The proportion of wetland, water body, desert land and artificial surface in the four zones increased during the 20 years studied. The artificial surface expansion in the L–L zone and H–L zone was the most significant, which increased by 1.59 times and 2.39 times, respectively. The expansion of artificial surface not only promotes the economic development of the low-ESV zone but also further enlarges the disturbance of human activities to the ecosystem, resulting in the decline of ecosystem services.

5. Discussion

5.1. Linking Landscape Ecological Risks with Ecosystem Services Value

As the spatial projection of the socio-ecological coupling system on the two-dimensional plane, the landscape is the result of the integrative action of multiple factors such as human interference and ecological processes and has obvious spatial differentiation [57]. Ecosystem services are the natural utility formed and maintained by the ecosystem and ecological processes [58]. Continuous land use change will not only change the surface structure but also affect a series of ecological processes such as material circulation and energy flow, causing the adjustment, reorganization and optimization of landscape patterns, thus affecting the structure and function of the entire ecosystem, resulting in damage to a variety of ecosystem services and aggravating ecological risks. Therefore, there is homology and correlation between landscape patterns and ecosystem services; the former is the carrier of the latter, and the latter is the connotation of the former [59,60].
Many studies take the combination of landscape ecological risks and ecosystem services as the key to generating different functional areas and implementing ecosystem management in different functional areas through land use policy formulation and human activity governance, thus enhancing the sustainability of the social ecological system. For example, based on the hot spot analysis results of the landscape pattern index and ecosystem services, De Vreese et al. formed four types of zoning and drew development zoning maps to provide a basis for land development and management, avoiding conflicts between landscape and nature management [61]. Gong divided the assessment results of LER and ecosystem service into three levels: high, medium and low. Based on the spatial overlay analysis of LER and ecosystem service, the region was divided into nine sub-functional zones, and differentiated management strategies were proposed for each zone [38]. At present, spatial partitioning methods are still being explored, and no unified standard system has been formed. The main partitioning methods include spatial autocorrelation analysis, spatial superposition analysis and hot spot analysis [20,62]. Among them, the bivariate spatial autocorrelation analysis has high applicability and effectiveness in describing the spatial correlation and dependence characteristics of two geographic elements, and it is more suitable for multi-dimensional comprehensive partitioning. Therefore, the spatial autocorrelation analysis method was used in this study to connect LER with ESV for ecological spatial zoning and management. This work provides a scientific basis and an integrated approach for implementing differentiated social ecosystem management at the landscape scale.

5.2. Characteristics and Differences of Social and Economic Development in Comprehensive Zones

Based on the above research results, we summarized the characteristics and differences of socio-economic factors in four comprehensive zones (Figure 9).
(1)
The overall development of the H–H zone is weak, and the regional economy is relatively small. In this zone, the ecosystem is fragile, and grassland landscape resources are rich. In 2020, the proportion of grassland in Sichuan and Yunnan research units was 68% and 46%, respectively. Economic development lags behind, mainly relying on primary agricultural and livestock products. The population is small, and population loss is relatively serious. The natural landscape of the zone is unique, and tourism resources are highly enriched. The tertiary industry accounted for more than 50% of research units in Sichuan and Yunnan in 2020. However, the tourism industry is still in the initial stage and lacks systematic industrial planning. It has not yet formed a stable and sustainable ability to drive economic growth, and its income cannot be the main support of local economic development. Moreover, the ecosystem vulnerability also prevents the region from developing large-scale resource-based industries to drive economic development [63]. In addition, it also faces the problems of ecological destruction such as overgrazing, deforestation and overmining due to insufficient development power [64].
(2)
The L–L zone has entered the middle stage of industrialization. It is mainly concentrated in the mountain areas around the Sichuan Basin and northern Guizhou, with rich forestry resources. In 2020, the forestland of Sichuan and Guizhou research units accounted for 66% and 53%, respectively. The landform in this region is mainly mountainous, the soil layer is barren and the land cultivation condition is poor. The cultivated land in Sichuan and Guizhou only accounted for 19% and 29%, respectively, of the research units in 2020. In the past 20 years, the industrial structure of the zone has gradually realized the transformation from the secondary industry to the tertiary industry, and the economic development has begun to enter the middle stage of industrialization, and the population has also increased [65].
(3)
The L–H zone is underdeveloped, and is in the early stage of industrialization. This region is mainly concentrated in southern Sichuan, western Yunnan and southeast Guizhou, which is the key area of ecological barrier construction and biodiversity conservation. It has prominent advantages in ecological, biological and tourism resources and occupies an extremely important ecological location. The forestland in Yunnan, Sichuan and Guizhou research units all accounted for more than 65% in 2020. However, at the same time, it also faces the challenges of weak industrial foundation, low industrial level and insufficient resource transformation. Moreover, complex terrain conditions and a fragile ecosystem limit the development of the region to some extent [66].
(4)
The H–L zone has a higher level of urbanization, and is in the middle and late stages of industrialization. The region is mainly concentrated in the Sichuan Basin and the central Yunnan urban agglomeration, and the urbanization level is much higher than other regions. The artificial surface in Sichuan, Chongqing and Yunnan research units all accounted for more than 3% in 2020. In most units of the zone, resource-intensive industries, such as metallurgy, mining and electricity, and chemical industry, are the main driving force for economic growth. Regional development faces many obstacles, such as high dependence on resources, low-end industrial chain, high population density, and high land use intensity [67].

5.3. Differentiated Development Strategy in Southwest China

In order to strengthen ecosystem management and promote coordinated regional development, policy makers should put forward differentiated and targeted development strategies for different comprehensive zones according to their own economic development stage and ecological environment status. Based on the above results, we propose the following policy recommendations.
(1)
The H–H zone should adhere to the ecological orientation and promote the integrated development of multiple industries by relying on tourism and ecological resources. In the future, the project of returning grazing land to grassland should be actively carried out, the appropriate management plan of rotational grazing should be formulated, and the system of rotational grazing, rest grazing and prohibition of grazing should be strictly implemented to improve the sustainability of grassland ecosystems [68]. Relying on excellent ecological environment and ethnic cultural background, efforts should be made to build a new system of rural eco-tourism, develop participatory eco-tourism products and promote the integrated development of multiple industries. While developing tourism resources, the government should pay attention to scientific evaluation and strengthen protection of biological and ecological resources, so as to avoid increasing ecological risk due to excessive development and disorderly competition of rural tourism. In addition, local fiscal revenue in the zone is weak. It is necessary to make rational use of the central assistance funds and actively introduce talents and technology, so as to better alleviate the contradiction between ecological protection and economic development.
(2)
The L–L zone should actively explore the feasible path to transform ecological resources into ecological economy. It is suggested that while strengthening the protection of natural forests and ecological red lines, the government should formulate appropriate subsidy policies to compensate for the development opportunities and ecological construction costs abandoned due to the construction of ecological barriers. Forestry departments and local governments should strengthen support for forest products, such as medicinal plants and precious trees; actively develop relevant forest products; drive the development of processing, storage and transportation and other related industries; and promote the transformation of regional ecological advantages to industrial advantages. At the same time, the region should accelerate the development of environmentally friendly and resource-saving emerging industries. Combined with its own rich resources such as hydropower, oil and gas, and mineral resources, the development of clean energy industry should be promoted orderly, gradually forming an industrial cluster dominated by clean energy and promoting the regional development of new industrialization [69].
(3)
The key task of the L–H zone is to develop the economy stably on the premise of continuously improving ecological function. In the future, local governments should continue to implement projects such as natural forests protection and returning farmland to forests and grasslands, strengthen forest resources management and conservation, improve biodiversity monitoring systems and build ecological corridors to further promote biodiversity conservation [70]. It is suggested to cultivate and consolidate ecotourism, e-commerce, health preservation and other service industries with its own characteristic resources. Make full use of the geography, climate and biological resources; focus on the development of tea, tobacco, fruit, coffee, flowers and other characteristics of agricultural products; and gradually promote the development of agricultural and sideline products processing and other characteristic processing industries. Focus on cultivating emerging industries such as bio-medical and green energy to undertake tertiary industry and promote the further extension of regional tourism industry chain. By promoting the coordinated development of the primary, secondary and tertiary industries, people’s dual needs for a good environment and economic growth can be sustainably met.
(4)
The H–L zone needs to strengthen the management and control of resource-based industries and implement sustainable industrial development policies. In order to alleviate the pressure on the ecological environment, it is necessary to speed up the upgrading of treatment processes, clean technology and equipment, improve energy efficiency and reduce resource consumption and industrial pollution. The development of innovative industrial clusters, such as high-end manufacturing, advanced material and communications, should focus on the transition from resource-based industries to emerging industries. Moreover, efforts should be made to promote land consolidation, improve the level of land conservation and intensification, optimize the structure of urban and rural construction land, reasonably arrange urban industrial and mining land and transportation land, and alleviate the contradiction between production, life and ecological space [46]. Waste treatment and ecological protection and restoration projects should be actively carried out. In addition to increasing investment in environmental protection in the treatment of urban waste gas, wastewater and solid waste, ecological projects should be positively carried out to protect natural forests, return farmland to forest and grassland, restore abandoned mines and control soil pollution, so as to ease the pressure on the ecological environment caused by dense population and excessive concentration of resources [71].

6. Conclusions

In southwest China, the ecosystem is complex and fragile, and the economic development is relatively limited. The continuous interference of human activities has further exacerbated the contradiction between ecological protection and economic promotion. How regional sustainable development should be realized is a major challenge for the government. Based on land use data and the related social economic data, the present study evaluated and comprehensively zoned the LER and ESV in 438 counties (cities or districts) in southwest China and explored the impact mechanism of regional socio-economic development on the ecosystem to seek a sustainable development path of ecological maintenance and economic improvement. The results showed that the overall LER level of southwest China increased, and the gap of internal LER narrowed gradually. The ESV per unit area showed an increasing trend, but the core metropolitan areas and northwest Sichuan had little change. According to the differences in population, industrial structure and land use, the low-ESV zone was densely populated, while the high-ESV zone was sparsely populated, and the population from the high-LER zone rapidly migrated to the low-LER zone. The economic development of the low-ESV zone was better than that of the high-ESV zone, and the secondary industry was an important driving force of regional economic development. Large-scale forestland can alleviate the LER, but the increase of cultivated land and grassland further aggravated the LER. This study put forward a differentiated development strategy according to the social and economic characteristics of each zone. The ecosystem is fragile and underdeveloped in the H–H zone. In the future, it needs to rely on tourism, ecology, environment and other resources for the integrated development of diversified industries. The L–L zone should pay more attention to the construction of ecological barriers and strive to promote the construction of cleaner production industrial system focusing on the development of characteristic and superior resources. The L–H zone is rich in ecological resources, so the ecological priority concept should be upheld to develop ecological economy stably in the future. Most of the H–L zone is resource-based towns with high population density and high industrial level. In the future, land consolidation, ecological environment management and resource-based industry control should be strengthened to implement the sustainable industrial development route.
This study aims to reduce the level of LER and improve the ESV and puts forward targeted countermeasures for the coordinated development of ecology and the economy in order to provide scientific basis for the sustainable development and ecosystem management in southwest China. Due to the vast territory and diverse ecosystem in southwest China, the sustainable development path proposed in this paper is only applicable to the large-scale scope. In the future, the research scope can be further narrowed to select typical regions of the conflict between ecological protection and economic promotion for analysis and put forward more specific suggestions for sustainable development.

Author Contributions

Conceptualization, R.Y. and X.L.; Methodology, M.S.; Software, C.W.; Validation, M.S.; Formal analysis, Y.Z.; Investigation, Y.L. (Yanrong Lu); Data curation, L.M.; Writing—original draft, Y.Z.; Writing—review & editing, R.Y.; Visualization, L.Z. and Y.L. (Yunzhi Liu); Supervision, X.L.; Project administration, L.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Key Research and Development Project of China (No. 2021YFC3201500) and the National Key Research and Development Project of China (No. 2016YFC0502106).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on reasonable request from the corresponding author. The data are not publicly available due to privacy.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Map of study area (location, elevation and land use in 2020).
Figure 1. Map of study area (location, elevation and land use in 2020).
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Figure 2. Spatial pattern and change in LER in southwest China from 2000 to 2020.
Figure 2. Spatial pattern and change in LER in southwest China from 2000 to 2020.
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Figure 3. Spatial pattern and change in ESV per unit area in southwest China from 2000 to 2020.
Figure 3. Spatial pattern and change in ESV per unit area in southwest China from 2000 to 2020.
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Figure 4. Local spatial autocorrelation LISA results of LER and ESV in southwest China.
Figure 4. Local spatial autocorrelation LISA results of LER and ESV in southwest China.
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Figure 5. Change in population quantity and population density in each zone from 2000 to 2020.
Figure 5. Change in population quantity and population density in each zone from 2000 to 2020.
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Figure 6. Change in GDP in each zone from 2000 to 2020.
Figure 6. Change in GDP in each zone from 2000 to 2020.
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Figure 7. Change in industrial structure in each zone from 2000 to 2020.
Figure 7. Change in industrial structure in each zone from 2000 to 2020.
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Figure 8. Change in land use types in each zone from 2000 to 2020.
Figure 8. Change in land use types in each zone from 2000 to 2020.
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Figure 9. The characteristics of social and economic development in each zone.
Figure 9. The characteristics of social and economic development in each zone.
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Table
Table 1. Landscape vulnerability index in southwest China.
Table 1. Landscape vulnerability index in southwest China.
TypesArtificial SurfaceForestlandGrasslandCultivated LandWetlandWater BodyDesert Land
Vulnerability index0.03850.07690.11540.15380.19230.19230.2308
Table
Table 2. Equivalent factor value per unit area of ecosystem services in southwest China. From Xie et al. [54].
Table 2. Equivalent factor value per unit area of ecosystem services in southwest China. From Xie et al. [54].
First Class TypesSecond Class TypesForest LandGrass LandCultivated LandWetlandWater BodyDesert Land
Provision servicesFood production0.330.431.000.360.530.02
Raw material production2.980.360.390.240.350.04
Regulation servicesGas regulation4.321.500.722.410.510.06
Climate regulation4.071.560.9713.552.060.13
Hydrological regulation4.091.520.7713.4418.770.07
Waste disposal1.721.321.3914.4014.850.26
Support serviceSoil formation and retention4.022.241.471.990.410.17
Biodiversity protection4.511.871.023.693.430.40
Cultural servicesRecreation services2.080.870.174.694.440.24
Table
Table 3. Traits of different zones from 2000 to 2020.
Table 3. Traits of different zones from 2000 to 2020.
IndicatorsH–HL–LL–HH–L
20002020200020202000202020002020
IERHighLowLowHigh
ESVHighLowHighLow
Area proportion (%)4.124.464.954.1038.5936.3116.1916.22
Population
Density (per/km2)56372273117077503466
Proportion (%)1.370.946.677.2315.9716.0848.4342.89
Quantity change (%)−27.90+13.55+3.46−7.26
GDP
Proportion (%)1.410.709.8011.489.9011.2150.6546.89
Land use
Forestlands (%)34.2127.8857.9063.2665.5967.0118.7720.44
Grassland (%)45.4757.2812.8312.3815.1011.9912.0010.36
Cultivated land (%)14.407.7828.0121.0318.0118.9266.7263.96
Wetland (%)1.741.780.070.090.040.020.120.06
Water body (%)0.870.990.320.550.400.661.351.66
Desert land (%)2.823.720.030.060.540.5600
Artificial surface (%)0.490.590.842.630.320.841.043.53
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Zhang, Y.; Yang, R.; Li, X.; Sun, M.; Zhang, L.; Lu, Y.; Meng, L.; Liu, Y.; Wang, C. Designing a Sustainable Development Path Based on Landscape Ecological Risk and Ecosystem Service Value in Southwest China. Sustainability 2023, 15, 3648. https://doi.org/10.3390/su15043648

AMA Style

Zhang Y, Yang R, Li X, Sun M, Zhang L, Lu Y, Meng L, Liu Y, Wang C. Designing a Sustainable Development Path Based on Landscape Ecological Risk and Ecosystem Service Value in Southwest China. Sustainability. 2023; 15(4):3648. https://doi.org/10.3390/su15043648

Chicago/Turabian Style

Zhang, Yuying, Rongjin Yang, Xiuhong Li, Meiying Sun, Le Zhang, Yanrong Lu, Lingyu Meng, Yunzhi Liu, and Chen Wang. 2023. "Designing a Sustainable Development Path Based on Landscape Ecological Risk and Ecosystem Service Value in Southwest China" Sustainability 15, no. 4: 3648. https://doi.org/10.3390/su15043648

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