Construction of an Ecological Security Pattern and the Evaluation of Corridor Priority Based on ESV and the “Importance–Connectivity” Index: A Case Study of Sichuan Province, China

Abstract

Constructing an ecological security pattern (ESP) is an important means to describe, manage, and control ecological security. However, there are few related studies on functional analyses and evaluations of landscape elements, and the distribution of identified elements cannot fully reflect reality. To accurately depict ecological security and strengthen the role of landscape planning for policy formulation, we used the spatial distribution patterns of ecosystem services to adjust the ecosystem service value to accurately identify the distribution of ecological sources. The gravity model and Centrality Mapper tool are used to build an “importance–connectivity” index that evaluates the importance of ecological corridors in linking the sources and the contribution to maintaining the overall connectivity of ecological networks. The results show that (1) spatial heterogeneity exists in seven kinds of ecosystem services in Sichuan Province, China, and the high-level areas are concentrated in the central region. Moreover, (2) a total of 179 ecological sources and 445 ecological corridors with woodland and grassland as the main land use types are identified, and (3) a total of 153, 49, 78, and 165 corridors are divided into high importance–high connectivity, low importance–high connectivity, high importance–low connectivity, and low importance–low connectivity ecological corridors, respectively. The study provides a new framework for the construction of an ESP and for the priority evaluation of ecological corridors. To achieve balance between economic development and environmental protection, priority should be given to the protection of high-priority corridors when maintaining ecological security.

1. Introduction

Ecosystem services (ESs) are all the benefits that human beings derive from the ecosystem. They are needed for human survival and development and are maintained by ecosystems and ecological processes [1]. With the continuous propulsion of global urbanization and industrialization, the scope and intensity of human activities keep increasing, causing negative impacts that are imparted on ecosystems and continuously become more serious [2]. As urbanization requires space for urban expansion and infrastructure construction, the demand for construction land and arable land leads to the shrinkage of ecological land, namely woodland and grassland areas [3], which ultimately causes various ecological problems, such as the reduction and fragmentation of ecological patch areas, the degradation of ecological corridor function, and the obstruction of landscape ecological processes [4,5,6,7]. With the background that the international community urgently needs a method to balance urbanization and ecological protection, the concept of ecological security has been put forward [8,9]. Generally speaking, ecological security refers to the ability of the ecosystem to achieve sustainable development, including the provision of stable ESs for nature and human society and self-regulation when subjected to external interference [10,11]. Scholars around the world have developed different technological schemes and planning strategies, such as ecological network construction [12], ecological reserve delimitation [13,14], and carrying capacity quantification [15]. Among these methods, the ecological security pattern (ESP) has attracted extensive attention because of its potential to describe the integrity and health of ecosystems in biodiversity conservation and landscape restoration projects [16,17]. Composed of ecological sources that provide different kinds of ESs and ecological corridors that maintain the flow of materials and energy, the ESP can effectively control and sustainably improve regional eco-environmental problems by protecting vital landscape elements as well as optimizing management measures [18,19]. By constructing an ESP, areas that are essential to ecological security are identified; hence, the normal functioning of key ecosystem processes can be guaranteed through scientific ecological conservation policies [20,21].

At present, research on ESP centers around ecological diversity [22] and natural reserves [23]. With the development of ES assessments, different kinds of conservation areas have been delimited, such as key biodiversity areas (KBAs) and biodiversity hotspots selected by the International Union for Conservation of Nature (ICUN) and Conservation International (CI) [24]. In this case, some scholars turn to the research of the relationship between biodiversity and ESs and policies related to ecological security [25]. In China, research on ESP focuses more on the amelioration of key ecological processes. This is mainly because China is in the process of rapid urbanization, and behind the rapid economic development is the long-term neglect of ecological processes. The decline in the quality of ESs continues to build the demand for environmental protection [26]. As studies on ESP become more in-depth, a paradigm of “ecological source identification–ecological corridor extraction” has been formed and has successfully been applied to studies at the national, provincial, and prefectural levels [27,28,29].

Ecological source is an important part of the ESP, playing a positive role in maintaining the exchange of materials, energy, and information and in promoting the process of landscape ecology [30]. At present, the selection of ecological sources is mainly based on land use type or multifactor comprehensive evaluation methods [31,32,33]. The former is simple and efficient and simply selects nature reserves, wetlands, and other important ecological lands as ecological sources based on the internal characteristics of ecological patches. However, this selection method is relatively subjective and ignores the heterogeneity within the ecological source [34]. The latter focuses on landscape ecological processes, constructing a comprehensive evaluation system by combining various quantitative evaluation indicators. Although the problem of heterogeneity in the selection of ecological sources is solved by calculating spatial and temporal distributions of different kinds of ESs, it is difficult to make a direct comparison, as the calculation method and measurement unit are different. It is important to consider all of the different types of ESs equally, as they will also affect the selection results. From this point of view, current research on the selection of ecological sources still needs to be augmented. The purpose of evaluating the ecosystem service value (ESV) is to monetize different kinds of ESs and to account for natural resource assets from an economic point of view that can be used as a reference for ecological protection policy formulation and land use structure optimization [35]. This method can accurately quantify differences in the importance of ESs and is suitable for large-scale research, but there are still few studies identifying ecological sources based on the ESV [36]. Existing research on ESV calculation using land use types also ignores the differences in the ESs within the same land use category. Therefore, it is necessary to characterize the spatial and temporal distribution of ESs as the basis for the accurate adjustment of the ESV [37].

As a kind of important landscape element connecting discrete ecological sources, ecological corridors can promote the flow of materials, energy, and information among different landscapes and maintain the integrity and continuity of landscape ecological processes [38,39]. Extracting and protecting critical corridors will help to increase the connectivity and stability of regional ecological networks and improve the quality of ESs. At present, the general methods for extracting ecological corridors include the minimum cumulative resistance (MCR) model and the circuit theory model [40]. The MCR model identifies corridors by simulating the minimum cost path for species to pass through different landscapes from the source [41,42]. This method is mature and requires fewer data. The circuit theory model comes from physics and is more in line with the characteristics of biological behavior [43]. The two methods have their advantages and disadvantages and complement each other.

As research on the construction of ESP deepens, scholars continue to improve and innovate ecological source identification and ecological corridor extraction methods, but most of these methods put forward suggestions for the improvement of ESP from the perspective of social ecology. These methods remain at the application level but lack an in-depth discussion of ecological processes and landscape elements [44]. In the study of landscape elements, the extraction of ecological corridors using the MCR model reflects the spatial distribution of corridors but does not reveal their inherent characteristics. In fact, ecological corridors can maintain the functional connectivity of ecological networks, while good connectivity plays an important role in maintaining gene flow [45,46], natal dispersion [47], animal population dynamics [48], and biological migration [49]. Therefore, it is necessary to study the connectivity of ecological corridors. The research of Xiao et al. [50] indicates that the characteristics of ecological corridors can be shown in the importance of providing a connection between two ecological sources and its contribution to maintaining the overall connectivity of the ecological network. Among them, species migration is compared to current flow, and the contribution of ecological corridors to connectivity can be obtained by simulating the current between ecological corridors, while the importance of ecological corridors can be calculated by the gravity model that is used to simulate the connection strength between sources [51]. Based on this, the priority of ecological corridors can be determined, and the order in which protection should be prioritized can be determined afterward. In China, there is a lack of a set of systematic long-term operation paradigms for the protection and functional restoration of ecological corridors, which are particularly evident in provinces and cities with low financial levels that are experiencing a fierce conflict between economic development and ecological protection [34]. How to use limited financial resources to protect the ecological environment as much as possible is a key point for the government to consider when formulating ecological protection policies. Therefore, the priority of ecological corridor protection is of great significance to the formulation of relevant policies and the rational and efficient allocation of resources.

The rapid development of China’s economy has not only improved the quality of life of the people but has also caused problems such as the reduction in the amount of ecological land and the fragmentation of ecological patches, which is more obvious in the developing regions of southwest China due to their fragile ecological environment and tight financial conditions [52,53]. Our study area, Sichuan Province, spans many geomorphological units and has a complex topography and diverse ecology and is an important ecological barrier in the upper reaches of the Yangtze River. In addition, the area occupies an important position in the “Yangtze River Economic Belt” and “The Belt and Road” strategies. There is an inevitable conflict between the demand for economic development and the necessity of ecological protection, which is also reflected in the relevant research [54]. Therefore, it is necessary to put forward scientific and efficient protection policies, to make use of limited policies and economic resources to protect the regional ecological environment as much as possible, and to achieve coordination between economic development and the ecological environment. In this study, the ESV estimation model proposed by Xie et al. [55] was used to calculate the ESV of Sichuan Province in 2018, and the ESV was adjusted to identify ecological sources according to the spatial distribution of the ESs. Using the MCR model to identify key ecological corridors and to construct the ESP, the contribution of ecological corridors to the overall connectivity of ecological networks and the importance of connecting two ecological sources were evaluated by applying the circuit theory and the gravity model, respectively. The “importance–connectivity” index of ecological corridors was constructed to comprehensively evaluate the priority of ecological corridors to maintain and improve ESs and to provide a theoretical basis and method support to coordinate the conflict between ecosystem and economic society.

Thus, the main objectives of this study are to (1) identify ecological sources based on the adjusted ESV, (2) construct the ESP of Sichuan Province, and (3) evaluate the priority of ecological corridors according to the “importance–connectivity” index.

2. Materials and Methods

2.1. Study Area and Data Sources

Sichuan Province is located in southwest China (26°03′~34°19′ N and 97°21′~108°12′ E), covering an area of approximately 486,000 km² (Figure 1). It is located the subtropical monsoon climate area and spans the Qinghai–Tibet Plateau, Hengduan Mountains, and the Sichuan Basin. Sichuan Province is high in the west and low in the east and has complex geomorphological types, mainly comprising plains, hills, mountains, and plateaus. There are great differences in climate among different regions, with a variety of climate types ranging from humid to arid and subtropical to cold zones, which can be divided into the Basin Hilly Area, Basin Mountain Area, Northwest Sichuan Plateau Area, Western Sichuan Alpine Canyon Region, and Southwest Sichuan Mountainous Region according to topographic characteristics, as shown in Figure 2 [56].

The ecological status of Sichuan Province is important. As the core part of the “Qinghai–Tibet Plateau Ecological Barrier” and “Loess Plateau–Sichuan–Yunnan Ecological Barrier” in China, the Western Sichuan Alpine Canyon Region and Southwest Sichuan Mountainous Region provide a number of ecological functions. In 2020, the per capita GDP of Sichuan Province was CNY 58,029, placing the province 16th among the 34 provincial administrative regions in China. The large room for economic development shows that a tradeoff between economic development and environmental protection is required.

According to the “Table of equivalent value per unit area of ecosystem services in China” made by Xie et al. [57], the ESV of Sichuan Province was calculated based on the land use data from Sichuan Province in 2018. Meteorological, soil, topographical, vegetation, and socioeconomic development data were obtained to calculate the spatial distribution of the ESs to adjust the ESV and construct the ESP. The required basic data are shown in

Table 1. Basic data required for research.

Data	Data Resolution	Data Source	Data Usage
Land use/cover type of Sichuan Province in 2018	1000 m × 1000 m	Resource and Environment Science and Data Center (https://www.resdc.cn/, (accessed on 4 April 2021))	ESV calculation
Grain crop yield, grain planting area, and grain price in Sichuan Province in 2018	-	Sichuan Statistical Yearbook National compilation of cost–benefit data of agricultural products	ESV calculation
Average precipitation in different meteorological stations in Sichuan Province in 2018	-	Resource and Environment Science and Data Center (https://www.resdc.cn/, (accessed on 13 May 2021))	Quantification of ESs; ESV adjustment
Global drought and potential evapotranspiration	1000 m × 1000 m	The Global Aridity Index and Global Reference Evapotranspiration dataset (https://figshare.com/articles/dataset/Global_Aridity_Index_and_Potential_Evapotranspiration_ET0_Climate_Database_v2/7504448/3, (accessed on 24 July 2020))	Quantification of ESs; ESV adjustment
Soil sand, silt, clay, organic matter content, and soil bulk density	1:100,000,000	Harmonized World Soil Database (HWSD) The second National soil Survey (http://westdc.westgis.ac.cn/data/611f7d50-b419-4d14-b4dd-4a944b141175, (accessed on 25 June 2020))	Quantification of ESs; ESV adjustment
Spatial distribution of watersheds in China	-	Resource and Environment Science and Data Center (https://www.resdc.cn/, (accessed on 12 July 2021))	Quantification of ESs; ESV adjustment
Digital Elevation Model (DEM) of Sichuan Province in 2018	30 m × 30 m	Geographical Information Monitoring Cloud Platform (http://www.dsac.cn, (accessed on 4 April 2021))	Quantification of ESs; ESV adjustment
Normalized vegetation Index (NDVI) of Sichuan Province in 2018	30 m × 30 m	Geospatial Data Cloud (http://www.gscloud.cn/, (accessed on 20 April 2021))	Quantification of ESs; ESV adjustment
Net Primary Productivity (NPP) of Sichuan Province in 2018	500 m × 500 m	National Earth System Science Data Center (http://gre.geodata.cn/, (accessed on 8 August 2021))	Quantification of ESs; ESV adjustment

.

Specifically, to correspond with the “Table of equivalent value per unit area of ecosystem services in China”, land use types were classified as “woodland, grassland, farmland, construction land, waterbody, and bare land” based on the China Land Resources Classification System. To ensure the accuracy of the results, all of the data that were acquired were resampled to a spatial resolution of 1 km using ArcGIS 10.6 software and uniformly converted to the WGS1984 ellipsoid and UTM projection coordinate system.

2.2. Methodology

This study proposed a new ESP construction method by calculating the spatial distribution of the ESs and quantifying different attributes of ecological corridors in the maintenance of ecological processes. As shown in Figure 3, the research framework in this study includes three steps. The first step is the calculation of the ESV and the adjustment of the ESV through the spatial distribution of the ESs to improve the defects in the mean distribution of the ESV with the same land use type. The second step is to construct the ESP, identify ecological sources based on the adjusted ESV, construct resistance surface, and extract ecological corridors using the MCR model. The third step is to use circuit theory and the gravity model to sort and prioritize the ecological corridors, and this prioritization is used as the basis for establishing the protection order of ecological corridors.

2.2.1. Calculation of Ecosystem Service Value

The ecosystem service value was first proposed by Costanza et al. [1] and is defined as the monetary value for resources used either directly or indirectly to support decision making. It is thought to be a practical tool in tandem with ESs assessments that can bypass the problem of value accounting caused by an incommensurate units of ESs through diverse assessment methods [58]. Hence, this method is widely applied in land use policy making as well as ecological security appraisal [59]. This study calculated the special distribution of the ESV in Sichuan Province following the calculation method proposed by Costanza et al. [1] and Xie et al. [57]. In this method, the value coefficient is derived by multiplying the equivalent factor by the equivalent coefficient, and the equivalent factor is represented by the following equations:

$$D=\frac{1}{7}\left(S_r\times F_r+S_w\times F_w+S_c\times F_c\right)$$

(1)

where D is the equivalent factor, representing the economic value of the grain output from 1 ha farmland [60]. S_r, S_w, and S_c are the proportions of the sown areas of rice, wheat, and corn in China. F_r, F_w, and F_c are the average incomes of planting rice, wheat, and corn per unit area in China.

This method evaluates the ESV of the whole country, and the equivalent factor should be modified when the study area changes. By calculating the equivalent factor of Sichuan Province, the value coefficient table of Sichuan Province was obtained. The formula is as follows:

$$\phi =\frac{Q}{\overline{Q}}$$

(2)

$$V{C}_{ij}=\phi \times V{C}_{oij}$$

(3)

where φ is the correction coefficient, Q is the grain yield per unit area of farmland in Sichuan Province, $\overline{Q}$ is the grain yield per unit area of the whole country, VC_ij is the i-th value coefficient of land use type j, and VC_oij is the original i-th value coefficient of land use type j.

According to the equivalent coefficient table, combined with the land use type of Sichuan Province in 2018, the spatial distribution of the ESV of Sichuan Province was obtained. The formula is as follows:

$$ESV={\displaystyle \sum }_{j=1}^n\left(A_j\times V{C}_j\right)$$

(4)

$$ES{V}_i=\sum \left(A_j\times V{C}_{ij}\right)$$

(5)

where ESV is the total value of ecosystem services, ESV_i is the value of the i-th ecosystem service, A_j is the area of land use type j, and VC_j is the total value coefficient of land use type j.

To verify the rationality of the calculation results, it is necessary to analyze the sensitivity of the ESV, that is, the degree to which ESV changes due to the change in the value coefficients. The coefficient of sensitivity is derived by raising or lowering value coefficients by 50% [61]. The formula is as follows:

$$CS=\left|\frac{\frac{\left(ES{V}_j-ES{V}_i\right)}{ES{V}_i}}{\frac{\left(V{C}_{jk}-V{C}_{ik}\right)}{V{C}_{ik}}}\right|$$

(6)

where CS is the coefficient of sensitivity, and ESV_i, VC_ik, ESV_j, and VC_jk represent the values and value coefficients of the ESs before and after adjustment, respectively. If CS > 1, it indicates that the response of ESV to the value coefficient is elastic, and the accuracy and credibility of the calculation results are poor; if CS < 1, it indicates that the response of the ESV to the value coefficient is inelastic, and the calculation results are accurate and reliable.

2.2.2. Adjustment of Ecosystem Service Value

ESs are fundamentally dependent on ecological processes, and the latter are not only spatial but also temporal [62]. The ESV calculated above is related to the land use type, which is static and cannot reflect the ecosystem dynamics [36,63]. Meanwhile, this method focuses on the ESs rather than ecological processes, making the results unable to accurately reflect the differences in the types and qualities of ESs provided in different regions [64]. In fact, the ESV is also affected by various driving factors, including the precipitation and vegetation index, so it is necessary to adjust the value according to the heterogeneity of the ESs. We adjusted the ESV by calculating the spatial distribution of the important ESs to make the results more in line with reality. According to the “Table of equivalent value per unit area of ecosystem services in China”, seven types of ESs including food production, raw material production, gas regulation, climate regulation, hydrological regulation, soil conservation, and maintenance of biodiversity were selected for evaluation.

• Grain production

Grain production is critical for the survival of humanity and dominates much of the world’s terrestrial and marine environments [65]. Related studies show that there is a positive correlation between soil fertility and soil organic matter content [66,67]. In this study, the content of soil organic matter was used to characterize the supply capacity of grain production. The soil organic matter content data in Sichuan Province were obtained from the HWSD, and the missing data were supplemented by kriging interpolation.

• Raw material production

Ecosystems convert solar energy into biological energy through photosynthesis and produce wood and other raw materials for human use [68]. Net primary production (NPP) represents the amount of energy used by plants for storage, growth, and reproduction and can be used as an index to measure the capacity of raw material supply [69]. In this study, NPP was calculated by the MuSyQ NPP algorithm [70]. The formula is as follows:

$$NPP=GPP-R_a$$

(7)

where NPP represents the total amount of organic carbon that flows from the atmosphere into the plant, GPP is the gross primary production that represents the total amount of organic carbon fixed by plants through photosynthesis, and R_a is the autotrophic respiration, including the energy needed for plants to maintain biomass and growth.

$$GPP=APAR\times \epsilon$$

(8)

where APAR is the photosynthetically absorbed active radiation, which is directly related to NPP, and ε is the light use efficiency calculated through the LUE model proposed by Cui et al. [71].

$$APAR=FPAR\times PAR$$

(9)

where FPAR is the fraction of photosynthetically absorbed active radiation derived from the global land surface satellite (GLASS) dataset [72]. PAR is the photosynthetically active radiation and is calculated as follows:

$$PAR=0.48\times S{W}_{surface}$$

(10)

where SW_surface is the downward surface solar radiation and was obtained from the ERA-Interim dataset.

• Air quality regulation and climate regulation

Ecosystems play an important role in climate regulation by sequestering greenhouse gases and removing harmful gases from the atmosphere [73]. In this study, the InVEST carbon fixed model was used to calculate the quality of the service, and the formula is as follows:

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

(11)

where C_above, C_below, C_soil, and C_dead represent aboveground and underground carbon storage, soil carbon storage, and dead organic matter carbon storage, respectively. The carbon storage parameters of each part are obtained from Bao, Y. [74].

• Water conservation

The ecological process in which ecosystems intercept precipitation, store and purify water, and maintain the normal functioning of the ecosystem is referred to as water conservation. It is essential for human survival and development [75]. The contribution of each landscape to water production is determined by regional annual water production, which is obtained from annual precipitation minus actual evapotranspiration [76]. The InVEST water production model is utilized in this study, and the formula is as follows:

$$Y\left(x\right)=\left(1-\frac{AET\left(x\right)}{P\left(x\right)}\right)\times P\left(x\right)$$

(12)

where Y(x) is the annual water production corresponding to grid x, AET(x) is the annual actual evapotranspiration of grid x, P(x) is the annual precipitation of grid x, and $\frac{AET\left(x\right)}{P\left(x\right)}$ is calculated based on the Budyko curve [77].

$$\frac{AET\left(x\right)}{P\left(x\right)}=1+\frac{PET\left(x\right)}{P\left(x\right)}-{\left. [1+{\left(\frac{PET\left(x\right)}{P\left(x\right)}\right)}^w\right]}^{\frac{1}{w}}$$

(13)

where PET(x) is the annual potential evapotranspiration of grid x, and w (x) is a nonphysical parameter that describes the soil properties under natural climatic conditions.

• Soil retention

Soil erosion is a natural process that shapes natural landscapes through the distribution of the weathering substances produced by geomorphological processes [78]. Soil retention is a general term for the role that ecosystems play in resisting soil erosion. The revised universal soil loss equation (RUSLE) can evaluate the quality of soil retention by calculating total soil conservation, in which the total soil conservation is obtained by subtracting potential soil erosion from actual soil erosion. The formula is as follows:

$$SD=R\times K\times L\times S\times \left(1-C\times P\right)$$

(14)

where SD is the total amount of soil conservation, and R, K, L, S, C, and P are the rainfall erosion factor, soil erodibility factor, slope factor, slope length factor, vegetation cover factor, and management measure factor, respectively.

• Biodiversity conservation

Biodiversity includes the genetic diversity, species diversity, and landscape diversity [79]. It is necessary for human survival and is of great significance to the survival and reproduction of natural species and the maintenance of a suitable environment for different species. In this study, the InVEST habitat quality model was used to calculate the supply capacity of the service. This method establishes the relationship between land use types and habitat threat sources. It evaluates habitat quality according to the influence mode and intensity of threat sources on various land use types, and then reflects the richness of the biodiversity. The formula is as follows:

$$D_{xj}={\displaystyle \sum }_{r=1}^R{\displaystyle \sum }_{y=1}^{Y_r}\left(\frac{{\omega }_r}{{{\displaystyle \sum }}_{r=1}^R{\omega }_r}\right)r_y{i}_{rxy}{\beta }_x{S}_{jr}$$

(15)

where D_xj is the habitat degradation degree of grid x in terms of land use type j, R is the number of threat sources, ω_r is the weight of threat source r, Y_r is the grid set of threat source r, r_y is the number of threat sources on the grid, β_x is the accessibility of threat sources to grid x, S_jr is the sensitivity of land use type j to threat source r, and i_rxy is the impact of grid y of the r-th threat source on habitat grid x. According to different threat sources, there are two types of linear attenuation and exponential attenuation with increasing distance:

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

(16)

$$i_{rxy}=exp\left. [-\left(\frac{2.99}{d_{rmax}}\right)d_{xy}\right] (\mathrm{exponential})$$

(17)

where d_xy is the linear distance between habitat grid x and grid y, and d_rmax is the maximum influence distance of threat source r.

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

(18)

where H_j is the ecological suitability of land use type j, k is a semi-saturation constant that is generally set to 1/2 of grid resolution, and z is a scale parameter that is generally set to 2.5.

We extracted the spatial distribution of seven types of ESs, adjusted the value of all kinds of ESs in each grid in the study area, overlayed each layer, and obtained the adjusted spatial distribution map of ESV in Sichuan Province in 2018. The formula is as follows:

$$V_{ij}={\displaystyle \sum }_{k=1}^K{\displaystyle \sum }_{i=1}^I{\displaystyle \sum }_{j=1}^{J_i}\frac{S_{ijk}}{\overline{S_{ik}}}\times V{C}_{ik}$$

(19)

where k is the ESs involved in the calculation, i is the land use type, J_i is the amount of grid of each land use type in the study area, S_ijk is the k-th ecosystem service quality of grid j in land use type i, $\overline{S_{ik}}$ is the average quality of the k-th ecosystem service in land use type i, and VC_ik is the value coefficient of the k-th ecosystem service in land use type i. To eliminate the influence of extreme values on the adjustment of ESV, it is stipulated that the value range of adjustment factor $\frac{S_{ijk}}{\overline{S_{ik}}}$ is 0.2 to 5 and that adjustment factors above or below the value range will be reassigned to 5 or 0.2.

2.2.3. Construction of Ecological Security Pattern

• Identification of ecological sources

The ESV can reflect the status of an ecosystem. The higher the ESV is, the better the ESs provided. Relying on ESV to carry out ecological planning and policy making can promote the sustainable development of society. The Getis-Ord Gi* tool in ArcGIS 10.6 software was used to identify the cold spots and hot spots of ESV, and the hot spots with 99% confidence were selected as the candidate ecological sources. Ecological sources need a large enough area to reduce external interference [80]. According to the relevant research, the candidate ecological sources with an area of less than 20 km² are excluded, and the remaining sources participate in the construction of the ESP.

• Construction of the resistance surface

The value of the resistance surface can indicate how easy it is for species to pass through a landscape. The lower the value is, the lower the resistance to species migration. To a certain extent, land use type can reflect ecological processes and human activities as well as influence the migration paths of different species. As a result, most existing studies are based on the land use types to set the value of a resistance surface [51]. However, this method cannot describe the internal differences between the same land use types, so we used the adjusted ESV based on land use types to construct the resistance surface. ESV can reflect habitat quality, and the latter is positively related to the moving speed of a species within the landscape unit. According to relevant research, the resistance value of construction land is assigned as 500, and the resistance surface is constructed by taking the reciprocal of ESV as the resistance value per unit area.

• Extraction of ecological corridors

The MCR model was used to extract the ecological corridors connecting ecological sources. Extracted corridors are the paths with the lowest cost for species movement between two adjacent ecological sources and can reflect the characteristics of species movement to a certain extent [81,82]. The formula is as follows:

$$MCR=f\left(min{\displaystyle \sum }_{j=n}^{i=m}{D}_{ij}\times R_i\right)$$

(20)

where D_ij is the distance spent by species from landscape unit i to j, R_i is the resistance value of landscape unit i, and f is a function for calculating the minimum resistance value from any point in the study area to the ecological source.

The Linkage Mapper plug-in in the ArcGIS 10.6 software was used to obtain the minimum cost path between ecological sources as the optimal ecological corridors for species movement to participate in the construction of the ESP.

2.2.4. Priority Assessment of Ecological Corridors

• Calculation of the importance of ecological corridors

The gravity model determines the importance and protection priority of ecological corridors by comparing the interaction intensity between ecological sources. High intensity indicates that the ecological sources of the corridor connection are of better quality or that the corridor provides a better connection [83]. The formula is as follows:

$$G_{ab}=\frac{N_a\times N_b}{D_{ab}^2}=\frac{L_{max}^2\times \ln S_a\times \ln S_b}{L_{ab}^2\times P_a\times P_b}$$

(21)

where G_ab is the interaction intensity of the ecological corridors connecting sources a and b; N_a and N_b represent the weights of ecological sources a and b, respectively; D_ab is the standardized cumulative resistance of the corridor; L_ab is the minimum cumulative resistance of the corridor connecting sources a and b; L_max is the maximum cumulative resistance of the corridor in the study area; S_a and S_b are the areas of sources a and b, respectively; and P_a and P_b are the resistance values of sources a and b, respectively.

• Calculation of connectivity of ecological corridors

The Centrality Mapper tool in the Linkage Mapper plug-in can quantify ecological corridor connectivity. Referring to the circuit theoretical model, the Centrality Mapper regards the study area as a conductive surface. It turns the current into different ecological sources and accumulates the currents successively to obtain the cumulative current value of each corridor [84]. The connectivity is determined by comparing the current value of each ecological corridor. The higher the current value is, the more ecological sources are affected by the corridor, and the greater the contribution to the connectivity of the ecological network.

• Priority classification of ecological corridors

Based on the calculation method above, the calculated interaction intensity and corridor current value were standardized. To reduce the influence of the data magnitude on the evaluation results, we took natural logarithms of the interaction intensity and corridor current value. The formula is as follows:

$$Z_i=\frac{x_i-\overline{x}}{s}$$

(22)

where Z_i is the evaluation index, x_i is the i-th evaluation indicator (interaction intensity or corridor current value), $\overline{x}$ is the mean value of the evaluation indicator, and s is the standard deviation of the evaluation indicator.

The standardized value of the interaction intensity and corridor current will participate in the priority classification as an importance index and connectivity index of the ecological corridors, respectively. A plane Cartesian coordinate system is established, where the horizontal axis represents the standardized interaction intensity index, and the longitudinal axis represents the standardized corridor current value index. Together, the two indexes form the “importance–connectivity” index. According to the quadrant, ecological corridors can be divided into four types: the corridors with an importance index and connectivity index greater than 0 are classified as “high importance–high connectivity” ecological corridors. Similarly, the corridors with a negative importance index and positive connectivity index, with a positive importance index and negative connectivity index, and with both a negative importance and connectivity index are categorized as being “low importance–high connectivity”, “high importance–low connectivity”, and “low importance–low connectivity” ecological corridors, respectively.

3. Results

3.1. Calculation and Adjustment of Ecosystem Service Value

The revised equivalence factor of Sichuan Province is 2237.64 CNY/ha, and the value coefficient table is calculated as shown in

Table 2. Value coefficient of ecosystem services in Sichuan Province in 2018 (unit: CNY/ha).

Ecosystem		Land Use Type
Primary	Secondary	Woodland	Grassland	Farmland	Waterbody	Bare Land
Provisioning services	Grain production	765.92	998.01	2320.96	1230.11	46.42
	Raw material production	6588.19	795.89	862.21	773.78	88.43
Regulating services	Air quality regulation	9664.87	3355.86	1610.81	1140.99	134.23
	Climate regulation	9117.36	3494.61	2172.93	4614.68	291.22
	Water conservation	8971.62	3334.20	1689.03	41,172.95	153.55
	Waste disposal	3825.52	2935.86	3091.55	33,028.48	578.28
Supporting services	Soil retention	9095.49	5068.14	3325.96	927.65	384.64
	Biodiversity conservation	10,097.60	4186.81	2283.71	7679.55	895.57
Cultural services	Recreation provision	4607.67	1927.24	376.59	9835.59	531.65
	Total	62,734.24	26,096.63	17,733.77	100,403.79	3103.99

.

The results of the sensitivity analysis (

Table 3. Results of the sensitivity analysis.

	Woodland	Grassland	Farmland	Waterbody	Bare Land
Coefficient of sensitivity	0.60	0.25	0.12	0.03	0.01

) show that the elasticity coefficient of each land use type is less than 1, the response of the ESV to the value coefficient is inelastic, and calculation results are accurate and reliable.

The ESV was adjusted according to the spatial distribution of the ESs. As shown in Figure 4, the high- and low-value areas of the seven kinds of ESs all reflect spatial heterogeneity to a certain extent. Among them, high-value areas of grain production are concentrated in the bottom of the Sichuan Basin, especially in the Basin Mountain Area around the Dalou Mountains. These areas have flat terrain, sufficient water resources, and a large output of agricultural products that are rich in variety. Low-value areas are mainly distributed in the Northwest Sichuan Plateau Area and in the Southwest Sichuan Mountainous Region.

Four types of ES, namely, raw material production, air quality regulation, climate regulation, and biodiversity conservation, show a similar spatial distribution pattern. High-value areas are mainly located in the Western Sichuan Basin and are mainly distributed in the Southwest Sichuan Mountainous Region and Basin Mountain Area. The higher quality of services is partly due to high-density plant distribution and less human disturbance in this area. Relatively speaking, the areas near the Sichuan Basin are characterized by low-value accumulation.

The spatial aggregation degree of water conservation is the most obvious, and the intensity of rainfall and different climatic characteristics within regions affect the spatial distribution of water conservation to a great extent. High-value areas are mainly distributed in the Basin Mountain Area, especially in the Qionglai Mountains and Dadu River, and some of the high-value areas are located in the Dalou Mountains. There is an obvious low-value accumulation in the Northwest Sichuan Plateau Area and in the Basin Mountain Area.

Soil retention also has obvious spatial aggregation characteristics. High-value areas are mainly distributed in the Basin Mountain Area, especially in the Longmen Mountains. Such areas are dominated by woodlands with high vegetation coverage that can retain a large amount of precipitation and reduce the soil erosion caused by rainwater. There are also banded high-value areas distributed in the Daba Mountains and along the eastern edge of the Liangshan Mountains.

As shown in Figure 5, the spatial distribution of the ESV in Sichuan Province was uneven. In terms of quantity, the ESV per unit area has a large span. Excluding the construction land with an artificial value of 0, the lowest value of the other land types is 1750.31 CNY/ha, and the highest value is 231,971 CNY/ha. From the spatial point of view, the ESV of the study area shows a spatial distribution pattern that is high in the middle and low on both sides. High-value areas are concentrated in the regions of the Longmen Mountains–Qionglai Mountains–Daliang Mountains. These areas have a complex topography, a high degree of woodland cover, and a low intensity of human activities, all of which can provide soil retention, water conservation, and other high-quality ESs. The low-value areas are mainly distributed in the Northwest Sichuan Plateau Area and in the Basin Hilly Area, corresponding to the Ganzi prefecture and various cities in the Sichuan Basin. The Basin Hilly Area is mainly composed of plains and hills, with flat terrain, intense human activity, and strong interference intensity. Continuous cultivated land and built-up areas have an obvious impact on the ecological environment. As for Northwest Sichuan, the altitude is high, the climate is cold, and the Gobi and bare land are widely distributed. Due to the harsh natural conditions, vegetation coverage in this area is obviously lower than that in other areas, and the fragile ecological environment is the direct reason for the low value of ESs.

3.2. Construction of Ecological Security Pattern

The Spatial Autocorrelation tool in the ArcGIS 10.6 software was used to measure the spatial autocorrelation degree of the ESV. Moran’s I index was 0.46, indicating that the regional spatial correlation was positive. The Z(I) score was much higher than 1.65, and the p-value was less than 0.01, indicating that the ESV shows significant agglomeration distribution characteristics in space [85].

• Identification of ecological sources

A total of 179 patches were identified as ecological sources that participate in the construction of the ESP, as shown in Figure 6. The total area of the ecological sources is 118,327 km², accounting for 24.28% of the study area. In terms of land use types, most of the ecological sources are composed of woodland and grassland. Among them, woodland accounted for 66.62%, and grassland accounted for 19.81%. From the perspective of spatial distribution patterns, ecological sources are mainly distributed in the middle of Sichuan. The ecological sources in the Longmen Mountains–Qionglai Mountains–Daliang Mountains are concentrated, running through Sichuan Province from south to north. There are also a series of ecological sources in the Daxue Mountains, the Daba Mountains, the Ridge and Valley Province of Chuandong, and the Dalou Mountains. These large patch areas constitute the framework of the ecological sources in Sichuan Province and play a key role in maintaining regional ecological security. The distribution of ecological sources in the Northwest Sichuan Plateau Area and in the Basin Hilly Area is sparse and scattered, the landscape connectivity is low, material and energy flow are subject to great resistance, and species migration is subject to many interference factors.

• Extraction of ecological corridors

A total of 445 ecological corridors were extracted to participate in the construction of the ESP, as shown in Figure 7. The total length of the ecological corridors was 2682.27 km. Affected by the source distribution and supply capacity of the ESs in the study area, the corridor density is high in the west and low in the east. Because of the dense ecological source distribution and high-quality ecological environment in the middle of the study area, corridors in this region have the highest density, short average length, and low cumulative resistance. The density of corridors in the western part of the province is moderate. Due to the complex geomorphological features of the region, the average length of the corridors has increased, and the decline in the number of ecological sources has led to a significant increase in the number of corridors connecting the same ecological source. This reflects the importance of ecological sources in maintaining the overall connectivity of the ecological network in this region. The density of the corridors in the eastern part of the province is the lowest and the average length is the longest. These corridors indicate that there are numerous ecological sources in the middle and east, but because of the large range and high intensity of human activities in this area, the connectivity of the ecological network is easily reduced due to the disturbance and fracture of the corridors.

The biodiversity in ecological corridors is rich and improves as the width of the corridors increases, and the wider the corridor is, the better the quality of the internal habitat is [86]. From the point of view of species migration, the corridor width required to meet the migration requirements of different types of species is different [33]. Species are diverse and widely distributed in Sichuan Province, and high-quality corridors can facilitate species migration. Comprehensively considering the landscape function of corridors combined with related research, the width of the ecological corridors in the study area was determined to be 1000 m. By superimposing the ecological corridor layer and the land use map, the proportion of each land use type in the ecological corridors was obtained. Woodland and grassland account for 64.86% and 17.85% of the total ecological corridor area, respectively.

3.3. Priority Assessment of Ecological Corridors

The assessment of the ecological corridors is shown in Figure 8. A total of 232 low-resistance ecological corridors connected to high-quality ecological sources were identified as high-importance corridors with an average length of 9768.53 m. These high-importance corridors are mainly distributed in the middle of the study area, which is dominated by woodland and grassland land types, and the terrain is steep. Among them, the proportion of high-importance ecological corridors in the Daliang Mountains is more than 50%. In this area, ecological sources are dense, the ecological environment is of good quality, and the risk of disturbances to species migration is weak. In addition, there are also high-importance corridors in the Daba Mountains. The rest of the corridors are mainly distributed in the east and west of the study area. The relatively long distance between sources increases the resistance of these corridors and decreases the connectivity.

The average length of the 203 high-connectivity ecological corridors was 16,713.86 m, and the distribution was relatively scattered. There are many highly connected ecological corridors in the northeast and southwest of Sichuan Province. The northeast corridors communicate two ecological sources of the Longmen Mountains and the Daba Mountains and play a key role in maintaining the connectivity of the ecological network in the north. The corridors in the southwest are mainly distributed in areas of the Daxue Mountains and the Daliang Mountains. These corridors are connected to a large number of ecological sources and have a great impact on the overall landscape connectivity.

Figure 9 shows the “importance–connectivity” index of all the ecological corridors. In the figure, the horizontal and vertical coordinate values of each point represent the importance index and connectivity index of the corresponding ecological corridor. There were 153 ecological corridors with high importance and high connectivity, accounting for 34.38% of the total number of corridors. Such corridors are mainly distributed near large ecological sources and need to be prioritized when formulating ecological protection policies. There were 49 ecological corridors with low importance and high connectivity, accounting for 11.01% of the total number of corridors. Such corridors are scattered in the study area and have long average lengths. The connectivity quality of these corridors can be improved by adding ecological “stepping stones” to provide species with a short stay and rest along the path. There were 78 ecological corridors with high importance and low connectivity, accounting for 17.53% of the total number of corridors. Such corridors are mainly distributed in the middle of the study area, and their connectivity can be improved by removing internal areas that hinder species migration (i.e., “obstacle points”). There were 165 ecological corridors with low importance and low connectivity, accounting for 37.08% of the total number of corridors. Most of them are located in the east and west of the study area, that is, the Northwest Sichuan Plateau Area and the Basin Hilly Area. The relatively long corridor length has a great impact on providing links between ecological sources and maintaining the overall connectivity of the region. To make expression clearer, we selected one example corridor from each of the different types of ecological corridors, marked their location in the study area (Figure 9), and provide various parameters of the selected corridors in

Table 4. Parameters of selected ecological corridors.

	Corridor Length (m)	Corridor Resistance	Connectivity Index	Importance Index	Corridor Type
Corridor A	137,852	3,995,130	−1.01	−1.84	low importance–low connectivity
Corridor B	21,071	415,213	−0.59	0.02	high importance–low connectivity
Corridor C	156,367	5,589,211	0.14	−2.01	low importance–high connectivity
Corridor D	13,485	257,641	3.16	0.45	high importance–high connectivity

Corridor resistance = $\sum cell length\times resistance value$

.

4. Discussion

4.1. Constructing Ecological Security Pattern Based on Ecosystem Service Value

Based on the interaction between landscape patterns and ecological processes, the ESP theory maximizes the utility of ESs by establishing landscape patterns and optimizing the process of ESs to achieve an effective and rational allocation of natural resources and green infrastructure, allowing ecological security to finally be realized. As a result, research on ESs has become a key element of the construction of the ESP. For a long time, the academic circle has failed to reach a consensus on the identification and construction of different kinds of landscape elements. Taking ecological sources as an example, at present, the mainstream method is to carry out quantitative identification by integrating ecological function and ecological sensitivity [87]. Starting from structural connectivity, some scholars use methods such as morphological spatial pattern analysis (MSPA) to identify ecological sources. By calculating the ESV, ESs can be converted to the same unit, thus solving the problem of comparison. In this study, the original value is adjusted according to the spatial distribution of the ESs, which eliminates the mean distribution of the ESV under a single land use type so that it can accurately reflect the quality of the ESs in the study area. In the construction of resistance surface, the resistance value calculated by the ESV fully takes into account ecological functions so that the calculated results can reflect the difficulty of organisms passing through the landscape unit and then obtain a more precise ecological corridor distribution. Compared to ecological processes, ESV pays less attention to landscape connectivity. To compensate for the deficiency in landscape connectivity in the process of ecological source identification, in this study, the contribution of ecological corridors to landscape functional connectivity was added to the evaluation content in the extraction of ecological corridors. The ESP of Sichuan Province in 2018 was constructed by comprehensively considering the importance of ESs and landscape connectivity.

The results show that the central part of Sichuan Province can provide high-quality and diversified ESs. This area is located at the junction of the first and second steps of the three steps of Chinese topography, which deserve more attention in the formulation of environmental protection strategies. It should be noted that the area is close to Chengdu, the capital of Sichuan Province, and is extremely vulnerable to interference from human activities. Therefore, in the formulation of urban policies, it is necessary to restrict urban development activities in this area through the introduction of an eco-environmental access list to prevent the quality and stability of ecological corridors from being destroyed. Eastern Sichuan presents fragile ecological security due to intensive human activities, and ecological corridors with a longer average length are prone to breaking up due to factors such as reclamation and urban expansion; thus, so special attention is needed to ensure the protection of these ecological corridors. Approaches such as returning farmland to woodland and strictly restricting human activities around corridors are effective methods that can be put into use. For more isolated mountains, such as the Longquan Mountains in eastern Chengdu, urban sprawl should be strictly restricted in order to protect biodiversity; ecological conservation measures are also needed to protect the mountains as “stepping stones” for species migration [3]. As an important part of ecosystems, low-intensity arable land provides important ESs such as gas regulation, grain production, and pollination. It is necessary to maintain its role in ecological protection based on following the national ecological red line strategy [88]. For high-quality farmland, strict protection measures ought to be implemented to put an end to the frequent changes in its use. Land fallow and crop rotation should also be applied in order to realize sustainable development [34].

The “Outline of the Construction Plan of Chengdu-Chongqing Economic Circle” issued by the Chinese government in October 2021 defines the development direction of urbanization in the region, and the exchanges of personnel and capital between the two cities are bound to promote urban expansion and infrastructure development. This makes it more urgent to achieve a balance between urbanization and ecological protection in Eastern Sichuan, where the environment is facing an imminent threat. Long-distance railways, highways, and infrastructure corridors will hinder the movement of species within the ecosystem, leading to the fragmentation of biological habitats and decreasing biodiversity [89]. Therefore, in the process of infrastructure construction, it is necessary to minimize its impact on important ecological corridors through building bridges and tunnels to ensure the normal passage of ecoflow. In addition, some cities close to the ecological sources in the economic circle, such as the cities of Yibin and Luzhou, should expand in the areas as far away from the ecological sources as possible to reduce the damage to the sources. It is worth noting that these areas are usually located in the border areas between Sichuan Province and other provinces (i.e., Yunnan Province, Shaanxi Province, and Chongqing Municipality), which makes it necessary to build a cross-regional ecological protection cooperation mechanism and explore protection measures for concentrated ecological sources and lengthy aquatic corridors.

4.2. The Importance of Ranking Ecological Corridors

With in-depth discussions in the construction of an ESP in academic circles, research on ecological corridors is becoming increasingly mature. As a typical network structure, ecological corridors have their redundancy, which leads to different contributions of different corridors to the maintenance of ecological network connectivity [90]. By analyzing the contribution of ecological corridors to landscape connectivity and determining important ecological corridors, we can have a deeper understanding of ecological security to formulate efficient environmental protection measures. However, most existing studies stop at the characteristics of the corridor itself, such as the corridor’s length, resistance, distribution, and so on, and lack a macro analytical perspective. Therefore, in this study, the ecological corridors were subdivided into four categories according to the “importance–connectivity” index through the usage of the gravity model and circuit theory model, and the priority of ecological corridor protection was defined. The idea presented here improves previous research methods and thoroughly discusses the role of the ecological corridor in the ecological network. It is worth mentioning that the conclusions that can be drawn using this method can be compared using relevant research in order to obtain more detailed results. For example, Zhou et al. analyzed the connectivity and complexity of the ecological network in eastern China with reference to graph theory [91]. By using the “importance–connectivity” index to analyze those corridors, more interesting conclusions can be drawn from the perspective of the region as a whole and the corridor itself.

Sichuan Province is an important province in Southwest China, and in recent years, its economic growth rate has been at the forefront of the country. Rapid economic growth usually leads to the deterioration of the environment, so it is necessary to formulate corresponding ecological protection policies to achieve sustainable development. The balance between economic development and ecological security is dynamic, and the excessive pursuit of economic development will result in serious or even irreversible damage to the environment. However, blindly pursuing the environment while ignoring economic benefits is not a sustainable means of protection. The sustainable development of the economy requires the continuous support of the environment, and achieving the goal of environmental protection also requires sustained political investment and a great deal of financial support. Therefore, the excessive pursuit of economic development or environmental protection will greatly reduce the actual effects of the environmental protection policy. The western region of Sichuan Province undertakes an important function of ecological security protection. Compared to Eastern Sichuan, the economic development in the western part of the province is severely lagging. To balance ecological protection and development opportunities, local governments need to explore and establish a standard system of ecological compensation; clarify the sources of ecological compensation funds, compensation channels, and compensation methods; and provide sufficient economic security for cities and states that sacrifice economic development in order to undertake ecological protection [91]. Classifying ecological corridors and determining the order of protection can enable decision makers to aim at the target when formulating relevant laws and regulations, maximize benefits under the condition of paying the same cost, and clarify policy implementation.

4.3. Limitations of the Study

Although the method used in this study has been improved and innovated to a certain extent compared to other methods, there is still some room for improvement. First of all, the study did not fully take into account the element of human activities, and social and economic data were not fully utilized, which led to the landscape elements close to cultivated land, construction land, and other areas to be underestimated in terms of their level of prioritization [10,34]. Secondly, the study does not factor in the diverse climatic conditions and unbalanced human activities in Sichuan Province; these factors will affect the future changes in land use types and make the ESP constructed in this study have a certain deviation from the real situation [10].

In addition, although the contribution of the urban ecosystem to all kinds of ESs is small, simply setting its value to 0 cannot reflect reality. Hani et al. showed that fragmented urban green spaces have a positive impact on bird biodiversity [3], so it is also meaningful to quantify the ESV of construction land in the study. Limited by the accuracy of data acquisition, glaciers, wetlands, and other ecosystems are not fully reflected in this study. Although these ecosystems are less distributed in the study area, they still affect the research results to a certain extent.

4.4. Directions for Future Research

In this study, we use the “importance–connectivity” index to represent the priority of ecological corridors, and the concept of “priority” can also be applied to other landscape elements. Taking the ecological source as an example, Su et al. predict the probability and degree of damage to the environment through the ecological risk model, and this model can also provide a reference for evaluating the protection priority of ecological sources [92]. Related research can appropriately expand the research objectives to formulate a relatively comprehensive ecological protection policy from multiple angles.

How to improve the accuracy of our method to calculate the values of various ESs is also the focus of our future research. We found that the leaf area index (LAI) can characterize air quality regulation services more precisely. The acquisition of relevant information requires a large number of field investigations, so our future work will focus on data collection.

5. Conclusions

Considering Sichuan Province in southwest China as the study area, we constructed an ESP based on the adjusted ESV, and carried out a priority assessment of ecological corridors by adopting multidisciplinary knowledge, including ecology, physics, and mathematics, to evaluate the importance of ecological corridors to provide connections between ecological sources and their contribution to maintaining overall ecological network connectivity, finally forming a more practical ESP construction framework.

The results show that Sichuan Province consists of 179 ecological sources of different sizes and a total area of 118,327 km², with most resources being concentrated in the middle of the study area. A total of 445 ecological corridors of different lengths are distributed in the east and west sides of the province and are bounded by the Longmen Mountains–Qionglai Mountains–Daxue Mountains. The main land use types of these landscape elements are woodland and grassland, and fewer resources are available in the eastern part due to the interference of human activities. According to the “importance–connectivity” index, the ecological corridors can be divided into four categories: high importance–high connectivity, low importance–high connectivity, high importance–low connectivity, and low importance–low connectivity, with each group comprising 153, 49, 78, and 165 ecological corridors, respectively. The four types of ecological corridors are different in terms of prioritization and method of protection. When implementing environmental protection measures, high-priority corridors should be protected first according to the level of local economic development to obtain a more obvious effect.

We used a variety of methods to calculate the value of seven kinds of ESs and systematically describe the ecological security in Sichuan Province. As areas with a dense distribution of landscape elements, the Basin Mountain Area, Western Sichuan Alpine Canyon Region, and Southwest Sichuan Mountainous Region constitute the cornerstones of the ESP in Sichuan Province. All levels of government need to strengthen environmental monitoring in this region, implement ecological compensation policies, and jointly build a cross-regional ecological protection cooperation mechanism with surrounding provinces and cities to take advantage of the ecological functions in this large area of ecological sources and long ecological corridors. In addition, research on ecological corridors from the perspective of ecological processes expands the existing research direction and deepens the research content from the characteristics of corridors to their ecological function, which can provide a more solid theoretical basis for policymaking. Future studies should explore the protection priority of ecological sources and create a systematic and comprehensive framework for ESP by integrating various landscape elements to improve the feasibility and effectiveness of environmental protection policies and achieve the goal of sustainable development.