Articulation of the cross-boundary effects of China’s ecological conservation redline program: A perspective on the ecological security network and ecological radiation

Abstract

China’s Ecological Conservation Redline (ECR) program ensures the coordination and sustainability of natural and economic development while maintaining regional ecological security. Current research focuses on the ecosystem services within ECR areas but ignores cross-boundary ecological flow and the interactions between the internal and external ecological effects of ECR areas. In addition, the ecological background has spatial continuity that is not limited by boundaries, and the radiation effect areas extending beyond ECR areas have not been quantified. In this study, the Beijing ECR areas and ecological security network were integrated in order to connect the ecological process and landscape pattern to the ECR through the circulation path of ecological corridors, and cross-boundary effects between patches were examined. The field spread model was used to quantify the radiation influence range of ECR areas. Additionally, 972.46 km of ecological corridors were identified in Beijing, and abundant corridors effectively linked the ECR areas and maintained the material cycle. In the surrounding areas, ecological corridors were spread radially, with a total length of 941.85 km, promoting cross-boundary ecological flow between the ECR and surrounding source areas. This study used 25 ecological nodes to constitute the cross-boundary ecological security network system. The total radiation area based on the ECR source was 9572.16 km². These results provide support for the radiation effect of ECR and cross-boundary ecological flows and suggest a useful model for sustainable ecological development and cross-boundary management.

Keywords

ecological conservation redline ecological security network field spread model cross-boundary effect ecological flow

I Introduction

Urbanization, population growth, and socioeconomic development have led to a large number of environmental problems around the world (Charfeddine, 2017; Elhacham and Alpert, 2021; Van Niekerk et al., 2019). Urban ecological security, which maintains the sustainable development of ecosystem services and weakens the destruction and degradation of ecosystems, is composed of the urban environment and future development security (Wang and Ouyang, 2007; Wang and Bao, 2021; Rodriguez-Rodriguez et al., 2019). To promote the high quality of inhabited environments and enhance the serviceability of urban ecosystems, the ecological security system concept was developed based on ecological restoration (Wang et al., 2020). Ecological security networks are frequently designed to maintain ecological security and moderate the conflict between ecological security and socioeconomic development (Peng et al., 2017). Ecological security networks connect complete landscapes and biological habitats, improving landscape connectivity, promoting species migration and gene flow among green patches, and resulting in a stable regional ecosystem structure (Kong et al., 2010; Wang et al., 2021).

The model formed using the “source-resistance surface-corridor” concept has become the paradigm of ecological security network construction (Liu and Chang, 2015). Ecological sources refer to areas with high ecological value from which regional species or ecological events spread out and are maintained. For the identification of ecological sources, scenic spots and natural reserves are widely selected based on the ecological status of source patches and their importance in the spatial structure of the landscape matrix (Shi et al., 2019; Wu et al., 2013; Zhou and Cadenasso, 2012). Ecological resistance surface is a reflection of the state and trend of biological space movement, indicating the resistance that species need to overcome in the process of movement from a source to a sink. When constructing ecological resistance surfaces, most studies have focused on different land use types (Wei et al., 2019) and the influence of socioeconomic factors (Chetkiewicz et al., 2006). Some ecological promotion factors, which are conducive to ecological security, are of great significance to ecological resistance surfaces. In addition, the construction of a resistance surface is mostly based on the scope of administrative divisions (Dai et al., 2021), and the continuity of substance energy between ecological backgrounds deserves further exploration. Ecological corridors provide channels for the ecological flow of organisms, materials, energy, and information across ecological patches, promoting the integrity and functionality of ecosystems (Ayram et al., 2016; Dong et al., 2020). The minimum cumulative resistance (MCR) model, with a simple data structure and rapid algorithm, has become the primary method for the identification of ecological corridors (dos Santos et al., 2020). Species movement is not always based on the understanding of the basic situation of the landscape and the selection of a single optimal path. Some sub-optimal paths can also become potential ecological corridors (Beaujean et al., 2021). To emphasize the random course of species movement, the effective application of the circuit theory has become a trend (McRae and Beier, 2007). Most of these studies are based upon the assumption that human activity and developed environments have a negative impact on the construction of ecological security networks. Nevertheless, some programs that benefit the construction of ecological security networks should be underscored, such as China’s Ecological Conservation Redline (ECR) program.

The ECR, formulated by the Chinese national government in 2011, was intended to increase the protection and restoration of the ecological functions in fragile ecological areas. To improve the connectivity and integrity of ecosystems, the ECR maintains regional ecological security and sustainable development by prohibiting industrialization and urbanization in selected areas (Ouyang et al., 2016). Additionally, the ECR provides a reference basis for other countries to formulate ecological restoration policies (Gao, 2019). Current research on the effects of the ECR has mainly focused on the ecosystem services in the interior of administrative regions and has emphasized the environmental benefits of the ECR. For example, Zhang et al. (2020) established an eco-environment management framework in the Fenghe River watershed in Xi’an that integrated ECR and trade-offs among ecosystem services. Hu et al. (2020) used the ECR to demonstrate the importance of green space preservation to ecosystem services in Shenzhen. However, understanding the ecological integrity of the environment beyond jurisdictional boundaries is also essential. To minimize the impact of urban expansion on regional environments and improve connectivity among ECR areas, the ECR program should be combined with solutions implemented outside of the ECR area (Ju et al., 2020). Ecological flow, which describes the exchange of material, energy, and information, connects spatially separate positions of supply and demand without administrative boundary limitations (Bagstad et al., 2013; Ge, 2008; Fang et al., 2015; Mitchell et al., 2015). With the channel space provided by ecological corridors in the network, ecological flow spreads horizontally across ecosystems and reflects the path and flux of dynamic flows in ecosystems (Guo et al., 2015). Additionally, ecological corridors enhance the connectivity between patches and maintain the stability of the ecological security network (Peng et al., 2018a; Sahraoui et al., 2021). The ecological security network plays a significant role in the bidirectional effects between landscape pattern and ecological processes and in the regulation of ecological restoration. Currently, the ECR has definitive boundaries, and the interaction between the internal and external ecological effects of the ECR is not considered. Moreover, the radiation effect of the ECR on the surrounding areas has not been quantified. Thus, the integration of ECR and the ecological security network concept can strengthen regional ecological protection and extend the ECR radiation effect through the ecological corridor flow path.

This study was conducted to explore the cross-boundary effect of ECR and to illustrate the interactions between ecological benefits in the surrounding areas. To accomplish this goal, this study integrated the ECR into the methodology of ecological security network construction and quantified the ECR radiation areas based on the field spread model and Getis-Ord Gi* statistics. This study extracted the ecological source area of Beijing on the basis of the ECR area. The ecological sources around Beijing were constructed from the surrounding forest lands and water areas, which have high ecological value. To underline the cross-boundary effect, the expansion probabilities of forest and water areas, obtained by the Geographic Simulation and Optimization System (GeoSOS), were incorporated into the resistance correction. This study identified the ecological security corridor system, combining the least-cost paths with the maximum current density and rivers. Through integration with the ecological security network and radiation areas, this study enhanced and promoted the ECR research approach and provided support for protection and restoration policy formulation after the delineation of ECR. In addition, the results of this study can provide a reference for the formulation of ECR spin-off policies.

II Materials and methods

2.1 Data sources

The ECR data for Beijing were obtained from the Beijing Municipal Ecology and Environment Bureau (http://sthjj.beijing.gov.cn/). These data were mainly used for ecological source extraction and land use expansion probability driving factor analysis in Beijing. The 30 m spatial resolution land use data of Beijing and its surrounding 18 regions in 2018 were obtained from the Resource and Environment Data Cloud Platform (http://www.resdc.cn/). The Digital Elevation Model (DEM) was downloaded from Google Earth, with an original resolution of 9 m. Slope data in the study area were extracted from the DEM. Based on the Landsat 8 OLI images of 24 scene data (https://glovis.usgs.gov/), the normalized differential vegetation index (NDVI) was calculated based on a linear combination of reflectance values in the red band and near-infrared, with a spatial resolution of 30 m. These data were mainly used for ecological resistance surface correction. The ecological resistance surface was modified by the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data, and the driving factors of land use change, which included human activities and natural effects, were analyzed based on water system data and road data. These data were all obtained from the Resource and Environment Data Cloud Platform (http://www.resdc.cn/).

2.2 Method framework

An ecological security network based on the “source-corridor-node” concept is a mainstream approach used to achieve ecological security and balance. The ecological source area in this study was based on the combination of the Beijing ECR area and surrounding patches with high ecological value. To reflect the spatial continuity between the ecological backgrounds, the GeoSOS model was used to calculate the expansion probability of forest lands and water areas. From the perspective of the main influencing factors of ecosystem services and socioeconomic, the first step in ecological resistance surface correction was to integrate the slope, vegetation coverage, and DMSP/OLS nighttime light data. Subsequently, the ecological resistance surface was modified by the expansion probabilities of forest and water areas, which demonstrated the interaction between adjacent pixels and the resistance diversity in different regions. In the identification of ecological corridors, this study combined the least-cost path and the maximum current density to consider the selection of optimal paths and random moving paths (Bishop-Taylor et al., 2015). The ecological corridors provide channels for ecological flow and promote cross-boundary effects. Using the ecological security network in Beijing and the outward radiation centered on Beijing, this study constructed an ecological security network. The flow path and the radiation effect of the ECR area on the surrounding areas were identified based on ecological corridors. Furthermore, the radiation effect areas of the ERC sources were quantified by the field spread model.

2.3.1 Expansion probability of forest and water area based on GeoSOS-Future Land Use Simulation (FLUS) model

Based on the probability of occurrence of the GeoSOS-FLUS model, artificial neural networks (ANN) were used to integrate and calculate the probability of different land use types in each pixel. Given the formation of an adaptive inertia competition mechanism, ANN fuses the suitability probability results of a single unit pixel with the mutual influence, conversion cost, and inertia coefficient of neighboring pixels (Liu et al., 2017). From the perspective of nature and socio-economics, this study selected elevation, slope, distance from water systems, and roads as driving factors.

Through the identification of the expansion probability of forest lands and water areas, the continuity of the underlying surface ecological background was explored, and the influences of surrounding geographical and ecological factors were analyzed. The formula is as follows

\begin{array}{c} s p (p, k, t) = \sum_{j} w_{j, k} \times s i g m o i d (n e t_{j} (p, t)) \\ = \sum_{j} w_{j, k} \times \frac{1}{1 + e^{- n e t_{j} (p, t)}} \end{array}

(1)

where w _j,k is an adaptive weight between the hidden layer and the output layer; the probability of occurrence of land use type k on grid cell p at training time t is denoted as sp (p,k,t) ; Sigmoid () is the excitation function from the hidden layer to the output layer; and net _j (p,t) is the signal received by neuron i in the hidden layer.

2.3.2 Construction of the ecological resistance surface

The ecological resistance surface is generated by the interaction between nature and human activities. The higher the ecological resistance coefficient, the more difficult the expansion of ecological areas. Based on previous research (Gao et al., 2020a), this study constructed the foundation ecological resistance system according to different land use types (Table 1).

Table 1.

Different landscape resistance values.

Land use	Forest land	Grassland	Water area	Cultivated land	Unused land	Construction land
Resistance value	1	10	50	100	200	250

Soil conservation and water retention are important metrics for the delineation of an ECR area. Gao et al. (2020b) used geographical detectors to analyze the influencing factors of soil erosion and water yield in the Beijing ECR area. They found that vegetation coverage was the dominant factor affecting soil erosion. The combination of slope and vegetation coverage significantly enhanced the spatial distribution of soil erosion, and the superposition of land use and slope explained more than 70% of the spatial distribution for water yield. Thus, this study combined DMSP/OLS nighttime light data, vegetation coverage (characterized by NDVI), and slope to modify the ecological resistance surface and established the revision index of the resistance surface from the perspectives of economy and nature to reduce the human subjectivity of resistance surface construction. The formula of ecological resistance is as follows

R_{i} = \frac{N L_{i}}{N L_{a}} \times R_{r},

(2)

where R _i is the grid ecological resistance coefficient based on the nighttime light data (NDVI or slope) correction; NL _i is the nighttime light data (NDVI or slope) of grid i ; NL _a is the average nighttime light index (average NDVI or slope) of landscape a corresponding to grid i ; and R _r refers to the basic ecological resistance index of the land use type corresponding to grid i .

As urbanization in Beijing and its surrounding areas increases, the influence of socioeconomic activities on ecosystems has strengthened. To balance the impacts of human activities and natural factors, a comprehensive resistance correction coefficient was constructed. The equation is as follows

R_{j} = 0.5 R_{D} + 0.3 R_{N} + 0.2 R_{S},

(3)

where R _j is the comprehensive resistance correction coefficient based on the nighttime light data, NDVI, and slope; R _D refers to the nighttime light data correction; R _N is the NDVI correction; and R _S refers to the slope data correction.

Regional ecological security is often affected by the geographical and ecological factors of the surrounding areas. The ecological background is continuous, and the substance and energy are spatially mobile (Peng et al., 2018b). The land use suitability probability based on an ANN considers the interaction and conversion constraints between adjacent pixels and effectively characterizes the relationship between the regional ecological background and land use expansion in surrounding areas. To emphasize the influences of forest lands and water areas on the ecological factors in the ECR area and realize its cross-boundary effect, the expansion probability of forest and water was considered in the ecological resistance system. The specific revision formula is as follows

R = R_{j} \times (1 - \sqrt{P_{f} \times P_{w}}),

(4)

where R is the comprehensive resistance correction coefficient; R _j is the comprehensive resistance correction coefficient based on the nighttime light data, NDVI, and slope to grid j ; P _f refers to the forest land expansion probability in grid j ; and P _w is the water area expansion probability in grid j .

2.3.3 Ecological corridor identification based on the MCR model and circuit theory

The MCR model, which quickly extracts the optimal flow between multiple points over a cost matrix, refers to the finding that biological resources overcome landscape resistance from a source point to a source place (Etherington and Penelope Holland, 2013). This reflects the accessibility of the biological resource movement process. To provide an optimal path for species diffusion and movement, this model determines the minimum cumulative distance cost from source to sink (Blazquez-Cabrera et al., 2016; Kupfer, 2012). In this study, the ecological source and ecological resistance surface were imported into ArcGIS for analysis, and the corridor distribution was obtained. This method emphasized the selection of an optimal path for species movement. The principle is as follows (Zhang et al., 2021)

M C R = f \min \sum_{j = n}^{i = m} D_{i j} \times R_{i},

(5)

where MCR refers to the value of minimal cumulative resistance; D _ij represents the species spatial distance from source point j to patch i ; R _i is the ecological resistance coefficient of spatial unit i to species movement; f refers to the positive correlation function between ecological process and the MCR; and min is the MCR value of i from different sources.

The circuit theory considers that the movement of species in the landscape has random walk characteristics and emphasizes the randomness of path selection, which is more consistent with the species behavior characteristics (Leonard et al., 2017). Doyle and Snell (1984) reported that the electric charge in the circuit had random walk characteristics, and circuit theory linked the circuit with motion ecology. In circuit theory, the landscape of species movement or gene exchange is regarded as a conductive surface, and the individual movement or gene flow of a species is considered as an electron (Gao et al., 2020c; Jin et al., 2020). The low-resistance landscape type represents the frequent movement or gene exchange of species, while the high-resistance landscape type symbolizes the obstacles (Li et al., 2018). The amount of current represents the probability of the species spreading along a certain path (McRae et al., 2008). Circuit theory emphasizes that, as species are not familiar with the landscape they cross, they are more likely to move along paths with high current densities. The circuit theory considers the redundancy of a corridor, which is a supplement to the ecological corridor based on the least-cost path. In this study, the circuit theory was analyzed using Circuitscape 4.0, and the pairwise mode was selected to identify the ecological corridor.

2.3.4 ERC radiation areas based on the field spread model and Getis-Ord Gi* statistics

The distance attenuation principle in field spread model represents the spatial interaction of Newton’s universal gravitational law between regions and other geographical entities (Chen et al., 2017). The radiation capacity of ecosystem service values in an ECR area decreases with the increase of distance, and it is consistent with the assumptions of Newton’s universal gravitational law. The ERC radiation areas depend on the gravitation and radiation capacity of the ERC area to the surrounding ecological patches. Thus, this study calculated the ecosystem service values of water retention, soil conservation, and biodiversity maintenance in each ecological source area based on the ecosystem service equivalent value per unit area proposed by Xie et al. (2015). Subsequently, the ecosystem service value was input into the field spread model to effectively simulate the radiation intensity of ecosystem service functions per unit area. The equation is as follows

F_{i k} = r_{i} \frac{P_{i}}{d_{i k}^{2}},

(6)

where F _ik represents the average radiation intensity of ecological source i at patch k ; P _i is the ecosystem service value of ecological source i ; d _ik refers to the distance from source i to patch k , which is represented by the cost distance based on the MCR model in this study; and r _i is the correction factor, which is the ratio of the ecosystem service value of source i to the ecosystem service value of all sources.

Getis-Ord Gi* statistics calculate the local autocorrelation index based on the dataset and use the local index to explore the spatial autocorrelation (Reddy et al., 2016). Getis-Ord Gi* statistics identify the hotspots of statistical significance. Given the aggregation of high radiation values, in this study, Getis-Ord Gi* statistics were used to obtain the influence range of ecological sources based on the ERC. The equation is as follows

G_{i}^{*} = \frac{\sum_{j = 1}^{n} w_{i j} (x_{j} - \bar{x})}{S \sqrt{\frac{[n \sum_{j = 1}^{n} w_{i j}^{2} - {(\sum_{j = 1}^{n} w_{i j})}^{2}]}{n - 1}}},

(7)

where G ^*_i refers a z-score of feature i ; x _j is the attribute value of feature j ; w _ij represents the space between feature i and j ; n is the total number of features; and S is the standard deviation.

2.3 Study area

This study focused on the ECR area of Beijing and the 18 regions around Beijing, including Manchu Autonomous County of Fengning, Luanping County, Chengde County, and Xinglong County, with a total area of 54,828.89 km², in order to analyze the cross-boundary effect of the Beijing ECR area. Beijing is located on the northern margin of the North China Plain and is surrounded by mountains to the west, north, and northeast. In total, 62% of Beijing’s area is mountainous. The southeast area is an alluvial plain tilted toward the Bohai Sea. The terrain distribution is high in the northwest and low in the southeast. Beijing is the capital of China and one of the largest cities in the world. It is strained under the constant pressure of urban expansion and resource limitations (Li et al., 2013). The ecological carrying capacity and the ecosystem service functions in Beijing have greatly decreased, and the current ecological situation is bleak. To repair and protect the natural ecological system of Beijing, strengthen the sustainable management of natural resources, and ensure ecological security, in 2017, Beijing’s government mandated the enhanced management of the ecological bottom line. This announcement, termed the Beijing City Master Plan (2016–2035), defines and stipulates strict compliance with the ECR and strengthens ecological conservation and construction rules (Gao and Zuo, 2021). The Beijing ECR involves the ecosystem services of water retention, soil conservation, biodiversity maintenance, and the preservation of important rivers and wetlands. These areas are mainly distributed in the western and northern areas, totaling 4289.07 km², which accounts for 26.1% of the Beijing area. The water retention and soil conservation ECR areas are the key ecosystem service areas in Beijing and are mainly distributed in the north and northeast. These ECR areas are closely connected to the Miyun reservoir basin and constitute an important source of surface water in Beijing. The biodiversity maintenance ECR area mostly consists of forest land and benefits from the implementation of afforestation in and around Beijing. Afforestation effectively reduces soil erosion and improves ecological sustainability and biodiversity. The adjacent areas northeast and southwest of Beijing are mostly forest lands and water areas that are closely connected to the ECR (Figure 1).

Figure 1.

The geographical location of the study area. ECR: Ecological Conservation Redline.

III Results

3.1 Beijing’s ECR and surrounding high-quality ecosystems provide ecological sources

Ecological conservation redline areas have high ecological value, protect important ecosystem services, and maintain ecological security (Bai et al., 2016). In this study, the ECR area was taken as the ecological source foundation of Beijing. Considering the effects of forest and water areas on the ECR area, this study selected patches of forest land and water areas surrounding Beijing as the basis of the ecological source. The area change tended to be gentle when the area threshold was greater than 10 km² (Figure 2). Thus, 10 km² was considered as the threshold of an ecological source area, and a large number of patches under this threshold value were removed.

Figure 2.

Total area of ecological sources with areas larger than threshold values of 1–15 km².

After merging the small patches, the ECR areas above the threshold of 10 km² were extracted as the ecological source area. These areas covered a total of 3944.91 km² and were mainly distributed in the north and southwest of Beijing. The forest land and water areas larger than 10 km² in the areas surrounding Beijing were set as the supplementary ecological source area, with a total area of 12,764.37 km². Beijing’s ECR and the surrounding ecosystems were considered mutual ecological sources totaling 16,709.28 km². There are large areas of construction and cultivated land in the southern plain that will play a pivotal role in future ecological restoration projects. To highlight the ecological construction in the southern plain, this study combined the maximum current distribution with the forest land and its surrounding cultivated land and added four sources of ecological restoration, covering an area of 640.46 km² (Figure 3). The spatial distribution of ecological sources was relatively compact. While this ECR area promotes ecological security and sustainable development in Beijing, it also has an ecological radiation effect on the surrounding areas. The patches with high ecological value around Beijing supplement the ECR area. On this basis, the ecological flow effect between the Beijing ECR area and the surrounding areas was analyzed. The ecological sources had high-quality environments and should be protected in future construction.

Figure 3.

Ecological source distribution.

3.2 Corrected ecological resistance surface for Beijing and its surroundings

In the ECR area of Beijing, forest land (89.11%) and water areas (6.12%) are the main land use types that promote the sustainable development of ecological processes and functions. On the basis of the GeoSOS-FLUS model, the expansion probabilities of forest land and water area were analyzed. Forest land areas with high expansion probability were mainly distributed in the ECR of Beijing and its adjacent areas. Compared with the expansion probability value of forest land, the water areas with high expansion probability were mainly distributed in the southeast and central areas (Figure 4). Natural vegetation is crucial for habitat quality and can substantially alter ecosystem function (Newbold et al., 2015). The distribution of forest land expansion probability indicated that the carbon storage and habitat quality in the north and west will be optimized in the future, which was similar to the findings of Chen et al. (2020). The dispersed distribution of water areas with high expansion probability demonstrates that the surrounding environment will constrain the extension of water areas. Thus, more attention should be focused on promoting water retention in Beijing and its surrounding areas.

Figure 4.

Probability of forest land (a) and water area (b) expansion.

To reflect the mutual feedback mechanism between the ecological background of Beijing and its surroundings, the ecological resistance surface was modified, and Beijing’s ecological resistance surface was extracted from the regional comprehensive resistance surface. Comparing the resistance surface with and without ecological mutual feedback mechanisms, it was found that the resistance surface considering the ecological mutual feedback mechanism had a greater ecological resistance value. Furthermore, the patches with high-resistance values on the corrected resistance surface were clustered, and the differences in resistance values were significant (Figure 5). This result indicates that considering the ecological background continuity of the surrounding area will optimize the construction of ecological resistance surfaces.

Figure 5.

Uncorrected (a) and corrected (b) ecological resistance in Beijing; comprehensive ecological resistance in the study area (c). MCR: minimum cumulative resistance.

Areas with high ecological resistance were mainly distributed southeast of Beijing, which coincided with the spatial aggregation of carbon emissions and sequestration reported by Xia et al. (2019). Human activity in this area is intense, and the city’s substance and energy cycles are frequent. Areas with low ecological resistance were located on the periphery of urban areas with better ecological security, mainly in the north and east. Specifically, the resistance surface was centered on Beijing and gradually decreased toward the city periphery. In the area surrounding Beijing, some high-resistance areas were distributed as satellites in the southeast. These were small urban clusters that had a negative impact on the environment. The ecological resistance increased with the distance from the ECR area (Figure 5(c)).

3.3 Identifying the ecological corridors from the Beijing ECR to surrounding areas

The ecological corridors included three categories: the least-cost path corridors, the maximum current density corridors, and the river corridors (Figure 6(a)). Ecological corridors enhance the connectivity between habitat patches and reduce isolation in ECR landscapes (Hüse et al., 2016). A total of 972.46 km of ecological corridors, based on the source of ECR in Beijing, were extracted. Of these, there were 361.11 km of least-cost corridors, which were mainly distributed in the southwest part of Beijing. These corridors represented the optimal path of species movement and had few obstacles. The interactions of the structure and functions between ECR areas were analyzed based on the ecological flow. The least-cost corridors were mainly located in forest land and grassland, which are conducive to species movement. The corridors based on maximum current density were 125.46 km in length and connected the north–south ECR areas in Beijing. These corridors, with frequent gene flow and species movement, were the path choice of most species. The river corridors were obtained based on narrow stretches of river, and the total length was 485.89 km (Table 2). The river corridors supplement the channels connecting ECR areas in the east–west direction.

Figure 6.

Distribution of each part of the ecological security network in Beijing (a) and around Beijing (b).

Table 2.

Length of different ecological corridors.

Types of ecological corridors	Length (km) in Beijing	Length (km) in Beijing surroundings
Ecological corridors with least-cost paths	361.11	713.98
Ecological corridors with maximum current density	125.46	92.05
River corridors	485.89	135.82

Through integrating ECR into ecological network construction, this study developed an ecological network system that prioritized the positive effect factors of ECR areas. Compared with the research reported by Li et al. (2021), the coverage of ecological corridors in the present study was greater, and ecological flows between patches in the southeast corner of Beijing were identified. The ecological flow between the ECR areas in Beijing was greater in the north–south direction than in the east–west direction. The ecological flows had a sparse distribution in the southeast and were mainly in urban areas with high ecological resistance. Fifteen ecological nodes were found to be distributed in the intersection points of ecological corridors and small ECR areas. These nodes played a significant role in controlling the ecological flow. The establishment of protection sites at ecological nodes can reduce the cost of species movement, which is of great significance for biological protection and the formation of sustainable landscapes (Forman and Richard, 1990).

This study analyzed the substance and energy flows in Beijing’s ECR and the surrounding area. Furthermore, the crossover characteristics of ecological effects were explored. The ecological corridors in Beijing’s surrounding areas were short and compact. There were 941.85 km of corridors around Beijing, including least-cost corridors with a total length of 713.98 km. The optimal current density corridors had a total length of 92.05 km, and river corridors had a total length of 135.82 km (Figure 6(b)). Ecological corridors describe the flows of energy and materials among ecological source patches. Ecological corridors with least-cost paths were mainly distributed in the southeast and southwest regions and reduced the costs of species movement. Among the widespread ecological corridors around Beijing, the least-cost corridors were tightly connected with ECR areas. The corridors provided the flow channels needed to transfer ecological services from the ECR supply areas to the service demand areas in the surrounding region. The corridors based on least-cost paths were radially distributed around Beijing, indicating that the overall ecological resistance in this area was low and the ecological fluidity between patches was good. These corridors also affected the cross-boundary flow of ecological services in the ECR area and alleviated some of the ecological problems in Beijing. The maximum current density corridors were located in the west and northeast and reflected the randomness of species movement. Ecological flow between the ECR areas in the northwest part of Beijing and surrounding patches was frequent and located near biodiversity maintenance areas. There were 10 ecological nodes, mainly distributed in the north, that provided resting places for species movement along the ecological corridors.

The ecological security network in Beijing and its surrounding areas constitutes the ecological security network based on the Beijing ECR (Figure 7). Different types of ecological corridors complement each other. Ecological security networks connected the fixed ecological patches and formed a dynamic circulatory system of ecological corridors. This system weakened the interference of administrative boundaries in the continuity of the ecological background.

Figure 7.

Ecological security network based on the Beijing Ecological Conservation Redline (ECR) areas.

3.4 Division of radiation areas of ecological sources based on the ECR

The ECR program focuses on the protection of areas with ecological functions and fragile ecosystem areas, and the ecological effects of ECR areas extend beyond jurisdictional boundaries. In this study, the total area of radiation based on Beijing’s ECR area was 9572.16 km², which was mainly affected by ECR sources from the north and southwest (Figure 8). Compared with other ecological sources, ECR sources in the north and southwest had a higher radiation intensity of ecosystem services. Moreover, the layouts of the radiation areas demonstrated that the mobility of ecosystem services and regional effects of ECR areas in the southwest spread to the interior of Beijing. In addition, the ecological radiation from ECR sources in the north spread more to the surrounding areas of Beijing, extending the impact of ecological services beyond administrative boundaries. Given the dominant ecosystem services of the ERC, the radiation effects of water retention and soil conservation ECR areas were greater.

Figure 8.

Radiation areas based on Ecological Conservation Redline (ECR) sources.

IV Discussion

4.1 Cross-boundary effects of ECR areas based on the ecological security network and the radiation capacity

The objectives of the ECR program are to protect ecologically fragile areas and important eco-function areas and to maintain ecosystem services. The ECR program provides an ecological security bottom line to support socioeconomic development. Exploring the mechanism and interaction of ecosystem services within ECR areas plays a vital role in defining and classifying the ECR area (Yan et al., 2017). However, ecosystem services exhibit regional differences and interdependence, as well as mobility and regional effects that extend beyond administrative divisions (Li et al., 2014; Cullum et al., 2016). In this study, the assessment of cross-boundary effects reduced the limitations of a static ECR area and revealed the extraterritorial effects of ECRs.

This study considered the influence of geographical and ecological factors in surrounding areas on Beijing itself. We identified the ecological flows between ECR areas and surrounding landscape patches in order to clarify the positive ecological effects of the Beijing ECR on the surrounding areas. Additionally, frequent ecological flows were found to be distributed in the north and southeast, which indicated that the cross-boundary effect between ECR areas and patches was intense in these regions. The ecological corridors integrated ECR areas and isolated ecological patches and revealed the ecological feedback mechanism among different areas. The division of ecological radiation based on ECR sources highlighted the spatial distribution differences of ecological radiation effects in different ECR areas. Cross-boundary effects can help solve the problem of the unbalanced distribution of ecological resources between Beijing ECR and surrounding areas and reduce the pollution caused by urban development. The inclusion of the ecological security network into ECR planning formed an ecological loop, transforming the fixed ECR patches into a dynamic circulating system with ecological flows.

4.2 Integrating ECR into the construction of ecological security networks

Ecological security networks play a significant role in maintaining ecological security and controlling urban growth. To address the conflict between urban construction and ecological protection, most analyses of ecological networks have been conducted from the perspective of obstacles to landscape connectivity, such as transportation infrastructure (Karlson and Mörtberg, 2015), impervious surfaces (Cui et al., 2020), and human disturbance, which is calculated based on the surface roads and railway systems of human settlements (Modica et al., 2021). However, the positive impacts of the surrounding environment on the construction of ecological security networks are also of value. Therefore, this study focused on a different perspective in order to explore the benefits of ECR to the ecological security network.

On the basis of the ecosystem service assessment, the ECR program has established priority protected areas in the study region. These areas have high ecological value and play an important role in maintaining ecological security, promoting sustainable development, and reducing environmental degradation (Bai et al., 2018). To highlight the ecological benefits of ECR to the ecological security network, this study took ECR as the basis of ecological sources in Beijing. In order to clarify the ecological coupling relationship between ECR areas and surrounding landscape patches, in the examination of the ecological resistance surface, the expansion probabilities of forest and water areas were used to emphasize the continuity between the ecological background and the interaction mechanism among adjacent grids. The ecological mutual feedback mechanism was considered in order to optimize the differences in ecological resistance between regions. This method reflected the influence of the Beijing ECR area and other high-quality ecological areas on ecological resistance.

4.3 Limitations and prospects

Based on the positive effects of ECR on the surrounding areas, this study identified the ecological flows and emphasized the cross-boundary effect. Through ecological resistance construction, the interactions and dynamic flow spaces between patches, provided by ecological corridors, were confirmed. However, some issues need to be further resolved. Ecological radiation has spatial characteristics, and thus, clarifying the scope and evolution of the ecological radiation of different ecological services in ECR areas will provide a reference for the spatial planning of land use and ecosystem management. China has paid more attention to ecological protection and sustainable development in recent years, and the possible synergistic effect of multiple measures should be explored. For instance, afforestation and reforestation programs in Beijing have effectively promoted the restoration of biodiversity and enhanced ecological value (Yang et al., 2020). How to optimally combine the ECR and afforestation plans to supplement and promote the beneficial effects of ecological security networks will require further study.

V Conclusion

This study integrated the ECR areas and the ecological security pattern to explore the cross-boundary effects of Beijing’s ECR areas. Methodologically, a new index was used for ecological resistance surface correction that considered the characteristics of ecosystem services in the ECR area, socioeconomic factors, and the continuity between ecological backgrounds. Through ecological resistance construction, the interactions and dynamic flows among patches, which reflected cross-boundary effects, were confirmed. In addition, the radiation effect areas of the ECR sources were identified. These findings could provide support for ecological restoration decisions and the refined management of ecosystems in other metropolitan areas.

The ecological security network system based on Beijing’s ECR area was analyzed using ecological sources, corridors, and nodes. The total ecological source area was 17,349.74 km², of which 640.46 km² was source area based on ecological restoration. The distribution of ecological source areas showed that the environmental quality in the north was superior to that in the south. The ecological corridors were composed of three categories, including 1075.09 km of least-cost corridors, 217.51 km of maximum current density corridors, and 621.71 km of river corridors. It was concluded that the ecological flows in the south–north direction were more abundant than flows in the east–west direction, and the ecological flows were mainly located in the north and southwest of Beijing. In the surrounding areas of Beijing, the ecological flows between the ECR areas and other ecological patches were distributed radially. These corridors strengthened the mobility and regional effects of ECR areas. A total of 25 ecological nodes were identified, of which 15 were located in Beijing, while 10 were located in the surrounding areas. In future construction, the preservation of green space can be emphasized at these ecological nodes to enhance the ecological security network connectivity. The total area of radiation based on ECR sources was 9572.16 km², which was mainly distributed in the north and southwest. The ECR sources in the north and southwest had a higher radiation intensity of ecosystem services.

Taking ECR into account in network construction, a more uniform and comprehensive ecological security network in Beijing was developed. This network effectively promoted the flow of substances and energy between ECR patches and enhanced the ability of the ecological security network to resist urban interference. Through the distribution of ecological corridors, it was found that the cross-boundary effects of ECR areas in the north and southeast were the strongest. The ecological radiation effects of ECR areas in the southwest spread to the interior of Beijing, and the ECR sources in the north spread to the surrounding areas of Beijing. The cross-boundary effect of ECR reduced the limitation of administrative boundaries on the continuity of the ecological background and improved the environment of Beijing and its surroundings. Therefore, the findings of this study support the utility of coordinating territorial spatial planning among different regions.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China (42071288 and 41671098), the Programme of Keizhen-Bingwei Excellent Young Scientists of the IGSNRR, CAS (2020RC002), the National Key Research and Development Program of China (2018YFC1508900 and 2018YFC1508801), and the Beijing Environmental Quality Monitoring Project(2018)-Ecological Assessment and Ecological Red Line Protection Remote Sensing Monitoring (Y88M1800AL).

ORCID iD

Jiangbo Gao

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