Thresholds for Rural Public and Ecosystem Services: Integration into Rural Green Space Spatial Planning for Sustainable Development

Abstract

Rural landscapes are experiencing ecosystem degradation due to urbanization and rapid suburban expansion. Ecosystem services derived from natural resources and essential public services facilitated by social capital collectively address the growingly diverse social and ecological requirements of rural residents. Even so, ecosystem services and public services are often trade-offs, highlighting the necessity to enhance their coordinated development. However, it remains unclear how to use the identified thresholds to delineate functional zones. This will scientifically guide sound and efficient spatial planning and ecological management. This study takes the suburban countryside of Jiangning in Nanjing as the study area. It explores the inclusion of the threshold value of rural public services and ecosystem services in the strategic design of sustainable suburban development in China. First, we quantify and map six types of ecosystem services (ESs) and 13 types of rural public services (RPSs). Secondly, we use the piecewise linear regression method to identify the response and threshold of 13 types of RPSs to six kinds of ESs. Finally, the combination and classification of threshold values are used to divide functional areas, and space-specific management and planning suggestions are put forward. The results are as follows (1) With the increase in RPSs, all ESs respond with a downward trend. (2) In addition to the negative linear relationship between education and social welfare services and ESs, the response thresholds of other RPSs and ESs were identified. (3) According to multiple density threshold analysis of each RPS’s response to ESs, four functional areas were obtained. We emphasize the priority of spatial planning and management, that is, the priority management of “ESs enhancement area and RPSs optimization area”. (4) The threshold values of ESs and RPSs can be used as tools to delineate functional zones and guide the spatial planning and management of rural functional areas. In general, our research helps ensure the maximization of rural ecological benefits while also meeting the growing diversity of needs of rural residents and enabling efficient, phased, gradient, and precise spatial management of suburban rural ecosystems and public services to promote the sustainable development of suburban rural areas and realize rural revitalization.

1. Introduction

The United Nations (UN) has designated the decade from 2021 to 2030 as the United Nations Decade for Ecosystem Restoration. This initiative aims to accelerate global efforts in ecological restoration to ensure the timely achievement of the SDGs (Sustainable Development Goals) [1,2]. Especially in the suburban countryside, which is no longer “rural” in the traditional sense and where the conflict between environmental protection and development is intense [3,4]. At the same time, Liu and Li (2017) pointed out in Nature that one of the four major priorities for rural revitalization is that “the government needs to promote rural urbanization while supporting urbanization [5], so that rural residents and urban residents can enjoy the same resources, public services, and social welfare”. Ecosystem services (ESs) and rural public services (RPSs) are two indispensable aspects to simultaneously meet different human needs and promote sustainable development [6,7].

On the one hand, these problems of rural ecological degradation and environmental pollution have made rural ecosystems increasingly important to decision-makers such as academics, government departments, and landscape practitioners [4,8,9]. Rural ecosystems deliver essential ecosystem services that are crucial for the survival of both urban and rural areas, including not only substances and products but also environmental protection to protect human beings from environmental disasters and pollution [4,7,10,11]. More importantly, the Intergovernmental Science-Policy Platform on Ecosystem Services (IPBES) and the International Council for Science (ICSU) have recognized that all Sustainable Development Goals will benefit from ecosystem services [12,13]. On the other hand, adequate provision of essential public services, including education and healthcare, is considered sufficient to support sustainable development. These services are important to enhance the quality of human life and promote long-term societal well-being. It has become an essential standard for sustainable development [7]. However, conflicts between public services and ecosystem services exist in many areas [14]. More and more researchers have proposed that we should not only pay attention to the provision of ESs and RPSs but also consider strategies to optimize the interrelationships between ESs and RPSs to enhance their overall benefits and sustainability [7,15,16,17,18], but also consider optimizing the relationship between them. There is, therefore, an urgent need to clearly understand and optimize the relationship between ecosystem services and public services in peri-urban villages to support rural revitalization and the achievement of the Sustainable Development SDGS, especially with SDG11 (Sustainable Cities and Communities) [19].

For a long time, the Chinese government has placed a high priority on enhancing rural public services development while also emphasizing rural ecosystem services. This is with a view to improving human well-being and realizing sustainable development in rural areas. On the one hand, the Chinese government has been committed to supporting rural public services such as water conservation, farmland infrastructure services, and traffic services since the 20th century [20]. Since the early 2000s, the Chinese government has introduced policies such as the New Socialist Rural Strategy, the Beautiful Rural China Plan, rural land consolidation, and agricultural supply-side reform, and put forward a national strategy for rural revitalization. Through these efforts, China has made significant strides in economic aspects, the optimization of infrastructure, and the promotion of harmonious urban–rural integration [3].

On the other hand, the rural revitalization strategy emphasizes that the countryside is the central area of ecological conservation, and ecology is the most significant development advantage of the countryside. Therefore, more attention should be paid to rural ecosystem services. China has introduced several policies to protect its ecological environment, including the establishment of the ecological protection red line system, the implementation of large-scale afforestation, the return of farmland to forest, the closure of mountains, and the ban on grazing. These measures are aimed at restoring and improving damaged ecosystems. However, most of these policies focus primarily on improving ecosystem services while ignoring both the quality of resource provisioning services (RPSs) and the need for coordinated development between ecosystem services (ESs) and RPSs. This oversight complicates the achievement of the Sustainable Development Goals.

Additionally, activities aimed at building basic public services often shift land use from forest, grassland, or farmland types to artificial landscapes or construction land. Such changes may irreversibly alter the natural environment, resulting in soil degradation, biodiversity loss, and a decline in ecological services [3,21,22]. How to properly balance rural public services construction and ecosystem protection is a crucial practical problem.

The importance of ecosystem services and public service levels for sustainable development is becoming increasingly prominent [7,23], and ESs and RPSs have been proven to have trade-offs by many scholars [6,7], especially in rural areas on the outskirts of Chinese cities. On the one hand, ecosystem services refer to the environmental conditions and benefits generated and maintained by ecosystems through ecological processes [24], including the benefits directly or indirectly obtained by human beings from ecosystems [17,25,26,27]. Rural ecosystems are complex networks of natural, economic, and social ecology composed of human beings, resources, and various environmental factors in rural areas. More importantly, rural areas provide both urban and rural areas with ecosystem services, which are healthier, greener, and more ecological than urban areas [28], and have important ecosystem service functions such as air purification, climate regulation, and water conservation [29]. They also play an important role in the livelihoods of urban and rural residents [11]; therefore, rural ecosystems are an integral part of ensuring high-quality, sustainable development in the region [29,30,31].

On the other hand, public services are used to meet human needs [32] and provide public services and infrastructure [23,33]. Rural residents also need essential services such as education, health care, and transportation [6]. Infrastructure services influence more than 70% of SDGs [34]. These services play a crucial role in fostering economic prosperity and enhancing human well-being, encompassing areas such as education and health [35]. Thus, the unbridled pursuit of public services can harm the provision of ESs in the long run [7,36], while excessive ESs protection will restrict economic growth and impede the provision and enhancement of RPSs [7,37]. Therefore, it is necessary to explore further the relationship between ecosystem services and rural public services to manage ESs and RPSs sustainably and reduce the adverse effects of the trade-off between the two.

At present, existing research has shown that there is a nonlinear relationship between public services and ecosystem services in the same region. Researchers have determined the threshold of public services and ecosystem services [6]. Generally speaking, ecosystems have critical points. Minor variations in influencing factors can result in the state of ecosystems [38,39,40], and their function and level to provide ecosystem services [41] have undergone disproportionately large shifts [42]. The threshold is defined as the critical turning point at which the relationship between the ecosystem state and its drivers changes from one model to another [27], and thus becomes the threshold that controls the development of public services based on the process of maximizing ecological efficiency [6,27]. Currently, scientific methods such as system dynamics models, meta-analysis, and piecewise linear regression have been proven and applied to threshold recognition [27]. Meta-analysis involves the statistical integration of results from multiple studies on the same topic. This method has a wide range of applications; however, it requires a series of highly consistent data [43]. System dynamics models require enormous amounts of information to accurately describe the impacts and responses of various components [44]. Consequently, it is seldom used to quantify the ecological effects of urbanization. Compared to previously mentioned methods, piecewise linear regression, functioning as a segmented model with modest data requirements, proficiently identifies the threshold point where two trends intersect [45]. It has found extensive application in researching ecosystem dynamics [27]. For example, Magney et al. (2016) used the method to determine the turning point of seasonal changes in NDVI [46]. Peng et al. (2017) analyzed ecosystem services’ response thresholds to urbanization in suburban areas, identifying thresholds related to population and economic urbanization factors [27]. Hou et al. (2021) employed the method to determine the threshold of public service density to prevent ecosystem services decline [6].

Consequently, piecewise linear regression can be employed to determine the thresholds at which ecosystem services respond to public services expansion. The establishment of clear and defined thresholds guides the development of effective adaptation measures [47]. The identification of threshold values can indicate the potential severity of consequences resulting from changes in public services [6]. Furthermore, it can elucidate the phased characteristics of ecological impacts under rural development [27], a crucial aspect of ecological management and environmental protection.

Threshold-based recognition is critical for further application in ecological management, and meeting decision-making needs [42]. At present, the “when and where” of human intervention to restore ecosystems remains a challenge in ecological restoration [48]. For threshold studies, this emphasizes not only the accuracy of ecological management at different stages, but also the importance of precisely controlling the scope of management at the spatial level. Currently, few studies fully meet this requirement. Hong et al. (2024) constructed a framework for zoning by applying the identified threshold value to prioritize the management of different regional spatial regions and put forward targeted ecological management suggestions for each spatial region [2]. However, most of the current studies on the impact of various driving factors on the threshold of ecosystem services still focus on threshold recognition, and few studies apply the identified threshold specifically to ecosystem service management, making it challenging to meet decision-making needs [42]. Therefore, there are high requirements for future research on the application of thresholds based on RPSs and ESs: it is not only necessary to carry out phased ecological management of thresholds to meet the phased demand for maximizing ecological efficiency under the development of rural public services; it is also essential to clarify their zoning scope at the spatial level to provide targeted and accurate zoning ecological management, zoning planning, and sustainable management strategies and recommendations.

In the complex rural landscape of Jiangning village in Nanjing, which is affected by urbanization and rural development, the tension between environmental protection and development is the most prominent [4]. How to balance the relationship between the two is the core issue to be solved urgently. Jiangning countryside is rich in natural resources, which promotes agricultural production and rural tourism. In addition, due to the guidance of policies, the establishment of industrial parks and university towns has promoted the economic prosperity of Jiangning, and Jiangning village has been rated as a typical village in the national rural revitalization case of urban–rural integration development. However, driven by urbanization and the development of villages themselves, the status quo of their ecosystem services is also faced with pollution problems such as water quality and soil pollution [4]. At the same time, the increasing pursuit of industrial diversification and the quality and equalization of public services in rural areas inevitably leads to competition for land and ecological resources, which continue to intensify the trade-off relationship between ESs and RPSs [4,7]. Under the call of rural revitalization strategy, by studying the relationship between ESs and RPS, ecological managers and planning practitioners can accurately, efficiently, and clearly understand and monitor the extent of RPSs affecting ESs’ capacity “where” and “when”. On the premise of ensuring the maximization of regional ecological benefits, it not only helps solve the problem of optimizing the allocation and management of public service resources in space but also clarifies the management degree of each stage, thus promoting the coordinated development of rural ESs and RPSs. Taking into account the above research gaps and practical problems, a key challenge is how to control the development of rural public services in stages accurately and comprehensively to maximize ecological efficiency. This issue must be addressed and can be directly applied to ecological management and spatial planning. To achieve this, we need to classify the threshold effects of RPSs and ESs and understand their ecological significance. This will enable us to develop targeted and phased ecological management and planning strategies for different regions. The suburban countryside of Jiangning in Nanjing presents a typical case of rural revitalization in China, influenced by both urbanization and rural development. We have chosen this area as our research focus, and the main research questions are as follows: (1) What are the spatial distribution patterns of public services and ecosystem services in each village of Jiangning countryside? (2) How can we identify the threshold at which different rural public services impact ecosystem services in Jiangning villages? (3) How can we apply the identified thresholds to delineate functional zones and propose space-specific planning recommendations? To address these questions, we have established a spatial planning and management framework based on RPSs–ESs. This framework integrates the spatial distribution of ESs and RPSs and analyses the nonlinear trade-off between them to inform zoning management strategies tailored to local conditions. By considering both RPSs and ESs, our research aims to accurately control the development stage of RPSs while avoiding blind expansion, implement effective spatial planning and management of RPSs and ESs, propose priority management to optimize the relationship between RPSs and ESs, and ensure the protection and enhancement of ESs. This study will support the development of ecological management strategies, precise spatial planning recommendations, and sustainable environmental management policies at the village level. These findings are crucial for balancing socioeconomic development and sustainable ecological management in the region.

2. Materials and Methods

2.1. Study Area

“Nanjing is the first city in China to implement comprehensive zoning planning according to international standards” [49].

The Jiangning (JN) District of Nanjing is located southeast of Nanjing, about 15 km from the landmark Xinjiekou in the city center (Figure 1). Jiangning District’s economic development level ranks among the top of all counties in the Yangtze River Delta. It is one of the regions with the fastest urbanization speed in China [4,50].

Jiangning District is also the only typical case of a rural revitalization strategy in Jiangsu Province, with rural development at the forefront of the country. The district has rich and diverse ecological functions, as well as rural landscape resources and cultural resources.

There are 73 cultural heritage reserves at or above the municipal level in China in the district [51]. In 2022, it received 34.3720 million tourists and achieved a comprehensive tourism income of about 28.61 billion yuan (Statistical Bulletin of National Economic and Social Development, 2022). The favorable terrain conditions and rich cultural heritage promote tourism development in the region. It also provides a range of important ecosystem services to the region, such as water conservation, purification, and carbon regulation.

Due to the continuous advancement of urbanization and rural development, the degree and scale of human intervention in rural natural ecosystems are gradually increasing. This brings about more prominent economic, social, and ecological contradictions [52]. This process also makes Jiangning countryside’s land use and landscape pattern more complex [51]. Therefore, the countryside in the Jiangning District of Nanjing is a typical example that balances rural ecological protection, economic sustainable development, and human welfare. The research results can ensure the sustainable development of the Jiangning countryside, prevent economic benefits from coming at the cost of ecological and environmental degradation, and take into account the multi-objective principle of promoting rural revitalization.

2.2. Sustainable Spatial Planning and Management Framework Incorporating ES and RPS Thresholds

This study constructs a spatial planning management framework integrating ES and RPS thresholds into sustainable suburban development in China (Figure 2) to coordinate ecological protection and economic development. The framework consists of three main phases:

2.3. Selection and Valuation of Ecosystem Services (ESs)

Selecting appropriate ESs indices is a key step in assessing ESs [53,54]. We adopt stakeholder analysis to determine relevant ESs, considering ESs consumption, policy relevance, and data availability [55]. Based on the local industrial structure, three stakeholders are considered: enterprises related to the agricultural production industry, residents, and local governments. Different stakeholders determine the difference in attention to ESs (see

Table 1. Indicators and interpretation of ecosystem services (ESs) of concern to relevant stakeholders in Jiangning.

Stakeholder	Target	ESs Concerned	Definition	Abbreviation	Category
Businesses and part of the working population	Rural industries are thriving, and the revitalization of the rural industrial economy is being achieved.	Soil retention: soil erosion accelerates significant nutrient loss.	Avoided overland sediment generation and delivery to streams [55]	SR	Regulated services
Residents	Access to sufficient clean water to ensure a good quality of life for residents.	Water yield: closely related to surface water available to the population of the region.	The amount of water running on each pixel in a landscape [55]	WY	Supply services
		Nitrogen output: reflects the ability of water to be purified, with some of the nutrient pollutants being removed as the water passes through the river.	Transportation of nutrient mass through a landscape	N-output	Regulating services
Governments	Government objectives: to ensure ecological health and coordinated regional development [56].	Carbon storage is an important indicator of governmental results and regional ecological importance, and there is a strong relationship between it and human beings, especially in combating climate change.	Total amount of carbon stored in a landscape [55]	CS	Regulating services
		Habitat quality: directly related to habitat security for many endangered wildlife species.	Ecosystems’ capacity to sustain the persistence of individuals and populations [57,58]	HQ	Support services
		Water conservation: the Qinhuai River is the mother river of the Jiangning region and a key ecological function area.	Water retention capacity of ecosystems [59]	WC	Regulating services

). Finally, six ESs indexes were selected: supply service (Water Yield–WY), Support services (Habitat Quality–HQ), and regulatory services (Carbon Storage–CS, Water Conservation–WC, Soil Retention–SR, and nitrogen export–N-output).

This study quantifies the six ESs above using InVEST3.11.0, utilizing several of InVEST’s modules: Carbon Storage and Sequestration (carbon storage), water yield (water yield, water conservation), Sediment Delivery Ratio (soil retention capacity), Habitat Quality, Nutrient Delivery Ratio (nitrogen export capacity), and Habitat Quality modules to assess the corresponding ESs in JN [54,60,61,62,63,64]. Details of all modules and the calculation process for each ES can be found in the Supplementary Material (Part II). Table S1 in the Supplemental Material (SI) lists the key parameters and biophysical tables required for the InVEST model [65,66,67,68]. For more information on the InVEST model reliability verification, see Supplemental Information.

Among these, WY and N-output are negatively correlated variables; the greater the value, the worse the ecosystem service capability. To directly describe the distribution relationship with public service facilities, a reciprocal operation is carried out for both of them. The value is minimized to the range of 0–1.

2.4. Selection and Quantitative Evaluation of Rural Public Services (RPSs)

With the advent of big data, a large amount of POI (Point of interest) reflecting urban infrastructure distribution can be obtained through the Internet [69,70]. POI data contain rich information such as precise location (address, latitude, and longitude), name, type, etc. [71]. POI data sets can provide helpful socioeconomic information for strategic locations and reflect the intensity of human activities and socioeconomic development [71,72]. Especially for shopping malls, public facilities, industrial sites, schools, and other facilities closely related to people’s lives, the distribution of public facility services can be well analyzed [3,70,73].

First, this paper uses the Python programming language to capture POI data in 2020 from the Baidu Map Open Platform (http://lbsyun.baidu.com/, accessed on 3 March 2020), the largest desktop and mobile map service provider in China [74]. In addition, corrections were made using human survey methods, and all original data were cleaned (removing duplicates, null values, and other missing information) and backed up with coordinate transformations.

Secondly, based on The Classification of National Economic Industries in China [75], combined with existing studies [6,70,76], we selected 13 types of POI that best reflect the level of rural development (

Table 2. Comprehensive table of rural public service classification and industry classification.

Rural Public Services (RPSs)	Classification
Administrative services	State departments, government agencies, public institutions, public security inspection, traffic law enforcement departments, grassroots autonomous organizations
	Environmental management, public facilities management,
Social services	Social welfare institutions, Red Cross Society, disabled persons’ Association, Youth Volunteer Association, and other social welfare organizations
Healthcare services	Plastic surgery clinic, community hospital, pharmacy, pet hospital, various specialized hospitals, general hospitals, China’s top three hospitals
Culture and art services	Journalism, radio, television, film and auditions, cultural and art venues, museums, libraries, media organizations, exhibition halls, cultural palaces
Entertainment and recreation services	Indoor entertainment activities (KTV, Internet cafe, chess and card room, game hall), amusement park, ecological industrial park, farm music
Education and scientific services	Scientific research institutions, training institutions, adult education, vocational and technical schools, preschool education, primary education, secondary education, higher education
Accommodation services	Hotels, guest houses, chain hotels
Sports services	Outdoor fitness, various courses, swimming pool, fitness center, racecourse
Catering services	Big hotels, chain restaurants, specialty snack bar
Market services	Leasing industry, retail trade, wholesale industry, living services, shopping services
Finance services	Bank, securities, insurance
Businesses services	Telecommunications business, computer, professional and technical services, software services, real estate services, corporate enterprises
Traffic services	Bus station, subway station, port terminal, bus station, airport, railway, parking lot, transportation service

), namely: administrative services, social services, healthcare services, culture and art services, entertainment and recreation services, education and scientific services, accommodation services, sports services, catering services, market services, finance services, business services, and traffic services.

Finally, the kernel density value of each POI type was used to measure its service level. The kernel density processing method in ArcGIS 10.8 software generated 13 categories of public service density layers. The reasons for this choice are as follows: There are generally two kinds of point pattern analysis methods for POI spatial research. Since Ripley’s K function is a distance-based method with dispersion as the baseline, it is difficult to express the distribution characteristics of many POIs. In contrast, the density-based method has a better visualization effect and a more precise expression [76].

At the same time, the method fits a kernel function into each observed geographical point. It forms a grid surface representing the density by assuming that each observation point is continuously distributed in its unit. This method has been widely used to determine urban functional facilities’ service capability [77,78,79]. The kernel value density in the study was calculated using the kernel density tool in ArcGIS 10.8, and the weight of each type of service was set to be equal. In addition, to intuitively find out the relationship between public service and ecosystem service, a log transformation is carried out on each type of rural public service data [6,27]. After the conversion of Formula (1), the values are uniformly maximized and minimized to the same interval (the interval chosen in this paper is 0~30).

$$X_i={\log }_{10}{x}_i$$

(1)

Among them, $X_i$ represents the level of the i-th category of public services, and $x_i$ is the kernel density value of the i-th category of public service facilities.

2.5. X Identifying the Potential Thresholds Utilizing a Piecewise Linear Model

Piecewise linear regression is an effective technique for identifying turning points in long-time series data. The principle behind this method involves linear fitting before and after each turning point. The optimal solution for piecewise fitting is achieved when the sum of squares of residuals is minimized. Compared to simple linear regression, piecewise linear regression provides a more accurate representation of the actual trend in the relationship between variables [6,27,80]. A piecewise linear model was used to fit the relationships of each ES variable’s response to UPS variables and calculate their turning points [27]. The process of a piecewise linear model can be summarized as follows [45]:

$$y=\left\{\begin{array}{c}{\beta }_0+{\beta }_{1}x+\epsilon , x\le a\\ {\beta }_0+{\beta }_1\left(x-a\right)+\epsilon , x>a\end{array}\right.$$

where $y$ is the ES variable; $x$ is the UPS variable; $a$ is the UPS variable at the turning point; ${\beta }_0$ and ${\beta }_1$ are coefficients, and $\epsilon$ is the error term. We performed least square linear regression before and after the turning point; the coefficients of the models were calculated using least squares estimation. Statistical significance was set at p ≤ 0.05. The piecewise linear model analyses and trend visualization were performed using the SiZer package [81] and the ggplot2 package in R software [82] in R software (Version 4.3.0).

2.6. Application of Spatial Planning and Management of Functional Zones Based on RPS Thresholds

It is often difficult to achieve positive synergy between public services and ecosystem services, and there is often a trade-off relationship between them [6,7]. To reduce the impact of RPSs on ESs in multiple dimensions and all aspects and to ensure the maximization of ecosystem service efficiency, it is necessary to consider various thresholds corresponding to the same RPSs, especially when determining ecological function areas [42]. The study conducted functional zoning based on multiple RPS thresholds for spatial planning and ecological management based on multiple RPS thresholds. The specific steps were as follows: Firstly, the results of threshold recognition of rural public services and various ecosystem services were collected. Secondly, the minimum value, average value, and maximum value of the threshold were used as threshold indicators to divide the limit RPSs and the management ESs. This was calculated to delineate areas to manage public services and maintain ecosystem services sustainability. Finally, from the perspective of spatial distribution and spatial scope, this paper proposes scientific, efficient, and accurate spatial ecological management and public service density thresholds. It also proposes spatial planning suggestions and ecological management strategies based on maximizing ES protection and improvement.

Regional zoning governance was conducted according to regional interchanges identified by multiple threshold conditions [42]. Based on three threshold points as the classification criteria for each region, the specific logic and process of functional zoning were shown in Figure 3: Multiple RPS–ES thresholds corresponding to a single RPS provide standards for ecological protection and restoration schemes, including the minimum value X1, average value M, and maximum value X6 of each type of RPS (Figure 3a).

In this study, the minimum value X1 represents the initial threshold for ecosystem response RPSs increase. In contrast, the average value M serves as the critical threshold for the rise of RPSs. The maximum X6 is the upper threshold for ecosystem services in response to increasing RPSs; exceeding this maximum value may lead to ecosystem collapse. These multiple thresholds can be applied to zoning, positioning, and post-monitoring for ecosystem conservation and restoration [2].

Based on the above three main thresholds of each type of public service as classification criteria, we divided Jiangning into four types of functional zones (Figure 3b) and proposed the management objectives of ecosystem services and public services with spatial specificity as follows: (1) ESs restoration zone (X ≤ X1): Areas below the first threshold (the minimum threshold, also referred to as the initial value) require ecological optimization and restoration. Simultaneously, attention should be paid to improving the type of ESs corresponding to the threshold value (see Figure 3b: ES1) to more efficiently enhance the ecosystem’s resilience to the growth of rural public services. (2) ESs restoration and RPSs control zone (X1 < X < M): this area meets the first threshold value (the minimum threshold value, also referred to as the initial value). Still, it does not meet the second threshold value (the average threshold value, also called the control value). It requires the restoration of ecosystem services, with a focus on improving the type of ecosystem services corresponding to the threshold value (see Figure 3b: ES2 and ES3). At the same time, it controls the development of public services and prevents the blind expansion of public services from reducing the ecosystem service capacity. (3) ESs enhancement and RPSs control zone (M ≤ X < X6): This zone exceeds the second threshold (the average value of the threshold, also referred to as the control value) but does not meet the third threshold (the maximum value of the threshold, also referred to as the early warning value). Such areas urgently need to enhance ecological reconstruction, improve ecological capacity, and control the expansion of public services while focusing on enhancing ES4 and ES5 (Figure 3b). (4) ESs enhancement and RPSs optimization zone (X ≥ X6): Regions exceeding the third threshold (the maximum threshold value, also referred to as the early warning value) need to strengthen the capacity of all types of ecosystem services while focusing on improving ES6 (Figure 3b). These regions should optimize public services by strengthening the market access mechanism, conducting thorough market research, strictly implementing the exit mechanism for public services, and fully realizing the principle of survival of the fittest.

3. Results

3.1. Spatial Distribution Pattern of Rural Public Services and Ecosystem Services in Jiangning

As shown in Figure 4, the distribution of public service kernel density in Jiangning village shows apparent similarities but also some differences. In central Jiangning, 13 types of rural public services have reached a considerable aggregation level (forming many “hot spot” areas). With the increase in radiation distance, the aggregation degree drops from 5 around the center to 2, and the distribution range is wider.

In contrast, in areas outside the central district of Jiangning, the high-value areas of traffic, business, social, culture and art, administration, sports, and entertainment services are more widely distributed, with larger areas relatively clustered into a “flake” distribution. The high-value areas of accommodation, catering, education, finance, market, and medical services in the region are relatively dispersed, showing a “point-like” distribution. To sum up, public services in Jiangning are generally concentrated in the central area, the earliest developed part of Jiangning, and closest to the main urban area of Nanjing, forming a flat cluster. This is the pattern of Jiangning’s 30-year development history.

As shown in Figure 5, various ecosystem services in Jiangning District showed obvious heterogeneity, with this study conducted at a grid scale of 30 m × 30 m (900m²). The spatial distribution of CS and SR showed similar patterns, first increasing, then decreasing, and finally improving from southwest to northeast.

WC and HQ followed a trend of first decreasing, then increasing, and then decreasing again; WY and N-output continuously increased and then decreased from southwest to northeast. More specifically, CS ranged from 10.71 t/900 m² to 32.409 t/900 m², with the highest concentrations mainly in the woodland areas in the southern and northern parts of Jiangning, as well as the scenic regions of Fangshan and Niushoushan. The lowest concentrations were observed in the Yangtze River basin, Lukou Airport, and the relatively developed areas in central Jiangning, followed by some cultivated land and grassland areas. SR ranges from 0 to 3923.84 t/900 m², while low in the Yangtze River basin. HQ ranges from 0 to 0.999747, while WC ranges from 0 mm to 1095.29 mm. The Yangtze River basin and the southern and northern forest margins showed the highest values for both HQ and WC. Conversely, low HQ and WC were distributed between Jiangning Regional Center and Lukou Airport. HQ and WC, with values increasing outward from these areas linearly. WY varied from 212.6 mm to 1216.18 mm, with higher values mainly around Jiangning, Lukou Airport, and the south of the Yangtze River. These areas are characterized by more construction land with opaque water surface. The N-output ranges from 0 t/900 m² to 0.734525 t/900 m², encompassing both construction areas and farmland. This spatial analysis highlights the complex distribution of ecosystem services across Jiangning District, reflecting the interplay between natural landscapes and urban development.

It can be seen from the results that the most beneficial ecosystem service areas in Jiangning are forest margin areas in the south and north, Fangshan Mountain and Niushoushan Scenic area, followed by the Yangtze River basin area. However, the ecosystem service level of construction land in central Jiangning, Lukou Airport, and the south bank of the Yangtze River is low, and the ecosystem service function of these areas is significantly decreased due to rapid urbanization.

3.2. The Thresholds of Rural Public Service and Ecosystem Service in Jiangning

Previous studies have shown that there is a trade-off effect between public service and ecosystem service [7], that is, the increase in public service will lead to the decline of ecosystem service supply capacity [6].

After threshold recognition and piecewise linear regression analysis, the ESs–RPSs scatter plot is shown in (Figure 6). The vertical line indicates the threshold, the green dots are located before the threshold, and the purple dots are located after the threshold, respectively. Our results showed that forest ecosystem services showed a downward trend with the growth of rural public services. Based on the details of the trend characteristics, we categorized the corresponding pattern of rural public services to ecosystem services into three types:

The first model: there is a significant negative linear relationship between ecosystem services (ESs) and rural public services (RPSs), and there is no threshold effect. That is, with the continuous increase in rural public services core density, ecosystem services will linearly decline. There are 29 pairs of ES–RPS relationships of this type. Among them, it is worth noting that the RPSs of education, scientific, and social all show a significant negative relationship with ESs, and there is no threshold. It may be because these types of public services easily attract human traffic and reduce natural resources. Moreover, the distribution of RPSs of these two types is relatively uniform and not concentrated. The combination of these factors leads to a linear and steady decline in ecosystem services.

The second model shows an obvious threshold effect between ecosystem services (ESs) and rural public services (RPSs). Initially, as rural public services decline, ecosystem services decline linearly. However, this decline becomes more gradual after reaching a threshold. There are seven pairs of ES–RPS relationships of this type: Administrative and WC, Traffic and WY, Market and WY, Finance and SR, Business and SR, Market and SR, and Traffic and N-output. This indicates that ecosystem services are highly sensitive to external interference as public services increase. At the same time, when the threshold is exceeded, it reflects the ecosystem’s ability to inhibit further decline. The threshold may trigger the ecosystem’s internal adjustment mechanism, resulting in slower ecological service decline rates.

In the third model, ecosystem services and rural public services also exhibit an obvious threshold effect. This model shows that ESs decrease rapidly after exceeding the threshold value. There are 42 ES–RPS relationships in this model. It reflects the ecosystem’s nonlinear response and indicates that the aggregation and expansion of public services will exceed the range the ecosystem can carry, resulting in a strong response.

Notably, we find that not all public services and ecosystem services have thresholds (Figure 6 and Figure 7). Specifically, no thresholds exist for class 2 public services in education and scientific, social services, and for all ecosystem services.

At the same time, there are individual public services, and most ecosystem services do not have thresholds. Only two types of ecosystem services have thresholds: businesses and healthcare services.

3.3. Function Zoning Based on the RPS–ES Thresholds

With the aim of maximizing ecological conservation efficiency, this study uses the minimum, average, and maximum values of the thresholds as indicators for dividing functional zones. These values are based on the threshold recognition results presented in Section 3.2. The intersections identified by pair-to-pair threshold conditions of the three thresholds result in our ES–RPS zones (Figure 8).

We can find that the spatial distribution of different types of ES–-RPS relationships presents heterogeneity, but the spatial pattern is relatively stable. Among them, the ESs enhancement and RPSs optimization area is the most concentrated and larger than other areas. This forms a “sheet” distribution feature concentrated in Jiangning’s central area. This area is mostly construction land and adjacent to Nanjing’s main urban area. There was also a focus on ESs restoration areas, which showed a “line-like” distribution characteristic connected by points. These areas are mostly farmland areas outside the central area, a small number of areas along the northern and southern forest margins, and along the Yangtze River. ESs repair and RPSs control areas, as well as ESs enhancement and RPSs control areas, are relatively small, scattered on the periphery of the central area. These areas largely consist of farmland areas. It should be noted that since the above studies (Figure 6) show a negative linear correlation between education and social services and ESs, with no threshold point, these two types of services will not be discussed in this section.

For these four types of rural functional areas, we determined the accurate function and location information of each rural environmental space to prioritize ecological and public service management and support differentiated spatial management. Our management recommendations for each functional zone are as follows:

• ESs restoration zone: Achieve sustainable growth of rural public services by improving ecosystem services resilience. For ecological compensation and restoration, such as vegetation restoration, water resources protection, and biodiversity conservation, to make up for ecological losses caused by the development of public services. Regular scientific monitoring and assessment of ESs is required.
• ESs restoration and RPSs control zone: Achieve coordinated and sustainable development of ecology and public services by simultaneously controlling rural public services expansion and improving ecosystem service restoration capability. In addition to the ESs restoration zone strategy, the zone should conduct market demand and trend analysis of RPSs, regularly evaluate the implementation effect and social and ecological impact of public service projects, and adjust project strategies in a timely manner according to evaluation results to prevent uncontrolled project expansion.
• ESs enhancement and RPSs control zone: Under the premise of simultaneously controlling the expansion of rural public services and enhancing the ecosystem service capability to ensure the maximization of ecosystem service efficiency. Strengthen the application of ecological engineering technologies, such as biodiversity conservation, wetland restoration, natural regeneration, etc., and implement the physical and biological reinforcement of ecosystems. Analyze the market demand and trend of RPSs, adjust the project strategy in a timely manner according to the evaluation results, and control the unplanned expansion of the project.
• ESs enhancement and RPSs optimization zone: On the premise of enhancing ecosystem service capabilities, optimize existing rural public services to ensure maximum ecosystem service efficiency. As with ESs enhancement and RPSs control zones, it is necessary to strengthen ecological engineering technology applications. To select and entrust competitive and qualified service providers, public bidding and bid evaluation mechanisms are also implemented. This can promote competition among service providers in terms of service quality, cost efficiency, and innovation ability to enhance public services. The existing public service quality assessment carries out the survival of the fittest.

4. Discussion

4.1. Relationship Between RPSs and ESs in Suburban Rural Areas

Our results are consistent with previous conclusions that it is difficult to achieve positive synergy between public services and ecosystem services; with the increase in RPSs, all ESs respond with a downward trend, and there is a trade-off relationship between them [6,7,19], which directly indicates that enhanced RPSs reduce ESs supply. Therefore, recognizing RPS threshold effects will draw policymakers’ attention to ecosystem restoration and enhancement. This study integrates the threshold effects of ESs and RPSs into spatial planning and management of sustainable suburban development in China. This may have important implications for implementing ecological management and making specific interventions to prevent ecosystem collapse.

In this study, we found that RPSs and ESs in education and social welfare are linearly negatively correlated without threshold values. In contrast, other RPSs and ESs all have critical threshold values, likely due to the distribution of RPSs in these two categories leading to a significant decline in ecosystem services. This finding contrasts with previous studies indicating a negative linear relationship between ESs and medical services in Hangzhou, which may result from medical resources being predominantly concentrated in the core urban area, leading to the loss of ecological land and a rapid decline in ecosystem services [6]. In Jiangning, education and social welfare services are indeed concentrated in rural areas, such as Jiangning University Town. Since universities typically occupy extensive land, it is essential to focus on planning and designing campus greening initiatives to enhance ecosystem serviceability. In addition, Figure 7 shows that the threshold values for traffic and market services are notably low among all services. The high intensity of human activities associated with traffic services often results in a negative correlation with ESs, contributing to a decline in ecosystem service supply [42]. Traffic and market services, tree buffers, green spaces, and even roof greening are encouraged to make the best use of space to improve ESs. This finding is consistent with recent studies that attempt to reduce the negative effects of trade-offs between RPSs and ESs by increasing green infrastructure planning [7]. The identified density thresholds for RPSs provide valuable guidance for policymakers [6].

In addition, multiple threshold identification is critical for phased ecosystem protection. We found that even for the same RPSs, RPSs and different ESs have different RPS thresholds. This observation aligns with other research suggesting that the influence of identical RPSs on different types of ESs is inconsistent [6,42]. In addition, both ecosystem services and public services are related to time scales [2,6], resulting in different ES and RPS states corresponding to different research sites at different time scales and development stages. This reinforces the need for considering one or more thresholds when determining “where” to implement ecological management [2,42]. Therefore, to reduce the impact of RPSs on ESs in multiple dimensions and all aspects, it is necessary to consider various thresholds corresponding to the same RPSs, especially when determining functional areas [40]. In this study, the RPSs threshold provides a standard for ecological protection and restoration schemes, including the minimum value, average value, and maximum value of RPSs. The minimum value is the warning point of the ecosystem in response to the increase in RPSs, the average value is the control point for the rise of RPSs, and the maximum value is the early warning value of the ecosystem service for the increase in RPSs. Higher than the maximum, it can lead to ecosystem collapse. The regional intersection of different threshold conditions leads to inconsistent focus directions at various stages of ecological and RPSs management. This reflects the phased, hierarchical, and accurate process of managing and optimizing RPS–ES relationships.

4.2. Implications for Incorporating RPS Thresholds and ESs into Spatial Planning and Management for Sustainable Development

For the protection and restoration of ecosystems, the “when and where” of human intervention is a difficult and critical issue [46]. This study addresses the challenges of examining RPSs and ESs while establishing stages for planning and management strategies for ecological and public service spaces. A major distinction of this research method from existing studies is ecological restoration is based on several RPS thresholds rather than just a single RPS threshold. This approach emphasizes the accuracy and hierarchy of phased management in ecological practice. Additionally, functional zoning informed by multiple RPS thresholds ensures accuracy in spatial scope and management within the ecological practice. Overall, incorporating multiple RPS thresholds into ecosystem conservation and restoration zoning not only promotes phased ecosystem management but also enhances precision and efficiency, optimizes economic management costs, and maximizes ecological effectiveness. Specifically, the incorporation of RPS thresholds and ESs into sustainable development spatial planning and management has two practical contributions, as follows:

On the one hand, multiple RPS thresholds determine spatial planning management priority. In this study, once the RPSs warning threshold is reached (Figure 6 and Figure 7), the focus of the functional area shifts from repairing ecosystem services to enhancing the supply of ecosystem services, and this area is the priority area for key management. Specifically, as seen in Figure 8, the “ESs enhancement area and RPSs optimization area” of traffic services are located in the central area of Jiangning, which has exceeded the early warning threshold of RPSs. The key point of the regional planning strategy is to increase the supply capacity of ecosystem services, not only to protect the remaining green infrastructure in the current area but also to enhance ecosystem services. It is also necessary to increase the scale of green infrastructure in a variety of flexible ways [7], such as increasing vegetation buffer zones on the periphery of the region. Simultaneously, it is necessary to carefully select vegetation for the green belt of each traffic area, choosing tree species with a strong ability to absorb carbon dioxide effectively and prevent dust. In addition, it is necessary to optimize transportation services, and it is recommended to develop and increase public transportation vigorously.

Currently, the Nanjing government has been committed to the integrated development of urban and rural transportation and the establishment of a seamless transfer mode of “subway + bus”. Furthermore, traffic flow and ecosystem impact assessment should be carried out on existing roads, road reduction and optimization measures should be implemented in areas with low traffic flow, and the reduced road area should be transformed into green spaces, parks, and walking paths. Moreover, different green patches in this area should be encouraged to connect through green corridors to form a green infrastructure network. This is essential for biodiversity and sustainable ESs supply [83,84]. The optimization of transport services has enabled the region to gradually achieve a safe, affordable, accessible, and sustainable transport system for all, aligning with SDG 11.2. Moreover, the planning strategy for the surrounding construction has improved the level of green infrastructure in rural areas, not only providing more public green space but also addressing the health needs of the population, thereby contributing to Goal 11.7. Overall, these efforts are closely linked to Sustainable Development Goal 11, which focuses on fostering sustainable cities and communities.

On the other hand, functional zones divided by multiple RPS thresholds can ensure accurate, efficient, and spatially targeted planning management and strategic recommendations, accurately control RPSs development progress, and thus mitigate the trade-off effect between ESs and RPSs. In addition, attempts to achieve the sustainable use of natural resources by integrating ecosystem services into land planning decisions with a high degree of alignment with Sustainable Development Goal 15 (Life on Land) (Goal 15.9). Functional partitioning for multiple thresholds implies different stages of ESs and RPSs development, which also implies different strategic priorities at the ecological and RPSs spatial planning management levels at each stage. Taking financial services as an example, this study integrated the corresponding thresholds and functional area characteristics of financial services. It proposes spatial planning and management strategies for financial services and various ecosystem services (Figure 9).

Zoning planning and management recommendations based on multiple thresholds provide more details. This is consistent with other studies that advocate zoning with various thresholds for ecological zoning conservation and monitoring [2]. China’s “three regions and three lines” policy has significantly promoted the coordinated development boundaries of public services and ecosystem services. This policy delineates the development boundaries for agricultural space, ecological space, and urban space within territorial spatial planning. By establishing these boundaries, the policy ensures that the red line area for ecological protection remains intact, thereby enhancing the function and integrity of ecosystems. Concurrently, urban space development fosters urbanization, which typically necessitates upgrading industrial structures, including the transition to energy-saving and environmentally friendly economic models [85]. This shift ultimately facilitates the sustainable use of natural resources [7,86]. Under the guidance of this policy, coupled with the urbanization and development of China’s rural economy, improvements in rural ecosystem services are expected.

Furthermore, this initiative promotes a certain degree of coordinated development between public services and ecosystem services. The integration of these elements not only supports ecological health but also enhances the quality of life for rural populations by providing better access to essential services and improving overall environmental conditions. Currently, the Chinese government is vigorously implementing the rural revitalization strategy. Rural revitalization is about “prosperous industry, livable ecology, civilized village style, effective governance, and prosperous life”, which includes innovation in five aspects: industry, ecology, culture, talent, and organization. This strategy addresses residents’ social, economic, and cultural needs. These require basic public services. For our generation, the greatest goal is to meet the growing needs of an increasing population while curbing environmental degradation [3]. This study proposes a spatial planning and management strategy for the sustainable development of suburban rural areas based on the RPS–ES threshold. On the one hand, it can highlight the management priority of spatial planning; on the other hand, it maintains coordinated and sustainable development of rural public services and ecosystem services, provided a precise spatial management strategy is provided.

5. Limitations

In future studies, several limitations need to be noted and addressed. First, the ESs and RPSs we selected are still limited. It is usually impossible to cover all types of ESs and RPSs in empirical studies [7]. We mainly focus on RPSs and ESs that are most important for revitalization and may not be able to cover all key ESs in Jiangning rural areas comprehensively. For example, food production [85], biodiversity maintenance [87], and cultural ecosystem services [88] will be analyzed more comprehensively and deeply in future studies. This study does not consider cultural ecosystem services inclusion into the framework. Many studies on cultural ecosystem services have been proven to promote cultural revitalization [4,88,89,90], and they are also an important entry point for public participation in landscape planning [4,91]. Their inclusion in the research will greatly increase the depth of the research scope. In future studies, we will comprehensively and deeply analyze the cultural ecosystem services closely related to rural sustainable development.

Secondly, although the InVEST model is extensively utilized for evaluating ESs, it has certain limitations. For example, surface water and groundwater interaction is ignored in the water production module [92]. The InVEST model provides a degree of simplification in assessing ecosystem services, such as interpreting faster degradation scores into habitat quality scores through half-saturation and functions. This simplification may overlook some complex ecological processes, affecting the accuracy of the assessment results.

The last limitation is that the availability of RPS and ES thresholds in studies of different sizes should be tested in more urban and rural areas. Different RPS functional area management recommendations may not be applicable in different socioeconomic-ecological contexts, for instance. In the future, we can use other representative suburban villages to explore the methods and strategies of suburban sustainable development spatial planning that integrate RPS and ES thresholds.

6. Conclusions

This study constructs a multi-level spatial planning framework that integrates ES and RPS thresholds into sustainable suburban development in China. By identifying RPS density thresholds that impact rural ecosystem services and using them as KPIs for ecosystem restoration or enhancement, informed ecological decisions and phased scientific management can be achieved. The results show that achieving a positive synergy between rural public services and ecosystem services is challenging. In addition, according to the four functional areas, we emphasize the priority management of “ESs enhancement area and RPs optimization area”. In general, this study’s threshold-based zoning framework has two practical implications for policymaking. First, it provides clarity on “where” to intervene to restore the ecosystem actively, thereby defining the scope of spatial scope and enhancing the accuracy of spatial zoning management. Second, it indicates “when” to intervene, promoting phased, accurate ecosystem management. In China’s rural areas, our zoning framework can guide the targeted spatial management of rural areas in phases, promoting the coordinated development of rural ecology and development with a view to rural revitalization and sustainable development.