Introduction

As an important bridge linking natural ecosystems with human social systems, quantitative methods of evaluating ecosystem services (ESs) have received increasing attention since the concept and systematic classification of ESs were first proposed (Peng et al. 2020). In the context of rapid urbanization, land use and land cover (LULC) changes caused by large-scale urban construction and high-intensity human activities have profound effects on the ESs (Burkhard et al. 2012). The Millennium Ecosystem Assessment (MA) pointed out that in the past 60 years more land has been reclaimed globally than in the eighteenth and nineteenth centuries combined. While the global ecosystem benefits human society and economic development, its ecological service functions are continuously degrading (Xie et al. 2021). Therefore, an increasing number of scientists are involved in mapping and measuring ES supply. ES supply is defined as “the capacity of ecosystems to provide goods and services to human society” (Burkhard et al. 2012). Many related studies have focused on topics relating to ESs including conceptual frameworks (Díaz et al. 2015); temporal and spatial distribution assessment of ESs according to ecological value (Sannigrahi et al. 2021) and biomass (Yi et al. 2018); ES driving factors (Song et al. 2021); relationships between agro-ecosystem services and food security (Bommarco et al. 2013); impact of biodiversity on ESs (Van der Biest et al. 2020); mutual feedback between ESs and human well-being (Chen et al. 2020); integration of ESs with planning, decision making, and policy to improve regional landscape management (Bai et al. 2018); environmental and socioeconomic impacts of urbanization and LULC changes on ESs (Peng et al. 2020); and ES prediction (Schirpke et al. 2020).

At present, great progress has been made in mapping and quantifying the ES supply. However, Paetzold et al. (2010) noted that the level of ESs was influenced not only by supply status, but also by human demands and future consumption trends, implying that the supply and demand of ESs were inseparable (Syrbe and Walz 2012). Thus, researchers have gradually shifted to methods that simultaneously consider both ES supply and demand. Studies of ES supply and demand have mainly focused on spatial and temporal distribution changes (Ala-Hulkko et al. 2019; Chen et al. 2019; Shen et al. 2019; Xu et al. 2021), influential factors (Sun et al. 2020), and mismatches between supply and demand (Baró et al. 2015; Meng et al. 2020).

Integrated assessments can improve our understanding of the interactions between ES supply and demand, and provide important information for landscape planning and ES management, all of which are effective tools for environmental conservation (Wei et al. 2017). However, previous studies had some common shortcomings. Semi-quantitative evaluation methods based on a matrix were widely used initially because of their convenience (Burkhard et al. 2012). With the deepening of research, in order to reflect the different ES supply capabilities and demand levels of the same land type in different areas, the ES supply was generally quantified by biophysical indicators, while the ES demand was measured by preference, perception, and the economic value for society. Different measurement units made it difficult to compare the results (Tao et al. 2018). Therefore, more appropriate indicators and data are needed to quantify a broad range of ESs to enhance the accuracy and practicability of research (Seppelt et al. 2011). In addition, the absence of a comprehensive framework within which to apply the ES research results to assist multiscale decision making poses a barrier to practicing integrated approaches to incorporate environmental issues into different levels of governmental development policy (Bai et al. 2018). In fact, policymakers urgently need to integrate information on the spatio-temporal relationships between ES supply and demand with land use planning to alleviate the mismatches between them.

Due to the rapid economic development, the agglomeration of urban populations, and the expansion of urban areas, urbanization has presented a great threat to the local ecological environment (Qiao et al. 2019). Many countries struggle to cope with the effects of urbanization on the burden of the urban environment (Kremer et al. 2016; Tallis et al. 2011; Zhang et al. 2016). China is experiencing a similar environmental crisis. In the past, rapid economic growth rather than the natural environment was the focus in China which caused serious environmental problems and in turn affected the sustainability of economic growth. The government realized that development patterns must be transformed from an “economic growth first” model to an “ecological civilization” model, in which ecosystem carrying capacity will play an important role. That is, development must be transformed by prohibiting the sacrifice of the environment in exchange for temporary economic growth. As an important part of the ecosystem, human beings cannot transcend nature and exist independently. A common knowledge should be established that balances economic development with environmental protection to help us develop a new path to realize the harmonious coexistence of humans and ecosystems. According to the latest national urbanization plan (2014–2020) and the development plan of the Yangtze River Economic Belt, the urbanization process of Jiangsu Province will be greatly promoted in future. Therefore, we used Jiangsu as a case study to quantify the mismatches in ESs in rapidly urbanizing and developing regions. The main objectives of this study are the following: (1) to establish a quantitative method for measuring the ES supply and demand and identify their spatio-temporal characteristics; (2) to assess the interrelationships between the supply and demand of ES; and (3) to determine the ES risks by regions to facilitate future regional land planning and ecosystem management. We hope that this study can help to alleviate ES deficits and to support regional ES sustainability.

Materials and methods

Study area

Jiangsu Province, belonging to the Yangtze River Delta urban agglomeration of eastern China, is located within 30°45′–35°20′ N and 116°18′–121°57′ E, with an area of 10.72×104 km2, including 78 county-level administrative districts (Fig. 1). Due to its favourable geographical conditions and prosperous economy, Jiangsu plays an essential role in modernization and urbanization and has become an important component of the development strategy of the ‘Yangtze River Economic Zone’. As one of the urbanized provinces in China, the urbanization rate of Jiangsu was 69.61% at the end of 2018, which was 10.03% higher than the national average. This massive urbanization resulted in a large amount of land conversion (Tian 2015).

Fig. 1
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Study area

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Moreover, Jiangsu is experiencing a contradiction between the demand and supply of land resources. For example, the rapid expansion of urban construction results in the loss of large quantities of farmlands; coastal reclamation leads to the loss of coastal shoal wetlands and natural shorelines; and residents increasingly demand urban green space. Over the last two decades, many groups have identified land use and climate changes as major factors affecting ESs (Ian J. Bateman et al. 2013; Wu et al. 2021). Simultaneously, they have found a negative linear relationship between land urbanization and ESs (Peng et al. 2017). Thus, Jiangsu is appropriate as a case study for the assessment of changes in ES supply and demand. This study applied the following methods and the study period was 2000–2018. Land use data were primarily obtained from Landsat remote sensing images at a spatial resolution of 30 m. Land use types in Jiangsu were divided into six categories (cultivated land, woodland, grassland, water bodies, built-up land, and unused land) based on research conducted at the Chinese Academy of Sciences and the Resource and Environment Science Data Center of the Chinese Academy of Sciences. The classification accuracy was evaluated by verification of random sampling field survey points, and randomized inspection of verification lines and the kappa coefficient was calculated. The overall accuracy of the evaluation of the classification results was 93%. All grid-scale data were uniformly sampled at 1 km×1 km for calculation. Visualization was performed in ArcGIS 10.5.

Quantification of the ES supply and demand

ESs were selected for assessment while aiming to maximize the coverage of the ES categories of MA, to reflect the particular interests and concerns of government and local residents, to represent co-occurrence of ES supply and demand to enable mismatches to be quantified, and to ensure that good data were available for calculations (Chen et al. 2019). The six ESs that were selected for assessment were: water yield service (WY), grain production service (GP), carbon sequestration service (CS), soil conservation service (SC), heat regulation service (HR), and recreation service (RE).

The temporal and spatial changes in ES supply and demand were quantified by objective indicators (Table 1). Each indicator was calculated for each 1×1-km2 grid using geographic models and related spatial technologies, to achieve a comprehensive evaluation while considering spatial heterogeneity. Specific methods and data sources are referred to in the Supplementary Information (Section 1. Quantification of the ES supply and demand).

Table 1 Ecosystem services (ESs) indicator description
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ES supply and demand relationship

Ecological supply-demand ratio (ESDR) links the actual supply and human demand of the ESs and can be used to reveal ES surpluses or deficits (Chen et al. 2019). In addition, the comprehensive supply-demand ratio (CESDR) calculated as the arithmetic mean of the ESDR is used to evaluate the ESs at an integrated level. Therefore, these two indicators were chosen to express the relationships between ES supply and demand. Specific formulas are provided in the Supplementary Information (Section 2. ES supply and demand relationship).

ES zoning

It is necessary to implement policies of ecological regionalization and differential management in order to support the implementation of policies based on analyses among the six ESs, to provide a rational basis for the development of an ecological civilization, and to promote sound ecological management. However, existing research is mostly based on the ES state at a specific time of partition, which restricts the application to decision support of the dynamic characteristics of ESs. Incorporation of ES dynamic characteristics into decision support would require superimposition of trends of various ES indicators for zoning. After referring to previous research (Maron et al. 2017) and adding some adjustments, the CESDR, CESDR trend, and ES supply trend were chosen to identify ES supply-demand risk zones. The specific partition method is shown in the Supplementary Information (Table A.2).

Results

Spatial distribution, quantitative characteristics, and matching of ES supply and demand

Water yield service

The WY supply in 35 counties decreased from 2000 to 2010 (supplementary information Fig. A.2). In 2018, the high-value WY supply area expanded from the south to the central and northern regions (Fig. 2). From 2000 to 2010, the province’s total WY demand increased by 1.46% (supplementary information Fig. A.1). More high-value WY demand areas were formed in suburban areas (Fig. 2). In 2018, more than 80.77% of the counties’ WY demand decreased (supplementary information Fig. A.2). The ESDR of WY in Jiangsu basically maintained a level above zero (supplementary information Fig. A.1). The distribution of the ESDR of WY showed an increase from the city centre to the surrounding areas (Fig. 2). In 2018, only 21 counties’ ESDRs of WY were below zero (supplementary information Fig. A.2).

Fig. 2
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Spatial distributions of water yield service (WY) supply, demand, and ecological supply-demand ratio (ESDR) from 2000 to 2018 at 1-km2 grid scale

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Grain production service

In 2000–2010, the GP supply of 52 counties increased, but it dropped significantly in the subordinate counties of Nanjing City, Changzhou City, and Suzhou City (supplementary information Fig. A.3). In 2018, the spatial distribution showed that the GP supply in northern Jiangsu was generally higher than that in southern Jiangsu, and the supply in urban centres was lower than that in suburbs (Fig. 3). From 2000 to 2010, the total demand for GP in Jiangsu dropped by 26.83% (supplementary information Fig. A.1). In 2018, although the demand for GP in most areas of northern Jiangsu continued to decline, the rate of reduction slowed significantly (Fig. 3). The ESDR of GP in Jiangsu increased to 0.0398 from 2000 to 2010 (supplementary information Fig. A.1). In 2018, the areas in northern Jiangsu where the supply exceeded demand gradually expanded (Fig. 3).

Fig. 3
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Spatial distributions of grain production service (GP) supply, demand, and ecological supply-demand ratio (ESDR) from 2000 to 2018 at 1-km2 grid scale

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Carbon sequestration service

In 2000, the CS supplies in the central urban areas and their surrounding areas in southern Jiangsu were slightly lower than the demand, while the CS supplies in the eastern and northern counties were slightly higher than the demand (Fig. 4). From 2000 to 2010, the CS supply in most counties showed a downward trend (supplementary information Fig. A.4). In 2018, the total CS supply in Jiangsu increased by 18.5% (supplementary information Fig. A.1). From 2010 to 2018, the total CS demand in Jiangsu increased steadily to 1.87×108 t, but the growth rate slowed (supplementary information Fig. A.1). From 2000 to 2010, the province’s ESDR of CS dropped by 204.37% (supplementary information Fig. A.1). The number of counties with CS surpluses increased to 25 in 2018 (supplementary information Fig. A.4).

Fig. 4
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Spatial distributions of carbon sequestration service (CS) supply, demand, and ecological supply-demand ratio (ESDR) from 2000 to 2018 at 1-km2 grid scale

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Soil conservation service

In 2000, downtown Lianyungang had the highest SC supply among all the counties (supplementary information Fig. A.5). The total SC supply of Jiangsu decreased to 7.26×106 t in 2010 (supplementary information Fig. A.1). However, SC supply in the suburbs of Nanjing City and the Taihu Lake area increased significantly (Fig. 5). In 2000, the areas of high SC demand were concentrated in the southwest and northern edges of the province (Fig. 5). In 2010, the total SC demand in Jiangsu fell by 42.55% (supplementary information Fig. A.1). From 2000 to 2018, the overall supply exceeded demand despite some fluctuations in SC at the county scale (supplementary information Fig. A.5).

Fig. 5
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Spatial distributions of soil conservation service (SC) supply, demand, and ecological supply-demand ratio (ESDR) from 2000 to 2018 at 1-km2 grid scale

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Heat regulation service

The annual variation in HR supply over a short period is largely affected by the increase in impervious surfaces caused by urbanization. Therefore, the province’s mean HR supply dropped sharply from 0.0008 °C in 2000 to −0.0007 °C in 2010 (supplementary information Fig. A.1), particularly in Wuxian, Qidong, and Rudong (supplementary information Fig. A.6). However, the HR supply in most of these counties increased in 2018. From 2000 to 2010, the HR demand of 78 counties increased (supplementary information Fig. A.6), especially in urban centres (Fig. 6), while the HR demand of all counties decreased by more than 85% in 2018. In 2000, the ESDR of HR in southern Jiangsu were lower than those of northern Jiangsu, and the ESDR gradually increased from the urban centre toward the outer suburbs (Fig. 6). The ESDR of Jiangsu first dropped (to −0.0089 in 2010) and then rose to −0.0007 from 2000 to 2018 (supplementary information Fig. A.1).

Fig. 6
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Spatial distributions of heat regulation service (HR) supply, demand, and ecological supply-demand ratio (ESDR) from 2000 to 2018 at 1-km2 grid scale

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Recreation service

From 2000 to 2010, RE supply dropped in 60 counties (supplementary information Fig. A.7). The decline in the mean supply of RE in Jiangsu slowed down in 2018 (supplementary information Fig. A.1). From 2000 to 2018, the province’s mean demand steadily increased (supplementary information Fig. A.1). The RE demand decreased from the city centre to the surrounding area (Fig. 7). During the study period, the ESDR of RE in Jiangsu dropped from 0.0385 to 0.0280, but the rate of decline gradually slowed (supplementary information Fig. A.1).

Fig. 7
figure 7

Spatial distributions of recreation service (RE) supply, demand, and ecological supply-demand ratio (ESDR) from 2000 to 2018 at 1-km2 grid scale

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Spatial distribution and quantitative characteristics of the CESDR

From 2000 to 2018, the CESDRs of Jiangsu showed that comprehensive ES surpluses gradually expanded (supplementary information Fig. A.1). In 2000, the CESDRs were lower in the south and higher in the north, and the CESDRs of the urban centres were below the surrounding areas (Fig. 8). In 2010, the spatial distribution remained the same, but the CESDRs increased in most parts of the north and decreased in the south. From 2010 to 2018, the CESDRs of the southern regions and the northern city centres increased significantly. At the county scale, the number of counties whose CESDR was below zero increased from 41 to 43 by 2010, and then decreased to 36 in 2018 (supplementary information Fig. A.8).

Fig. 8
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Spatial distributions of comprehensive supply-demand ratio (CESDR) from 2000 to 2018 at 1-km2 grid scale

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Spatial distribution of ES supply-demand risk zones

The area ratios of the ES critically endangered zone, ES endangered zone, ES observation zone, ES stable area, and ES advantage zone in Jiangsu were 17.8375%, 13.6407%, 2.2691%, 15.7597%, and 50.493%, respectively (Fig. 9). This indicates that more than 65% of the regions were in a safe state of ES supply and demand with comprehensive supply surpluses. The critically endangered zones were mainly located in Nanjing City, Zhenjiang City, Changzhou City, northern Wuxi City, and northern Suzhou City, all of which were also surrounded by ES endangered zones. In more than 78% of the ES endangered zones, only one or two of the six ES supplies declined from 2000 to 2018.

Fig. 9
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Spatial distribution of ecosystem service (ES) zone

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Discussion

The land cover-based matrix model has been proven around the world to be a quick and valid method to measure ES supply and demand (Jacobs et al. 2015; Sun et al. 2020; Zhang et al. 2017). However, considering the spatial heterogeneity in ES supply and demand within the same land cover type (Funes et al. 2019) and complex influential factors other than land cover, spatio-temporal information of ESs cannot be expressed accurately by the matrix model (Schröter et al. 2012). In this study, the supply and demand of each ES were calculated by specific formula or model instead of being determined by using the matrix method.

Different management strategies for sustainable ES development

Because ESs include both supply and demand, it is necessary to combine the analyses of the two aspects when making policy recommendations to improve the deficits of different ESs. Management strategies and policy recommendations are as follows.

The main problem of WY in northern Jiangsu was the continuous increase in water demand caused by industrial development and extensive agricultural irrigation. At present, southern Jiangsu has entered a stage of transformation and upgrading of industrial structure, and many industrial enterprises have been moving to central and northern Jiangsu, especially to the latter region. The proportion of industrial output in northern Jiangsu increased from 16% in 2006 to 22% in 2017. However, northern Jiangsu generally exports raw materials, minerals, and other primary and low-technology products, resulting in an increased demand for water and severe pollution in aquatic environments (Yu et al. 2021). In addition, Cao et al. (2018) reported that expanding agricultural water consumption to meet grain demand has been an important reason for the increase in regional water stress in northern Jiangsu. The results of this study reinforce the conclusion that in order to balance WY, the northern region should eliminate high water-consuming technologies and equipment in enterprises, recycle industrial water, promote agricultural high-efficiency water-saving facilities, and implement ecological restoration and water improvement projects like those in southern areas. Taking Nanjing as an example, the measures of vigorously constructing high-standard farmland projects, upgrading water conservancy facilities in farmlands, and improving farmland irrigation and drainage projects will be implemented according to the “Implementation Plan of Nanjing Water Saving Action”.

Regarding GP, the problems faced by northern and southern Jiangsu were different. The northern regions should be concerned about the abandonment of farmland caused by rural residents attracted by high economic income to move to southern areas. In southern areas, although agricultural technologies have become increasingly advanced and grain yields continue to increase, a large amount of farmland was occupied for the development of industries and this led to a decrease in grain production. Along with this, some counties in southern Jiangsu diverted some waters into cultivated land to ensure regional food supply in the early period. However, Wu et al. (2020) found that this diversion was the main reason for the loss of ES value in southern Jiangsu. To ensure food security and prevent the continuous degradation of GP, Jiangsu adopted a development strategy of requisition-compensation balance of farmland (RCBF). While ensuring the food supply in southern regions, RCBF also promoted the return of population and accumulated capital based on agriculture, to northern Jiangsu, to promote the development of high-income industries such as tourism. However, the requisition of superior cultivated land and compensate the inferior cultivated land often occurred during the implementation period, which led to ecosystem degradation and soil erosion (Liang et al. 2015).

In addition, increasing the area of urban green space (UGS) has become an effective choice to further improve the comprehensive level of CS, SC, HR, and RE. Escobedo et al. (2010) estimated that the net CO2 storage of UGS in Gainesville, USA, could offset 3.4% of urban carbon emissions. Our research on SC showed that the Grain to Green Program (GTGP) along the Taihu Lake, which is building a green ecological barrier for the lake, significantly increased the local SC supply. This was similar to the research reported by Kong et al. (2018) that soil erosion decreased by 19.5% in the Yangtze River Basin during 2000–2015 as a result of the GTGP. In addition, based on our results, the temporal and spatial distribution of HR deficits in Jiangsu during the study period were mainly caused by anthropogenic heat generation, urban modifications, and industrial development. The direct effects included reduction in environmental quality (Fahed et al. 2020), increases in energy cost and pollution concentrations (Agarwal and Tandon 2010), acceleration of heat related public health problems (Kotharkar et al. 2019), and underestimated economic losses (Xia et al. 2018). Sanchez and Reames (2019) pointed out that the lower the green coverage, the higher the intensity of urban heat.

The area of UGS in Jiangsu continuously reduced due to the continuous advance of urbanization and this affected various ES supplies. It was obvious that early urbanization in China was mainly driven by urban expansion, during which local governments sought to maximize land lease revenue under the current tax share system (Qun et al. 2015). Existing studies unanimously found that, fortunately, wealthy cities had more UGS funding (Li et al. 2018). Therefore, after realizing the importance of UGS for long-term economic development, Jiangsu as a province with strong economic development has the capacity to combine national policies and residents’ needs to expand UGS, increase the ES supply, and realize the development of new urbanization.

Importance of the spatial changes in the CESDR for urban development

As ecosystems are complex and dynamic; the relationships between ES supply and demand are constantly changing. Research on spatio-temporal characteristics can accurately identify potential areas for urban development and resource allocation (Baró et al. 2017). Our results have demonstrated that the comprehensive ES supply and demand relationship in Jiangsu has changed significantly. Although Jiangsu’s CESDR increased, with fluctuations, the ES supply deficits in urban regions were still obvious. The same result also appears in Shanghai, which is also located in the Yangtze River Delta. Chen et al. (2019) indicated that all four ESs had major spatial mismatches between supply and demand, particularly in the city centres where demand was high. Urban expansion from 2000 to 2014 aggravated these mismatches. Meanwhile, our results indicated that the ES supply in the suburbs of northern cities was clearly in surplus.

In fact, supply and demand have their own relative ideal levels for each ES and each situation, which is determined by the relationship between urban development and ecological protection (Xin et al. 2021). Due to population agglomeration and widely distributed artificial surfaces in the urban centres of Jiangsu, the CESDR in these regions was generally below zero. Therefore, for policymakers, strengthening ecological restoration and controlling city size are of great significance for sustainable ES development. Conversely, in some regions with extreme mismatches characterized by high supply and low demand (i.e. the utilization efficiency of ecological resources was extremely low), more attention should be paid to the development of ecological resources.

Practical significance of identifying the ES supply-demand risk zones for planning decisions

Identifying key areas of risk and implementing effective ecological management countermeasures are key ways to achieve sustainable regional development. Our classification framework comprehensively considers the current situation, dynamic characteristics of the CESDR, and changing trends of the ES supply in order to evaluate the ES supply and demand risks. The proposed framework and indicator system are significant tools that help inform urban planning and ecological protection. Specifically, determining the zones of ES supply and demand risk can help stakeholders identify hotpots with ES degradation, which is helpful in determining priorities and formulating targeted intervention strategies.

In this study, an approach was proposed to identify the ES critically endangered zones, which included Nanjing City, Zhenjiang City, Changzhou City, northern Wuxi City, and northern Suzhou City. In addition, these critically endangered zones were surrounded by ES endangered zones. In fact, the high risk in these regions was mainly due to the developed economy, which attracted a large population inflow. While the demand for ESs is rising, the area of original natural ecosystem land is decreasing due to the continuous expansion of urban built-up areas, which affects the supply of ESs. The same phenomenon also occurred in Western Greece. A study conducted by Lorilla et al. (2019) in the Ionian Islands of Western Greece pointed out that the Ionian Islands had a surplus of ES supply in highly natural areas, but that excess societal demand for services was concentrated in urban areas, which was affected by the high population density in these locations. Thus, if effective ecological control cannot be achieved in the ES critically endangered zones, then the surrounding areas with high ES endangerment risk may fall into danger. ESs will continue to deteriorate, eventually leading to the expansion of area with high ES risk.

Pan and Wang (2021) also found that the ES deficit in southeast China (such as the counties in southern Jiangsu) was serious. They analyzed that this was mainly because, although these regions have a high urbanization level and a high resource utilization efficiency, the substantial increase in the area of land under construction in south-eastern China occupied a large amount of farmland and ecological land. This led to an increase in landscape fragmentation and a decline in ecosystem structure and function, which brought about a decline in ES supply. Therefore, it is necessary to strictly control the intensity of land development, to limit unordered expansion of ES critically endangered zones, and to reduce the demand for ESs. At the same time, damaged ecological resources should be restored by improving the ES supply capacity. Improving infrastructure, strengthening the flow between the ES supply and demand, and optimizing the structure of the ecosystem are all effective measures to improve ES deficits.

Mapping the ES supply-demand mismatches at a precise spatial geographic level for formulating accurate ES management policies at different scales

Determining supply-demand mismatches of ESs can help inform environmental management and generate useful information for planning and decision-making processes (Maes et al. 2012). Due to the nature of decision making being influenced by administrative subordination, an approach quantifying the ES supply and demand over multiple scales is usually imperative for supporting the implementation of ES management in planning and decision-making (García-Nieto et al. 2013). At the same time, it should be noted that mapping ESs at a fine scale is particularly necessary, which is helpful for operating with the ES framework in urban management at the municipality level (González-García et al. 2020). Moreover, the ES supply-demand dynamics should be considered carefully, which can be beneficial for assessing how mismatches evolve over time.

Thus, we proposed a quantitative approach to assess the evolution of ES supply-demand mismatches spatially and temporally from 2000 to 2018 at a scale of 1×1-km grid in this study. This approach provided an effective tool to explore ES mismatches, which could and should be used in local development planning at regional levels. In addition, our study was conducted over a multi-administrative scale (provincial and county scale) to analyze ES mismatches. The advantage of this analysis was that it could integrate socioeconomic data to accurately explain the reasons for the ES mismatches, which was helpful in implementing decision-making (Larondelle and Lauf 2016). To offset the ES deficits in Jiangsu, linking land use patterns with the ESs at multiple scales to complete land use management is a practical option. At the provincial scale, rational land use planning should be implemented to control the unlimited sprawl of construction land (McGranahan et al. 2015). At the county scale, policy implementation should increase the feasibility of multi-angle analysis, making policy formulations more tailored to actual local conditions.

The spatial distribution of the CESDR indicated that the ES deficits in urban areas were more severe than those in suburban areas. Because ESs can flow in the space ignoring administrative boundaries (González-García et al. 2020) and a city is a comprehensive administrative area that includes central urban and suburb areas, we highlight the need for more integrated land use planning at a city scale. In the processes of urbanization in Jiangsu, spatial mismatches between ES supply and demand tend to change continuously over time due to the changing population size. For example, the migration of rural people (moving from rural to urban areas) has led to the abandonment of farmlands in the hinterland, which has affected food supply. At the same time, the food demand in urban areas has tended to increase gradually owing to an increase in population. Thus, we suggest that spatially tracking supply and demand of ESs within a city and quantifying how much the ES supply needs to increase in urban areas and the ES demand needs to reduce in suburban areas would enable planners to achieve a regional equilibrium between ES supply and demand. In addition, urban areas should also promote land use efficiency and transform extensive land use patterns into intensive utilization (Hersperger et al. 2018).

However, it is not sufficient to adjust only the areas of land use types. Sun et al. (2020) proved that patch density is one of the most important drivers of ESs at both the state and metropolitan scales. Thus, optimizing the structure and distribution of spatial patches will be the focus of future research, which may enhance capacity for ES supply at the landscape patch scale and further alleviate or offset ES deficits.

Future perspectives

In this study, the mismatches between ES supply and demand not only provided a valuable means to quantify the sustainability of ESs, but also provided a reference for the protection and management of ESs in Jiangsu. However, there are still some limitations to be addressed in future research.

First, we will attempt to improve the accuracy of the parameters for calculating ESs. For example, more precise grain production in different regions can be obtained based on field investigations rather than statistical data spatialization. Second, only six key ESs in Jiangsu were quantified due to the lack of appropriate quantifying methods and data. Actually, other ESs (e.g., air purification) are also important to the human well-being in this region. In the future, more novel ES mapping methods will be used to quantify other important ESs. Additionally, when calculating the CESDR value, the weights of six ESs were determine based on previous researches and qualitative analysis of the actual situation in the study area. In the future, quantitative analysis (e.g. the participatory survey of different stakeholders) can also assist to define the weights of different ESs for obtaining more accurate estimation results.

Conclusion

Co-occurrence of the selected six ES supply, demand, and spatial mismatches were quantified at three scales (province, county, and grid) in Jiangsu from 2000 to 2018. The results indicated that during the study period, the CESDR at the provincial scale in Jiangsu was greater than zero and the ES surplus gradually expanded. However, the specific situations of each ES were diverse. CS and HR deficits always existed, but the difference was that the CS deficit progressively deteriorated, while the ESDR of HR first decreased and then increased steadily since 2010. The ESDR of the remaining four ESs all showed surpluses. Among them, GP, SC, and WY fluctuated during the study period, but the ESDR in 2018 was better than that in the initial study period (2000). In contrast, the ES surplus of RE has been declining. As for spatial distribution at the grid scale, the ESDR of each ES was lower in city centres than in surrounding areas, which demonstrated that urban expansion was one of the major factors aggravating the mismatches between ES supply and demand. However, owing to the spatial coupling between urban centres and suburbs, except for CS and RE, other ESDRs in all counties tended to be better at the county scale.

In conclusion, this study established a comprehensive research framework that applied the academic research results of ES supply and demand to local specific policy formulation. This served to define different ES management areas and to propose specific suggestions for planning adjustment. Specifically, controlling the unlimited expansion of built-up areas, improving land use efficiency, reducing industrial carbon emissions, and increasing urban green areas are all efficient land use strategies to offset ES deficits. While enhancing the sustainable development of ESs, these strategies also lay a solid foundation for urban social and economic development.