Evaluation of the Public Welfare of China’s Nature Reserves

Abstract

To achieve the sustainable development of nature reserves, the public welfare associated with these areas has been assessed based on ecological supply and social demand. The Public Welfare Index comprehensively incorporates ecological factors, such as landforms, resource endowment, and ecological quality, as well as socio-economic factors, including travel costs, economic base, and population distribution. This index reflects both the ecological supply capacity of nature reserves and the equity with which they provide welfare to different groups. The findings indicate that the Public Welfare Index is an effective measure of the rationality of welfare distribution. Currently, the public welfare of nature reserves in China exhibits a spatial pattern of high welfare in the west and low welfare in the east. This issue of welfare inequality in nature reserves is highly pronounced. The primary objective of this research is to identify the characteristics of welfare distribution and to offer novel perspectives and strategies for optimizing the spatial layout of nature reserves and informing policy decisions.

1. Introduction

Nature reserves are designated geographical areas established for the long-term conservation of natural ecosystems with their associated ecological services and cultural values [1]. These areas are critical for safeguarding biodiversity, contributing substantially to climate regulation, and mitigating the risks of ecosystem degradation [2,3,4]. The abundance and diversity of vegetation within nature reserves play a vital role in reducing soil erosion and minimizing the likelihood of landslides and mudslides [5]. Enhanced connectivity between nature reserves is proposed to significantly increase conservation efficiency, leading to greater ecological benefits from protected areas [2]. From a societal perspective, nature reserves provide substantial public benefits through channels such as ecotourism, scientific research, and environmental education. These reserves facilitate cultural exchange and knowledge dissemination, thereby promoting sustainable development within local communities [6]. The establishment and maintenance of nature reserves generate diverse employment opportunities for local residents, thus contributing to the enhancement of regional income levels [7].

Despite the considerable ecological and social benefits provided by nature reserves, quantifying their contributions to public well-being remains a significant challenge, particularly in terms of evaluating their public good attributes. The failure to accurately measure the public good value of nature reserves not only limits welfare gains for vulnerable populations but can also impede regional economic development. Due to an underestimation of their welfare value, countries such as Brazil, Canada, and Indonesia have started reducing the area of nature reserves [8], a practice that weakens global protected area networks and adversely affects conservation efforts [9]. This issue stems from misconceptions regarding the welfare benefits of nature reserves. While some studies focus on quantifying the benefits to primary stakeholders, they often neglect whether these reserves provide equitable welfare opportunities to vulnerable groups, especially low-income communities [10,11]. To address this gap, this study proposes the Public Welfare Index, a novel metric designed to comprehensively assess the welfare contributions of nature reserves to all population groups, with particular emphasis on ensuring equitable benefits for low-income communities.

Globally, the assessment of public welfare in nature reserves has garnered significant attention [12,13]. Ecological conservation in nature reserves provides direct welfare benefits to society by enhancing biodiversity and promoting ecosystem services [14]. The ecological benefits of nature reserves not only support ecosystem restoration but also enhance climate change adaptation [15], thereby offering widespread environmental benefits to society. In Europe, ecotourism in nature reserves has brought considerable economic benefits to local communities [16]. In Africa and Latin America, significant progress has also been made in the study of public welfare in nature reserves. Africa’s Protected Area Governance and Management Program highlights that nature reserves in Africa provide employment opportunities and income sources for local communities, particularly through promoting ecotourism and environmental education [17]. However, due to weak economic foundations and poor transportation infrastructure, many low-income groups have not been able to equally enjoy the benefits provided by these reserves, a problem that is particularly pronounced in nature reserves in Southeast Asia and South America.

With a population of 1.426 billion and an area of 9.6 million square kilometers [18], China faces significant challenges in ensuring an equitable distribution of welfare from its nature reserves. By 2023, 95% of the Chinese population will earn less than CNY 5000 per month (approximately USD 684), with the majority’s income levels restricting their access to the ecological and recreational services provided by nature reserves, thus preventing the realization of the inclusive ecological benefits from these reserves. China is used as a case study to examine whether nature reserves can offer low-income groups access to their services at reduced costs. Through the construction of a Public Welfare Index for nature reserves, this study addresses the lack of quantification of public service attributes in existing research, particularly the neglect of the welfare contributions to vulnerable groups. The innovative theoretical framework for evaluating the public welfare of nature reserves is provided, and the spatial pattern analysis based on the Public Welfare Index reveals the spatial characteristics of public welfare in nature reserves, offering practical guidance for the spatial optimization of reserves. This is of significant importance in balancing ecological protection and social equity and in promoting regional economic development. The research is framed around the following three key questions: (1) How should the public welfare of nature reserves be measured? (2) What are the characteristics of the spatial pattern of public welfare in China’s nature reserves? (3) How can the public welfare of nature reserves be enhanced through spatial planning and policy intervention? An in-depth exploration of these questions will provide theoretical support and practical guidance for the scientific management of nature reserves, alongside actionable recommendations for promoting their sustainable development.

2. Materials and Methods

2.1. Study Area

The study compiled spatial data for 762 nature reserves (Figure 1), including 335 national nature reserves, 197 provincial nature reserves, and 230 local nature reserves, which encompass various types such as steppe meadow, geological relic, paleontological relic, marine coast, desert ecology, forest ecology, wetland ecology, wild animals, and wild plants. Among all ecosystem types, forest ecology represents the largest category, with 324 nature reserves, accounting for 42.52% of the total. Of these, 159 are at the national level, 69 are at the provincial level, and 96 are at the local level (Figure 1B). Steppe meadows and paleontological relics have the fewest nature reserves, with nine each, representing only 1.18% of the total.

In terms of spatial distribution, the western region of China has the highest number of nature reserves, accounting for 46.66% of the total, followed by the eastern region, which accounts for 19.39%. The northeastern region has the fewest nature reserves, constituting only 16.12% of the total. Provincially, Sichuan Province has the highest number of nature reserves (82), followed by Heilongjiang Province (69) and Yunnan Province (49) (Figure 1C).

2.2. Experimental and Technical Design

Nature reserves play a crucial role in ecological conservation and significantly influence human well-being through the ecosystem services they provide. By constructing the Public Welfare Index, the abstract concept of “Public Welfare” is transformed into a quantifiable form, thereby laying the foundation for a scientific understanding of welfare distribution in China. To ensure a comprehensive evaluation of public welfare, the Public Welfare Index developed in this study incorporates two components, ecological supply and social demand, which are measured using distinct approaches.

For the measurement of ecological supply, this study employs the equal-weight overlay method to assess ecological supply [19,20]. This method integrates various ecological factors, such as natural resource endowment, topographic conditions, and ecological quality, to derive the ecological supply capacity of nature reserves. For the measurement of social demand, this study utilizes a Two-Step Floating Catchment Area Method, which has been widely applied in supply–demand analysis [21]. In this study, ecological supply is regarded as the carrying capacity of nature reserves, while local economic base and transportation costs are used as weights for population distribution to measure social demand. This method enables a supply–demand analysis of public welfare in nature reserves, thereby facilitating a comprehensive evaluation of public welfare level.

This study not only identifies the spatial clustering of public welfare but also emphasizes spatial disparities in welfare distribution. The study comprises the following two main steps: the first involves the measurement of the Public Welfare Index, and the second focuses on the spatial pattern analysis of public welfare (Figure 2).

2.2.1. Measuring Public Welfare

Gong and Huang [22] analyzed the experiences of establishing nature reserves in various countries and proposed that the following two key conditions must be met to achieve public welfare in nature reserves: (1) the provision of high-quality ecological services by the reserve and (2) the ability for low-income populations to access these services at low cost [23]. The aim of the research is to construct a Public Welfare Index for nature reserves from both ecological supply and social demand perspectives. Ecological supply reflects the capacity of nature reserves to provide ecological services, while social demand assesses the accessibility and equity of these services, focusing on whether economically disadvantaged groups can benefit and ensuring a more balanced distribution of welfare among the public. This approach broadens the understanding of the value of nature reserves, extending beyond ecological functions to include the dual objectives of ecological protection and social equity.

In summary, a comprehensive measure of the public welfare value of nature reserves is constructed from the perspectives of ecological supply and social demand. Ecological supply refers to the capacity of nature reserves to provide ecological services, typically measured through indicators such as landforms, natural resource endowments, and ecological quality [19]. Social demand focuses on the accessibility of different regions and populations, influenced by factors such as population density, economic base, and travel costs. For feasibility, the Fishnet tool was used to divide China’s population and economy into 100 km × 100 km fishnet cells. Social demand for nature reserves was measured based on the population, economic output, and travel costs to each nature reserve within each cell. Public welfare was then calculated by multiplying ecological supply and social demand. To ensure the stability of the index, the study tested the robustness of the Public Welfare Index by adjusting the threshold distance for transportation modes.

2.2.2. Spatial Pattern Analysis

To conduct a spatial pattern analysis, the degree of public welfare across administrative regions is examined [24]. The spatial pattern analysis is primarily divided into two components. The first component identifies spatial differences in public welfare and the clustering characteristics of nature reserves at various administrative levels through spatial autocorrelation analysis. The second component assesses the spatial balance of public welfare in nature reserves across the provinces of China using the Gini Index and the Lorenz curve.

2.3. Indicators and Research Methods

2.3.1. Calculation of Public Welfare

The Public Welfare Index is measured from two perspectives, ecological supply and social demand. Ecological supply measures the ecological endowment that generates public welfare (

Table 1. Indicator system.

Primary Category	Secondary Category	Indicator Layer	Definition
Ecological supply	Landform	Elevation [25,26]	Lower elevation areas exhibit higher oxygen content, rendering them more suitable for public activities and recreational tourism. In nature reserves, low-altitude regions can accommodate a greater number of visitors, thereby enhancing human health and well-being. Ecosystem services in these areas, such as improved air quality and recreational opportunities, can be extended to a larger population, particularly low-income groups, thereby generating inclusive ecological benefits [27].
		Slope [26,28]	Regions characterized by gentler slopes offer greater accessibility, suitability for tourism development, and enhanced comfort for visitors. Within nature reserves, such areas can be extensively developed into trails or tourist attractions, mitigating constraints related to transportation and travel costs and enabling broader public participation [29].
	Resource endowment	Landscape Naturalness Index [30]	Highly natural landscapes provide more comprehensive ecosystem services and possess higher ecological value. These landscapes are more effective in delivering ecological products and services, including air purification and water provision. Such highly natural environments afford the public more direct ecological benefits, such as access to clean air and protection of water resources [29].
		Water distance [19]	The natural landscape around the water is relatively high quality, has high scenic value, and is attractive to the public.
	Ecological quality	Vegetation coverage [26]	Vegetation cover directly augments carbon sequestration and ecological supply capacity. Abundant vegetation not only sequesters carbon dioxide but also enhances air quality and biodiversity, exerting a positive influence on human health [19].
		Shannon Diversity Index [19]	The Shannon Diversity Index reflects the richness of the natural environment. Nature reserves with higher biodiversity are more likely to attract scientific research and ecotourism activities. For the public, regions with elevated ecological diversity provide greater access to natural resources and health benefits, while offering more low-cost ecotourism opportunities [22].
Social demand	Population distribution		Nature reserves that encompass more densely populated areas can deliver abundant ecological services to a larger population, thereby maximizing the utilization of ecological resources [29].
	Economic base		The measurement of the local economic base enables the determination of whether a nature reserve provides greater ecological welfare to low-income groups. The greater the coverage of low-income groups by a nature reserve, the higher its public welfare value [31].
	Travel costs		Elevated transportation costs may impede access to nature reserves for low-income groups. Reducing these costs, for instance through the provision of public transportation and subsidies, can enhance participation by low-income groups, ensuring the broader distribution of nature reserve benefits and promoting both ecological conservation and social equity [32].

) [20], which refers to the degree of environmental suitability for ecological activities that nature reserves provide for the public. Social demand reflects the degree to which people from different geographical and economic backgrounds benefit from nature reserves. The method of calculation is as follows:

$${PWI}_i={ES}_i\times {SD}_i$$

(1)

where ${PWI}_i$ is the public welfare of nature reserve $i$, ${ES}_i$ is the ecological supply of nature reserve i, and ${SD}_i$ is the social demand of fishnet i.

Ecological supply is weighted by landform, resource endowment, and ecological quality indicators. The formula is as follows:

$${ES}_i=\sum _{i=1}^n{A}_i$$

(2)

where ${ES}_i$ represents ecological supply, $A_i$ is the indicator score, and $n$ is the number of ecological supply indicators.

Studies believe that the lower the income group, the more they can benefit from nature reserves at a lower cost and the higher public welfare. The decisive factors for social demand include the regional economic base, travel costs, and the population distribution. Based on this, the formula for calculating ${SD}_i$ is as follows:

$${SD}_i={\sum }_{i=0}^n{\displaystyle \frac{P_{COUNT}}{T\times P_{GDP}}}$$

(3)

where $T$ represents the travel cost from fishnet to the nature reserve, $P_{GDP}$ represents the total GDP of each fishnet, $P_{COUNT}$ represents the total number of people of each fishnet, and $n$ represents the total number of fishnets.

Sensitivity analysis can be used to measure the impact of input variables on the nature reserve’s Public Welfare Index and to check the stability of the index [33]. As the choice of transport mode varies from person to person, there is a great deal of uncertainty. By adjusting the threshold distance of the transport mode, the public welfare measurement changes from a static perspective to a dynamic perspective, which can best reflect the actual situation.

The transport threshold distance of the control group and its cost calculation method are as follows: if the distance is less than 300 km, choose road transport; if the distance is between 300 km and 1000 km, choose rail transport; if the distance is more than 1000 km, choose air transport. The cost of road travel is 1 RMB/km, high-speed rail travel is 0.46 RMB/km, and air travel is 0.75 RMB/km. The formula is as follows [34]:

$$T=\left\{\begin{array}{cc}\hfill d,& d<300\hfill \\ \hfill 0.46d,& 300\le d<1000\hfill \\ \hfill 0.75d,& x\ge 1000\hfill \end{array}\right.$$

(4)

where $T$ is the travel costs from each fishnet to the nature reserve, and $d$ is the distance from the fishnet to the nature reserve.

Spearman’s rank correlation coefficient [35] is a nonparametric test that measures the monotonic correlation between two variables. In this study, Spearman’s rank correlation coefficient is employed to examine the relationship between the Public Welfare Index and transportation factors across varying transportation threshold conditions. By computing the correlation coefficients under diverse transportation threshold scenarios, the stability of the Public Welfare Index can be evaluated; correlation coefficients approaching 1 indicate a more stable monotonic relationship between the Public Welfare Index and transportation factors under these conditions. Conversely, lower correlation coefficients may suggest that the Public Welfare Index is more substantially affected by variations in transportation factors. The equation is shown as follows:

$$\rho =1 - {\displaystyle \frac{6\sum d_i^2}{n\times \left(n^2 - 1\right)}}$$

(5)

where $\rho$ is the Spearman correlation coefficient, $d_i$ is the difference in the ranks of each pair of observations, and $n$ is the total number of observations.

2.3.2. Space Pattern Analysis

In order to understand the spatial pattern of public welfare, the research puts the results of the Public Welfare Index into the perspective of administrative regions [24], and the calculation is as follows:

$${APW}_i={\displaystyle \frac{{\sum }_{i=1}^n{NRPW}_i\times S_n}{S_A}}$$

(6)

where ${APW}_i$ is public welfare for administrative area $i$, $S_n$ indicates the area of the nature reserve that falls within the administrative area $n$, and $S_A$ indicates the area of the administrative area.

Local Moran’s I can reveal the spatial distribution characteristics of public welfare in different regions, identify hotspot areas with high and low public welfare, and provide a theoretical basis for spatial optimization of nature reserves [36] with the following expression formula:

$$I_i={\displaystyle \frac{n\times \sum _{j=1}^n{w}_{ij}\left(x_i - \overline{x}\right)\left(x_j - \overline{x}\right)}{W\times {\sum }_{i=1}^n{\left(x_i - \overline{x}\right)}^2}}$$

(7)

where $I_i$ represents Local Moran’s I for region $i$; $n$ represents the total number of administrative regions; $w_{ij}$ represents the weight between region $i$ and region $j$, which is usually the element of the adjacency matrix and reflects the spatial proximity between the two; $x_i$ represents the public welfare of region $i$; $\overline{x}$ represents the global mean of the public welfare of all regions; $W$ represents the sum of all adjacency weights, which is usually used for standardization.

In studies of the spatial equity of public resources, the Gini index and the Lorenz curve are commonly employed [37,38]. The specific formula is as follows:

$$G_n=1 - \sum _{i=1}^{n-1}\left(x_{i+1}-x_i\right)\left(y_i+y_{i+1}\right)$$

(8)

where $G_n$ is the Gini index of public welfare in province $n$, $x_i$, $x_{i+1}$ is the population of county-level administrative regions in the province, and $y_i$, $y_{i+1}$ is the public welfare of the county in the province. The value of the Gini index lies between 0 and 1. The closer the value is to 0, the more balanced the spatial distribution of public welfare is, and the closer the value is to 1, the more unbalanced the spatial distribution of public welfare in nature reserves.

2.3.3. Data Sources and Processing

The nature reserve data used in the study came from the China Specimen Resource Sharing Platform for Nature Reserves (http://www.especies.cn/ (accessed on 24 July 2025)). Based on the original dataset, records of duplicate or substantially overlapping nature reserves were identified and removed to ensure data accuracy and avoid redundancy, and the research resulted in a final list of 762 nature reserves in China. The dataset provides detailed information on the type, level, and location of China’s nature reserves, covering the entire country [39]. In addition, the GDP grid, DEM data, and land use data were obtained from the Resource and Environmental Scientific Data Platform (http://www.resdc.cn (accessed on 24 July 2025)), and the Normalized Difference Vegetation Index (NDVI) was used to represent vegetation cover. Data were obtained from the Earth Resources Data Cloud (http://www.gis5g.com (accessed on 24 July 2025)), water body data in China were obtained from GitCode (https://gitcode.com (accessed on 24 July 2025)), water distance was calculated using ArcGIS Pro, and the population grid was obtained from ORNL LandScan Viewer (https://landscan.ornl.gov/ (accessed on 24 July 2025)).

The ecological supply indicators were divided into five levels from high to low according to their suitability for carrying out public activities. The landscape naturalness index refers to Yanzhen Hou’s scoring method [19] (

Table 2. Scoring table for the Landscape Naturalness Index.

Score	Land Use Type
1	Urban land; Rural settlements; Other construction land
2	Paddy fields; Dry fields; Grassland with low coverage; Rivers and canals; Reservoirs; Ponds; Tidal flats; Beach; Marshes; Bare soil; Bare rocky soil
3	Shrubland; Sparse woodland; Other woodland; Grassland with medium coverage; Lakes; Sandy soil; Gobi, Saline soil; Sea
4	Wooded land; Grassland with high coverage
5	Glacier and snow

), and the other indicators were divided into five levels from high to low by the Natural Breaks and are numbered 5, 4, 3, 2, and 1.

In this study, extreme values in travel costs and GDP could significantly impact the results. To ensure stable outcomes, the data were processed using Winsorization one-sided trimming, aimed at reducing the influence of extreme values on the public welfare index. Specifically, values below the 5% quantile were replaced with the 5% quantile value for both travel costs and GDP. This approach was implemented because excessively low values in these variables, particularly as denominators in the public welfare calculation, could cause inflated estimates of welfare, thereby affecting the accuracy and stability of the results.

3. Results

3.1. Nature Reserve’s Public Welfare

China’s nature reserves exhibit a spatial pattern of “high in the west and low in the east” (Figure 3A), with the public welfare of nature reserves in western provinces such as Tibet, Sichuan, and Yunnan being significantly higher than those in the eastern coastal provinces. The welfare in this region is 14.38% higher than in the central region, 66.29% greater than in northeast China, and 69.27% higher than in the eastern region (Figure 3B). Among these, 9.31% of the nature reserves have a public welfare value below 0.25, primarily located in Xinjiang, along the northeast border, and on the eastern coast of China. A total of 57.61% of nature reserves have a public welfare value between 0.25 and 0.5, widely distributed in areas outside the Qinghai-Tibet Plateau. Additionally, 27.30% of nature reserves have a public welfare value between 0.5 and 0.75, mainly concentrated in Sichuan, Chongqing, central and southern Yunnan, western Hunan, western Henan, southern Gansu, and southern Shaanxi. Only 44 nature reserves (5.77%) have a public welfare value higher than 0.75, with these predominantly located in Tibet, southern Sichuan, and northern Yunnan. Currently, the top ten nature reserves in China are all situated in the western region, specifically in Yunnan (6), Tibet (3), and Sichuan (1) (Figure 3D). Among them, Cibi Lake has the highest public welfare and is located in Yunnan Province.

Wetland ecology nature reserves exhibit the highest public welfare, while the level of the nature reserve has a lesser influence on public welfare compared to factors such as type and location. In terms of type, China’s wetland ecology nature reserves have the highest public welfare (0.4948), followed by wild animal reserves (0.4613), with marine coast reserves exhibiting the lowest public welfare (0.1289) (Figure 3E). There is minimal variation in public welfare based on the level of the nature reserves, with local-level reserves having the highest public welfare (0.4854), followed by provincial-level reserves (0.4443), and national-level reserves (0.4261).

Public welfare remains highly consistent relative to controls when transport mode adjustments occur within a ±20% distance threshold. Public welfare in the western region consistently remains the highest, followed by the central region. As the threshold distance for transport choice increases, public welfare in China experiences a slight increase. Conversely, when the threshold distance for transport choice decreases, public welfare in China declines, with the western region exhibiting the most pronounced decrease, while the northeastern region is the least affected.

3.2. Spatial Pattern of Public Welfare

At the provincial level, the highest public welfare is observed in the nature reserves of Tibet (0.2468), Gansu (0.0877), Sichuan (0.0725), Qinghai (0.0695), and Ningxia (0.0587), which are all located in the western region of China. Public welfare in nature reserves in the eastern region is lower, with Shandong (0.0051), Guangdong (0.0049), Zhejiang (0.0031), and Shanghai (0.0003) exhibiting the lowest values (Figure 4A). At the municipal level, four cities report a public welfare value greater than 0.3, all of which are in the western region. Sanmenxia, located in the central region, has a public welfare value of 0.1539, ranking among the top ten in the country. Notable nature reserves in this city include the Yellow River Wetlands, Huanglongshan Brown-headed Chicken, and Lushi Giant Salamander. In the eastern region, Suqian nature reserve has the highest public welfare value of 0.0431 (Figure 4C). At the county level, Chenggong County in Yunnan (0.6423), Tashkurghan Autonomous County in Xinjiang (0.5566), and Guandu County in Yunnan (0.5551) report the highest public welfare values for nature reserves (Figure 4E).

The scale of positive spatial correlation for nature reserves across all administrative levels is greater than that of negative spatial correlation. High–high clusters are mainly concentrated in the western region of China, while low–low clusters are predominantly located in the eastern region. At the provincial level, three provinces—Xinjiang, Tibet, and Qinghai—fall into the high–high category. Anhui is categorized as high–low, and 11 other provinces, primarily in the eastern and central regions (such as Hubei, Jiangsu, and Jiangxi), are classified as low–low (Figure 4B). At the municipal level, 206 municipalities exhibit a positive spatial correlation, with 36 classified as high–high, and are mainly located in the western regions of Tibet, Qinghai, Gansu, and Inner Mongolia, and 170 are classified as low–low, predominantly in the eastern region. Forty municipalities show a negative spatial correlation, including 21 high–low municipalities in the southeastern part of the high–high region and 19 low–high municipalities located in the eastern region (Figure 4D). At the county level, there are 1735 counties with a positive spatial correlation and 508 counties with a negative spatial correlation. Among these, 208 counties are classified as high–high, mainly in northern Tibet, western Inner Mongolia, and southwestern Sichuan. Additionally, 352 counties are categorized as low–high that are located in the western region of China around high–high clusters. The remaining 1527 counties, which are low–high, are located in the eastern and northeastern regions of China, and 156 counties are high–low and are distributed around low–high clusters (Figure 4F).

The distribution of public welfare across China’s provinces is uneven, with this phenomenon being particularly pronounced in the eastern region. Studies indicate that the Gini index exceeds 0.5 in all provinces (Figure 5), with only four provinces reporting a Gini index lower than 0.8, which are Hainan, Ningxia, Tibet, and Shanghai. Among these, Hainan Province has the lowest Gini index of 0.5759, followed by Ningxia with a Gini index of 0.5833. Nature reserves in these two provinces are distributed across many parts of the region, improving spatial equity. In contrast, nine provinces exhibit a Gini index for public welfare higher than 0.9, reflecting a highly uneven distribution. These provinces include Xinjiang (0.9128), Shanxi (0.9259), Jiangsu (0.9265), Henan (0.9397), Hebei (0.9417), Anhui (0.9523), Shandong (0.9571), Beijing (0.9653), and Zhejiang (0.9661). These regions are among the most populous or economically important in China, which may influence the distribution of public welfare. For instance, Jiangsu Province had the second-largest GDP in the country in 2024, followed by Shandong Province in third, Zhejiang Province in fourth, and Henan Province in sixth. Economic development and the demand for land resources to support livelihoods have constrained the establishment of nature reserves in these provinces.

4. Discussion

4.1. Theoretical Contribution

The assessment of welfare constitutes a critical research focus for achieving sustainable development in nature reserves [40,41]. However, the focus within the literature has primarily been on the benefits to direct beneficiaries such as residents and tourists. The Public Welfare Index developed in this study adopts a national perspective. It incorporates indicators such as GDP and travel costs to assess whether nature reserves can enable more low-income individuals to access their services at lower costs, thereby achieving broader welfare benefits. Previous studies have indicated that the public welfare of China’s nature reserves follows a spatial pattern of “high in the west and low in the east.” Nature reserves in the eastern region are unable to provide satisfactory income and living conditions, and residents report lower satisfaction with the development of nature reserves [42]. Tourists also perceive the cost-effectiveness of expanding nature reserves around eastern cities as low [43]. In contrast, nature reserves in the western region have effectively mitigated the conflict between ecological protection and local development [44]. In summary, the relatively advanced economic conditions in eastern China suggest that establishing nature reserves may incur substantial opportunity costs, while the associated benefits in terms of employment and income generation remain limited. In contrast, nature reserves in the western region have created better local employment opportunities and increased income. Most studies to date have relied on questionnaire surveys from single nature reserves, limiting the efficiency of assessing public welfare [42]. The Public Welfare Index enhances the efficiency of evaluating public welfare on a national scale.

Due to the relatively weak economic base in China’s western region and the large number of people living in poverty, nature reserves in the west can provide both ecological and economic value to the public, benefitting everyone. The Human Carbon Footprint Map shows an increase in human activity within nature reserves in Tibet in recent years, as evidenced by rising tourist numbers and greater employment opportunities for local residents [39]. Nature reserves in the western region cover more than 50% of the area [45], yet their economic base remains relatively weak. For example, in 2023, Tibet’s GDP per capita is projected to be 26.39% lower than the national average, Yunnan’s by 28.36%, Qinghai’s by 28.49%, and Gansu’s by 46.68%. The public in these regions faces more urgent physical and safety needs [46]. With the ongoing transformation of tourism concepts, ecotourism based on nature reserves has gradually become mainstream, especially in China’s western regions. The ecotourism markets in nature reserves such as Dunhuang Yadan and Qinghai Lake are particularly popular [47], fostering employment opportunities for local communities and enhancing public welfare.

Serving as the core of national economic development, eastern China faces considerable limitations in land use flexibility due to its intensive economic activities and high population density. The establishment of nature reserves is closely linked to local resource availability and the socioeconomic development conditions of the region [48]. These factors present considerable challenges to the development of nature reserves in eastern China [49]. For example, the distribution of nature reserves in Guangdong Province displays pronounced regional disparities, as indicated by a Gini coefficient of 0.956 [50]. Such uneven distribution is a common issue across eastern China [51].

Globally, many countries’ nature reserves face the challenge of balancing local development with ecological conservation while providing ecological benefits. In some regions of Europe and South America, there is an imbalance in the distribution of public welfare benefits from nature reserves. Nature reserves in Western Europe primarily serve the middle class and high-income groups [52,53], while residents in poorer areas have not fully benefited. Countries like Indonesia still face conflicts between the establishment of nature reserves and the development of other industries, which has reduced the focus on nature reserves [8]. Compared to other regions of the world, China has certain advantages in the distribution of public welfare in its nature reserves. In China’s western regions, especially the Tibetan Plateau, despite challenges such as a weak industrial base, nature reserves not only provide higher ecological benefits but also offer more employment opportunities and income sources for local residents. Nature reserves in these regions effectively promote the development of ecotourism, improving local economic conditions, particularly among low-income groups, thereby enhancing welfare. This context-specific development approach is worth learning from by other countries.

In contrast to other studies, this research introduces the Public Welfare Index, which focuses on the welfare provided by nature reserves from the perspective of the entire population, with particular emphasis on the welfare of low-income groups. This framework posits that public welfare depends on ecological supply and social demand. Ecological supply encompasses factors such as landforms, resource endowment, and ecological quality. Social demand is primarily determined by travel costs, economic base, and population distribution. This is because the benefits derived from the same nature reserve vary for people located in different regions with differing economic circumstances. Nature reserves should enable a greater proportion of low-income people to access these resources at lower costs, thereby maximizing the welfare benefits derived from these reserves.

4.2. Practical Implication

The Chinese government has now issued the ”National Plan for the Integration and Optimization of Nature Reserves,” and China is currently at a critical stage in optimizing the spatial pattern of nature reserves. This study takes a national perspective and provides a reference for the future optimization of nature reserves through a spatial pattern study of public welfare.

The provinces of Tibet, Qinghai, and Sichuan, which have relatively high levels of public welfare, can be developed into nature reserve demonstration zones. Local governments should use the relatively high public welfare of Nagqu, Yushu, Ganzi, Aba, and Gannan to improve local public service capacity on the premise of doing a good job of ecological protection. They should promote local social development through the economic spillover effects of nature reserves and build Dalian, Yueyang, Yiyang, Nanchang, Beihai, and Fangchenggang into regional ecological cities. Natural resource conditions and social development levels at national and regional levels have been considered to ensure the demand for nature reserves in the eastern, central, and western regions of China, as well as the feasibility of tourist flows.

Moreover, after recognizing the relatively high public welfare in the western regions, it is recommended to further increase fiscal investments in nature reserves in these areas, establish special ecological compensation funds, and support ecological protection, construction, and management. Given the relatively weak economic foundation in these regions, targeted support policies should be implemented to promote the dual benefits of economic and ecological enhancement.

For the low public welfare in remote areas, the primary cause is the high transportation costs. In the future, investments in railway technology research and development should be increased to enhance railway transportation capacity and operational speed. However, the reallocation of resources to the western regions may overlook the sociopolitical complexities of these areas. Therefore, when formulating specific policies, it is essential to consider the unique social, political, and cultural contexts of the region. The ethnic diversity and historical background in these regions may lead to variations in policy acceptance and implementation across different areas. Policy makers should refine the resource allocation process by thoroughly understanding the needs and perspectives of various ethnic groups and local governments, ensuring the smooth and effective implementation of policies.

4.3. Limitations and Suggestions for Future Research

This research has limitations, and future studies should address the following issues. First, while constructing the Public Welfare Index of nature reserves, the analysis focuses on ecological supply and social demand, neglecting the evaluation index system for public service functions such as tourism, education, and culture within nature reserves. In the future, scholars can evaluate public welfare from a functional perspective. Additionally, the current research does not account for non-use values (such as cultural and spiritual values), which could be an important aspect of the public welfare of nature reserves. This represents a limitation of the study, and we suggest that future research consider incorporating these non-use values into the welfare assessment. The construction of nature reserves in China is a long-term project. The spatial analysis in this study is based on 100 km fishnets and provincial-level aggregation, which inevitably compromises the granularity of the analysis. This approach may obscure intra-provincial regional inequalities, such as disparities between urban and rural areas. Such imbalances at this level could have a substantial impact on the accurate assessment of public welfare. Therefore, future research should incorporate finer spatial resolutions, potentially employing smaller administrative units, such as county or municipal levels, to more precisely capture intra-regional variations. In the future, China plans to establish 49 national parks, and the development trend of public welfare in China deserves further research.

5. Conclusions

This study constructs a Public Welfare Index for nature reserves based on two perspectives, which are ecological supply and social demand. The index measures the extent to which reserves provide equal opportunities for middle- and low-income populations to enjoy welfare. The spatial pattern analysis of the Public Welfare Index effectively guides the optimization of the spatial layout of nature reserves. The study finds that wetland ecological reserves have the highest public welfare, while marine and coastal reserves have the lowest. Currently, public welfare in China’s nature reserves follows a “high in the west, low in the east” spatial pattern. The clustering of public welfare in China is mainly characterized by positive spatial correlation, but there is a widespread uneven distribution of public welfare across provinces, with this issue being particularly severe in eastern China. In the future, the spatial optimization of nature reserves should take regional characteristics into account to achieve a win–win scenario for both ecological protection and social development. This study provides new ideas and methods for measuring welfare in nature reserves, offering a theoretical foundation and recommendations for optimizing the spatial layout of nature reserves in China.