Study on the ecosystem service value and inter-basin ecological compensation between provinces in China

BY

billion yuan

EC

ecological compensation

ECPS

ecological compensation priority sequence

ESV

ecosystem service value

GLP

Global Land Project

HEC

horizontal ecological compensation

IGBP

International Geosphere-Biosphere Programme

IHDP

International Human Dimension Programme on Global Environmental Change

LUCC

land-use/land-cover change

PEB

payment for ecological benefit

PES

payment for ecological services

SDGs

Sustainable Development Goals

SMB

seven major basins

VEC

vertical ecological compensation

The land served not only as a foundation for natural ecosystem processes but was also utilized by humans for diverse purposes (Hao et al., 2012). Land-use/land-cover change (LUCC) encompassed the alterations in land cover resulting from human activities, including land use and management practices (Meyfroidt et al., 2022), which represented the most immediate evidence of human influence on the earth's surface system (Mooney et al., 2013). During the 1990s, driven by the International Geosphere-Biosphere Programme (IGBP) and International Human Dimension Programme on Global Environmental Change (IHDP), LUCC emerged as a crucial aspect of global environmental change (Howells et al., 2013; Magliocca et al., 2015) and sustainable development (Magliocca et al., 2015). With the intensification of global human activities, the early 21st century saw the launch of the Global Land Project (GLP) by the IGBP and IHDP, highlighting the issues of vulnerability and resilience in global LUCC (Popp et al., 2014; Newbold et al., 2015; Meyfroidt et al., 2022). The impact of global LUCC on biodiversity surpassed the planetary boundaries (Steffen et al., 2015; Newbold et al., 2016). The United Nations Sustainable Development Goals (SDGs) 2030 underscored LUCC's significance in achieving sustainable development (Gao & Bryan, 2017; Nagendra et al., 2018; Pretty et al., 2018). Creutzig (2017) advocated for orderly development, utilization, and land management as a global consensus. In China, rapid economic growth and certain land use policies led to particularly complex LUCC (Galic et al., 2012), especially in construction land (Wu et al., 2013b), resulting in significant ecological and environmental issues (Liu et al., 2014). LUCC affected the structure and function of natural elements through key environmental processes such as energy exchange and water cycling, leading to ecosystem changes (Houghton et al., 1999; Sala et al., 2000). As the primary focus of ecosystem change research (Modernel et al., 2016), accurately understanding the ecological and environmental effects of LUCC was crucial for addressing related problems (Liu et al., 2014).

Ecosystems provide essential material and non-material resources necessary for human survival and development (Costanza et al., 1997). Ecosystem services denoted the benefits humans receive from the various functions of ecosystems (Holdren & Ehrlich, 1974; Costanza et al., 1997) and included both direct and indirect contributions to human well-being (Faber & van Wensem, 2012). Assessing and quantifying these ecosystem services (Kang et al., 2016) enhanced our understanding of their functions and the state of sustainable development (Su et al., 2014). Current evaluations of ecosystem service value (ESV) employed diverse perspectives and methodologies, including direct market methods, alternative market methods, hypothetical market valuation, emergy analysis, dynamic modeling evaluation, and the equivalent factor method (Costanza et al., 1997; Wu et al., 2013a; Luo & Zhang, 2014; Zadehdabagh et al., 2022; Li et al., 2023). The equivalent factor method, noted for its simplicity and broad evaluation scope (Sannigrahi et al., 2019), was widely adopted (Zhao & Su, 2022b) and applied to various ecosystems such as farmland, grassland, forest, wetland, and urban areas (Wang et al., 2019; Ping et al., 2021). However, the equivalence factors proposed by Costanza et al. (1997) were not suitable for China. Consequently, Xie et al. (2001) adapted the equivalent factor method to the Chinese context, establishing a localized ESV evaluation system. Chinese scholars have extensively used this localized method to evaluate ESV across different regions and scales (Luo & Zhang, 2014), becoming a standard approach in ESV assessments (Liu & Yang, 2019; Zhao & Mo, 2022a; Zhao et al., 2023).

Ecological compensation (EC), also termed ‘payment for ecological services (PES)’ or ‘payment for ecological benefit (PEB)’ (Pascual et al., 2014; Grima et al., 2016; Wang et al., 2019), was a crucial economic policy tool aimed at internalizing the external costs associated with river water pollution within watershed ecological protection efforts (Yu et al., 2023). By using financial incentives, EC encouraged the maintenance and preservation of ecosystem services, addressing the externalities of environmental benefits resulting from market failures and promoting social development fairness, ultimately achieving ecological protection and benefit goals (Engel et al., 2008). Research on EC primarily focused on theoretical connotations, spatiotemporal allocation, effective fund allocation, willingness to pay, compensation effect evaluation, biodiversity compensation, fairness, and market mechanisms (Wünscher et al., 2008; Börner et al., 2009). Determining EC standards was essential for quantifying EC, requiring rigorous and scientific methods to evaluate the ESV of regions participating in EC schemes (Costanza et al., 2014). Methods for calculating EC amounts included the willingness to pay method (Eskandari-Damaneh et al., 2020; Ren et al., 2020; Zhu et al., 2023), the ESV method (Sheng et al., 2017; Zhong et al., 2020), the opportunity cost method (Engel et al., 2008; Adhikari et al., 2017; Souza et al., 2021), the ecological footprint method (Yang et al., 2020, 2021b), the value theory method (Sheng et al., 2017), the environmental protection total cost method (Adhikari et al., 2017; Zheng et al., 2019), the water resource value method (Wan et al., 2022), the combination accounting method (Alarcon et al., 2017; Costanza, 2020), the game negotiation method (Yi et al., 2021, 2022), the travel cost method (Mäntymaa et al., 2021), the conditional value method (Jiang et al., 2022), the choice experiment method (Sinclair et al., 2021), the market substitution method (Liu et al., 2021), and the equivalent factor method (Costanza et al., 1997, 2014; Wang et al., 2014; Gao et al., 2021). ESV was a critical indicator reflecting regional economic development and ecological environment quality (Hu et al., 2020) and was pivotal in resolving EC issues between basin regions (Liu et al., 2018; Gao et al., 2021). Calculating EC standards based on the ESV method allowed for a comprehensive valuation of regional ecosystems and was highly recognized in EC research (Dai et al., 2020). This was because (1) ESV assessment provided insights into ecosystem structure and function (Li et al., 2022), (2) changes in ESV were closely linked to socioeconomic development (Zhang et al., 2021), and (3) the method incorporated objective LUCC and was suitable for assessing ecological function value in regional and large-scale areas (Wang et al., 2014). Thus, the ESV effectively addressed basin EC issues (Gao et al., 2021).

In 2016, the ‘Guiding Opinions on Accelerating the Establishment of a Horizontal Ecological Protection Compensation Mechanism for the Upstream and Downstream of Basin’ was issued (Ministry of Finance, Ministry of Ecology and Environment, Development and Reform Commission, and Ministry of Water Resources, 2016). The 14th Five-Year Plan for National Economic and Social Development of the People's Republic of China and the Outline of Long-Range Objectives for 2035 highlighted the need to improve the ecological protection compensation mechanism and implement horizontal EC (HEC) in basins (Chinese Government website, 2021). For the Yangtze River Basin, the Ministry of Finance released the ‘Guiding Opinions on Establishing and Improving a Long-Term Mechanism for Ecological Compensation and Protection in the Yangtze River Economic Belt’ in 2018 (Ministry of Finance, 2018). In 2022, the ‘Guiding Opinions on Promoting the Establishment of the Ecological Protection Compensation Mechanism in the Taihu Lake Basin’ was issued (National Development and Reform Commission, Ministry of Ecology and Environment and Ministry of Water Resources, 2022). Regarding the Yellow River Basin, a pilot plan to support and guide the establishment of a HEC mechanism for the entire basin was introduced in 2020 (Ministry of Finance, Ministry of Ecology and Environment, Ministry of Water Resources, and National Forestry and Grassland Administration, 2020). Additionally, in 2022, the ‘Yellow River Basin Ecological Environment Protection Plan’ was published by the Ministry of Ecology (Ministry of Ecology and Environment, National Development and Reform Commission, Ministry of Natural Resources, and Ministry of Water Resources, 2022), along with the ‘Implementation Rules on Establishing a Horizontal Ecological Compensation Mechanism in the Yellow River Basin within the Province’ (Henan Provincial Department of Finance and Henan Provincial Department of Ecology and Environment, 2022). Therefore, it was imperative to establish EC in seven major basins (SMBs) in China.

Research on LUCC primarily examined various administrative scales, including basins, economic zones, and natural regions (Sun, 2012; Yang et al., 2017b; John et al., 2019). LUCC and ESV influenced and limited one another (Luo et al., 2021). Although studies on ESV have been conducted globally (Costanza et al., 1997; de Groot et al., 2012), national (Li et al., 2016), provincial and city (Han et al., 2016), county (Li et al., 2016; Lu et al., 2017), and township levels (Hu et al., 2015), research focusing on the basin scale was relatively scarce. Basins served as vital centers of human civilization, rich in natural resources, and crucial for functions such as climate regulation and soil protection (Cheng & Li, 2015). This study aims to investigate ecological concerns in different regions of the SMB through the lens of ESV, with the following five objectives: (1) to analyze LUCC in SMB between 1980 and 2020; (2) to assess the changes in ESV in response to LUCC; (3) to evaluate the elasticity of ESV changes related to LUCC; (4) to identify inter-basin EC schemes among provinces; and (5) to quantify the amount of HEC and vertical EC (VEC) in the SMB.

To assess and quantify the ecological impact of various ecosystem types, this study used national average data on the percentage and net profit per unit area for rice, wheat, and corn from 1990 to 2020. This data led to a D value of 1,404.05 yuan/hm². Using the ESV equivalents per unit area for Chinese ecosystems as proposed by Xie et al. (2008), we calculated the value equivalent for 1 hm² of each ecosystem (Table 1).

In the four decades, the elasticity relative to LUCC in SMB was 0.62, 0.23, 0.23, and 0.29, respectively, indicating that 1% land area conversion led to an average change in ecosystem value of 0.629, 0.23, 0.23, and 0.29% (Table 2). Among the seven watersheds, HURB had the highest elasticity coefficient, with a mean of 0.45 in the past 40 years. YTRB had the lowest elasticity coefficient, with a value of 0.22. Between 1980 and 2020, the elasticity coefficients of SHRB and PRB increased while other watersheds decreased. Although the elasticity coefficient fluctuates, the response of ecosystem services to LUCC was not significant.

The total VEC for SMB in 2020 was 357.5 BY (Table 3). SHRB had the highest VEC at 134.13 BY (37.52%). HURB had the lowest VEC at 0.33%. In the HRB, Hebei had the largest VEC at 2.09 BY, accounting for 41.76%. In the HURB, Henan had the largest VEC at 0.34 BY (28.85%). In the YRB, Qinghai had the largest VEC at 32.31 BY (48.55%). In the LRB, Inner Mongolia had the largest VEC at 14.83 BY (72.08%). In the SHRB, Inner Mongolia had the largest VEC at 67.69 BY (50.47%). In the YTRB, Qinghai had the largest VEC at 30.86 BY (29.64%). In the PRB, Guangxi had the largest VEC at 15.73 BY (60.66%). Among the 29 provinces, IM had the highest VEC amount at 97.13 BY, accounting for 27.17%. SH, BJ, and TJ had the smallest VEC amount, accounting for less than 0.01%.

Among the 29 provinces/cities, HLJ undertook the highest HEC amount of 31.09 BY, followed by JS and AH with 13.4 and 9.79 BY, respectively. IM received the highest compensation amount of 31.94 BY, followed by JL and SD, with 13.56 and 7.28 BY, respectively. IM had the highest net HEC amount of 31.18 BY, followed by JL and SD, with 13.52 and 6.75 BY, respectively.

LUCC was regarded as a primary driver of global change and a concentrated reflection of human activities on the land surface and environment (Mooney et al., 2013). LUCC influenced not only land productivity but also sustainable development (Mottet et al., 2006) and the global environment (Foley et al., 2005), as well as social and economic changes (Borrelli et al., 2017). Human activities were a significant cause of changes in the earth's ecosystem, with LUCC evolving into a global phenomenon (Tao et al., 2013). The integration of natural and human disciplines in LUCC research became a focal point in global environmental change studies (Yang et al., 2017a; Deng et al., 2018). Changes in land use, such as the conversion of agricultural land to forest land and urbanization, significantly impacted the global ecosystem (Rudel et al., 2005). Analyzing the driving forces behind LUCC was essential. Zhou et al. (2021) observed that from 1995 to 2015, China's farmland and urban areas increased by 1.88 × 10⁶ and 3.41 × 10⁶ km², respectively, with over 80% of urban expansion occurring at the expense of farmland. Between 2010 and 2015, China's built-up areas increased by 24.6 × 10³ km², while cultivated land decreased by 4.9 × 10³ km², and the total area of forest and grassland decreased by 16.4 × 10³ km² (Ning et al., 2018). Kuang et al. (2022) noted that from 2015 to 2020, the total LUCC area in China was 4.50 × 10⁴ km², with a net increase of 2 × 10⁴ km² in urban areas and 1.14 × 10³ km² in water areas and a net decrease of 6.51 × 10³, 2.53 × 10³, and 6.48 × 10³ km² in farmland, forest, and grassland, respectively. These findings align with this study's results, showing an increase in water and urban areas by 1.22 and 72.40%, respectively (Figure 3). Rivers, as areas with high human activity, experienced more severe LUCC (Asnake et al., 2021). LUCC was the most direct and objective reflection of human activities on natural ecology. China's land policy evolution has transitioned from strict control of farmland utilization quotas to intensive land use, focusing on land use quality and comprehensive ecosystem protection (Wang et al., 2018). Economic growth, rural migration to cities, land-use management policy changes, ecological protection, restoration projects (such as the Grain for Green Project), and climate change have all driven LUCC in China. However, the main driving forces varied by land use type and geographical location (Zhou et al., 2021).

Natural and socioeconomic factors influenced ESV. Natural factors included climate, elevation, terrain, and precipitation. Climate affected ecosystem services by regulating water and thermal conditions (Braun et al., 2019). Elevation influenced human activities and vegetation distribution, while terrain impacted ecosystem service functions through factors like water storage capacity and light intensity (Wang et al., 2021). Precipitation changes affected soil conservation and hydrological cycling. Socioeconomic factors include land use, population, and economy (Aziz, 2023). From 1990 to 2010, China's terrestrial ESV experienced a significant decline due to ecological protection policies, land development strategies, economic growth, rapid urbanization, and industrialization (Li et al., 2016). China's total ESV fluctuated downward from $3,265.3 billion in 1992 to $3,253.29 billion in 2018, with an annual decrease of $550 million. Human-driven factors had both positive and negative impacts on provincial ecosystems, with per capita GDP, road length, number of researchers, and crop planting area positively correlated with ESV growth, while remaining energy, population, infrastructure, and ecological restoration variables were negatively correlated (Yang et al., 2021a). From 1990 to 2020, the ESV of rivers, lakes, reservoirs, ponds, and swamps in China showed an overall upward trend, with reservoirs and ponds experiencing the most significant growth at 58% (Xu et al., 2023). This study found that the total ESV in SMB decreased from 11,522 BY in 1980 to 11,375 BY in 2020 (Figure 4), consistent with previous studies. Evaluating the ESV of basins was crucial for global ecosystem service evaluation, aiding in understanding ecological evolution and development and helping policymakers in resource allocation and ecosystem management.

In the YRB, Shandong and Henan, as well as Sichuan and Gansu, have established effective EC mechanisms similar to those in Hubei, Hunan, Jiangsu, and Anhui in the YTRB. Based on existing research, the following recommendations are proposed to facilitate EC: (1) Enhance the cross-provincial watershed EC guarantee mechanism, including financial guarantees, public participation, and third-party monitoring and evaluation. (2) Develop a big data platform for ecological environment management and a comprehensive decision-making platform using artificial intelligence and big data technologies to optimize information sharing and decision-making in water environment governance. (3) Create a horizontal transfer payment pathway for EC within basins, clarifying involved parties, compensation standards, and methods. (4) Foster communication and cooperation to build consensus and innovate organizational structures, establishing an authoritative cross-basin coordination agency. (5) Improve inter-provincial cooperation mechanisms, including joint environmental monitoring and unified river basin management systems. (6) Strengthen the legal framework for cross-regional water pollution control through comprehensive legislation.

In 1980, the SMB's largest land area was forest (35.38%), followed by farmland (31.27%) and grassland (23.85%), with other areas comprising 9.51%. By 2020, water and urban areas increased by 1.22 and 72.40%, respectively, while farmland, forest, and desert areas decreased by 1.33, 3.16, and 11.16%. The total ESV of SMB was 11,522 BY in 1980 and 11,375 BY in 2020, a 1.27% decrease over 40 years. 1% land area conversion led to an average ESV change of 0.629, 0.23, 0.23, and 0.29%, respectively. The ECPS was higher in the southwest and northeast regions. The total VEC for SMB in 2020 was 357.5 BY, with the SHRB having the highest VEC at 134.13 BY (37.52%), followed by YTRB and PRB at 104.13 BY (29.13%) and 66.54 BY (18.61%). The total HEC for SMB was 103.78 BY, with the SHRB receiving the most HEC at 31.12 BY (29.99%), followed by YTRB and PRB at 17.91 and 15.08 BY. To ensure effective EC implementation, suggestions include improving the EC guarantee mechanism, building data platforms, establishing transfer payment pathways, fostering communication, enhancing cooperation mechanisms, and strengthening legal frameworks.

The work is supported by the National Natural Science Foundation of China (52309092), the Yellow River Water Science Research Joint Fund (U2243214), the Yellow River Basin Ecological Protection and High-quality Development Joint Study (Phase I) (2022-YRUC-01-0202), the Science and Technology Development Fund of the Yellow River Institute of Hydraulic Research (202112, 202310), the Basic R&D Special Fund of Central Government for Non-profit Research Institutes (HKY-JBYW-2024-08, HKY-JBYW-2021-05), and the Major Science and Technology Project of Henan Province (231100320100, 232102320112).

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.