Spatial–Temporal Patterns and the Driving Mechanism for the Gross Ecosystem Product of Wetlands in the Middle Reaches of the Yellow River

Abstract

Wetlands are crucial for sustainable development, and the evaluation of their GEP is a key focus for governments and scientists. This study created a dynamic accounting model for wetland GEP and assessed the GEP of 39 wetlands in the middle reaches of the Yellow River in Ningxia province. The results indicate that Ningxia province’s wetlands have an average annual GEP of CNY 5.24 billion. Haba wetland contributes the most at 0.52, while Qingtongxia, Sha, and Tenggeli wetlands follow with 0.12, 0.04, and 0.03, respectively. Climate regulation is the most valuable function at 38.24%, with species conservation and scientific research/tourism at 24.93% and 15.11%, respectively. Ningxia’s northern wetlands are vast and shaped by the Yellow River, while the smaller, seasonal southern wetlands are more affected by rainfall and mountain groundwater. Southern wetlands show a strong correlation between GEP and precipitation (0.82), whereas northern wetlands have a moderate correlation between GEP and evapotranspiration (0.52). The effective conservation and management of these wetlands require consideration of their locations and weather patterns, along with customized strategies. To maintain the stability of wetland habitats and provide a suitable environment for various species, it is essential to preserve wetlands within a certain size range. Our study found a strong correlation of 0.85 between the wetland area and the GEP value, indicating that the size of wetlands is a key factor in conserving their GEP. The results provide accurate insights for creating a wetland ecological benefit compensation mechanism.

1. Introduction

Gross ecosystem product (GEP) represents the cumulative value of final ecosystem goods and services provided annually to inhabitants within a specified region, be it a country, province, or county. GEP accounting holds significance in elucidating and advancing the shift from “clear water and green mountains” to “mountains of gold and silver” in China [1]. The valuation of GEP is fundamentally based on the evaluation of ecosystem service values [2]. Ecosystem services encompass the life-sustaining products and services acquired directly or indirectly via ecosystem structures, processes, and functions [3]. The evaluation of the ecosystem service value encompasses the standardized measurement and monetary valuation of the various functions provided by ecosystems. Notably, Costanza et al. (1997) pioneered a comprehensive estimation of global ecosystem service value, publishing their findings in Nature [4]. Subsequent to this, numerous studies have explored the evaluation of ecosystem services, with noteworthy examples including the expansive evaluation of the global ecosystem service value by Costanza et al. (1997) [4] and the extensive “Ecosystems and Human Welfare” study conducted by the Millennium Ecosystem Assessment Working Group [5]. Within China, scholars have appraised the country’s ecosystem service value, subsequently introducing the ecosystem service equivalent factor table in 2003 and later updating it in 2008 [6,7], which has gained wide-scale adoption across varying scopes within China.

In total, more than 5000 studies on ecosystem service valuation have been published in the past 20 years, indicating a boom of research interest on this topic [8]. As a comprehensive monetization indicator, GEP reflects the rise in new integrated studies based on ecosystem service assessment and, as a result, GEP studies on different ecosystems are rapidly emerging. In China, the central and local governments at all levels attach great importance to GEP accounting research and practical application and many provinces, cities, and counties have carried out GEP accounting research and practical applications in different ecological geographical regions of the country in an attempt to provide a theoretical basis for ecological protection effectiveness assessment, government performance assessment, and ecological compensation standards [1]. Some scholars have applied the GEP theory to evaluate the effectiveness of regional ecological restoration [9,10] or to assess the regional ecological compensation mechanism [11]. In addition, some studies have focused on integrating GEP into the ecological environment management system of government departments [12]. Furthermore, a number of studies have focused on improving the level of GEP accounting in terms of methodology and modeling; however, at the basic logic level, most research still relies on the traditional method of ecosystem service value assessment [13]. Internationally, the United Nations Statistical Commission has incorporated GEP into its international standard “System of Environmental-Economic Accounting-Ecosystem Accounting” (SEEA-EA) [1]. Sweden, Belize, Costa Rica, Colombia, and other countries have begun to learn from China’s experience in assessment and accounting work. Existing studies and practices have shown that GEP can be used to improve the evaluation system of social–economic–natural complex ecosystems and promote sustainable development policy innovation through measuring the value created by natural ecosystems.

Being a crucial area for ecological conservation, wetland ecosystems provide vital functions such as flood control and storage, water purification, climate regulation, water conservation, and species preservation [14]. These functions play a significant role in maintaining ecological equilibrium and fostering sustainable and robust economic development. Nonetheless, wetland ecosystems are exceedingly delicate, being susceptible to change, degradation, and even extinction. As human activities intensify, conflicts between wetland preservation and exploitation become increasingly apparent [15]. The precise scientific computation of wetland GEP alongside its temporal and spatial driving mechanisms holds benefits not only for the safeguarding and management of wetland ecosystems but also for advancing sustainable development across the economy, society, and environment. Assessing wetland GEP has garnered focused attention from both governmental bodies and the scientific community. Various studies have already explored wetland GEP assessment, with some concentrating on categorizing and valuing specific functions of wetland ecosystem services [16,17,18,19], while others have comprehensively investigated the value of wetlands within different regions of China [20]. Regardless of the approach taken, these evaluations encompass essential wetland ecological functions such as climate regulation, flood control and storage, and species conservation. However, distinct researchers possess individual subjectivity in their comprehension of wetland ecosystem service functions, leading to the adoption of diverse assessment methodologies and data sources. Consequently, the calculated ecological service value per unit area in different studies exhibits significant disparities [21]. Therefore, the need for comprehensive technical guidelines for the statistical accounting of wetland GEP has become pressing, with the goal of providing a consistent framework from top to bottom.

In September 2020, the Ministry of Ecology and Environment of the People’s Republic of China established the Technical Guide for Gross Terrestrial Ecosystem Product accounting (referred to as the Guide hereafter) [22]. The Guide delineates the index system, accounting methods, data sources, and key parameters which are essential for GEP accounting. It has effectively enhanced the scientific rigor, standardization, and practicality of calculating both the physical quantity and the value of land GEP [1]. Building upon this Guide, numerous regional GEP assessments have been conducted [23,24], serving as foundational support for eco-compensation initiatives. The Guide emphasizes that GEP accounting is a dynamic process and should be performed annually [1]. Nonetheless, due to the brief temporal scope of existing studies and the absence of analyses concerning spatial–temporal evaluation and driving mechanisms, static assessment outcomes are likely to diverge from the recommendations for wetland construction and preservation. This study aims to develop a comprehensive general dynamic wetland GEP accounting model. It merges geometeorological factors with spatial and temporal variations into the conventional GEP accounting framework. The wetlands in Ningxia province stand as a prominent landmark in the central section of the Yellow River. Its geographical positioning, climatic factors, and ecological surroundings are all singularly distinctive. It serves as a vital juncture and breeding haven for numerous migratory birds on their migratory routes. The objectives of this study are to analyze the spatiotemporal variation in wetland GEP in Ningxia and reveal the driving factors behind its spatiotemporal evolution. The results are considered to be of great significance for maintaining ecological security, implementing ecological compensation measures, and maintaining ecological balance in the Yellow River Basin.

2. Methods and Case Studies

2.1. General Dynamic Wetland GEP Accounting Model

The general dynamic wetland GEP accounting model (Figure 1) was developed by considering wetland characteristics, geometeorological conditions, data availability, the guidance provided in the Guide [22], and the pertinent literature. Specifically, the model’s input factors encompass both fixed values and dynamic factors. Once these factors are fed into the model, it becomes possible to trace the temporal and spatial evolution of a wetland’s GEP, as well as to discern the interplay between GEP and its determinants. Consequently, this facilitates a quantitative analysis of the forces driving changes in GEP.

Calculation formulas: Through field investigations and references to the Guide [22], Ningxia wetland covers eight ecosystem service functions, namely water purification, water conservation, climate regulation, flood control and storage, species conservation, soil conservation, carbon fixation, and oxygen release, as well as scientific research and tourism. The total GEP is the sum of these eight ecological service function values. The calculation formulas and their corresponding parameters are illustrated as follows:

$${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{D}\mathrm{y}\mathrm{n}\mathrm{a}\mathrm{m}\mathrm{i}\mathrm{c}}={\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{W}\mathrm{P}}+{\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{W}\mathrm{C}}+{\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{C}\mathrm{R}}+{\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{F}\mathrm{S}}{+\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{M}\mathrm{B}}{+\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{S}\mathrm{C}}+{\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{C}\mathrm{O}}+{\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{S}\mathrm{T}}$$

(1)

where ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{D}\mathrm{y}\mathrm{n}\mathrm{a}\mathrm{m}\mathrm{i}\mathrm{c}}$ is the dynamic GEP for a wetland, in CNY; ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{W}\mathrm{P}}$, ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{W}\mathrm{C}}$, ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{C}\mathrm{R}}$, ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{F}\mathrm{S}}$, ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{M}\mathrm{B}}$, ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{S}\mathrm{C}}$, ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{C}\mathrm{O}}$, and ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{S}\mathrm{T}}$ refer to the ecosystem service function values for water purification, water conservation, climate regulation, flood control and storage, species conservation, soil conservation, carbon fixation, oxygen release, and scientific research and tourism, respectively, in CNY.

(1) Water purification refers to the function of a wetland to reduce the concentration of water pollutants and purify the water environment through physical and biochemical processes, such as adsorption, degradation, and the biological absorption of water pollutants. The calculation method for ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{W}\mathrm{P}}$ comes from reference [25].

$${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{W}\mathrm{P}}=3.6\times \mathrm{A}\times {\mathrm{V}}_{\mathrm{W}\mathrm{P}}$$

(2)

Here, A is the wetland area, m²; ${\mathrm{V}}_{\mathrm{W}\mathrm{P}}$ is the water purification value equivalent per 1 standard unit, CNY/m².

(2) Water conservation refers to the function of a wetland to intercept and store precipitation, enhance soil infiltration, conserve soil water, replenish groundwater, regulate river flow, and increase the amount of available water resources through its structure and processes. The calculation method for ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{W}\mathrm{C}}$ comes from the Guide [22].

$${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{W}\mathrm{C}}=\mathrm{A}(0.85\mathrm{P}-\mathrm{E}\mathrm{T})\times {\mathrm{V}}_{\mathrm{W}\mathrm{C}}$$

(3)

Here, A is the wetland area, m²; $\mathrm{E}\mathrm{T}$ is the actual evapotranspiration, m; and ${\mathrm{V}}_{\mathrm{W}\mathrm{C}}$ is the market price for water trading, CNY/m³.

(3) Climate regulation refers to the function of a wetland to absorb energy, reduce temperature, and increase humidity through vegetation transpiration and water surface evaporation. The calculation method for ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{C}\mathrm{R}}$ comes from the Guide [22].

$${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{C}\mathrm{R}}=\mathrm{A}\times {\mathrm{E}\mathrm{T}}_{45}(\mathrm{V}\mathrm{L}+\mathrm{P}\mathrm{C}){\mathrm{V}}_{\mathrm{C}\mathrm{R}}$$

(4)

Here, A is the wetland area, m²; ${\mathrm{E}\mathrm{T}}_{45}$ is the actual evapotranspiration with humidity below 45%, m; $\mathrm{V}\mathrm{L}$ is the latent heat of vaporization (i.e., the heat required for the evapotranspiration of 1 m³ of water), 675 kWh/m³ [26]; $\mathrm{P}\mathrm{C}$ is the power consumed by a humidifier to convert 1 m³ of water into steam, 750 kWh/m³ [26]; and ${\mathrm{V}}_{\mathrm{C}\mathrm{R}}$ is the price of electricity, CNY/kWh.

(4) Flood control and storage refers to the function of a wetland to reduce flood risk through regulating storm runoff and reducing flood peak flows. The calculation method for ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{F}\mathrm{S}}$ comes from the Guide and references [27,28].

$${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{F}\mathrm{S}}=\mathrm{A}({\mathrm{U}}_{\mathrm{F}\mathrm{S}}+275\mathrm{P})\times {\mathrm{V}}_{\mathrm{F}\mathrm{S}}$$

(5)

Here, A is the wetland area, m²; ${\mathrm{U}}_{\mathrm{F}\mathrm{S}}$ is the amount of flood water that can be controlled and stored per unit area of wetland annually, 0.81 m³/m² [29]; ${\mathrm{V}}_{\mathrm{F}\mathrm{S}}$ is the engineering and maintenance cost of reservoir per unit storage capacity, CNY/m³; and $\mathrm{P}$ is the precipitation, m.

(5) Species conservation refers to the role and value of wetlands in providing survival and reproduction places for rare and endangered species. The calculation method for ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{M}\mathrm{B}}$ comes from the Guide [22].

$${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{M}\mathrm{B}}=\mathrm{A}[1+0.1({\sum }_{j=1}^x{\mathrm{E}}_j+{\sum }_{k=1}^y{\mathrm{B}}_k\left)\right]\times {\mathrm{V}}_{\mathrm{M}\mathrm{B}}$$

(6)

Here, A is the wetland area, m²; ${\mathrm{E}}_j$ is the endangered score for species j, dimensionless; ${\mathrm{B}}_k$ is the endemic value of species k, dimensionless; ${\mathrm{V}}_{\mathrm{M}\mathrm{B}}$ is the species conservation value per unit area, CNY/m²; and x and y are the numbers of endangered index species and endemic index species, respectively.

(6) Soil conservation refers to the function of a wetland to protect soil, reduce the erosion capacity of rain, and reduce soil loss through its structure and process. The calculation method for ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{S}\mathrm{C}}$ comes from the Guide [22] and reference [30].

$${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{S}\mathrm{C}}=\mathrm{A}\times \mathrm{Q}[{\sum }_{i=1}^n({\mathrm{C}}_i\times {\mathrm{V}}_i)+{\displaystyle \frac{\mathsf{\gamma }}{\mathsf{\rho }}}\times {\mathrm{V}}_{\mathrm{F}\mathrm{S}}]$$

(7)

Here, A is the wetland area, m²; Q is the soil retention per unit area, kg/m²; ${\mathrm{C}}_i$ is the average content of organic element i in a wetland, kg/kg; ${\mathrm{V}}_i$ is the price of converting organic element i for use as a local fertilizer, CNY/kg; $\mathsf{\gamma }$ is the sediment accumulation coefficient, 0.24 [31]; $\mathsf{\rho }$ is the soil bulk density, 1250 kg/m³; ${\mathrm{V}}_{\mathrm{F}\mathrm{S}}$ is the engineering and maintenance cost of a reservoir per unit storage capacity, CNY/m³; and n is the number of organic elements.

(7) Carbon fixation refers to the function of a wetland to absorb carbon dioxide to synthesize organic matter, fix carbon in plants and soil, and reduce the concentration of carbon dioxide in the atmosphere. Oxygen release refers to the function of a wetland releasing oxygen through photosynthesis to maintain the stability of the atmospheric oxygen concentration. The calculation method for ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{C}\mathrm{O}}$ comes from the Guide [22].

$${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{C}\mathrm{O}}=\mathrm{A}\times \mathrm{V}(3.67{\mathrm{V}}_{{\mathrm{C}\mathrm{O}}_2}+2.67{\mathrm{V}}_{{\mathrm{O}}_2})$$

(8)

Here, A is the wetland area, m²; $\mathrm{V}$ is the carbon sequestration rate of a wetland, where the values for the lakes and wetlands in the Eastern plain, Mongolia New Plateau, Yunnan–Guizhou Plateau, Qinghai–Tibet Plateau, Northeast Plain, and the mountain areas of China are 0.05667, 0.03026, 0.02008, 0.01257, and 0.00449 kg/m², respectively [22]; ${\mathrm{V}}_{{\mathrm{C}\mathrm{O}}_2}$ is the carbon trading price, CNY/kg; and ${\mathrm{V}}_{{\mathrm{O}}_2}$ is the industrial oxygen production price, CNY/kg.

(8) Scientific research value refers to the value of a wetland for human scientific research, while leisure tourism refers to the non-material benefits that human beings receive from wetlands. The calculation method for ${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{S}\mathrm{T}}$ comes from references [6,32].

$${\mathrm{G}\mathrm{E}\mathrm{P}}_{\mathrm{S}\mathrm{T}}=({\mathrm{U}}_{\mathrm{S}}+{\mathrm{U}}_{\mathrm{T}})\mathrm{A}$$

(9)

Here, A is the wetland area, m²; ${\mathrm{U}}_{\mathrm{S}}$ is the esthetic landscape value of a wetland per unit area, 0.210628 CNY/m² [6]; and ${\mathrm{U}}_{\mathrm{T}}$ is the scientific research value of a wetland per unit area, 0.28978 CNY/m² [32].

2.2. Study Area

Ningxia province stands as the sole province in China where the entirety of its territory falls within the Yellow River basin. The region benefits from the life-giving waters of the Yellow River, which has led to the development of a diverse array of wetland resources, each with its own unique characteristics. At present, Ningxia province has 39 wetlands with an area of 158,200 hectares. According to different geographical and meteorological factors, these wetlands are distributed in three different areas (

Table 1. Zoning and characteristics of wetlands in Ningxia province (data sourced from the third National Land Survey, supplied by the Forestry and Grassland Bureau of the Ningxia province).

Region	District	Meteorological Characteristics	Total Wetlands Area (ha)
I	Shizuishan and Yinchuan	Located in the arid region of northern Ningxia province, the wetlands here constitute a typical arid inland ecosystem. They provide vital resting, roosting, and feeding grounds for rare and endangered species such as black storks, white-tailed sea eagles, spotted pelicans, bustards, and many migratory birds. The average annual precipitation in the region is about 183 mm, while evaporation is about 1987 mm.	29,828
II	Wuzhong, Zhongwei and Yinchuan	Located in the semi-arid region of the middle temperate zone, where rainfall is sparse and evaporation rates are extremely high, resulting in a relative scarcity of water resources. Wetland ecosystems consist primarily of riverine wetlands that provide important refuges, breeding grounds, and feeding areas for rare, endangered, and vulnerable species, including falcons, black storks, and golden eagles. The average annual rainfall and evaporation in the region are about 254 mm and 2015 mm, respectively.	124,093
III	Guyuan	Located in the southern temperate sub-humid region. The climate is notably temperate, with a relatively high level of rainfall and excellent vegetation coverage, contributing to a superior ecological environment. The wetlands here serve as critical habitats for rare, endangered species and migratory birds. On average, the annual rainfall reaches approximately 507 mm, while evaporation totals around 1360 mm.	4286

, Figure 2). A wetland conservation network has been established, primarily comprising wetland nature reserves and wetland parks, complemented by wetlands of varying significance at all levels. Wetlands are treasured in Ningxia province, offering vital habitats for a multitude of wildlife and flora. An increasing number of avian species in Ningxia province have taken to utilizing these wetlands as stopover sites, roosting grounds, and breeding habitats, resulting in a surge in both the diversity and population of wetland birds. Over the past few years, we have consistently observed 12 recently documented bird species, including the relict gull, Pallas’s fish eagle, Oriental white stork, and the Dalmatian pelican, within the wetlands bordering the Yellow River. For two consecutive years, the world’s critically endangered species have been monitored in these areas. The populations of first-class national protected animals, such as the relict gull, great bustard, black stork, and white-tailed eagle, have been increasing annually. The number of common cranes, which reside and stay along the Yellow River during winter and spring, has reached nearly 10,000. The whooper swan and cygnet, which are second-grade state-protected animals, reside in Ningxia province for more than a month, and their population is also growing annually. For the northwest inland part of Ningxia province, the wetlands have significant roles in areas such as flood control and storage, water conservation, and climate regulation. Wetlands enhance the living environment of citizens. At present, wetlands such as Sand Lake, Mingcuihu, Qingtongxia, and Jinsha Bay have become popular destinations for ecotourism and nature experiences, achieving a win-win situation for both high-quality economic development and high-level wetland protection.

2.3. Data Sources and Processing

2.3.1. Biomass Data

Biomass data are variable resources which are obtained through field research, government reports, the literature reviews, and so on. The driving forces of biomass factors are mainly wetland protection measures. As the implementation of policies takes a certain period of time to produce positive feedback, the biomass factor typically has low variability. The biomass data for wetland areas (Supplementary Information Table S1), as well as information regarding endangered and endemic species, were sourced from the Forestry and Grassland Bureau of Ningxia province. Soil conservation data were compiled through literature reviews [30]. The contents of organic elements within the wetlands were derived from departmental research and literature reviews [33]. It is worth noting that we used detailed research and interviews to obtain valuable first-hand data on biomass. However, due to the relative stability of statistical information during the study period, the data we collected mainly revealed the trend in spatial change and could not fully reflect the dynamic change between years.

2.3.2. Monetary Value

Monetary value refers to the alternative monetary value used to calculate different types of ecological services, which is obtained through policy documents or literature reviews. Being affected by the level of economic development and technical level, these factors are generally variable. The equivalent unit value for water purification was determined through literature reviews [6,7,25]. Market prices for water trading and local electricity prices were sourced from documents issued by the Development and Reform Commission of Ningxia province. The cost of engineering and maintenance per unit storage capacity of the reservoir was calculated based on literature reviews [28]. Prices for organic elements in fertilizers were gathered from investigations conducted by the Agriculture and Rural Affairs Department of Ningxia province. Carbon trading prices were sourced from the China Carbon Trading Platform, while industrial oxygen prices were derived from literature reviews [34]. It is crucial to recognize that not all indicators experience annual fluctuations. For instance, market prices for water trading and local electricity prices typically remain relatively stable for several years. Nonetheless, our goal is to access real-time and dynamic factors. However, the data or documentation currently supplied by the department are often static, presenting a challenge for the annual update of these factors (Supplementary Information Table S2).

2.3.3. Meteorological Data

Meteorological factors refer to the indicators that affect the spatial–temporal changes in wetland GEP, which have strong variability. Meteorological data, including precipitation, evapotranspiration, and humidity for the 12 meteorological stations in Ningxia province over the period 1999–2019, were obtained from the China Meteorological Administration platform (http://www.cma.gov.cn/, accessed on 13 November 2024). These values exhibit evident spatiotemporal variation.

2.3.4. Data Processing

Based on the ArcGIS10.2 platform, the Thiessen polygon interpolation method and geostatistical analysis method were used to allocate meteorological data with spatial differences to corresponding wetlands (Supplementary Information Figure S1). The meteorological conditions of each wetland are affected by its geographical location. For example, the meteorological data of the Haba wetland were determined by Region 6, while the meteorological data of the Qingtongxia wetland were determined by Regions 5 and 11 (Supplementary Information Table S2).

3. Results and Discussion

3.1. Spatial and Temporal Evolution of Wetland GEP

3.1.1. GEP Composition of Different Wetlands

The total GEP and its proportion across various wetlands in Ningxia province are illustrated in Figure 3. The annual average GEP for Ningxia province amounts to CNY 5.24 billion. Influenced by meteorological conditions, the GEP of Ningxia province’s wetlands varies slightly from year to year. The peak GEP value reached CNY 5.66 billion in 2013, while the trough was CNY 4.87 billion in 2019. These disparities in GEP are attributed to the differences in wetland areas, geographical locations, and meteorological conditions. Notably, the Haba wetland exhibited the highest average GEP proportion at 0.52, followed by Qingtongxia, Sha, and Tenggeli, with average proportions of 0.12, 0.04, and 0.03, respectively. The remaining 31 wetlands collectively had an average GEP ratio of 0.2.

Figure 4 illustrates the area and mean GEP values across various wetlands for different regions. Ningxia province’s distinctive geographical location and topographical characteristics result in its north–south elongated shape. The region’s geographical structure is singular, contributing to the varied distribution of its wetlands. These variations are evident not only in the size and shape of the wetlands but also in the climatic zones and precipitation patterns they encompass. Specifically, the wetlands in Region I are extensively spread and significantly shaped by the Yellow River system. Although Region II has fewer wetlands than Region I, its total wetland area is larger, comprising 78% of Ningxia province’s entire wetland area. Major wetlands such as Haba, Qingtongxia, and Tengger are situated within this region. Conversely, Region III’s wetland area is smaller and predominantly seasonal, rendering its ecological health more vulnerable to fluctuations in precipitation and groundwater replenishment from the surrounding mountainous regions. The GEP of wetlands in each region correlates with the size of their area; yet, it exhibits distinct characteristics influenced by meteorological conditions. For instance, Qingshuihu and Yuehai in Region I share a similar GEP, but Qingshuihu’s area is only 48.06% of Yuehai’s. Similarly, in Region II, Taiyanshan and Tengri have a comparable GEP, with Taiyanshan’s area being 47.58% of Tengri’s. In Region III, the wetland GEP is more evidently impacted by climatic drivers, thus presenting a more complex set of characteristics.

3.1.2. Variation Trend and Composition of GEP in Wetland

The trend in and composition of wetland GEP in Ningxia province from 1999 to 2019 are depicted in Figure 5. Wetlands possess a robust capacity for climate regulation, primarily due to their significant heat storage and vaporization capabilities, which effectively lower ambient temperatures and increase air humidity. On average, the value of their climate regulation function is the highest, constituting 38.24% of the total wetland GEP. During periods of hot weather, wetlands release substantial quantities of water vapor via evaporation and transpiration, thereby lowering the temperature of the surrounding area and mitigating the heat island effect. In 2005, Ningxia province experienced a severe drought, with an average rainfall that was just 56% of the norm. Against this backdrop, the value of the climate regulation function peaked, estimated at CNY 2.35 billion. In contrast, the climate regulation value in 2019—a year with abundant rainfall—was a mere 53.23% of that in 2005.

The second most significant value is the species conservation function, which constitutes 24.93% of the total wetland GEP. The wetland ecosystems of Ningxia province are crucial in preserving biodiversity and conserving species. These areas are not merely natural treasures but also serve as habitats for a multitude of flora and fauna. The presence of wetlands offers a fitting habitat for numerous rare and endangered species, thereby fulfilling an indispensable role in the preservation of biodiversity. Additionally, Ningxia province’s wetlands serve as crucial resting spots for migratory waterfowl and other avian species. During spring and autumn, thousands of these birds pause here to replenish their energy reserves before continuing on their arduous journeys. The abundant food resources and secure habitats within the wetlands ensure the successful completion of these migrations, a development of considerable importance for the global conservation of migratory birds. The contribution of scientific research and tourism to Ningxia province’s wetland GEP stands at 15.11%, underscoring their significant role in the region’s ecological profile.

The wetland resources in Ningxia province have been fully developed and utilized, yielding impressive outcomes in the tourism sector and demonstrating significant potential within the scientific research domain. Through strategic planning and scientific management, wetland tourism has successfully drawn in a substantial influx of visitors, thereby propelling the growth of the local economy. The combined scientific research and tourism value constitutes 15.11% of the total wetland GEP. To effectively rejuvenate and safeguard the wetland ecosystem in Ningxia province, it is imperative to allocate a suitable volume of water resources from the Yellow River to compensate for the water depletion in the wetland resulting from natural evaporation, human activities, and other contributing factors. However, the significance of water conservation has often been overlooked in the literature. The value of flood control and water storage is also considerably influenced by meteorological conditions, exhibiting considerable variability. For instance, in 2008, Ningxia province experienced an average precipitation of 423 mm, which resulted in a flood control and water storage value of merely CNY 20 million. However, by 2014, the average precipitation in Ningxia province surged notably to 661 mm and, correspondingly, the flood control and water storage value of the wetlands also escalated significantly to CNY 320 million. Contrasting the data from these two years, it becomes evident that the flood control and water storage value in 2008 was a mere 7.19% of that in 2014.

3.2. Driving Force for GEP Evolution

Natural elements such as temperature, light, and precipitation are primary determinants of wetland formation, subsequently influencing the wetland ecosystem’s function and its GEP level. Human activities alter land uses and modify the fundamental functions of ecosystems, thereby impacting the structure and aggregate value of the wetland GEP. Consequently, both natural and anthropogenic factors are crucial drivers of changes in wetland GEP.

3.2.1. Natural Influence

Wetlands rely on a variety of natural conditions, encompassing hydrological and climatic factors. For instance, the volume of precipitation plays a pivotal role in maintaining surface water reserves which, in turn, influences groundwater replenishment and the overall quality of the wetland’s aquatic environment. This investigation elucidates the effects of precipitation and evapotranspiration on the GEP of various wetlands, as depicted in Figure 6. In the northern regions, the mountainous terrain contrasts sharply with the southern wetlands. The significant geographical and meteorological disparities across these wetlands result in varying factors influencing their ecological service functions. The Wolong wetland, situated in the southern part of Ningxia province, exhibits a strong positive correlation between its GEP and precipitation, primarily due to substantial variations in rainfall and seasonal inundations. Notably, this correlation is quite robust, with a correlation coefficient of 0.82. Flood control and storage is the predominant ecological service function of the Wolong wetland. From 1999 to 2019, the value of flood control and storage constituted an average of 71.34% of the total GEP. Conversely, the Qingtongxia wetland, which is situated in the northern region of Ningxia province, displays distinct ecological traits. The geographical position of the Qingtongxia wetland reduces the likelihood of flooding, yet its dry climate underscores its critical role in climate regulation. Research has indicated a positive correlation between GEP and evapotranspiration in the Qingtongxia wetland, with a correlation coefficient of 0.52. Climate regulation is the leading ecological service function of the Qingtongxia wetland. Between 1999 and 2019, climate regulation accounted for an average of 42.66% of the total GEP. Consequently, to ensure the effective protection and management of these wetland resources, it is imperative to take into account their unique geographical and meteorological conditions and to develop tailored conservation measures and management strategies. Studies on the GEP in the existing literature have not deeply discussed the effects of rainfall and evapotranspiration on the GEP of wetland; however, studies on their regulatory functions, such as flood control and climate regulation, are relatively abundant and so they are still comparable to a certain extent. In most studies, the regulatory function of wetlands was found to occupy a large proportion. For example, the contribution rate of the climate regulation function for the Dianchi Lake wetland in southern China has been reported to be as high as 90.0% [35]. Evaluation results for the Yellow River Delta wetland show that due to its unique coastal geographical location, the regulation functions of wave protection and flood control and storage account for 54.59% of the total value [36]. In the Beijing–Tianjin–Hebei urban agglomeration, which is located in the core region of China, the function of flood control and storage accounts for 75% of the total value [37].

3.2.2. Anthropogenic Influence

This study conducted an analysis of 21 literature sources on the evaluation of wetland ecological service values in China [38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58], allowing for a correlation between value and area to be established (Figure 7). The unit values of wetlands ranged from 2.96 to 116.5 CNY/m², with an average of 15.82 CNY/m². In the case of wetlands in Ningxia province, the values ranged from 2.96 to 8.7 CNY/m², with an average of 4.13 CNY/m². Due to variations in data sources, statistical methodologies, and specific algorithms employed in different evaluation methods, the calculated ecological service values for diverse wetlands vary. In studies focused on the Sanchahe wetland and the Nanhu wetland, the GEP per unit wetland area was 4.1 [41] and 5.1 [42] CNY/m², respectively, which is similar to the average value in this study. However, in studies of the Yeya Lake wetland and the Beijing Olympic Forest Park constructed wetland, the GEP per unit area of wetlands was 116.5 [43] and 115.1 [44] CNY/m², respectively, which is 28 times higher than the average in this study. The strong correlation coefficient of 0.8521 between the area and value indicates that wetland area predominantly influences the preservation of wetland GEP. Previous studies have evaluated the close relationship between wetland area and GEP; for example, the correlation coefficient between GEP and area for the Dianchi Lake wetland in southern China was found to be 0.998 [33]. Only within a certain area can the stability of wetland habitats be upheld, ensuring a suitable living environment for numerous animals and plants. Larger wetland areas typically offer a greater abundance of ecological services, whereas smaller wetlands are less capable in this regard. Consequently, safeguarding and rejuvenating wetland areas is crucial for sustaining and enhancing their ecological service functions. In our analysis, we meticulously considered a range of factors, such as meteorological conditions, geographical location, and other influences on wetland GEP. For instance, in the drier northern climates, factors such as flood control and water storage were not taken into account. By doing so, the GEP values obtained are more reflective of reality and can more accurately depict the actual productivity of wetlands within a given environment. Thus, the findings indicate that the GEP per unit area of wetlands was relatively low in our study.

4. Conclusions and Policy Recommendations

4.1. Conclusions

Assessing the composition and historical evolution of the GEP is instrumental in comprehending the impacts of climatic factors and human activities on the GEP of wetland ecosystems. Through the establishment of a general dynamic wetland GEP accounting model, we conducted a rigorous evaluation of the wetland GEP in Ningxia province, further delving into the spatial and temporal patterns of the GEP value alterations.

(1) From 1999 to 2019, the GEP of Ningxia’s wetlands ranged from CNY 4.87 to 5.66 billion, averaging CNY 5.24 billion. Ningxia’s geography contributes to these diverse GEP characteristics. Among 39 wetlands, Haba led with an average proportion of 0.52, followed by Qingtongxia, Sha, and Tenggeli. Northern wetlands are mainly influenced by the Yellow River and terrain, while southern wetlands are smaller, seasonal, and vulnerable to precipitation and groundwater replenishment. Climate regulation dominates the GEP of Ningxia’s wetlands, accounting for 38.24%. The wetlands exhibit a robust climate regulation mechanism, especially during dry years. Species conservation ranks second, contributing 24.93% to the total GEP. The value of flood control and storage varies significantly with meteorological conditions. The change in GEP and its ecological service functions in the Ningxia wetlands is a complex and dynamic process. Through comprehensively considering the influences of variable factors, our model can obtain more accurate and reliable wetland GEP calculation results, providing a solid scientific basis for wetland evaluation.

(2) The wetlands situated in the northern region of Ningxia province frequently endure the adverse effects of droughts and sandstorms, stemming from their proximity to deserts. Conversely, the wetlands located in the southern region are more susceptible to the mountainous climate, encountering fluctuations in rainfall and seasonal floods. The model employed in this study meticulously determined the GEP and its influencing factors for each wetland. Notably, the Wolong wetland, situated in Region 3, exhibited a robust positive correlation between GEP and rainfall, with a notable correlation coefficient of 0.82. On the other hand, the Qingtongxia wetland, positioned in Region 2 and less prone to flooding, displayed a positive correlation between GEP and evapotranspiration, attributed to the arid climate, with a correlation coefficient of 0.52. The processes of evapotranspiration in Regions 1 and 2 play a pivotal role in climate regulation. These environmental factors significantly shape the structure and function of the wetland ecosystem, thereby contributing to the distinctive features and ecological services of the wetlands in Ningxia province.

(3) The area of a wetland positively influences its GEP, with a correlation coefficient as substantial as 0.85 between the wetland size and its overall value. Consequently, safeguarding and rehabilitating wetland areas are crucial for sustaining and enhancing the ecological service functions of these ecosystems. The unit values for wetlands were found to vary between 2.96 and 116.5 CNY/m², with an average of 15.82 CNY/m². Specifically, in the case of wetlands in Ningxia province, the values ranged from 2.96 to 8.7 CNY/m², with an average of 4.13 CNY/m². We investigated the driving factors influencing the GEP of various wetlands and performed a detailed quantitative analysis. The GEP calculated in our study more accurately reflects the actual ecological value of wetlands, which not only contributes to a more precise assessment of wetland ecological functions but also provides a robust scientific foundation for the implementation of ecological compensation policies tailored to different wetlands.

(4) For all parameters, the biomass factors—including wetland area and endangered species—exhibited low variability. Meanwhile, monetary values, influenced by the degree of economic development and technological advancement, demonstrated general variability. In contrast, meteorological factors such as annual and inter-annual precipitation changes, evapotranspiration rates, and the geographical location of wetlands presented strong variability. During the data collection phase, the ideal state involves gathering parameters that change over time. At present, it is easy to acquire geographical and meteorological data that exhibit spatial and temporal variations. However, obtaining currency data that span the entire period from 1999 to 2019 presented a significant challenge. In the future, it will be essential to develop more robust methods for collecting and preserving economic data in order to ensure that long-term trends and patterns can be accurately analyzed and understood. This will enable researchers and policymakers to make more informed decisions regarding the management and conservation of wetland ecosystems, taking into account both ecological and economic dimensions.

4.2. Policy Recommendations

To further bolster the conservation of wetlands and enhance the performance evaluation system for ecological benefits, the following countermeasures and suggestions are proposed:

(1) The general dynamic wetland GEP accounting model developed in this study is suitable for a nationwide dynamic accounting of wetland GEP. It also meets the requirements for calculating the spatiotemporal patterns of wetlands in Ningxia province, providing a more comprehensive understanding of the value of the Ningxia province wetland ecosystem. Nonetheless, the inherent diversity, complexity, and non-linearity of wetland ecosystems can introduce inaccuracies when evaluating the service function value that humans derive from them. To minimize these inaccuracies and attain a goal of scientifically grounded, standardized, and practically applicable accounting, it is recommended to employ a hybrid approach that merges top-down and bottom-up methodologies. This strategy would foster the development of a standardized platform for the accounting of Ningxia province wetland system’s green economic productivity (GEP), fully capturing the contextual nuances of the Ningxia province wetlands, as well as offering appropriate support for assessment and management endeavors. First, the technical guidelines and statistical statements of Ningxia province’s wetland GEP statistical accounting should be formed from top to bottom. Experts from ecological and environmental protection departments, landscape gardening departments, regulation departments, and universities should be gathered to compile GEP statistical statements; standardize data sources, survey frequency, and submission requirements; ensure data stability and accuracy; and provide an institutional guarantee for the regular GEP accounting of Ningxia province’s wetlands. The second is to improve the monitoring and investigation system and basic database of Ningxia province’s ecological resources from bottom to top. Basic data are an important guarantee to carry out GEP accounting, involving development and reform, agriculture, land, forestry, water, meteorology, ecological environment, tourism, electricity, statistics, and other departments. At present, there is a gap in the statistical data of ecological resources in Ningxia province. According to the basic data requirements of GEP accounting for Ningxia province’s wetlands, a grid-based, dynamic monitoring investigation and statistical management system should be built. At the same time, it is necessary to establish a data sharing mechanism among departments in order to form a monitoring investigation system and basic database that can serve the needs of GEP accounting.

(2) The wetland resources of significant or representative wetlands, key waterfowl habitats, and vital water sources along the river are being progressively safeguarded, effectively activating the robust feedback adjustment mechanism of Ningxia province’s wetlands. A wetland ecosystem is a delicate, dynamic, and intricate system with complex interrelations among its various elements. Consequently, in the conservation of Ningxia province’s wetlands, the value of any particular service should not be overlooked due to its current minor proportion. For instance, while the biological conservation value constitutes only 24.93% of the total GEP, it serves as a vital indicator of ecosystem health and the foundation for the existence of other values. Therefore, it is imperative to establish a development plan that aligns with the unique characteristics of Ningxia province’s wetland ecosystem while exploiting and utilizing wetland resources. This strategy is essential for ensuring the sustainable exploitation of wetland resources. Additionally, wetlands hold a unique position, offering substantial potential as destinations for tourism, leisure, and scientific research. At present, the value attributed to scientific research and tourism in Ningxia province’s wetlands is only 15.11%. Thus, it is crucial to fully realize the potential of tourism and scientific research within these wetlands. Through leveraging the advantages of wetland resources and highlighting their distinctive features, the design and development of a tourism industry centered around wetlands should be emphasized. This initiative will encourage individuals to immerse themselves in nature, experience the satisfaction derived from wetland restoration and construction, and ultimately promote harmonious coexistence between humanity and the natural world.

(3) At present, China’s GEP and GDP dual assessment has entered the exploratory period. The organic integration of GEP with the existing performance appraisal system and the establishment of a performance view with GDP growth as the goal and GEP growth as the bottom line are conducive to guiding the construction of a new pattern of green development. From a pragmatic standpoint, both Zhejiang and Jiangsu provinces have endeavored to implement a dual evaluation system that combines the GEP with the traditional GDP. This approach has yielded a more comprehensive ecological value through the use of a dual assessment methodology. The findings of this research indicate that the GEP of wetlands is substantially influenced by natural elements, with its value ranging from CNY 4.87 billion to 5.66 billion—a significant factor that cannot be overlooked. Accounting for GEP is fundamental to ecological compensation and the trading of ecological products in the marketplace, as well as the inclusion of GEP in assessment frameworks. Consequently, in practical applications, it is imperative to thoroughly consider analyses of the spatiotemporal differentiation and internal driving mechanisms of the GEP. Moreover, the impacts of natural factors, geographical conditions, and ecological characteristics must be integrated into the overall evaluation framework in order to ensure that such assessments are accurate, objective, and fair.