Temporal and Spatial Analysis of the Changes in the Supply of Ecological Products in State-Owned Forest Farms after the Reform

Abstract

To reveal the changes in the supply efficiency of forest farm ecological products after the reform of state-owned forest farms, this study uses the ecological product accounting method to calculate the physical quantity and value of state-owned forest farm ecological products using data from 2015 and 2020. Through exploratory spatial data analysis, the spatial distribution of the supply efficiency of ecological products of state-owned forest farms and its primary index are studied to explore the temporal and spatial evolution of ecological products from state-owned forest farms in China. The results show the following: (1) Through the reform of state-owned forest farms, the supply capacity of forest farms’ ecological products has been greatly improved, and the physical quantity and value quantity of ecological products have shown an increasing trend, with growth rates of 31.7% and 24.2%, respectively. (2) There is strong spatial heterogeneity in the supply efficiency of ecological products from state-owned forest farms in various provinces, and the overall distribution pattern is gradually decreasing from the northwest to the southeast coastal provinces. (3) There is a negative correlation between the supply capacity of ecological products and provincial GDP. The supply capacity of ecological products in provinces with high per capita GDP is relatively low. (4) The comprehensive index of the supply efficiency of ecological products and its first-level index of state-owned forest farms are characterized by different degrees of agglomeration in space, which are mainly represented by three distribution modes: “H–H”, “L–L”, and “L–H”. Therefore, it is necessary to clarify the ecological function orientation of state-owned forest farms, improve the endogenous power of ecological product supply, actively explore and connect social ecological needs, and achieve coordinated progress in terms of ecological environmental protection and economic development.

1. Introduction

Forests, as the main body of terrestrial ecosystems, are of great significance in improving human well-being and maintaining ecological balance, providing a large number of rich ecological products [1]. With the development of the economy, humankind is constantly changing and reshaping the surface ecological pattern. The quantity and quality of forest resources are directly related to the development of human society and economy, and they play an important role in the maintenance of the global carbon cycle, biodiversity protection, climate regulation, and other aspects [2,3]. The forest transformation in China began in the early 1980s [4]. With the implementation of natural forest protection projects and key area protection forest construction projects, the total forest coverage rate in China has increased from 12.7% in the early 1980s to 23.04% by the end of 2020. According to statistics, from 2010 to 2020, China’s forest area growth and artificial forest area ranked first in the world [5,6,7]. However, local ecological damage is still quite severe, and the increasingly beautiful ecological environment of the people fundamentally requires a greater supply of high-quality ecological products [8]. The report of the 20th National Congress of the Communist Party of China pointed out the need for “establishing a mechanism for realizing the value of ecological products and improving the compensation system for ecological protection” [9]. The value accounting of ecological products is a prerequisite for establishing a mechanism for realizing the value of ecological products, and it is an inevitable requirement for improving the ecological damage identification and compensation system [10]. In April 2021, the General Office of the Central Committee of the Communist Party of China and the General Office of the State Council issued the “Opinions on Establishing and Improving the Mechanism for Realizing the Value of Ecological Products”, which clearly stated that, by 2035, a comprehensive mechanism for realizing the value of ecological products will be established, and a new model of ecological civilization construction with Chinese characteristics will be fully formed [11]. Accounting for the supply of existing ecological products is the foundation for achieving this goal.

The concept of an “ecological product” appeared late, and it is being constantly clarified and expanded. The concepts of ecological products and ecosystem services are very similar, and the value accounting of ecological products can also be traced back to the evaluation of ecosystem service value [12,13,14]. The value of ecosystem services is an important reference for the coordination of ecological and economic systems, and it is an indicator for measuring the natural environmental conditions and utility of human survival formed and maintained by regional ecosystems and ecological processes [15,16,17]. Practice has proven that the value of ecosystem services can be evaluated and measured. The Millennium Ecosystem Assessment and Environmental Economic Accounting System implemented by the United Nations and other organizations have further explored the theoretical connotations, indicator systems, policy applications, and other aspects of ecosystem services [18,19].

Since the 1980s, Chinese scholars have attempted to define the concept of ecological products [20]. In 2010, the State Council issued the National Main Functional Area Plan, which officially defined ecological products for the first time [21]. “Enhancing the production capacity of ecological products” has become an important aspect of China’s ecological civilization construction. In 2013, Ouyang Zhiyun et. proposed the concept of Gross Ecosystem Product (GEP) [22,23]. Since then, multiple scholars have conducted accounting research at different scales, such as province, city, and county [24,25,26]. In recent years, scholars have continuously expanded their research ideas and methods regarding ecological products from different perspectives. The research objects have shifted from a single type to national, regional, and private ecological products. The research content has shifted from the value accounting of forest ecological products to the value accounting of composite ecological products, such as oceans, deserts, and wetlands [27,28,29,30]. The market value method, shadow engineering method, and alternative cost method have been confirmed in practice. In this study, they are defined as products or services provided to human society for use and consumption by the joint action of the biological ecosystem and human social production. This action includes human welfare or benefits, such as safeguarding the living environment, maintaining ecological security, and providing material raw materials and spiritual and cultural services. The ecological functional area is important to the supply of ecological products, and improving the supply capacity is the main goal of ecological restoration [31]. The essence of ecological product supply accounting is to quantify the contribution of ecosystems to economic activities and to “value” various outputs of “priceless” ecosystems [32]. Currently, significant progress has been made in research on ecological products, and multiple pilot projects have been performed. However, the classification of ecological product types is still currently not unified, and there persist many problems with the accounting scope and application of ecological product value accounting. There has been relatively little research on the measurement of ecological product supply efficiency.

Since their establishment in the 1950s, state-owned forest farms have created and protected one-fifth of China’s forest resources, serving as an important supply base for ecological products and forming the basic framework for national ecological security [33]. From 2015 to 2020, state-owned forest farms underwent reform work, and cultivating and protecting forest resources and maintaining national ecological security became the main functional positions of state-owned forest farms [34]. A good ecological environment and ecological products provided by state-owned forest farms are important material foundations for improving the ecological well-being and quality of life of residents. Providing better ecological products for the people has become a key focus of the deepening reform of state-owned forest farms in the future. However, there are significant differences in the number, scale, resource status, regional economic development, and infrastructure construction of state-owned forest farms among different provinces. Therefore, it is of practical significance to calculate the ecological product supply situation of state-owned forest farms in each province and evaluate the reform effectiveness of state-owned forest farms.

Currently, relevant research on the reform of state-owned forest farms focuses on exploring the effects of the reform of state-owned forest farms, including changes in the wages and salaries of employees after the reform [35], the difficulties and suggestions associated with the reform [36], and the evaluation of the reform’s results based on employees’ sense of gain [37]. There have been relatively few studies of the changes in ecological function orientation after the reform of state-owned forest farms and the supply quantity and supply efficiency of their ecological products. Based on the review of the above literature, this paper takes the ecological products of state-owned forest farms as its research object and divides them into three types: material supply, regulation services, and cultural services. The physical quantity and value quantity of ecological products of state-owned forest farms are measured by statistical survey methods, market value methods, shadow engineering methods, and other methods; the temporal and spatial distribution is studied by exploratory spatial data analysis methods; the comprehensive evaluation index of supply efficiency is calculated by entropy methods; and a conclusion is provided to evaluate the reform effects of state-owned forest farms. Suggestions are offered that state-owned forest farms should continue to adhere to ecological function positioning and actively explore paths to realize the value of ecological products in state-owned forest farms. This study fills a gap in the research related to state-owned forest farms and provides a reference for the next step of deepening reform in state-owned forest farms.

2. Research Area

According to statistics, as of 2020, there were 4297 state-owned forest farms in China, covering more than 1600 counties in 30 provincial administrative regions. The overall distribution of forest farms shows a decreasing trend from the northeast and central provinces to the coastal and western provinces. Heilongjiang and Nei Monggol have the largest number of state-owned forest farms: 424 and 316, respectively, accounting for 17% of all state-owned forest farms in China. The number of state-owned forest farms in each provinces of China in 2020 is shown in Figure 1.

In 2020, the forest land area of state-owned forest farms reached 59.3 million hectares, the forest stock volume reached 4.83 billion m³, the average forest land area reached 13.81 thousand hectares, the average forest stock volume reached 1.124 million m³, and the area of public welfare forests for management and protection reached 43 million hectares. The overall area of forest farms showed a decreasing trend from the northwest and northeast provinces to the southeast coastal provinces. State-owned forest farms were dominated by forest ecosystems, with forest coverage exceeding 80%.

The change in ecosystem of state-owned forest farms is mainly reflected by the increase in forest area. The forest area and growth rate of state-owned forest farms in each provinces in 2020 are shown in Figure 2. From 2015 to 2020, the forest area of state-owned forest farms increased by 11.33 million hectares, an increase of 23.6%, and the forest volume increased by 1.47 billion m³. The forest area of state-owned forest farms in all provinces showed a net increase, with an average growth rate of 20.41%. The forest area of state-owned forest farms in Shanxi, Guangxi, Qinghai, Shanxi, and other provinces increased by more than 50%.

3. Research Methodology

3.1. Accounting Method of Ecological Products

3.1.1. Accounting Indicators

The accounting of the supply of ecological products includes determining the physical quantity of ecological products and the value quantity of ecological products to explore the social and ecological benefits from the reform of state-owned forest farms. The ecological products of state-owned forest farms include three functional categories: material product supply, regulation service products, and cultural service products. The supply accounting of mediation service products mainly focuses on water and soil conservation, flood regulation, air purification, carbon fixation, oxygen release, and climate regulation.

3.1.2. Accounting Method

The value accounting of ecological products is a popular topic in ecological products research, and there are many related research methods. This paper conducts a comparative analysis and then calculates the supply of ecological products of state-owned forest farms on the basis of the Technical Specifications for the Evaluation of Natural Resources (Forest) Assets, the Specifications for the Evaluation of Forest Ecosystem Service Functions, and the Specifications for the Accounting of Total Value of Ecological Products [38].

First, according to the forest resources of the state-owned forest farms in each province, we confirm the types of ecological products provided and select scientific and reasonable technical parameters in line with regional characteristics. The physical quantity of various ecological products is calculated according to the ecological environment, hydrology, meteorological monitoring, land type, and statistical data of the area in which the state-owned forest farm is located. The market value method, shadow engineering method, and other methods are used to determine the market or alternative prices of various elements of ecological products according to the economic development level of each province, and the value of ecological products can then be calculated based on the physical quantity of ecological products. Finally, the total supply of ecological products of state-owned forest farms in China can be obtained by summarizing the value of ecological products of state-owned forest farms in each province. See Table 1 for detailed accounting methods.

Table 1. Summary of accounting methods for ecological product supply of state-owned forest farms.

Classification	Physical Quantity Index	Accounting Method of Physical Quantity	Value Index	Value Accounting Method
Material supply	Forest material harvest	Statistical survey method $$Q_{substance}={\displaystyle {\sum }_{i=1}^n}{Q}_i$$ (1) $Q_{substance}$ represents the total amount of material products obtained from the ecosystem of the state-owned forest farm; $Q_i$ represents the quantity of the ith substance product; $i$ is the type of material product i; and $n$ is the quantity of the material product category.	Output value of forestry products	Market value method $$V_{substance}={\displaystyle {\sum }_{i=1}^n}{Q}_i\times P_i$$ (2) $V_{substance}$ indicates the supply value of material products from the ecosystem of state-owned forest farms; $Q_i$ represents the quantity of the ith substance product; $P_i$ is the market price of category i products; I is the type of material product i; and N is the quantity of the material product category.
	Yield of seedlings		Output value of seedling industry
Regulation service	Water conservation	Water balance method $$Q_{water}=A\times \left(P-R-ET\right)\times {10}^3$$ (3) $Q_{water}$ source refers to the physical quantity of water conservation in state-owned forest farms, and the unit is m3 per year; A is the forest area of the state-owned forest farm in km2; P is rainfall (in millimeters per year); R is surface runoff (in millimeters per year); and ET is evapotranspiration (in millimeters per year).	Water conservation value	Shadow engineering method (water conservancy project construction cost) $$V_{water}=Q_{water}\times (C_{\mathrm{r}}+P_{\mathrm{r}}\times D)$$ (4) $V_{water}$ source represents the value of water conservation in the forest area of China’s state-owned forest farms, in CNY per year; $Q_{water}$ indicates the physical quantity of water conservation on state-owned forest farms, in m3 per year; $C_{\mathrm{r}}$ is the annual operating cost of the unit storage capacity of the reservoir; $P_{\mathrm{r}}$ is the engineering cost of the unit storage capacity of the reservoir, in CNY per cubic meter; and D represents the annual depreciation rate of the reservoir.
	Soil conservation	Modified general soil loss equation $$Q_{sc}=R\times K\times L\times S\times \left(1-C\right)\times A\times {10}^2$$ (5) where $Q_{sc}$ is the soil conservation amount of the state-owned forest farm, and A is the area of the state-owned forest farm, in units of km2; R is the rainfall erosion factor; K is the soil erodibility factor; L is the slope length factor (dimensionless), reflecting the impact of the slope length on soil erosion; S is the slope factor (dimensionless), reflecting the impact of the slope on soil erosion; and C is the vegetation coverage factor (dimensionless), reflecting the impact of the ecosystem on soil erosion.	Reduction of the value of sediment deposition	Alternative cost method (dredging cost) $$V_{sc}=V_{s1}+V_{s2}$$ (6) $$V_{s1}=Q_{sc}\times B_i\times E_i$$ (7) $$V_{s2}=\lambda *\left(\frac{Q_{sc}}{\rho }\right)*c$$ (8) where $V_{sc}$ represents the soil conservation value of the ecosystem of the state-owned forest farms; $V_{s1}$ represents the value of reducing non-point source pollution; $V_{s2}$ represents the value of reducing sediment deposition; $Q_{sc}$ is the soil conservation amount of state-owned forest farms; $B_i$ refers to the pure content of Class i pollutants; $E_i$ refers to the unit treatment cost or market price of Class i pollutants; $c$ is the dredging cost of the reservoir project, in CNY per cubic meter; λ is the sediment deposition coefficient; and ρ is the soil bulk density (t/m ^ 3).
	Water regulation and storage capacity of forest land	Water balance method $$Q_{fr}=P-R\times A\times {10}^3$$ (9) $Q_{fr}$ is the flood regulation and storage capacity of the state-owned forest farm, and P is the rainstorm rainfall (mm/a); R is the rainstorm runoff of the forest ecosystem (mm/a); and A is the area of the state-owned forest farm in km2.	Flood regulation and storage value	Shadow engineering method (water conservancy project construction cost) $$V_{fr}=(C_r+P_r\times D)\times Q_{fr}$$ (10) $V_{fr}$ represents the value of flood regulation and storage; $Q_{fr}$ is the flood regulation and storage capacity of state-owned forest farms; $C_r$ is the annual operating cost of the unit storage capacity of the reservoir; $P_r$ is the engineering cost of the unit storage capacity of the reservoir in CNY per cubic meter; and D represents the annual depreciation rate of the reservoir.
	Purified sulfur dioxide	Plant purification model $$Q_{air}={\displaystyle {\sum }_{i=1}^n}{Q}_i\times A$$ (11) $Q_{air}$ represents the physical quantity of air purification; A is the area of the state-owned forest farm in km2; $Q_i$ represents the unit area purification capacity of the forest ecosystem to Class I air pollutants; and I represents the category of air pollutant.	Value of purified sulfur dioxide	Alternative cost method $$V_{air}={\displaystyle {\sum }_{i=1}^n}{Q}_i\times C_i$$ (12) $V_{air}$ represents the value of air purification; $Q_i$ represents the purification capacity of the forest ecosystem regarding Class I air pollutants; $C_i$ represents the unit treatment cost of Class I air pollutants; and I is the category of air pollutant.
	Amount of purified nitrogen oxide		Value of purified nitrogen oxides
	Purified industrial dust		Value of industrial dust purification
	Fixed carbon dioxide	Volume expansion method $$\begin{array}{c}{Q}_{fc}=Q_1+Q_2+Q_3\\ =V\times \partial \times \rho \times \gamma +\alpha \left(V\times \partial \times \rho \times \gamma \right)+\beta \left(V\times \partial \times \rho \times \gamma \right)\end{array}$$ (13) $Q_{fc}$ represents the carbon sink of state-owned forest farms; $Q_1$ indicates forest carbon sink; $Q_2$ represents the carbon sink of understory plants; $Q_3$ represents forest carbon sink; V indicates forest volume; partial indicates the volume expansion coefficient; ρ represents the bulk density; γ indicates carbon content; α represents the carbon conversion coefficient of understory plants; and β indicates the carbon conversion coefficient of forest land.	Fixed carbon dioxide value	Market value method (carbon market price) $$V_{fc}=Q_{fc}\times C_{cp}$$ (14) where $V_{fc}$ represents the carbon fixation value of the forest ecosystem; $Q_{fc}$ sequestration refers to the amount of carbon sequestration in the forest ecosystem; and $C_{cp}$ represents the price of carbon dioxide.
	Oxygen generation	Mass balance equation $$Q_{og}=NPP\times A\times 1.19$$ (15) $Q_{og}$ represents the amount of oxygen released by the forest ecosystem; NPP represents net productivity; and A represents the forest area of the state-owned forest farm.	Oxygen production value	Market value method (oxygen production price) $$V_{og}=Q_{og}\times C_{op}$$ (16) $V_{og}$ represents the oxygen release value of the forest ecosystem; $Q_{og}$ release represents the amount of oxygen released by the forest ecosystem; and $C_{op}$ represents the oxygen price.
	Climate regulation	Evapotranspiration model $$Q_{cr}=EPP\times A\times D\times \frac{{10}^6}{3600\times r}$$ (17) $Q_{cr}$ represents the energy consumed by evaporation of the forest ecosystem (kW$·$h/a); EPP represents the heat consumption per unit area of evapotranspiration of the forest ecosystem (kJ/($m^2·d$)); A represents the forest area of the state-owned forest farm; R is the energy efficiency ratio of air conditioning; and D is the number of days on which the air conditioner is operating for cooling.	Vegetation transpiration consumption value	Alternative cost method (manual cooling cost) $$V_{cr}=Q_{cr}\times P_e$$ (18) $V_{cr}$ represents the value of climate regulation of the forest ecosystem (CNY/a); $Q_{cr}$ represents the energy consumed by evaporation of the forest ecosystem (kW$·$h/a); and $P_e$ is the local domestic electricity price (CNY/kW$·$h).
Cultural services	Total number of tourists	Statistical survey method $$Q_t={\displaystyle {\sum }_{i=1}^n}{N}_{ti}$$ (19) $Q_t$ refers to the total number of tourists to the natural scenic spots of state-owned forest farms; $N_{ti}$ refers to the number of tourists to the ith natural scenic spot; I stands for natural scenic spots of state-owned forest farms; and N represents the number of natural scenic spots on state-owned forest farms.	Ecotourism value	Travel expense method $$V_t={\displaystyle {\sum }_{j=1}^j}{N}_j\times T_j\times C_j$$ (20) $V_t$ represents the value of leisure tourism in state-owned forest farms; N_ J represents the total number of tourists visiting natural scenic spots of the state-owned forest farms; J represents the number of natural scenic spots of state-owned forest farms; $T_j$ indicates the time that tourists spend on the trip; and $C_j$ refers to the average direct travel cost of tourists.

Table 1. Summary of accounting methods for ecological product supply of state-owned forest farms.

Classification	Physical Quantity Index	Accounting Method of Physical Quantity	Value Index	Value Accounting Method
Material supply	Forest material harvest	Statistical survey method $$Q_{substance}={\displaystyle {\sum }_{i=1}^n}{Q}_i$$ (1) $Q_{substance}$ represents the total amount of material products obtained from the ecosystem of the state-owned forest farm; $Q_i$ represents the quantity of the ith substance product; $i$ is the type of material product i; and $n$ is the quantity of the material product category.	Output value of forestry products	Market value method $$V_{substance}={\displaystyle {\sum }_{i=1}^n}{Q}_i\times P_i$$ (2) $V_{substance}$ indicates the supply value of material products from the ecosystem of state-owned forest farms; $Q_i$ represents the quantity of the ith substance product; $P_i$ is the market price of category i products; I is the type of material product i; and N is the quantity of the material product category.
	Yield of seedlings		Output value of seedling industry
Regulation service	Water conservation	Water balance method $$Q_{water}=A\times \left(P-R-ET\right)\times {10}^3$$ (3) $Q_{water}$ source refers to the physical quantity of water conservation in state-owned forest farms, and the unit is m3 per year; A is the forest area of the state-owned forest farm in km2; P is rainfall (in millimeters per year); R is surface runoff (in millimeters per year); and ET is evapotranspiration (in millimeters per year).	Water conservation value	Shadow engineering method (water conservancy project construction cost) $$V_{water}=Q_{water}\times (C_{\mathrm{r}}+P_{\mathrm{r}}\times D)$$ (4) $V_{water}$ source represents the value of water conservation in the forest area of China’s state-owned forest farms, in CNY per year; $Q_{water}$ indicates the physical quantity of water conservation on state-owned forest farms, in m3 per year; $C_{\mathrm{r}}$ is the annual operating cost of the unit storage capacity of the reservoir; $P_{\mathrm{r}}$ is the engineering cost of the unit storage capacity of the reservoir, in CNY per cubic meter; and D represents the annual depreciation rate of the reservoir.
	Soil conservation	Modified general soil loss equation $$Q_{sc}=R\times K\times L\times S\times \left(1-C\right)\times A\times {10}^2$$ (5) where $Q_{sc}$ is the soil conservation amount of the state-owned forest farm, and A is the area of the state-owned forest farm, in units of km2; R is the rainfall erosion factor; K is the soil erodibility factor; L is the slope length factor (dimensionless), reflecting the impact of the slope length on soil erosion; S is the slope factor (dimensionless), reflecting the impact of the slope on soil erosion; and C is the vegetation coverage factor (dimensionless), reflecting the impact of the ecosystem on soil erosion.	Reduction of the value of sediment deposition	Alternative cost method (dredging cost) $$V_{sc}=V_{s1}+V_{s2}$$ (6) $$V_{s1}=Q_{sc}\times B_i\times E_i$$ (7) $$V_{s2}=\lambda *\left(\frac{Q_{sc}}{\rho }\right)*c$$ (8) where $V_{sc}$ represents the soil conservation value of the ecosystem of the state-owned forest farms; $V_{s1}$ represents the value of reducing non-point source pollution; $V_{s2}$ represents the value of reducing sediment deposition; $Q_{sc}$ is the soil conservation amount of state-owned forest farms; $B_i$ refers to the pure content of Class i pollutants; $E_i$ refers to the unit treatment cost or market price of Class i pollutants; $c$ is the dredging cost of the reservoir project, in CNY per cubic meter; λ is the sediment deposition coefficient; and ρ is the soil bulk density (t/m ^ 3).
	Water regulation and storage capacity of forest land	Water balance method $$Q_{fr}=P-R\times A\times {10}^3$$ (9) $Q_{fr}$ is the flood regulation and storage capacity of the state-owned forest farm, and P is the rainstorm rainfall (mm/a); R is the rainstorm runoff of the forest ecosystem (mm/a); and A is the area of the state-owned forest farm in km2.	Flood regulation and storage value	Shadow engineering method (water conservancy project construction cost) $$V_{fr}=(C_r+P_r\times D)\times Q_{fr}$$ (10) $V_{fr}$ represents the value of flood regulation and storage; $Q_{fr}$ is the flood regulation and storage capacity of state-owned forest farms; $C_r$ is the annual operating cost of the unit storage capacity of the reservoir; $P_r$ is the engineering cost of the unit storage capacity of the reservoir in CNY per cubic meter; and D represents the annual depreciation rate of the reservoir.
	Purified sulfur dioxide	Plant purification model $$Q_{air}={\displaystyle {\sum }_{i=1}^n}{Q}_i\times A$$ (11) $Q_{air}$ represents the physical quantity of air purification; A is the area of the state-owned forest farm in km2; $Q_i$ represents the unit area purification capacity of the forest ecosystem to Class I air pollutants; and I represents the category of air pollutant.	Value of purified sulfur dioxide	Alternative cost method $$V_{air}={\displaystyle {\sum }_{i=1}^n}{Q}_i\times C_i$$ (12) $V_{air}$ represents the value of air purification; $Q_i$ represents the purification capacity of the forest ecosystem regarding Class I air pollutants; $C_i$ represents the unit treatment cost of Class I air pollutants; and I is the category of air pollutant.
	Amount of purified nitrogen oxide		Value of purified nitrogen oxides
	Purified industrial dust		Value of industrial dust purification
	Fixed carbon dioxide	Volume expansion method $$\begin{array}{c}{Q}_{fc}=Q_1+Q_2+Q_3\\ =V\times \partial \times \rho \times \gamma +\alpha \left(V\times \partial \times \rho \times \gamma \right)+\beta \left(V\times \partial \times \rho \times \gamma \right)\end{array}$$ (13) $Q_{fc}$ represents the carbon sink of state-owned forest farms; $Q_1$ indicates forest carbon sink; $Q_2$ represents the carbon sink of understory plants; $Q_3$ represents forest carbon sink; V indicates forest volume; partial indicates the volume expansion coefficient; ρ represents the bulk density; γ indicates carbon content; α represents the carbon conversion coefficient of understory plants; and β indicates the carbon conversion coefficient of forest land.	Fixed carbon dioxide value	Market value method (carbon market price) $$V_{fc}=Q_{fc}\times C_{cp}$$ (14) where $V_{fc}$ represents the carbon fixation value of the forest ecosystem; $Q_{fc}$ sequestration refers to the amount of carbon sequestration in the forest ecosystem; and $C_{cp}$ represents the price of carbon dioxide.
	Oxygen generation	Mass balance equation $$Q_{og}=NPP\times A\times 1.19$$ (15) $Q_{og}$ represents the amount of oxygen released by the forest ecosystem; NPP represents net productivity; and A represents the forest area of the state-owned forest farm.	Oxygen production value	Market value method (oxygen production price) $$V_{og}=Q_{og}\times C_{op}$$ (16) $V_{og}$ represents the oxygen release value of the forest ecosystem; $Q_{og}$ release represents the amount of oxygen released by the forest ecosystem; and $C_{op}$ represents the oxygen price.
	Climate regulation	Evapotranspiration model $$Q_{cr}=EPP\times A\times D\times \frac{{10}^6}{3600\times r}$$ (17) $Q_{cr}$ represents the energy consumed by evaporation of the forest ecosystem (kW$·$h/a); EPP represents the heat consumption per unit area of evapotranspiration of the forest ecosystem (kJ/($m^2·d$)); A represents the forest area of the state-owned forest farm; R is the energy efficiency ratio of air conditioning; and D is the number of days on which the air conditioner is operating for cooling.	Vegetation transpiration consumption value	Alternative cost method (manual cooling cost) $$V_{cr}=Q_{cr}\times P_e$$ (18) $V_{cr}$ represents the value of climate regulation of the forest ecosystem (CNY/a); $Q_{cr}$ represents the energy consumed by evaporation of the forest ecosystem (kW$·$h/a); and $P_e$ is the local domestic electricity price (CNY/kW$·$h).
Cultural services	Total number of tourists	Statistical survey method $$Q_t={\displaystyle {\sum }_{i=1}^n}{N}_{ti}$$ (19) $Q_t$ refers to the total number of tourists to the natural scenic spots of state-owned forest farms; $N_{ti}$ refers to the number of tourists to the ith natural scenic spot; I stands for natural scenic spots of state-owned forest farms; and N represents the number of natural scenic spots on state-owned forest farms.	Ecotourism value	Travel expense method $$V_t={\displaystyle {\sum }_{j=1}^j}{N}_j\times T_j\times C_j$$ (20) $V_t$ represents the value of leisure tourism in state-owned forest farms; N_ J represents the total number of tourists visiting natural scenic spots of the state-owned forest farms; J represents the number of natural scenic spots of state-owned forest farms; $T_j$ indicates the time that tourists spend on the trip; and $C_j$ refers to the average direct travel cost of tourists.

3.2. Entropy Method

The entropy method is also an objective weighting method used to determine whether entropy can effectively reflect the degree of information disorder. The smaller the entropy, the lower the degree of system disorder, the higher the information utility value, and the higher the weight to ensure the accuracy and comparability of indicator data weighting [39]. This paper mainly measures the supply efficiency of and changes in ecological products in state-owned forest farms in 2015 and 2020. To render the results of each year comparable and draw on research results, the method of adding time variable entropy is used to determine the weights of each evaluation index, and the comprehensive index of ecological product supply efficiency in state-owned forest farms in different years is calculated. The specific steps are as follows:

Assume that the state-owned forest farms in n provinces are selected as samples, and m evaluation indicators are designed to represent the jth evaluation index value of state-owned forest farms in i province (i = 1, 2, 3 … n; j = 1, 2, 3 … m). The raw data are dimensionless to negate the impact of physical quantities. $X_{ij}^{’}$ ‘is $X_{ij}$ normalized value, and $X_j^{min}$ and $X_j^{max}$ are $X_j$ maximum and minimum values.

$$X_{ij}^{’}=\frac{X_{ij}-X_j^{min}}{X_j^{max}-X_j^{min}}$$

(21)

To negate the impact of negative indicator values and ensure the value of data processing, the overall translation amplitude A of dimensionless data is determined to be a unit, determining the entropy value; A is generally 0.0001.

$$e_j=-\frac{1}{\ln n}{{\displaystyle \sum }}_{i=1}^n\frac{X_{ij}^{’}+A}{{\displaystyle {\sum }_{i=1}^n}{X}_{ij}^{’}}ln\frac{X_{ij}^{’}+A}{{\displaystyle {\sum }_{i=1}^n}{X}_{ij}^{’}}$$

(22)

The comprehensive evaluation index of ecological product supply capacity can be obtained by multiplying the standardized data by the weight of each index:

$$W_j=\frac{1-e_j}{{\displaystyle {\sum }_{j=1}^n}\left(1-e_j\right)}$$

(23)

$$Y_j={{\displaystyle \sum }}_{j=1}^n{X}_{ij}^{’}{W}_j$$

(24)

3.3. Exploratory Spatial Data Analysis Method

To explain the spatial distribution characteristics of ecological product supply and supply on China’s state-owned forest farms, this paper uses exploratory spatial data analysis methods to identify the distribution characteristics and patterns of certain attributes from geographical space, which can effectively determine whether there is spatial correlation between regions. The ESDA method mainly includes two aspects: first, global spatial autocorrelation, which reflects the spatial correlation of observations as a whole; and second, local spatial autocorrelation, which is used to analyze the spatial heterogeneity of spatial data in local subregions. Usually, a certain geographical or economic attribute value of a region is interrelated with the same attribute value in its adjacent regions [40]. The ESDA method is based on the concept of spatial autocorrelation and simultaneously processes location information and attribute information, compensating for the shortcomings of classical statistics, which ignored geographical spatial orientation. This paper first conducts quantitative analysis from a global perspective [41]. Based on this consideration, it is necessary to further use local indicators to deepen the research and explore the specific characteristics of ecological product supply in state-owned forest farms, to guide practice and minimize regional disparities, and to provide a basis for detailed quantitative analysis.

3.3.1. Global Spatial Autocorrelation

In this paper, the global spatial autocorrelation analysis method is used to measure the spatial correlation of the supply level of ecological products of state-owned forest farms in each province in the region to determine whether there is spatial aggregation.

$$Mora{n}^{\prime }I=\frac{{\sum }_{i=1}^n{\sum }_{j=1}^n{W}_{ij}\left(y_i-\overline{y}\right)(\left(y_j-\overline{y}\right)}{S^2{\sum }_{i=1}^n{\sum }_{j=1}^n{W}_{ij}}$$

(25)

where $S^2$ is the sample variance, $y_i$ is the observed value of area i, $\overline{y}$ is the average value, and $W_{ij}$ is the spatial weight matrix. The value range of Moran’s index is [−1, 1]. The closer it is to 1, the stronger the correlation. In contrast, there is no spatial autocorrelation.

3.3.2. Local Spatial Autocorrelation

Local spatial autocorrelation analysis can identify the various spatial correlation phenomena caused by the spatial location differences in the observation subjects. According to the local Moran’s I index, spatial autocorrelation patterns can be divided into four types: high–high clustering (H–H), where areas with high observation values are surrounded by areas with high observation values, showing a local positive correlation; high–low clustering (H–L), where areas with high observation values are surrounded by areas with low observation values, exhibiting a local negative correlation; low–high clustering (L–H), where areas with low observation values are surrounded by areas with high observation values, exhibiting local negative correlation; and low–low clustering (L–L), where areas with low observed values are surrounded by areas with low observed values, exhibiting a local positive correlation [42]. The calculation formula of local Moran’s I is as follows:

$${\mathrm{Local} \mathrm{Moran}}^{’}\mathrm{I}=\frac{y_i-\overline{y}}{S^2}{\displaystyle \sum }_{j=1}^n{W}_{ij}(\left(y_j-\overline{y}\right)$$

(26)

3.4. Data Source and Processing

The data on state-owned forest farms in 2015 and 2020, including forest area, forest stock, timber production, sales income, tourism income, etc., were obtained from the database of state-owned forest farms and the basic situation of forest farms in the provincial reports of Twenty Years of Poverty Alleviation in State-owned Forest Farms [43,44]. A total of 4493 valid data were gathered from the database, and missing data were obtained from the average of the relevant data in 2014 and 2016. Because the number of state-owned forest farms in the Tibet Autonomous Region and Tianjin was small, these provinces were not included in the accounting scope.

The seedling price parameters refer to the National Seedling Supply and Demand Analysis Report provided by the State Forestry and Grass Administration. The average annual rainfall, evaporation, rainstorm rainfall, and average annual temperature of each province were obtained from the China Climate Bulletin and China Water Resources Bulletin. The relevant forest ecosystem parameters, such as the surface runoff coefficient, soil bulk density, storm runoff, and purification capacity of the forest ecosystem for various air pollutants per unit area, refer to the Accounting Specifications for the Total Value of Ecological Products issued by the State Council. The price parameters of soil conservation, flood regulation, and storage refer to the Technical Specifications for GEP Accounting of Zhejiang Province, Terrestrial Ecosystem, and they are adjusted according to the consumer price index of the government and residents in 2020. The nitrogen, phosphorus, and potassium contents in the soil were obtained from the national land survey data. The price parameters of air purification refer to the Comprehensive Work Plan for Energy Conservation and Emissions Reduction formulated by the National Development and Reform Commission. The coefficient of carbon sequestration products refers to the internationally accepted United Nations Intergovernmental Panel on Climate Change default value. The carbon trading price is obtained based on the average price from the carbon trading markets in Hubei, Guangdong, and Shenzhen, which were the top three in terms of carbon trading volumes. The provincial electricity price was obtained from the provincial development and reform commission website. For the number of tourists, please refer to the Bulletin of China’s Land Greening Status. For the price parameters of leisure tourism, refer to the Annual Report on China’s Domestic Tourism Development.

4. Results and Analysis

4.1. Accounting Results

4.1.1. Material Supply Products

In 2015, the main material products supplied by the state-owned forest farms were wood products, with a main cutting volume of 172.59 thousand hectares. In total, 9.03 million m³ of wood were harvested, and the total revenue from wood production, processing, and sales was CNY 6.041 billion. In 2020, the total value of material products from state-owned forest farms was CNY 3.647 billion, a decrease of CNY 2.394 billion. The volume of timber harvested was 3.47 million m³; the sales revenue of timber was CNY 2.321 billion, a year-on-year decrease of 61.58%; and about 490 million seedlings of improved varieties were provided, with a value of about CNY 1.326 billion.

4.1.2. Regulation Service Products

(1)

Physical quantity accounting

The physical quantity of regulation service products of state-owned forest farms in each province in 2020 is shown in

Table 2. Summary of physical quantity of regulation service products in 2020.

	Water Conservation	Soil Conservation	Flood Regulation and Storage	Air Purge			Carbon Fixation and Oxygen Release		Climate Regulation
	Water Conservation (106 m3/a)	Soil Conservation (106 t/a)	Flood Regulation and Storage (106 m3/a)	So2 Purification Capacity(103 t/a)	NOx Purification Amount (103 t/a)	Dust Purification Capacity (103 t/a)	Carbon Fixation (106 t/a)	Oxygen Release (106 t/a)	Climate Regulation (106 kW*h/a)
Beijing	107.94	0.80	388.75	2.20	1.40	7.00	1.88	0.41	9863.14
Hebei	1778.9	13.4	6563.0	37.50	23.50	112.00	76.1	7.0	166,512.6
Shanxi	5826.2	42.9	20,935.6	119.70	75.10	356.00	128.5	22.2	531,161.8
Inner Mongolia	9276.3	123.2	60,121.6	343.80	215.60	1023.00	516.7	63.7	1,525,361.3
Liaoning	2411.1	13.3	6501.3	37.20	23.30	111.00	80.1	6.9	164,945.9
Jilin	9302.3	50.0	24,395.1	139.50	87.50	415.00	431.0	25.9	618,934.7
Heilongjiang	14,762.9	84.4	41,178.2	235.50	147.60	700.00	690.5	43.7	1,044,743.2
Jiangsu	868.0	2.9	1416.4	8.10	5.10	24.00	26.9	1.5	35,936.5
Zhejiang	1521.1	3.7	1803.6	10.30	6.50	31.00	32.2	1.9	45,760.8
Anhui	1762.9	4.4	2134.8	12.20	7.70	36.00	46.0	2.3	54,163.3
Fujian	2253.9	6.5	3158.9	18.10	11.30	54.00	70.8	3.3	106,861.5
Jiangxi	11,573.3	25.8	12,596.6	72.00	45.20	214.00	201.1	13.4	319,590.3
Shandong	426.3	2.1	1025.8	5.90	3.70	17.00	14.1	1.1	26,026.8
Henan	1511.4	7.1	3486.8	19.90	12.50	59.00	62.3	3.7	88,463.2
Hubei	5200.8	13.1	6386.0	36.50	22.90	109.00	99.7	6.8	162,020.5
Hunan	7492.2	17.9	8751.0	50.00	31.40	149.00	161.6	9.3	222,024.1
Guangdong	4469.4	11.7	5726.8	32.70	20.50	97.00	86.0	6.1	193,729.5
Guangxi	9914.4	24.5	11,978.5	68.50	42.90	204.00	167.9	12.7	405,211.8
Hainan	2588.8	6.5	3181.7	18.20	11.40	54.00	87.4	3.4	107,631.9
Chongqing	2157.8	6.2	3031.6	17.30	10.90	52.00	51.7	3.2	76,914.4
Sichuan	12,837.6	50.3	24,542.9	140.30	88.00	417.00	412.4	26.0	622,683.5
Guizhou	1923.7	5.6	2737.4	15.70	9.80	47.00	48.9	2.9	69,451.8
Yunnan	13,926.3	49.7	24,272.8	138.80	87.00	413.00	546.5	25.7	615,832.3
Shaanxi	10,478.0	62.7	30,606.0	175.00	109.70	521.00	409.0	32.5	776,512.3
Gansu	5420.5	67.0	32,693.7	187.00	117.20	556.00	404.2	34.7	829,481.1
Qinghai	7662.6	86.3	42,100.4	240.70	150.90	716.00	54.2	44.6	1,068,140.7
Ningxia	517.5	6.9	3370.2	19.30	12.10	57.00	8.1	3.6	85,506.8
Xinjiang	4939.7	144.1	70,311.8	402.10	252.10	1196.00	651.1	74.6	1,783,897.1
Total	152,911.96	933.18	455,397.52	2604.10	1632.80	7746.70	5566.88	482.85	11,757,363.03

. All kinds of regulatory service products achieved net growth compared with data from 2015, indicating an enhancement in the supply capacity of ecological products from state-owned forest farms. In 2020, the physical quantity of regulation service products of state-owned forest farms included 152.912 billion tons of water conservation, 930 million tons of soil conservation, 455.398 billion tons of flood regulation and storage, 12 million tons of air purification, 5.567 billion tons of carbon sequestration, 480 million tons of oxygen release, and 11,757.3 billion kilowatts per hour of climate regulation.

In general, the supply capacity of regulating service products of state-owned forest farms is relatively high, and the supply difference among various products is relatively obvious. This finding indicates that, since the reform of state-owned forest farms, the ecological function construction of state-owned forest farms in different provinces has reached different levels, and the difference is significant. In provinces with relatively poor natural environmental conditions and economic development, the supply capacity of ecological products of state-owned forest farms is higher. Limited by the distribution of state-owned forest farms, the amount of ecological products provided by Beijing’s state-owned forest farms is relatively low compared to other provinces.

(2)

Value accounting

In 2015 and 2020, the values of ecological product regulation service products from China’s state-owned forest farms were CNY 6.74 trillion and CNY 8.6 trillion, respectively, representing an increase of CNY 1.907 trillion (28.29%). Climate regulation and water conservation are the most valuable ecological products. The value and growth rates of state-owned forest farm regulation service products in 2015 and 2020 are shown in the Figure 3.

The values of climate regulation in 2015 and 2020 were CNY 4.42 trillion and CNY 5.71 trillion, respectively, representing an increase of CNY 1.29 trillion (28.29%) and accounting for 66.91% and 66% of the total value of ecological products of regulation services.

The values of water conservation was CNY 1.66 trillion and CNY 1.97 trillion, respectively, an increase of CNY 0.31 trillion (18.64%), accounting for 23.5% and 22.87%, respectively.

The values of flood regulation and storage were 240.19 billion and 403.98 billion, respectively, an increase of CNY 163.78 billion, with the highest growth rate of 68.19%. These changes accounted for 3.48% and 4.67%, respectively. In the flood season of 2020, China’s rainfall was unusually high, and the rainstorms and flood disasters were serious. The ecological function of state-owned forest farms to regulate and store floods was highlighted.

The values of carbon sequestration were CNY 128.51 billion and CNY 187.05 billion, respectively, an increase of CNY 58.54 billion, with a growth rate of 45.55%. These changes accounted for 1.77% and 2.17%, respectively.

The values of oxygen release were CNY 252.54 billion and CNY 337.80 billion, respectively, an increase of CNY 85.26 billion, with a growth rate of 33.84%. These changes accounted for 3.95% and 3.91%, respectively.

The values of air purification were CNY 18.39 billion and 24.05 billion, respectively, an increase of CNY 5.66 billion (30.76%). The values of soil conservation were 6.59 billion and 8.18 billion, respectively, an increase of CNY 1.59 billion (24.02%). Although the proportion of soil conservation and air purification value was low, at less than 1% of the total value of the regulation service products for that year, it still maintained the growth trend.

4.1.3. Cultural Service Products

The values of cultural service ecological products from state-owned forest farms were CNY 7.503 billion and CNY 28.928 billion in 2015 and 2020, respectively, an increase of CNY 21.425 billion or 146.94%. The number of tourists increased from 140 million to 375 million, an increase of 235 million. Travel expenses increased from CNY 53.59 per person to CNY 77.14, an increase of CNY 23.55 per person.

The number of domestic tourists increased from 3.99 billion in 2015 to 6.006 billion in 2019 (an increase of 50.53%). The ecotourism industry, including destinations such as natural reserves, special forest and grass parks, state-owned forest farms, state-owned forest areas, and other regions, also developed rapidly. Ecotourism has become an important green industry in various regions, driving local economic development and promoting the transformation of residents’ lifestyles. As a result of the COVID-19 pandemic, China saw only 1.877 billion ecotourists in 2020—1.113 billion fewer than the previous year. With the gradual improvement in the epidemic situation and the continuous strengthening of the brand construction of forest tourism in state-owned forest farms, the value of ecotourism will gradually return to pre-pandemic levels and continue to increase.

4.1.4. Total Value of Ecological Products

The values of ecological products supplied by state-owned forest farms in 2015 and 2020 were CNY 6.74 trillion and CNY 8.64 trillion, respectively, an increase of CNY 1.9 trillion (28.19%). In addition to ecological products of material products, ecological products of regulatory services and cultural services increased significantly, and the composition of ecological products became greener and lower in carbon.

4.2. Analysis of Space–Time Distribution

4.2.1. Time Change Characteristics

From 2015 to 2020, the values of ecological products regulation services of state-owned forest farms in 25 provinces increased by different degrees, accounting for 89.28%. The provinces with increased values are widely distributed throughout the country. The Qinghai, Shanxi, Guangxi, and Shaanxi provinces experienced increases of more than 50%, while the regions distributed in the coastal provinces of southeast China—namely Hainan, Fujian and Guangdong—decreased in value.

Specifically, the proportion by which the regulation service products increased and decreased in various regions is as follows: water conservation (71.43%, 28.57%), soil conservation (78.57%, 21.43%), flood regulation and storage (100%), air purification (78.57%, 21.43%), carbon fixation (96.43%, 3.57%), oxygen release (78.57%, 21.43%), and climate regulation (78.57%, 21.43%).

4.2.2. Spatial Distribution Characteristics

As far as the country is concerned, the distribution of regulating service value of state-owned forest farms has an obvious regional distribution law, showing high overall characteristics in the northwest and low characteristics in the southeast and gradually decreasing from the northwest to the southeast. The average value of mediation services is CNY 307.769 billion. Among the total value of ecological products of mediation services of state-owned forest farms, the values of state-owned forest farms in Xinjiang and Inner Mongolia are the highest, accounting for 12.22% and 10.13%, respectively. The ecology of Xinjiang and Inner Mongolia is relatively fragile, with characteristics such as a large area, windy sand, drought and water shortages, widespread desert conditions, and a sparse population. The state-owned forest farms in this region have large forest areas (accounting for 14.35% and 13.20% of the forest area of China’s state-owned forest farms, respectively). State-owned forest farms play an important ecological role in observation of the natural ecological security boundaries, mitigating regional desertification, salinization, and sandstorms. The value is between CNY 400 billion and 800 billion (25%), and it is mainly distributed across various provinces in the northwest, southwest, and northeast. From a topographical perspective, it is located in the second ladder of China. These areas are China’s key ecological functional areas, and they play an important role in regulating climate and conserving water resources. As such, they are an important part of China’s ecological security strategic pattern. The quantity with a value of 200–400 billion accounts for 14.29%, mainly in some provinces in South China and Northeast China. The majority of provinces with a value of less than 200 billion, accounting for 53.57%, are primarily distributed in the provinces along the southeast coast of China, with some located in the middle and lower reaches of the Yangtze River. The region is economically developed, with a small number of state-owned forest farms and a small area.

Comparing the per capita regulatory service value of China’s provinces in 2020 with the per capita gross domestic product (GDP) shows that the lower the per capita GDP, the higher the per capita regulatory service values of the provinces. The per capita regulatory service value of Qinghai Province exceeds the per capita GDP of the province, indicating that the value created by the state-owned forest farms in Qinghai Province in the conservation ecosystem is far greater than the value created by the economic system. A comparison of per capita GDP and per capita regulated service value among provinces in 2020 is shown in Figure 4.

4.2.3. The Value and Change of Ecological Products per Unit Area of State-Owned Forest Farms

In 2020, the value of ecological products per unit area of state-owned forest farms was 14.5119 million CNY/km². This value shows that state-owned forest farms are an important supply area that enable the repair and improvement of the ecosystem and provide ecological products and services. The value of ecological products per unit area in Anhui, Fujian, Jiangxi, Hubei, Hunan, Guangdong, Guangxi, and Hainan has exceeded 20 million CNY/km², while the value of ecological products per unit area in Ningxia state-owned forest farms is the lowest, at 9.701 million CNY/km². From 2015 to 2020, the value growth rate of ecological products per unit area of state-owned forest farms was as high as 12%, significantly lower than the national average (21.1%). Meanwhile, the value growth rate of ecological products per unit area of state-owned forest farms in Chongqing was 19.16%, and the growth rate of Anhui, Hubei, Sichuan, Shaanxi, and Xinjiang was greater than 15%, while the growth rate of Fujian, Shandong, Guangdong, Hainan, and Ningxia declined by −0.79% to −10.88%.

At the indicator level, the supply value per unit area of climate regulation is the highest, at 9.55 million CNY/km², of which the supply value per unit area of climate regulation of Hainan state-owned forest farms is the highest, at 15.7259 million CNY/km²; The second-highest supply value is the unit value of water conservation, at 3.3084 million CNY/km². The unit area supply value of climate regulation of Jiangxi state-owned forest farms is the highest, at 9.0857 million CNY/km². The unit value of other regulatory service products is relatively low.

4.3. Spatial Distribution Characteristics of Ecological Product Supply

4.3.1. Global Spatial Autocorrelation Analysis

Using GeoDa software (version 1.20.0.20, Chicago, IL, USA) and exploratory spatial data analysis, the Moran’s coefficient of ecological products of state-owned forest farms in each province in 2020 was calculated to be 0.405 (Z = 3.44, P = 0.003). The p value was less than 0.05 at the 0.05 significance level. This outcome indicates that there is a certain degree of spatial agglomeration in the supply of ecological products between adjacent provinces regarding China’s state-owned forest farms. This finding may be related to the policy dividend generated by the successive completion of state-owned forest farm reforms in various provinces in 2020, which strengthened the supply capacity of ecological products for state-owned forest farms. The Moran scatter chart of ecological products of state-owned forest farm in 2020 is shown in Figure 5. The Z score of ecological product supply in state-owned forest farms in 2020 is shown in Figure 6.

According to the scatter diagram, the ecological products of state-owned forest farms in the northwest and northeast regions show a high degree of spatial aggregation, while the supply of ecological products of state-owned forest farms in the southeast regions shows a low degree of spatial aggregation.

4.3.2. Local Spatial Autocorrelation Analysis

To further investigate the local spatial agglomeration of the ecological product supply of state-owned forest farms in each province, GeoDa software was used to calculate the local Moran’s 1 index of the ecological product supply from state-owned forest farms in each province in 2020. According to the calculation results, the spatial correlation forms of the ecological product supply in each province can be divided into three types: L–H, L–L, and H–H. H–H clusters are concentrated in the northwest region with strong supply capacity of ecological products, mainly in the Gansu and Qinghai provinces. The main reason for this phenomenon is that the state-owned forest farms in the abovementioned provinces have large areas and strong natural resource advantages, promoting the supply capacity of ecological products to a high level and driving the surrounding areas. L–L clusters are concentrated in the eastern region with poor supply capacity of ecological products, mainly in the Shandong, Jiangsu, and Anhui provinces. The supply capacity of ecological products of state-owned forest farms in these provinces is weak, and the supply capacity of ecological products of surrounding provinces is also poor. The L–H type is dominated by Gansu Province, indicating that, although the supply capacity of its own ecological products is weak, the supply capacity of the surrounding provinces can maintain a high level. In general, the supply capacity of ecological products of China’s state-owned forest farms is closely related to the geographical location and resource endowment of the state-owned forest farms.

5. Calculation of the Supply Efficiency of Ecological Products in China’s State-Owned Forest Farms

5.1. Score of Comprehensive Evaluation Index

The above comprehensive evaluation method model is used to assess the ecological products of the regulation services of state-owned forest farms in 2015 and 2020, and the comprehensive rating index, evaluation scores, and rankings of each subsystem can be calculated. The results are shown in

Table 3. Comprehensive evaluation index and ranking change of supply efficiency.

	2020 Comprehensive Evaluation Index	2015 Comprehensive Evaluation Index	Rank 2020	Rank 2015	Sequence Change
Xingjian	0.1391	0.1306	1	2	1
Inner Mongolia	0.1188	0.1367	2	1	−1
Heilongjiang	0.0973	0.1182	3	3	0
Qinghai	0.0750	0.0548	4	8	4
Gansu	0.0695	0.0636	5	5	0
Shaanxi	0.0690	0.0547	6	9	3
Yunnan	0.0634	0.0742	7	4	−3
Sichuan	0.0604	0.0576	8	7	−1
Jilin	0.0585	0.0615	9	6	−3
Shanxi	0.0420	0.0317	10	11	1
Jiangxi	0.0341	0.0414	11	10	−1
Guangxi	0.0319	0.0240	12	12	0
Hunan	0.0236	0.0238	13	13	0
Hubei	0.0163	0.0160	14	15	1
Guangdong	0.0151	0.0191	15	14	−1
Liaoning	0.0140	0.0152	16	16	0
Hebei	0.0137	0.0122	17	17	0
Hainan	0.0092	0.0120	18	18	0
Fujian	0.0082	0.0102	19	19	0
Henan	0.0079	0.0072	20	21	1
Chongqing	0.0072	0.0068	21	22	1
Guizhou	0.0063	0.0076	22	20	−2
Ningxia	0.0055	0.0065	23	23	0
Anhui	0.0053	0.0051	24	24	0
Zhejiang	0.0042	0.0050	25	25	0
Jiangsu	0.0029	0.0025	26	26	0
Shandong	0.0017	0.0019	27	27	0
Beijing	0.0010	0.0012	28	28	0

.

The comprehensive evaluation index is obtained by totaling the ecological product index of state-owned forest farms in each province, and the gap between provinces is relatively significant. In 2020, the average value of the comprehensive evaluation index of ecological products of state-owned forest farms was 0.0357, and only 10 provinces achieved a value higher than the average. Most of the state-owned forest farms in these regions were distributed in the northwest, northeast, Yunnan–Guizhou Plateau, Sichuan Basin, and Loess Plateau, supporting the important role of state-owned forest farms in maintaining national ecological security. The comprehensive evaluation index of state-owned forest farms in Xinjiang was the highest, at 0.1391, and that of state-owned forest farms in Beijing was the lowest, at 0.1381. These findings are directly related to the number and area of state-owned forest farms in each province. In terms of ranking changes, the comprehensive evaluation index of state-owned forest farms in most provinces has remained consistent, and the rankings of seven provinces have increased. Qinghai and Shanxi provinces have increased rapidly, while the ranking of six provinces, including Yunnan and Jilin, have decreased significantly.

5.2. Comparison of Supply Efficiency of Ecological Products of State-Owned Forest Farms in Different Regions

According to the division of administrative regions and the scores of various indicators, we analyzed the advantages, disadvantages, and gaps in the supply of mediation services of ecological products by state-owned forest farms in each region. The supply scores of each product in the three provinces of North China are quite different, and the water conservation capacity is relatively low compared with other products. All provinces in South China share relatively close ecological product scores, with no significant shortfalls. Guangxi and Hunan are relatively high, while coastal Guangdong and Hainan are relatively low. The significant weakness of Northeast China is its water conservation capacity, and Liaoning Province has a significantly lower score than other provinces. The shortfall of Northwest China lies in water conservation and carbon sequestration, related to the natural climate with less rainfall and fewer lakes, and the gap between provinces is large; East China has no significant disadvantage. Except for Jiangxi Province, the scores of other provinces are generally low. The scores for Chongqing and Guizhou in the southwest region are relatively close, while those of Sichuan and Yunnan also are relatively close, and they have significant advantages in terms of carbon sequestration.

6. Discussion and Conclusions

6.1. Discussion

On the basis of defining the connotations of ecological products, this study divides the types of ecological products, constructs an accounting system for the supply and value of ecological products, and uses exploratory spatial data analysis and entropy methods to analyze the spatiotemporal distribution of ecological products from state-owned forest farms. Subsequently, empirical research was conducted on the supply of ecological products from state-owned forest farms in China. This analysis has important practical guiding significance for the future development planning of state-owned forest farms.

(1)

State owned forest farms have a large supply capacity for ecological products. According to calculations, the supply of ecological products related to regulation services and cultural services in state-owned forest farms has significantly increased compared to before the reform of state-owned forest farms, while the supply of ecological products related to material supply has shown a significant downward trend. This finding is consistent with the functional positioning of state-owned forest farms in cultivating and protecting forest resources and maintaining national ecological security, indicating that state-owned forest farms are important ecological product supply areas in China. Under the guidance of the Natural Forest Protection Project, the conversion of farmland to forests, the construction of ecological function zones, and the policy of cutting cessation, the timber output of state-owned forest farms has been significantly reduced. Presently, the main forest products exported by state-owned forest farms are seedlings, flowers, and fine and strong seedlings of local trees. As a result of the continuous promotion of the rural revitalization strategy and the construction of a beautiful China, the market demand for seedlings is also increasing, the output and benefits of improved and strong seedlings will continue to rise, and the value of the material products of state-owned forest farms will also gradually increase; these outcomes are conducive to promoting the development of green industry and promoting a win–win situation between industry and ecology.

(2)

Among all kinds of ecological products, the proportion of regulation service ecological products is high. Compared to 2015, various regulatory service products have achieved net growth, reflecting the effectiveness of forest farm reform abroad. The economy of the northwest provinces is underdeveloped, but the ecological product supply capacity of state-owned forest farms is still among the top in the country, indicating that the inclusion of forest farm expenditures in the financial budget provides a solid material foundation for the subsequent development of forest farms, and it is also closely related to the construction of the Three North (Northwest, North China, and Northeast) protective forests being implemented in China.

(3)

Based on the previous calculation of ecological product supply in a certain province, this paper selected more than 4000 state-owned forest farms in 28 provinces as the research objects, selected relatively mature models and complete parameters, and calculated the supply of ecological products and supply efficiency. Compared with previous studies [26,27,45], it was found that state-owned forest farms, like other forest management institutions (such as national forest parks), have a higher proportion of ecological products related to climate regulation and water conservation. State-owned forest farms have a stronger ability to fix carbon and release oxygen, which may be related to the natural attributes of forest ecosystems.

(4)

There is a significant difference in the supply capacity of ecological products among state-owned forest farms in various provinces. In Figure 5 and Figure 6, it can be seen that the ecological products of state-owned forest farms in the northwest and northeast regions show a high degree of spatial aggregation, while the supply of ecological products of state-owned forest farms in the southeast region shows a lower degree of spatial aggregation. The supply capacity of ecological products on China’s state-owned forest farms is closely related to their geographical location and resource endowment.

6.2. Conclusions

(1)

This paper proves that the supply of ecological products can be accounted for. From the perspective of time change, the total value of ecological products of state-owned forest farms in 2015 was CNY 6.74 trillion, of which the value of material supply was CNY 6.041 billion, the value of mediation services was CNY 6.74 trillion, and the value of cultural services was CNY 7.503 billion. In 2020, the total value of ecological products of state-owned forest farms was CNY 8.64 trillion, of which the value of material supply was CNY 3.647 billion, the value of mediation services was CNY 8.6 trillion, and the value of cultural services was CNY 28.928 billion. From 2015 to 2020, the total value of ecological products of state-owned forest farms increased by 28.95%.

(2)

From the perspective of the types of ecological products, the proportion of regulatory service ecological products is high. The value of climate regulation, water conservation, carbon fixation, and oxygen release is high, indicating that these products are the core ecological products of state-owned forest farms.

(3)

From the provincial perspective, there are significant differences in the supply of ecological products from state-owned forest farms in various provinces. The state-owned forest farms in all provinces have advantages and disadvantages that match the characteristics of the regions.

(4)

From the perspective of spatial distribution, the supply of ecological products from China’s state-owned forest farms is high in the northwest and low in the southeast, gradually decreasing from the northwest to the southeast. It shows obvious spatial agglomeration, manifested in three distribution modes: “H–H”, “L–L”, and “L–H”.

This study has certain limitations. The lack of data in the database of state-owned forest farms in China’s coastal provinces and parts of the Qinghai–Tibet Plateau may increase the uncertainty of the research results. Additionally, due to the incomplete time coverage of the data, it is impossible to determine the change characteristics of all state-owned forest farms from 2015 to 2020. This paper selected two time cut-off points from 2015 and 2020 for research, which may have affected the research results. In addition, during the selection of accounting parameters and unit prices, the reference materials came from different years and provinces, and there were deviations.

From the current analysis, the direction for further deepening the reform of state-owned forest farms should continue to adhere to ecological positioning and promote the application of ecological product accounting results in the formulation of ecological compensation standards and market-oriented trading of ecological products. Designing the value of different types of ecological products is the realization path, such as the direct market transaction path of material supply ecological products, the ecological industrialization path of cultural service ecological products, and the ecological compensation and financial transfer payment path of regulating service ecological products.