Research on Forest Ecological Product Value Evaluation and Conversion Efficiency: Case Study from Pearl River Delta, China

Abstract

Exploring an effective scientific method to measure the economic benefits of ecological products is of great significance for green development. Based on the InVEST model, this paper, taking the Pearl River Delta (PRD) as an example, evaluated the FEPs value in the PRD from 2000 to 2015; using a super-efficient DEA model, the conversion efficiency of ecological products was estimated, and its temporal and spatial variation characteristics were analyzed using the Malmquist index. The results showed that the value of FEPs in the PRD shot up during 2000–2015, and that the regulation services value is the main part of FEPs, followed by the value of cultural service. The overall conversion efficiency of FEPs is improving. However, cities differ greatly. Technical efficiency is the key driving factor for improving forest product conversion efficiency. The main reasons for the current efficiency loss are redundant inputs and insufficient outputs. This paper also suggests that conversion efficiency is a convincing method to evaluate the degree of transformation of ecological environment resources into economic benefits and the degree of ecological and economic coordinated development.

1. Introduction

With the advancements in urbanization and industrialization in China, the conflict between human beings and ecology has become increasingly prominent [1]. These problems include poor infrastructure [2], poor air quality [3], severe soil pollution [4], and the growth in energy consumption far exceeding domestic energy production [5]. Resolving the conflict between economic development and ecological environment protection is undoubtedly a major challenge. As a factor of production in the economic system, the influence of ecological capital on the regional economy has attracted widespread attention from scholars [6,7]. Through comprehensive governance of the ecological environment, the international community promotes the coordinated development of ecological construction while improving the local socio-economic level, environmental protection, and socio-economic systems [8]. Therefore, an indicator is needed to evaluate the degree of transformation of ecological environment resources into economic benefits to measure the degree of ecological and economic coordinated development in this region [9].

The concept of ecological products has not yet been uniformly defined. Research is more focused on ecosystem services [10] or environmental services (Environmental Services) [11], and some of these are expressed as eco-label products [12]. Ecosystem services refer to the benefits that humans derive directly or indirectly from ecosystems [13], including the provision, regulation, support, and cultural services necessary to sustain life and protect the integrity of ecosystems [14]. As far as the relationship between ecosystem services and ecological products is concerned, on the one hand, ecological products are equated with ecosystem services that generate positive externalities and are collectively referred to as tangible material products and intangible services provided by pure, natural systems; on the other hand, ecological products are divided into narrow and broad concepts. Ecosystem services in the narrow sense are equivalent to ecological products, and ecological products in the broad sense include products or services produced by human activities, in addition to products or services produced by natural systems, including artificial attributes and human labor [15]. Ecological products refer to the collection of goods and services for the purpose of human consumption and utilization through the interaction between ecosystem production and human social production, and constitute the necessities of human life together with agricultural products and industrial products. Forest ecological products are considered to be ecosystem services that use forest resources to provide human beings with high-quality life and production factors within a certain period of time. Forest ecological products have three main characteristics: tradability, which has the transaction attributes of human economic activities [16]; consumption, which has the consumption attributes of human economic activities and contains added value; relevance, which is the relationship between natural resources and human activities. The recognition of ecological products is not only necessary to enhance the supply of ecological services, but also to convert ecological products into economic gains [17,18]. At the national level, converting ecological products into economic benefits has become a priority.

The value conversion of ecological products relies on scientific calculations of the ecological services value. The accounting methods are various. Some scholars adopt the equivalence factor method on the basis of ecosystem classification; this is the service value equivalent for an overall accounting of different ecosystems [19,20]. The functional value method has also been recognized by scholars [21]. Based on field measurements and statistical data, the physical quantity and service quantity of products provided by the ecosystem are calculated, and the total value is obtained by summing them up [22,23]. The former method is widely comparable; however, it is difficult to distinguish the value of each service. The calculation results of the latter method are more authentic and credible, but too many parameters and data are required [24,25]. Research on ecological products mainly focuses on the supply of ecosystem products, ecosystem regulation services, cultural services, and gross ecosystem product (GEP).

Research on the conversion of ecological products to economic value focuses on the analysis of the transformation path. Considering the public goods characteristics of ecological products, a variety of policy tools have been used to convert ecological products into economic profit [26,27,28]. However, there are defects, such as policy support system construction, and lagged market evolution; additionally, competition incentives struggle to meet diversified needs [29]. Other conversion paths include the market path [30] and the social path. The specific conversion methods mainly include ecological protection compensation [31], ecological ownership transactions [32], commercial development [33], green financial support [34], policy incentives [35], and other measures [36]. Different implementation methods for the same ecological product have different effects [37]. Research on the value conversion evaluation of ecological products is still in its infancy, and the evaluation methods mainly include two types based on numerical ratio and efficiency. The former mainly includes the green (green water and lush mountains) gold (gold and silver mountains) index represented by the ratio of GEP to EDP (gross domestic product adjusted by ecological environment factors) [38]. The latter incorporates GEP into the economic efficiency system to measure the value-conversion efficiency of ecological products [39]. The former only uses simple mathematical ratios for evaluation, and the economic significance of the conclusion is slightly insufficient, while the latter can still be further improved in the construction of the evaluation system.

As a production factor existing in the economic system, ecological capital affects the growth of the regional economy [40], and promotes the welfare of the people and wealth accumulation [41]. Therefore, based on the framework of ecological efficiency [42], ecological capital is included in the variables of the ecological economic growth model, and, together with traditional production factors, is the main factor to enhance the coordination between ecology and economy [43]. The ecological product conversion efficiency, representing the efficiency of converting GEP into GDP, was selected to evaluate the degree of transformation of ecological environment resources into economic benefits to measure the degree of ecological and economic coordinated development [44], which is an important basis for the scientific evaluation and continuous optimization of ecological product value. To empirically analyze the forest ecological products (hereafter referred to as FEPs) conversion efficiency, this paper uses the Pearl River Delta (hereafter referred to as PRD) region as an example.

2. Materials and Methods

2.1. Study Area

The nine cities in the PRD are Guangzhou, Shenzhen, Foshan, Zhaoqin, Dongguan, Zhongshan, Zhuhai, Jiangmen, and Huizhou [45] (Figure 1), and they make up the main component of the Guangdong–Hong Kong–Macao Greater Bay Area [46]. In 2020, the PRD had a total land area of 54,766 km², a regional GDP of CNY 8952.4 billion, and a resident population of 78,235,400. With a land area of 0.57%, it houses 5.12% of the population and is responsible for 7.82% of the GDP. The area of forest land is 2.83 million hectares, with a forest-coverage rate of 51.73%. All nine cities have been named “National Forest Cities” and have basically built the country’s first “National-level Forest City Cluster Demonstration Zone” [47]. Therefore, taking the PRD as an example by quantitatively evaluating the value of FEPs and value conversion efficiency in large-scale urban agglomerations, and proposing optimization countermeasures to promote the development of an ecological socio-economic system of high quality, this study will provide a reference for large-scale urban agglomerations to explore the ecological product value conversion mechanisms.

2.2. Method

2.2.1. Calculation Method of GEP

The calculation of GEP refers to the methods of Ouyang [48] and divides GEP into three parts: the value of material products, regulation services products, and cultural products [49] (

Table 1. GEP calculation method.

GEP	Index	Methods
Material product value	Forest products	Market value method
Regulating service value	Conservation of water sources	Shadow price method
	Carbon fixation and oxygen release	Alternative costing method
	Air purification	Alternative costing method
	Soil conservation	Alternative costing method
Cultural service value	Forestry tourism	Travel expense method

). The physical quantity and its distribution characteristics are calculated based on the InVEST model and GIS technology.

$$V_m={\sum }_{i=1}^n{F}_i\times P_i$$

(1)

where $V_m$ is the value of forest material products. $F_i$ is the yield of forest product i. $P_i$ is the market price of forest product i.

The regulating service consists of four parts: the conservation of water sources; carbon fixation and oxygen release; air purification; and soil conservation. Using the shadow price method, we estimated the value of the forest ecosystem’s water conservation services. According to previous studies, the storage cost per unit is 1.5 CNY/m³ [50]. The Water Balance Equation was used to estimate the output of aquatic products. Monthly water production is as follows:

$$WY=PPT-ET\pm S\approx PPT-ET$$

(2)

where $S$ is the change in water storage capacity. $PPT$ is monthly precipitation. $ET$ is the actual monthly evaporation amount, which can be estimated as follow:

$$ET\left(R,t\right)=\frac{A\ast R}{A+B\ast R^2\ast EXP\left(-\frac{C\ast t}{235+t}\right)}$$

(3)

Among them, A, B, and C are empirical coefficients, which are related to the temperature in various places. Therefore, the values in the PRD region are 3100, 1.8, and 34.4, respectively. $R$ is the monthly precipitation (mm), and $t$ is the monthly average temperature (°C).

The calculation of the carbon fixation and oxygen release value adopts the method of alternative cost. This study uses the average value of CNY 272.65/t of China’s afforestation cost per ton of CO₂ fixed in the forest ecosystem calculated in the relevant research [51]. The net primary production (NPP) of the ecosystem was evaluated to measure its carbon sequestration and oxygen release. The productivity of vegetation is influenced by natural factors such as climate, soil, topography, and human factors [52]. This study used the CASA (Carnegie Ames Stanford Approach) model [53] to estimate NPP and further calculate the CO₂ absorption of vegetation.

Alternative cost methods have also been used to calculate the value of air purification based on an assessment of the amount of air pollutant purification by the forest ecosystem. With reference to relevant research, the treatment costs of ${SO}_2$,${NO}_X$, and retained dust are 1200, 630, and CNY 150/t, respectively, and the purification amounts per unit area of forest ecosystem for ${SO}_2$,${NO}_X$, and retained dust are 22.64, 0.82, and 3831.7 $\mathrm{t}/({\mathrm{km}}^2·\mathrm{a})$, respectively.

The soil conservation value of forest ecosystems is mainly reflected by a reduction in sediment deposition in rivers and lakes, and a reduction in soil-erosion-induced reservoir loss and soil fertility loss. Soil loss is calculated using the restoration cost method, which is a substitute for the value of soil protection. Potential soil erosion is estimated as:

$$A_p=R\times K\times LS$$

(4)

Actual soil erosion is estimated as:

$$A_r=R\times K\times LS\times C\times P$$

(5)

The soil conservation service capacity provided by the ecosystem is

$$A_c=A_p-A_r$$

(6)

where R is the rainfall erosion factor, which is related to rainfall amount, rainfall duration, intensity and kinetic energy. It is generally reflected by the product of heavy rain kinetic energy and the maximum 30 min rainfall intensity. The daily rainfall erosivity model is applied to calculate rainfall erosion:

$$R_i=\alpha {\sum }_{j=1}^k{\left(P_j\right)}^{\beta }$$

(7)

where $R_i$ is the erosive force in the i-th half-month period (MJ mm hm⁻² h⁻¹), $k$ and $P_j$, respectively represent the number of rainfall days in the half-month period and the daily rainfall on the j-th day. The daily rainfall is required to be ≥12 mm, otherwise it will not be calculated. $\alpha$ and $\beta$ are model parameters, estimated based on rainfall characteristics:

$$\begin{gathered} \beta =0.8363+\frac{18.144}{p_{d12}}+\frac{24.455}{p_{y12}} \\ \alpha ={21.586\beta }^{-7.1891} \end{gathered}$$

(8)

where $p_{d12}$ is the daily average rainfall with daily rainfall ≥12 mm, and $p_{y12}$ is the annual rainfall with daily rainfall ≥12 mm.

$K$ is the soil erodibility factor, which reflects the ease with which soil is eroded and transported by rainwater. The EPCI model for estimating soil erodibility is established based on the physical structure of the soil (percentage of sand, silt, and clay) and the content of organic matter:

$$\begin{gathered} K=\left\{0.2+0.3exp\left[-0.0256S_d\left(1-S_i/100\right)\right]\right\}\times {\left[\frac{S_i}{\left(Cl+S_i\right)}\right]}^{0.3}\times \left\{1-\frac{0.25C}{\left[C+\exp (3.72-2.95C\right]}\right\}\times \\ \left\{1-\frac{0.7\times (1-\frac{S_d}{100})}{\left\{1-\frac{S_d}{100}+exp\left[-5.51+22.9\left[-5.51+22.9\left(1-S_d/100\right)\right]\right]\right\}}\right\} \end{gathered}$$

(9)

where $S_d$ is the sand content, $S_i$ is the powder content, $Cl$ is the clay content, and $C$ is the organic carbon content. $L$ and $S$ are slope length and slope factor, respectively, reflecting the impact of topography and landforms on soil erosion. The slope length factor is calculated as follows:

$$L={\left(\lambda /22.13\right)}^{\alpha }$$

(10)

where $L$ is the amount of soil erosion normalized to a slope length of 22.13 m; $\lambda$ is the slope length.

$S$ is the slope factor, calculated as follows:

$$S=\left\{\begin{array}{c}10.8\sin \theta +0.03 \left(\theta <5°\right)\\ 16.8\sin \theta -0.50 \left(5°\le \theta \le 10°\right)\\ 21.9\sin \theta -0.96 \left(\theta \ge 10°\right)\end{array}\right.$$

(11)

$C$ is the vegetation coverage and management factor, which is mainly affected by surface land use type and vegetation coverage. $P$ is the soil and water conservation measure factor. The values of $C$ and $P$ are derived from relevant research on the PRD region [54].

According to the “Forest Ecosystem Service Function Evaluation Specification”, the cost of manually digging 1 m³ of Class I and II soil is CNY 8.4/m³ [55]. The soil conservation amount is converted into the volume of the topsoil layer, and is then multiplied by the cost of excavating 1 m³ of soil to obtain the annual soil conservation value of the ecosystem.

2.2.2. Method of Evaluation for Ecological Product Conversion Efficiency

Data envelopment analysis (DEA) is a method of operations research and is used in the study of economic production boundaries. This method is generally used to measure the production efficiency of some decision-making units. The DEA model can effectively identify multiple inputs and multiple outputs of efficiency and is currently the most well-constructed efficiency measurement method, widely used by scholars in many research fields [56]. The super-efficient DEA model further evaluates units that are at the same frontier [57]. Therefore, the DEA model with input-oriented constant returns to scale is used in this paper, and can be specifically expressed as

$$\left\{\begin{array}{c}\mathbf{m}\mathbf{i}\mathbf{n}\left[\mathit{\theta }-\mathit{\epsilon }\left({\displaystyle \sum _{\mathit{i}=\mathbf{1}}^{\mathit{m}}}{\mathit{S}}_{\mathit{i}}^{-}+{\displaystyle \sum _{\mathit{r}=\mathbf{1}}^{\mathit{s}}}{\mathit{S}}_{\mathit{r}}^{+}\right)\right]\\ \mathit{s}.\mathit{t}.{\displaystyle \sum _{\begin{array}{c}\mathit{j}=\mathbf{1}\\ \mathit{j}\ne \mathit{k}\end{array}}^{\mathit{n}}}\mathit{\lambda }\mathit{j}\mathit{x}\mathit{i}\mathit{j}+{\mathit{S}}_{\mathit{i}}^{-}=\theta \mathit{x}\mathbf{0},\mathit{i}=\mathbf{1},\mathbf{2},\cdots ,\mathit{m}\\ {\displaystyle \sum _{\begin{array}{c}\mathit{j}=\mathbf{1}\\ \mathit{j}\ne \mathit{k}\end{array}}^{\mathit{n}}}\mathit{\lambda }\mathit{j}\mathit{y}\mathit{r}\mathit{j}-{\mathit{S}}_{\mathit{r}}^{+}=\mathit{y}\mathbf{0},\mathit{r}=\mathbf{1},\mathbf{2},\cdots ,\mathit{s}\\ \lambda \mathit{j}\ge \mathbf{0},\mathit{j}=\mathbf{1},\mathbf{2},\cdots ,\mathit{n},{\mathit{S}}_{\mathit{r}}^{+}\ge \mathbf{0},{\mathit{S}}_{\mathit{i}}^{-}\ge \mathbf{0}\end{array}\right.$$

(12)

where the decision-making unit’s super-efficiency value is given by $\theta$, which represents the relative forest ecological product value-conversion efficiency of each city; the non-Archimedean infinitesimal is given by $\epsilon$; $m,s,n$ stand for input variable dimension, output variable dimension, and number of decision-making units, respectively; $S_{i,}^{-} S_r^{+}$ represents the slack variable; the input variables and output variables are given by $xij$ and $yij$, respectively; $\lambda$ is the weight coefficient. $\theta$ < 1 means that the decision-making unit has not achieved the optimal efficiency, while $\theta$ > 1 means that it has achieved the optimal efficiency.

Based on the Total Factor Productivity (TFP) index, this study uses the productivity index decomposition method to identify the main factors leading to production inefficiency. Referring to Cooper et al. [58], the sources of the inefficiency items of multi-agent and multi-efficiency units are disassembled.

$$\begin{gathered} IE=\overrightarrow{S_{}^t}=I{E}_{}^x+I{E}_{}^y \\ =\frac{1}{2N}{\sum }_n^N\frac{s_n^x}{q_n^x}+\frac{1}{2M}{\sum }_m^M\frac{s_m^y}{q_m^y} \end{gathered}$$

(13)

where ${IE}^x$ and ${IE}^y$ are the inefficiency values of factor input and output, respectively.

Since there are input variables such as ecological products, land, labor, and capital, Formula (13) can be further disassembled to obtain detailed information that leads to inefficiency.

$$IE={IE}_{GEP}+{IE}_{land}+{IE}_{labour}+{IE}_{capital}$$

(14)

Combined with the constructed directional distance function and the characteristics of the Malmquist–Luenberge productivity index, the efficiency subject is disassembled.

$$M{L}_t^{t+1}=\underset{TF{P}^x}{\underbrace{I{E}^x\left(t\right)-I{E}^x(t+1)}}+\underset{TF{P}^y}{\underbrace{I{E}^y\left(t\right)-I{E}^y(t+1)}}$$

(15)

By dismantling the efficiency subject, the influence of the input factor (TFP^x) and output ($TF{P}^y$) on the total output ($TFP$) can be analyzed.

The Malmquist index can clearly reflect the trend and composition of efficiency changes [44]. TFP consists of Comprehensive Technical Efficiency (EC) and Technical Progress (TC), among which EC can be disassembled into Scale Efficiency (SE) and Pure Technical Efficiency (PE). Therefore, to dynamically analyze the changes in FEPs conversion efficiency in the PRD, this paper used the Malmquist index.

2.3. Index Construction

The indicator system used to estimate forest ecological product value conversion efficiency includes input and output parts (

Table 2. Input–output indicators of forest ecological product value conversion efficiency.

Category	Primary Index	Secondary Index	Tertiary Index
Input indicators	The value of forest ecological products	Material product value	Forest products
		Regulating service value	Conservation of water sources
			Carbon fixation and oxygen release
			Air purification
			Soil conservation
		Cultural service value	Forestry tourism
	Labor	Number of forestry practitioners
	Physical capital	Amount of forestry fixed assets investment
Output indicators	Economic growth	Output value of forestry industry

). The input indicators are regional GEP, completed investment in forestry fixed assets, and the number of forestry industry employees. Considering that economic growth is mostly reflected in the growth of the industry, this paper chooses the output value of forestry as an indicator.

2.4. Data Sources

This paper used socioeconomic data, meteorological data, remote sensing data, soil data, etc., to estimate the value of forestry products and their conservation efficiency (

Table 3. Data sources.

Classification	Data	Data Sources
Socioeconomic data	Forest products	China Forestry Statistical Yearbook; Guangdong Statistical Yearbook; Guangdong Rural Statistical Yearbook; Statistical Yearbook of various cities (http://stats.gd.gov.cn/gdtjnj/index.html (accessed on 20 August 2019))
	Number of forestry practitioners
	Forestry fixed assets investment
	GDP
Meteorological data	Daily average rainfall	National Meteorological Science Data Center (http://data.cma.cn/ (accessed on 20 August 2019))
	Solar radiation
	monthly average temperature
Remote sensing data	land use	Chinese Academy of Sciences cloud platform
	NDVI data	NASA MODIS (MOD13Q product)
	Soil physical structure components	scientific data center of cold and dry areas (http://bdc.casnw.net/ (accessed on 20 August 2019))
	DEM data	geospatial data cloud (https://www.gscloud.cn/ (accessed on 20 August 2019))

). Socioeconomic data mainly came from the “China Forestry Statistical Yearbook”, “Guangdong Statistical Yearbook”, “Guangdong Rural Statistical Yearbook”, and the “Statistical Yearbook” of various cities from 2000 to 2016. Meteorological data including the daily average rainfall, solar radiation, and monthly average temperature were collected from meteorological stations in Guangdong Province through the National Meteorological Science Data Center. The data on land use were sourced from the Chinese Academy of Sciences cloud platform for resources and the environment. The NDVI data were obtained from NASA MODIS (MOD13Q product). The soil physical structure components were from the scientific data center of cold and dry areas. The DEM data were taken from the geospatial data cloud.

3. Results and Analysis

3.1. Forest Ecological Product Value

During the period 2000 to 2015, the value of FEPs in the PRD ranged from CNY 222.381 billion to 314.051 billion (calculated at constant prices in 2000) (Figure 2). In 2015, the total value of forestry ecological products in the PRD was about 0.97 times the total forestry output value. Among them, the regulatory services value was the highest, CNY 242.844 billion, accounting for 77.33% of the total value; the value of cultural services was CNY 66.36 billion, accounting for 21.13% of the total value; the value of material products was CNY 4.847 billion, accounting for 1.54% of the total value (

Table 4. FEPs value in the PRD in 2015.

Ecological Products	Value/RMB 100 Million	Proportion (%)
Material products	48.47	1.54%
Regulatory services	2428.44	77.33%
Water retention	47.25	1.50%
Carbon fixation and oxygen release	222.7	7.09%
Air purification	77.21	2.46%
Soil conservation	2081.27	66.27%
Cultural services	663.6	21.13%
Sum	3140.51	100%

). Six ecological products can be ranked in order of value: soil conservation > cultural service > carbon fixation and oxygen release > air purification > material product > water retention. Among them, the values of soil conservation and cultural services accounted for 87.40% of the total, making up the largest proportion.

During the period 2000 to 2015, a fluctuating upward trend was seen in the value of FEPs in the PRD (Figure 3). Following a slow increase in 2000–2005, there was a downward trend in 2010, but then a substantial increase. The total value increased from CNY 232.381 to 314.051 billion from 2000 to 2015, with an increase of 35.14%. In terms of ecological product composition, material products and cultural services values both showed an upward trend, while the value of regulatory services rose slightly but fluctuated. Specifically, the value of material products increased from CNY 2.183 billion to 4.837 billion from 2000 to 2015, an increase of 122%. The regulatory products showed a fluctuating upward trend, while the value of carbon fixation and oxygen release showed a slow upward trend after a sharp decline. As for cultural services, the value shot up from CNY 35 million in 2000 to CNY 66.35 billion in 2020, showing the most significant increase.

The distribution of FEPs in the PRD is quite different (

Table 5. The value of forest ecological products in the Pearl River Delta cities in 2015.

City	Guangzhou	Shenzhen	Zhuhai	Foshan	Jiangmen	Zhaoqin	Dongguan	Zhongshan	Huizhou
Material products	2.47	0.12	0.2	0.78	4.83	37.02	0.21	0.01	2.84
Regulatory services	269.57	55.62	31.27	54.09	365.92	986.11	35.17	29.26	601.43
Water retention	6.29	0.99	0.51	1.34	6.91	18.11	0.91	0.52	11.67
Carbon fixation and oxygen release	23.64	5.76	2.58	6.06	37.01	86	3.47	2.58	55.61
Air purification	8.14	2.08	1.38	1.84	11.69	29.88	2.1	0.85	19.26
Soil conservation	231.51	46.78	26.8	44.85	310.31	852.13	28.69	25.31	514.89
Cultural services	293.26	46.78	28.9	56.95	37.37	26.05	40.6	22.52	33.19
Sum	565.3	180.5	60.37	111.81	408.11	1049.18	75.98	51.79	637.46

), being higher in Guangzhou, Zhaoqing, and Huizhou. The main ecological products in Guangzhou are cultural service products, while in Huizhou and Zhaoqing, they are regulatory service products with a high soil conservation value. The FEPs values in Zhuhai, Dongguan, and Zhongshan are relatively low.

3.2. Comparison of Forestry Output Value and Forest Ecological Product Value

Different from FEPs, the total output value of forestry in the PRD showed a continuous upward trend (Figure 4). From 2005 to 2015, the output of the forestry industry rose rapidly, benefiting from the rapid development of the secondary and tertiary industries, while the value of FEPs showed a downward trend between 2005 and 2010, mainly due to the decline in the regulating services value; water conservation, and carbon fixation and oxygen release values also declined. However, in the following five years, the FEPs value greatly improved. This growth mainly came from the improvements in cultural value. In terms of cities, the output values of Guangzhou, Jiangmen, Zhaoqing, and Huizhou are higher than the value of FEPs, while the value of FEPs is higher in other cities.

3.3. Spatio-Temporal Characteristics of FEPs Value-Conversion Efficiency

3.3.1. FEPs Value-Conversion Efficiency

Based on the index in Table 2, this paper used MATLAB to measure the value-conversion efficiency of FEPs every five years from 2000 to 2015 in nine cities in the PRD. The conversion efficiency of FEPs in the PRD differs. Specifically, Guangzhou, Shenzhen, Zhaoqing, Dongguan, and Zhongshan achieved relatively high efficiencies, while Zhuhai, Foshan, Jiangmen, and Huizhou achieved relatively low efficiencies (

Table 6. FEPs value conversion efficiency from 2000 to 2015.

City	2000	2005	2010	2015	Average
Guangzhou	0.028	0.032	0.186	1.936	0.546
Shenzhen	0.013	0.006	1.121	2.772	0.978
Zhuhai	0.028	0.004	0.358	0.137	0.132
Foshan	0.073	0.018	2.805	0.406	0.826
Jiangmen	0.132	0.059	2.270	0.321	0.696
Zhaoqin	2.253	1.075	0.423	1.001	1.188
Dongguan	0.046	0.003	1.320	4.502	1.468
Zhongshan	0.029	0.005	1.258	1.493	0.696
Huizhou	0.444	0.163	0.524	0.048	0.295
Average	0.338	0.152	1.141	1.402

). In 2015, among the nine prefectures and cities in the PRD, five cities with a high efficiency remained effective, while the conversion efficiency of FEPs in Huizhou in 2015 was only 4.8%. From the perspective of changing trends, the conversion efficiency showed a downward trend for Zhaoqing and Huizhou, from 2.253 and 0.445 in 2000 to 1.001 and 0.048 in 2015, respectively. Guangdong, Shenzhen, Dongguan, and Zhongshan maintained a continuous growth trend, rising from 0.028, 0.013, 0.046, and 0.029 in 2000 to 1.936, 2.772, 4.502, and 1.493 in 2015, respectively. Zhuhai, Foshan, and Jiangmen, which also had an increasing trend, reached their peak efficiencies in 2010, being 0.358, 2.805, and 2.270, respectively; however, these values dropped to lower levels in the following five years. It is worth mentioning that although Zhaoqing experienced a fluctuating downward trend, in 2000, 2005, and 2015, its conversion efficiency was effective. Nevertheless, there are large differences in conversion efficiency between cities in the PRD, and the overall trend of fluctuating growth can be seen.

3.3.2. Dynamic Analysis of Value-Conversion Efficiency of FEPs

The dynamic analysis of the conversion efficiency of FEPs in the PRD was conducted using the Malmquist index. From a regional perspective (

Table 7. TFP of FEPs in 2000–2015.

	EFF	TE	PE	SE	TFP
2000–2005	0.524	4.725	0.838	0.626	2.477
2005–2010	2.885	0.076	1.285	2.245	0.218
2010–2015	1.276	1.141	1.105	1.155	1.456
Average	1.245	0.742	1.06	1.175	0.924

), the average TFP of the conversion efficiency of the PRD is 0.924, indicating that during the study period, the value of FEPs did not significantly correspond to an economic benefit. This varied greatly in other years, from 2.477 in 2000–2005, and rapidly dropping to 0.218 in 2005–2010. However, in 2010–2015, it rose quickly to 1.456, showing a more violent fluctuation trend. Specifically, the average value of the technical efficiency change index (EC) is 1.245, indicating that the level of resource utilization in the PRD has improved significantly. The technical efficiency fluctuated from 2000 to 2015. Due to the double impact of the pure technical efficiency change index (PE) and scale efficiency change index (SE), it rose from 0.528 to 2.885 during 2000–2010, and then fell to 1.276 in 2015. The average technological progress index (TE) is 0.724, and the lowest value is seen in the 2005–2010 period, which shows a synchronous fluctuation in the total factor productivity change index (TFP), indicating a limited level of technological advancement; therefore, the promotion effect of technological innovation on improving conversion efficiency is not obvious.

The difference in the pure technical efficiency change index between cities in the PRD is small, and the change in the EFF is mainly caused by the change in SE (

Table 8. TFP of FEPs of each city in 2000–2015.

	EFF	TE	PE	SE	TFP
Guangzhou	1.557	0.671	1.524	1.021	1.044
Shenzhen	0.803	0.816	1	0.803	0.655
Zhuhai	2.134	0.491	1.018	2.095	1.049
Foshan	2.563	0.759	1.022	2.507	1.946
Jiangmen	0.978	1.087	1.060	0.922	1.063
Zhaoqin	1	0.989	1	1	0.989
Dongguan	0.571	0.418	1	0.571	0.239
Zhongshan	1.883	0.591	1	1.883	1.112
Huizhou	1	1.254	1	1	1.254
Average	1.245	0.742	1.060	1.175	0.924

). The differences between cities are mainly reflected in the TE. The TFP values of Guangzhou, Zhuhai, Foshan, Dongguan, Shenzhen, and Zhongshan all exceeded 1, Zhaoqing was close to 1, at 0.989, and, in Shenzhen and Dongguan, the values were less than 1. The city with the highest TFP was Foshan. Regarding the changing trends, the TFP of each city was relatively high during 2000–2005 and 2010–2015, and fell sharply during 2005–2010. Overall, the TFP of most cities showed a downward trend between 2000 and 2015.

3.3.3. The Input–Output Slack Rate of the Conversion Efficiency of FEPs Products

All cities in the PRD have experienced redundant input and insufficient output during FEPs value conversion (

Table 9. Redundancy rate and insufficient rate of each city in 2015.

	Redundancy Rate					Insufficient Rate
City	Material Products	Regulatory Products	City	Material Products	Regulatory Products	City
Guangzhou	3.31	1.37	Guangzhou	3.31	1.37	Guangzhou
Shenzhen	2.48	0.02	Shenzhen	2.48	0.02	Shenzhen
Zhuhai	0.99	0.99	Zhuhai	0.99	0.99	Zhuhai
Foshan	0.56	0.72	Foshan	0.56	0.72	Foshan
Jiangmen	0.44	0.45	Jiangmen	0.44	0.45	Jiangmen
Zhaoqing	0	0.01	Zhaoqing	0	0.01	Zhaoqing
Dongguan	2.53	12.06	Dongguan	2.53	12.06	Dongguan
Zhongshan	0	0	Zhongshan	0	0	Zhongshan
Huizhou	0.99	0.85	Huizhou	0.99	0.85	Huizhou

). The lack of output is more prominent. Zhuhai, Foshan, Jiangmen, and Huizhou have not realized the effective allocation of resources, and there are many deficiencies in their input and output indicators. Both Zhuhai and Huizhou have a large deficit in their forestry output value. Foshan has a 90% redundancy in fixed capital investment. Jiangmen has a surplus of more than 90% in both cultural service value and labor input. The conversion efficiency of FEPs in Guangzhou, Shenzhen, Zhaoqing, Dongguan, and Zhongshan has reached the production front, and the efficiency of production resource allocation has reached an effective level, but there is still room for optimization in terms of input. Guangzhou, Shenzhen, and Dongguan all have a certain degree of overinvestment in material products, while overinvestment in regulatory services has appeared in Dongguan. There is also a certain degree of redundancy in cultural service investment in Dongguan and Zhongshan. The surplus of forestry labor is more prominent in Shenzhen, as is the investment in fixed capital. Therefore, it is still necessary to optimize investments in ecological products across various cities.

4. Conclusions

This paper evaluates the forestry ecological products values of the PRD from 2000 to 2015, and bases these on the input–output perspective to estimate the conversion efficiency of FEPs using the Super-SBM model, Malmquist index, and InVEST model. The conclusions are noted below.

First, the total value of FEPs in the PRD is fluctuating upwards. In 2015, the value of FEPs reached CNY 314.051 billion, with an increase of 1.35 times compared with the value of CNY 2321.381 billion in 2000. The regulatory service value is the main component of FEPs, followed by the cultural service value. Specifically, soil conservation and forest recreation are the main FEPs in the PRD, indicating that forests regulate climate in a significant way, especially in regard to water and soil conservation. With the development of the economy, the value of cultural services in FEPs has become increasingly prominent, and is inseparable from the construction of the PRD National Forest City Group [47] and forest parks, and the excavation of ecological space. However, the value of FEPs is still slightly lower than the total output value of the forestry industry, suggesting that the development of the forest ecological industry is lagging, and that there is still room for improvement in ecological civilization construction and value conversion for ecological products in the PRD.

Second, the conversion efficiency of FEPs in the PRD has continued to rise, and it achieved overall efficiency in 2010, indicating that the PRD has made remarkable achievements in the exploration and construction of the forest cities cluster. However, the imbalance in conversion efficiency among cities cannot be ignored. Although the overall conversion efficiency of FEPs in the four cities—Zhuhai, Foshan, Jiangmen, and Huizhou—is relatively low, other cities still show a trend of fluctuating growth. With the comprehensive construction of the national forest city group agglomeration and the in-depth development of the “Forest Chief System”, the PRD will be able to make better use of its forest ecological resources, thereby promoting forest product value conversion. Regardless of whether this development involves the construction of forest parks or forest towns, it will vigorously activate FEPs and provide multiple paths for the conversion of their values.

Third, the TFP of FEPs in the PRD fluctuates greatly. The total factor productivity is below one, but technical efficiency is above one, and the technological progress is below one, indicating that FEP conversion efficiency has been changed primarily due to forestry technical efficiency improvements in the PRD. Technology advancements in forestry, however, have yet to show positive results. Through enhancing the efficiency of FEP conversion, it is necessary to establish a corresponding forestry technology service system urgently, increase the promotion and application of new technology, and improve the conversion efficiency of FEPs through technological progress.

Fourth, the PRD’s loss of conversion efficiency is primarily due to excessive inputs and insufficient outputs, with specific reasons for variation in the loss of efficiency.

5. Discussion

Based on the value calculation of the forest ecological products, this paper constructs an input-output index system from the perspective of efficiency, which provides a new perspective for evaluating the value transformation of forest ecological products.

The forest ecosystem is the main body of the terrestrial ecosystem. It provides humans with a variety of regulatory ecological products such as water conservation, carbon fixation and oxygen release, wind and soil fixation, air purification, and climate regulation, as well as supply ecological products such as timber, economic forest fruits, and biomass energy [59]; and cultural ecological products such as tourism and health care, landscape value, etc. [60]. However, areas rich in forest resources and ecological products are mostly areas with relatively backward economic development [61]. Considering that forest ecological products maintain the livelihood of forest farmers, the evaluation of the value conversion of ecological products is an important factor in measuring the economic development of forest areas. Through the calculation of the value of forest ecological products in the PRD region, we found that during the research period, cultural services showed a significant increase. The development of forest tourism resources is an explicit means to realize the economic development of forest areas [62,63]. Government departments can promote the value of ecological products by innovating forest ecological industries.

The economic benefits brought by forestry material products and cultural products have been taken into consideration, but the role of regulating services in realizing economic benefits is not yet obvious [64]. With the development of the carbon trading market, carbon sinks play an important role in forest environmental benefits, and their economic value should be included in the forest ecological product value conversion evaluation system [65]. Government departments should further improve the forest ecological protection compensation mechanism and promotion mechanism.

From the perspective of conversion efficiency, it is urgent to establish a forestry technology service system, promote the application of new technologies and new products, and improve conversion efficiency through technological progress. Institutional innovation is another effective means to improve conversion efficiency. The focus should be on developing the “Forest Chief System”, the development and construction of forest parks and forest towns, promoting the precise connection between the supply and demand of forest ecological boards, promoting the trading of forest ecological resources rights and interests, and improving the protection level of forest ecological resources.

This study is a useful attempt to evaluate the value transformation of forest ecological products in large-scale urban agglomerations, and there is still room for optimization. Restricted by existing data, forestry output can be further refined, and the indirect economic benefits could be included. At the same time, the cost of ecological damage caused by forestry economic development could also be taken into consideration.