Simulation and Analysis of Changes in Carbon Storage and Ecosystem Services Against the Backdrop of Land Transfer: A Case Study in Lvzenong Park

Abstract

Land transfer is a key issue affecting ecosystem services and carbon storage. Land use change can promote or inhibit carbon emission. To study these impacts, a carbon flow model for Lvzenong Park, Yi County, Taihang Mountains, China, was developed using Odum’s energy systems language. The model simulates carbon flow and storage changes from 2015 to 2115 and analyzes changes in ecosystem service values using the equivalent factor method. Finally, two scenarios of economic development and carbon sink protection are set, and the evolution characteristics of carbon storage and ecosystem service under different scenarios are discussed. The key findings include the following: (1) From 2015 to 2115, carbon storage in apple orchards, forests, and grassland systems initially increase then decrease, while soil carbon storage declines steadily and the overall atmospheric CO₂ carbon pool increases. Ecosystem service value decreases by 71.30%. (2) Economic development positively affects apple orchards and atmospheric CO₂ carbon storage but negatively impacts grassland carbon storage. Conversely, carbon sink protection benefits grassland and soil carbon storage but harms the atmospheric CO₂ carbon pool. (3) Under economic development, ecosystem service values initially increase then decline, while under carbon sink protection, they generally rise. These findings provide scientific guidance for formulating land transfer policies and promoting low-carbon development in mountainous regions.

1. Introduction

As the world’s second largest economy, China has become the world’s largest greenhouse gas emitter. At the 75th session of the United Nations General Assembly, the Chinese government pledged to peak its carbon emissions before 2030 and achieve carbon neutrality before 2060 (the “dual carbon” goal) [1]. Land use change is an important source of carbon emissions and a key factor affecting ecosystem services, such as water sources, soil quality, and biodiversity. Crop rotation and mulch planting on cultivated land can significantly contribute to maintaining soil fertility while reducing reliance on synthetic fertilizers. The implementation of soil and water conservation techniques effectively mitigates soil erosion and nutrient loss. Afforestation along waterways not only reduces sediment accumulation, but also enhances water quality. Additionally, cultivating crops within tropical woodlands supports the maintenance of biodiversity [2,3]. In 2020, global carbon emissions resulting from land use change (including deforestation, agricultural expansion, accelerated urbanization process, etc.) were estimated at 0.9 ± 0.7 GtC, constituting approximately one-third of the total carbon emissions attributed to human activities since the Industrial Revolution. Land use change has emerged as the second largest contributor to carbon emissions following fossil fuel combustion [4]. To achieve the ’dual carbon’ goal, the Chinese government has implemented measures to reduce carbon emissions and increase carbon storage. Storing carbon plays a key role in maintaining ecosystem stability, and can effectively absorb CO₂ from the atmosphere, which is conducive to increasing ecosystem carbon storage and mitigating climate warming, and is an important link in the global carbon cycle [5]. As an important means of promoting land use efficiency, land transfer behavior often accompanies changes in land use forms, which can lead to changes in ecosystem carbon storage and ecosystem service value by altering the structure and function of ecosystems [6,7]. Therefore, in the context of the “dual carbon” target, accurately quantifying the impact of land use changes on carbon storage and ecosystem services during land transfer is crucial for improving ecosystem carbon storage and formulating policies that balance economic development and environmental protection.

As a type of land use change, land transfer is committed to encouraging the adoption of sustainable agricultural methods that minimize the use of chemical fertilizers. The purpose is to reduce soil erosion and nutrient loss, inhibit carbon emissions, reduce environmental pollution, and prevent ecological damage [3]. Land transfer is a necessary path for the development of modern agriculture, which is conducive to optimizing land resource allocation, effectively improving rural land use efficiency and labor productivity, ensuring food security and the supply of major agricultural products, achieving stable and increased agricultural production, and steadily increasing farmers’ income [8]. Through land transfer, farmers have freed themselves from the constraints of land and achieved a scale effect of land management. The Taihang Mountains in Hebei Province serve as a crucial ecological barrier for the Beijing–Tianjin–Hebei region, playing a pivotal role in supporting both the production and ecological functions of Beijing and Tianjin. The agricultural development in the Taihang Mountains region is characterized by a sluggish pace. The irrational utilization of land resources has resulted in a significant phenomenon of land abandonment, thereby exacerbating the degradation of the ecological environment. Therefore, it is of paramount significance to promote emission reduction and sink enhancement while ensuring economic development in order to achieve the dual carbon target and ensure the sustainable utilization of land resources in the Beijing–Tianjin–Hebei region.

The main purpose of our research is to understand the changes in carbon storage and ecosystem services under different land use scenarios, aiming to reveal the process mechanism of carbon storage and ecosystem services formation in the “economic development scenario” and “carbon sink protection scenario” over a medium-to-long-term (100 years) time span, and provide a valuable reference for evidence-based land use policies in the Taihang Mountains of Hebei Province. It is noteworthy that the Lvzenong Modern Ecological Agriculture Park in Yi County, Hebei Province, as a quintessential example of successful land transfer in the region, is an agricultural science and technology project focused on by the county government. It not only facilitates the transformation of agriculture, but also significantly promotes local economic development and enhances farmers’ income. This study focuses on Lvzenong Park in Yi County, Hebei Province, as the research subject. A carbon flow model based on the land transfer process was established using Odum’s energy system language (ESL) model [9]. The changes in carbon storage across different ecosystems during the land transfer process from 2015 to 2115 were simulated. Furthermore, the value of ecosystem services was evaluated using the equivalent factor method of unit area value, and the impacts of land transfer on carbon storage and ecosystem services were explored under two land use scenarios. This research can serve as a valuable reference for promoting green and low-carbon development, as well as informing the formulation of evidence-based land use policies in the future in the Taihang Mountains of Hebei Province.

2. Literature Review

The research on the impact of land transfer on ecosystem services and carbon storage focuses on three areas: (1) rural land transfer behavior, as well as influencing factors and effects; (2) the verification or prediction of the impact of land use change on carbon storage and ecosystem services; and (3) summarizing research methods on the impact of land use change on carbon storage.

Land transfer originated from the rapid urbanization that led to rural decline, farmland abandonment, and rural labor loss [10], with the aim of improving land use efficiency and promoting sustainable development. The rural land defined in this paper includes uninhabited arable land, grassland, forest land, etc. Regarding land transfer behavior, scholars have mainly studied different types of land use changes, such as farmland invasion of natural vegetation, reductions in forests and water bodies, the expansion of shrubs and forests, and using trees as buffer zones [11,12,13,14]. Along with changes in land functions, the above land transfer behaviors are also influenced by multiple factors, such as geographical environment, economic development level, government aid policies, the transfer of surplus rural labor, rural household economic status, non-agricultural employment stability, household livelihood capital, and rural financial markets [10,15]. For example, during the period of 1900–2000, the socio-economic transformation in Spain became an important factor driving the rapid transition from mountainous areas to transitional forests, and the expansion of forests improved local regulations and supply services [12]. In the short term, land transfer is beneficial for promoting an increase in farmers’ income [16,17], reducing multidimensional poverty [18,19,20], and improving land use efficiency [21,22,23], which is reflected in economic, environmental, and social benefits [24,25,26]. In addition, scholars have also studied the synergistic effects caused by land use change in the long run [27,28,29]. A study found that in areas with sufficient water quality in the Yellow River Basin, combining grasslands, shrubs, and forests can effectively coordinate the goals of sediment retention and carbon sequestration in the long term [30]. In Norway, using trees as buffer zones reduces carbon storage and soil nutrient loss, thereby increasing the long-term yield of crops such as barley [13].

At present, there is a lack of research on the impact of land transfer behavior on carbon storage and ecosystem services. Scholars mainly explore the relationship between land use change and carbon storage or ecosystem services [31,32,33,34]. Relevant research focuses on the impact of land use change on regional ecosystem carbon storage and ecosystem services from a multi-scale perspective, as well as predicting the spatiotemporal evolution mechanism of future carbon storage or ecosystem services under various land use scenarios. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model is capable of simulating alterations in the quality and value of ecosystem services under diverse land cover scenarios [35]. It offers a scientific foundation for decision-makers to strike a balance between the benefits and impacts of human activities, and enables the spatialization of the quantitative assessment of the value of ecosystem service functions [36]. Leh et al. used the InVEST model to verify that land use changes in Arkansas farms and dairy operations led to a reduction in ecosystem service losses, while overall land use changes had the most significant impact on carbon storage and biodiversity [37]. Sadat et al. used the InVEST model to verify that the land use changes in the Raniyan River Basin in Iran from 2000 to 2020 have directly affected the ecosystem service structure of the basin, leading to a significant reduction in ecosystem services [38]. Yin et al. found, based on the InVEST model, that under the scenario of urban expansion in the Miaodao Islands, the areas of forest land, grassland, and cultivated land all show a decreasing trend, carbon storage generally decreases, and ecosystem services depend on the synergistic effect of internal functions [39]. In addition, Romero et al. used the IPPC method to validate a 24% increase in carbon storage in forest ecosystems in southern Spain over the past 50 years (1957–2007), mainly occurring in coniferous, eucalyptus, and mixed forest land use scenarios [40]. Masalvad et al. conducted a study on the Telangana region of India based on CA–Markov models and machine learning techniques, which showed that reductions in agricultural land threaten ecosystem services such as water resources and biodiversity, and pose a long-term threat to environmental sustainability [41]. Liu et al. quantitatively evaluated carbon storage and soil conservation services based on remote sensing images and InVEST models, and the results showed a significant synergistic relationship between the two [42]. Shao et al. used a multiple linear regression model to evaluate the spatiotemporal characteristics of ecosystem service functions in South China from 2000 to 2020 [43]. The results showed that the ecosystem service value showed a decreasing trend from 2000 to 2020, and the ecosystem service value of water resource protection, soil conservation, carbon sequestration, and habitat quality showed a synergistic relationship with product supply.

Zarandiana et al. used the InVest model to predict that, in 2028, the Karagi region of Iran showed a trend of natural cover reduction and artificial structure increase in ecosystem services, indicating that most agricultural land will be replaced by artificial settlements [44]. Farinosi et al. evaluated climate and land use changes in the Brazilian Amazon basin and stated that agriculture and animal husbandry in the basin will significantly increase land cover and reduce overall river flow in the coming decades [45]. Lin et al. predicted the land use and carbon storage distribution in Guangdong Province in 2050 based on the InVEST-PLUS model, and the results showed that land use change directly affects the level of regional carbon storage [35]. Net Ecosystem Productivity (NEP) is also a commonly used indicator for calculating changes in carbon storage. The NEP model reflects the energy absorption and utilization capacity of an ecosystem by calculating the difference between the rate at which plant photosynthesis converts solar energy into organic matter and the rate at which respiration consumes organic matter over a certain period of time [32]. Xiang et al. used the Markov–FLUS model to explore the impact of land use change on carbon storage in the main urban area of Chongqing from 2000 to 2020 and predicted the carbon storage changes in the main urban area of Chongqing in 2035 under four utilization scenarios [32]. Yang et al. used the PLUS model to simulate the ecosystem service value of Hanzhong City in 2030 under scenarios such as natural development, ecological protection, and economic development, in order to explore the impact of land use change on ecosystem service value [34]. Jiang et al. took the southern section of the Yellow River as a research area to construct an evaluation model, explored the impact of land use change on ecosystem services from 1980 to 2020, and simulated the impact of different development modes on ecosystem service heterogeneity in 2035 using the FLUS model [34].

The existing research methods for evaluating the impact of land use change on carbon storage mainly include field investigation, remote sensing models, InVEST models, FLUS models, bookkeeping models, etc. The field investigation method struggles to reflect large-scale and long-term changes in carbon storage, and remote sensing models have certain shortcomings in reflecting the relationship between carbon storage changes and human activities [46]. Bookkeeping models have been widely used to calculate carbon storage changes caused by land use changes, but their emphasis on static spatial variability neglects temporal changes, resulting in model results that cannot be directly compared with observed results [47,48]. Among various models for evaluating ecosystem services, the InVEST model has the most mature technology and the highest utilization rate. However, the carbon storage module of InVEST excessively simplifies the carbon cycle process and cannot obtain the carbon flow between different carbon pools. Furthermore, ecological processes are oversimplified in this model and the accuracy of ecosystem service assessment is questionable [49]. The ESL model was developed by the renowned American ecologist H. T. Odum [9]. He used the concept of emergy (the quantity of another type of energy contained in a flowing or stored energy, often based on solar energy) to measure the amount of solar energy directly and indirectly used to form various resources, products, and services [9]. According to the principle of energy conservation, the ESL model is widely used to analyze the energy flow process in ecosystems, which can simplify the analysis of the true value and contribution of different forms of energy in ecosystems [50]. As a carrier of energy, matter also follows the law of conservation, and the flow of energy is closely related to the circulation of matter. Carbon is a key component in the material cycle; therefore, the ESL model provides us with a new approach to analyzing the carbon flow process and carbon storage changes in ecosystems [51]. And using ESL model to analyze carbon storage has more prominent merits than other models. Its core advantage lies in the ability to simulate carbon dynamics under different land use patterns, such as forests, agriculture, urbanization, etc. By constructing the material balance of ecosystems, simulating processes such as plant photosynthesis, soil respiration, and plant respiration, we can calculate the input, storage, and output of carbon, as well as the impact of different land use types on carbon storage [52]. In addition, the ESL model has applicability across time and space scales. Land use change is a long-term and dynamic process [53]. This model can quantitatively evaluate the trend of carbon storage changes in different time periods under different land use scenarios based on historical data and predicted land use scenarios. By adjusting the parameters in the model, policy makers can predict the long-term impact of land use change on regional and global carbon storage [54]. In summary, the ESL model not only has a simple structure and wide applicability, but also effectively simplifies and explains complex ecosystems across multiple fields and scales, accurately quantifying changes in regional carbon storage and ecosystem service values. Compared with other models, the ESL model demonstrates stronger applicability and advantages in simulating changes in carbon storage and ecosystem services under different land use scenarios, especially in long-term timescale scenario simulations.

3. Materials and Methods

3.1. Research Area

The Lvzenong Modern Ecological Agriculture Park (hereinafter referred to as “Lvzenong Park”) is located in Xiahuanghao Village, Lianggezhuang Town, Yi County, Taihang Mountains, Hebei Province. It is situated in the hinterland of Beijing, Tianjin, and Baotou, on the northwest edge of the North China Plain. In July 2012, the Xiahuanghao 10,000 mu Forest and Fruit Science and Technology Demonstration Park project was initially launched. After preliminary development and construction, it has begun to take shape and has been listed as a key agricultural project by the county party committee and government. In 2015, it was rated as a modern agricultural park in Baoding City. The total planned area of the project is 145 square kilometers, involving 27 villages, which is the focus of the county’s poverty alleviation policy. Lvzenong Park involves five villages, namely Xiahuanghao, Zhonghuanghao, Shimendian, Beishimen, and Tawa, with a total of 4986 people. The climate is a temperate monsoon, with an average annual rainfall of 572.40 mm and an average annual temperature of 12 °C. Before the land transfer in Lvzenong Park, the crops mainly consisted of grain crops (corn, sweet potatoes). Through three years of land consolidation and land transfer, the project had transferred 667 hectares of land and mountain areas by 2015, with an investment of CNY 80 million. After the land transfer, the crops were mainly apples, with a total of 200 hectares of fruit trees planted, including 167 hectares of high-quality apples. Lvzenong Park has driven nearly 5000 impoverished people to lift themselves out of poverty and become prosperous, as well as produced 6667 hectares of forest and fruit cultivation land in its western mountainous areas, forming an industrial chain to drive regional economic development. The geographical location of the research area is shown in Figure 1.

3.2. Research Methods

3.2.1. The Carbon Flow Model Based on ESL

Odum’s ESL model is a method based on mathematics, energy, cybernetics, and hierarchical relationships that can transform static network graphs representing traffic, reserves, and their interactions into dynamic models, thereby simplifying and reasonably explaining complex ecosystems across multiple domains and scales [9,55]. To explore the carbon flow relationship among various ecosystems and between the entire system and the external environment during the land transfer process in Lvzenong Park, a carbon flow model of the “land transfer system” was constructed from a micro level using Odum’s ESL model based on the land transfer process. The construction of the carbon flow model mainly includes four steps. Step 1: Define the system boundary. Step 2: List the main sources of carbon elements and plot them outside the system boundaries. The main carbon sources of this study include external natural carbon source inputs (solar energy, atmospheric CO₂) and external artificial carbon source inputs (fertilizer, pesticide, diesel, agricultural film, agricultural irrigation). Step 3: List the main components of the system within the system boundary. This study mainly includes four systems, namely the apple orchard system, forest system, grassland system, and soil system. Step 4: Analyze the carbon flow process and its relationship to each component, and connect each component. The relationships between each component are mainly divided into three categories: (1) Carbon elements flow into the system, including the natural inflow process and the anthropogenic inflow process. The natural inflow process is manifested as CO₂ being fixed in the plant body through photosynthesis under the action of solar energy, while the artificial inflow process is manifested as carbon being input into the apple orchard system in the form of fertilizers, pesticides, etc. (2) The flow of carbon between components, including the absorption and utilization of carbon elements in soil by vegetation, as well as the flow of carbon elements into the soil in the form of litter. (3) Carbon elements flow out of the system, including carbon elements entering the market in the form of crops, soil respiration emitting CO₂, soil erosion causing carbon outflow from the system, and carbon loss of the ecosystem caused by land transfer behavior. The specific carbon flow process is shown in Figure 2.

In the Odum ESL model, the equilibrium equation is a mathematical expression that describes the flow and storage of matter or energy. By analyzing the inflow, outflow, storage, and conversion of matter and energy in a system, we can understand and describe the dynamic behavior of matter and energy in ecosystems, economic systems, social systems, etc. According to the carbon flow process, typical indicators are selected to reflect the change in carbon reserves of each component in the process of the land transfer system. Equilibrium equations are constructed to quantify the carbon flow and change process of the land transfer system. The equations are as follows:

$$S=R+K_0\times O\times C\times GR\times R+K_1\times C\times R\times F\times P\times D\times N\times G\times O\times AE+K_2\times C\times R\times O\times FT$$

(1)

Equation (1) represents the conservation of matter and energy in the entire system, where S represents solar energy, which is the source of all energy in the system. It enters the grassland system (GR), apple orchard system (AE), and forest system (FT) through plant photosynthesis, where R represents unutilized solar energy.

$$R={\displaystyle \frac{S}{1+K_0\times O\times C\times GR+K_1\times C\times F\times P\times D\times N\times G\times O\times AE+K_2\times C\times O\times FT}}$$

(2)

From Equations (1) and (2) can be derived, where R is the unutilized solar energy.

$$DC=K_9\times O-K_3\times O\times C\times GR\times R-K_4\times C\times R\times F\times P\times D\times N\times G\times O\times AE-K_5\times C\times R\times O\times FT$$

(3)

DC represents the annual rate of change in atmospheric CO₂ carbon pools (tC/y), which is equal to carbon input (carbon dioxide emitted by soil respiration) minus carbon output (carbon dioxide fixed by photosynthesis in grasslands, apple orchards, and forests).

$$AE=K_7\times C\times R\times F\times P\times D\times N\times G\times O\times AE-K_{12}\times AE-K_{13}\times AE-K_{11}\times AE$$

(4)

DAE represents the annual rate of change (tC/y) in carbon storage in the apple orchard system, which is equal to its carbon input (including artificial carbon source input, carbon sequestration through photosynthesis, and the absorption of carbon elements from the soil) minus its carbon output (entering the atmosphere, soil, and market).

$$DFT=K_8\times C\times R\times O\times FT-K_{15}\times FT-K_{17}\times FT$$

(5)

DFT represents the annual rate of change (tC/y) in carbon storage in a forest system, which is equal to its carbon input (carbon sequestration through photosynthesis and the absorption of carbon elements from the soil) minus its carbon output (entering the soil and market).

$$DGR=K_6\times O\times C\times GR\times R-K_{19}\times GR-K_{10}\times GR$$

(6)

DGR represents the annual rate of change (tC/y) in carbon storage in grassland systems, which is equal to the carbon input (carbon sequestration through photosynthesis and the absorption of carbon elements from soil) minus the carbon output (entering soil and human grassland destruction).

$$\begin{array}{c}DO=K_{13}\times AE+K_{15}\times FT+K_{19}\times GR-K_9\times O-K_{14}\times C\times R\times F\times P\times D\times N\times G\times O\times AE\\ -K_{16}\times C\times R\times O\times FT-K_{18}\times O\times AE/FT/GR-K_{20}\times O\times C\times GR\times R\end{array}$$

(7)

DO represents the annual rate of change in soil carbon storage (tC/y), which is equal to carbon input (degradation of litter in apple orchards, forests, and grasslands) minus carbon output (soil erosion, and providing nutrients for apple orchards, forests, and grasslands). In addition, K₀–K₂₀ represent the coefficient values of carbon flow between various systems. On this basis, by setting the initial parameter values of the model and solving the equation, we can analyze and predict the dynamic changes in carbon storage of each carbon pool. The specific meanings of the variables and parameters in the equilibrium equations are shown in

Table 1. Meaning of variables in equilibrium equations.

Variable	Meaning	Variable	Meaning	Variable	Meaning	Variable	Meaning
S	Solar energy	F	Fertilizer	N	Agricultural film	AE	Carbon storage of apple orchard system
R	Unutilized solar energy	P	Pesticide	G	Agricultural irrigation	FT	Carbon storage in forest system
C	Atmospheric CO2 carbon storage	D	Diesel	O	Soil carbon storage	GR	Carbon storage in grassland system

and

Table 2. Meaning of parameters in equilibrium equations.

Parameter	Meaning	Parameter	Meaning	Parameter	Meaning
K0	Solar energy absorbed by grassland	K7	Formation of apple orchard vegetation biomass	K14	Soil nutrients absorbed and utilized by apple orchard
K1	Solar energy absorbed by apple orchard	K8	Formation of forest vegetation biomass	K15	Degradation of litter in forest vegetation
K2	Solar energy absorbed by forest	K9	CO2 emissions from soil respiration	K16	Soil nutrients absorbed and utilized by forest
K3	CO2 absorbed by grassland	K10	Changes in grassland area caused by human activities	K17	Forest output
K4	CO2 absorbed by apple orchard	K11	Changes in apple orchard area caused by human activities	K18	Soil erosion
K5	CO2 absorbed by forest	K12	Apple orchard output	K19	Degradation of litter in grassland vegetation
K6	Formation of grassland vegetation biomass	K13	Degradation of litter in apple orchard vegetation	K20	Soil nutrients absorbed and utilized by grassland

, respectively.

In the equations, the calculation formulae for ecosystem carbon storage and soil carbon storage are

$$C_i=S_i\times F_{CADi}$$

(8)

$$C_s={\displaystyle \sum }_{i=1}^n{S}_i\times F_{SCDi}$$

(9)

where C_i represents the carbon storage of the i-th ecosystem; Si is the area of the i-th ecosystem; FCAD_i is the carbon density of vegetation in the i-th ecosystem; C_s is the soil carbon storage; n is the number of ecosystem types; and FSCD_i is the soil carbon density under the i-th ecosystem vegetation.

3.2.2. Evaluation of Ecosystem Service Values Based on Carbon Flow Model

Land transfer behavior leads to changes in land use types, which affect ecosystem patterns, processes, and functions, thereby affecting the value of ecosystem services. To explore the changes in ecosystem service values during the land transfer process of Lvzenong Park in Yi County, combined with the Chinese terrestrial ecosystem value equivalent method newly established by Xie et al., a carbon flow model was constructed to evaluate the ecosystem service value of Lvzenong Park [56]. Referring to relevant research, ecosystem service types are divided into several categories, including supply services (food production, raw material production), regulating services (gas regulation, climate regulation, hydrological regulation, and waste treatment), supporting services (soil conservation, biodiversity conservation), and cultural services (providing aesthetics), and the model of the equivalent factor method is obtained as follows [56,57,58,59]:

$$E_a={\displaystyle \raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$7$}\right.}{\displaystyle \sum }_{i=1}^n{\displaystyle \frac{p_i{q}_i}{M}}$$

(10)

$$ESV={\displaystyle \sum }_{i=1}^n{\displaystyle \sum }_{j=1}^k{E}_a{S}_i{D}_{ij}$$

(11)

In Equation (10), E_a represents the ecosystem service value of one standard equivalent, which is the economic value provided by grain crops per unit area of farmland ecosystem in China; n refers to the type of major grain crop, including rice, corn, and wheat; p_i and q_i are the yield and price of the i-th crop, respectively; M is the total area of grain crops. According to the calculation results of Xie et al.’s 2015 [57] study, E_a is determined to be 466.69 USD/hm². In Equation (11), ESV represents the total value of ecosystem services in the study area; S_i represents the area of the i-th type of ecosystem, obtained through the survey statistics; D_ij represents the value equivalent of the j-th service function of the i-th ecosystem; and E_a represents the ecosystem service value of one standard equivalent. Xie et al. defined this as the economic value of the annual natural grain yield of farmland with an average yield of 1 hm² in China, which is 466.69 USD/hm² [57]. Regarding the determination of equivalent factors, scholars have not yet formed a unified standard due to differences in calculation methods and subjective opinions. Among them, Xie et al., based on statistical research, referred to a large number of other scholars’ studies and adjusted the equivalent factors after consulting experts, forming a relatively systematic, objective, and comprehensive ecosystem service value assessment system [56,57,58,59,60,61]. Therefore, based on the research results of Xie et al., this study determined an equivalent factor table of ecosystem service values in Lvzenong Park, as shown in

Table 3. Ecological system service values per unit area of Lvzenong Park (dollar/hm²).

First Class	Second Class	Farmland (Apple Orchard)	Grassland	Forest
Supply services	Food production	466.69	200.68	154.01
	Raw material production	182.01	168.01	1390.74
Regulating services	Gas regulation	336.02	700.04	2016.10
	Climate regulation	452.69	728.04	1899.43
	Hydrological regulation	359.35	709.37	1908.76
	Waste treatment	648.70	616.03	802.71
Supporting services	Soil conservation	686.04	1045.39	1876.10
	Biodiversity conservation	476.02	872.71	2104.77
Cultural services	Providing aesthetics	79.34	406.02	970.72

[56,57].

3.3. Data Sources

The data used in this study were obtained through surveys conducted by the research team in Lianggezhuang Town, Yi County, Baoding City, Hebei Province. These data were mainly obtained through household surveys, expert consultation, literature analysis, and querying the 2015 statistical data of Lvzenong Park in Yi County, Baoding City. The data related to land transfer included three types of land use: apple orchards, forests, and grassland, derived from on-site research in the demonstration park and relevant information from the Yi County Agricultural Bureau. The carbon source data of the research area were obtained by querying the 2016 Hebei Province Statistical Yearbook, Baoding City Statistical Yearbook, and 2015 Lvzenong Park statistical data in relation to fertilizers, pesticides, diesel, agricultural film, agricultural irrigation, etc. The values of vegetation carbon density, soil carbon density, atmospheric CO₂ carbon pool, and the main parameters of model calculation in different ecosystems were derived from existing relevant studies [11,62,63,64]. The storage of different components and the coefficient values of the specific carbon flow model are shown in

Table 4. Components, carbon flow, storage, and coefficient values of the carbon flow model.

Parameter	Component	Initial Value	Unit	Coefficient	Parameter	Component	Initial Value	Unit	Coefficient
S	Solar energy	1000.00	Constant		J12	Apple orchard output	368.28	tC/y	0.50
F	Fertilizer	198.63	tC/y		J13	Degradation of litter in apple orchard vegetation	73.66	tC/y	0.10
P	Pesticide	14.20	tC/y		FT	Carbon storage in forest systems	831.79	tC
D	Diesel	1.15	tC/y		J2	Energy utilized by forests	20.00		2.26 × 10−11
N	Agricultural film	32.99	tC/y		J8	Forest vegetation growth	748.61	tC/y	8.47 × 10−10
G	Agricultural irrigation	21.67	tC/y		J15	Degradation of litter in forest vegetation	582.25	tC/y	0.70
R	Unutilized solar energy	950.00	tC/y		J17	Forest output	41.59	tC/y	0.05
C	Atmospheric CO2 carbon storage	74,126.00	tC		GR	Carbon storage in grassland systems	10,740.38	tC
J3	CO2 absorbed by grassland	805.53	tC/y	7.06 × 10−11	J0	Energy utilized by grassland	17.50		1.53 × 10−12
J4	CO2 absorbed by apple orchards	368.28	tC/y	2.03 × 10−11	J6	Grassland vegetation growth	966.63	tC/y	8.47 × 10−11
J5	CO2 absorbed by forests	665.43	tC/y	7.53 × 10−10	J10	Changes in grassland area (human activities)		tC/y
J9	CO2 emissions from soil respiration	905.03	tC/y	0.06	J19	Degradation of litter in grassland vegetation	751.83	tC/y	0.07
AE	Carbon storage of apple orchard system	736.57	tC		O	Soil carbon storage	15,083.90	tC
J1	Energy utilized by apple orchard	12.50		6.89 × 10−13	J14	Soil nutrients absorbed and utilized by apple orchards	110.49	tC/y	6.09 × 10−12
J7	Apple growth	589.25	tC/y	3.25 × 10−11	J16	Soil nutrients absorbed and utilized by forests	301.68	tC/y	3.41 × 10−10
J11	Changes in apple orchard area (human activities)		tC/y		J18	Soil erosion	3.77	tC/y	0.30
					J20	Soil nutrients absorbed and utilized by grasslands	905.03	tC/y	7.93 × 10−11

.

4. Results

4.1. Simulation of Carbon Storage Changes in Lvzenong Park

Before the land transfer in Lvzenong Park, sweet potatoes were mainly planted. Due to factors such as insignificant economic and social benefits, and the low degree of concentrated land use, after three years of project construction, the sweet potato planting area was transferred to apple orchards and forests. Therefore, it is of no practical significance to evaluate the changes in carbon storage of each carbon pool before the land transfer. Based on this, the carbon storage changes in each carbon pool from 2015 to 2115 after land transfer were evaluated, and the specific results are shown in Figure 3.

From Figure 3, it can be seen that the carbon storage of the apple orchard system increased rapidly in the early stage, reaching a peak of 1247.75 tC in the 6th year, and then showed a downward trend, decreasing to the minimum value of 203.88 tC in the 22nd year. Finally, the carbon storage slowly increased to a stable state. The trend of carbon storage in the forest system is similar to that of the apple orchard system, with a rapid increase to 1081.86 tC in the first 3 years and a rapid decline to a valley value of 155.19 tC in the 17th year. Subsequently, carbon storage slowly recovered to a stable state. The rate of carbon storage decline in forest systems was significantly higher than that in apple orchard systems in the early stage. The carbon storage of the grassland system increased to a peak of 11,279.01 tC in the first five years, followed by a downward trend. The decline rate gradually accelerated 40 years ago, and slowed down 40 years later. The carbon storage of the grassland system decreased to 618.07 tC in the 100th year, and the average annual decline is 3.01%. The soil carbon storage continued to decrease in the early stage and reached a stable state of 6139.73 tC after 51 years, with an average annual decrease of 1.75%. The atmospheric CO₂ carbon pool decreased from an initial value of 74,126.00 tC to 62,569.05 tC after 19 years, with an average annual decrease of 0.89%. It gradually increased to 72,722.09 tC in the 100th year, which is lower than the initial value of the atmospheric CO₂ carbon pool, and the atmospheric CO₂ carbon storage showed a downward trend.

This article combines the carbon flow relationship between each component in the carbon flow model and selects three time points (the 1st year, the 20th year, and the 100th year) to study the carbon storage changes and their interaction relationships for each carbon pool in the system during land transfer. The carbon flow changes between each carbon pool in the system are shown in

Table 5. Carbon flow changes among different carbon pools in Lvzenong Park.

Carbon Flow	The 1st Year	The 20th Year	The 100th Year	Carbon Flow	The 1st Year	The 20th Year	The 100th Year
J0	16.63	7.66	0.42	J11	0	0	0
J1	13.98	2.31	2.40	J12	441.94	133.80	169.13
J2	21.43	2.34	3.57	J13	88.39	26.76	33.83
J3	765.62	352.68	19.36	J14	123.54	20.42	21.19
J4	411.81	68.07	70.64	J15	669.59	133.76	248.98
J5	713.07	77.77	118.85	J16	323.28	35.26	53.88
J6	918.75	423.22	23.23	J17	47.83	9.55	17.78
J7	658.90	108.92	113.02	J18	3.65	4.02	28.65
J8	802.21	87.50	133.70	J19	766.86	646.98	43.26
J9	855.94	524.63	368.38	J20	860.20	396.25	21.75
J10	0	0	0

.

Lvzenong Park is continuously expanding apple planting areas through land transfer, resulting in a significant increase in the volume of apple cultivation and the carbon storage of the apple orchard system in the early stage. Due to the limited carrying capacity of land, sustaining optimal growth conditions becomes challenging, leading to a declining trend in carbon storage within the apple orchard system beyond its sixth year. The continuous increase in apple cultivation causes damage to the ecological environment, deteriorating soil erosion and leading to a continuous decline in soil carbon storage in the initial stage. Consequently, the assimilation and utilization of nutrients from the soil by forests and grasslands exhibit a persistent decline, leading to an ongoing reduction in carbon storage within grassland and forest ecosystems. After the carbon storage of apple orchard, forest, and grassland systems shows a decreasing trend, the soil organic matter required for their growth gradually decreases, leading to a continuous slowdown in the rate of soil carbon storage decline, ultimately reaching a stable state. The atmospheric CO₂ flows into the vegetation of various ecosystems, and the main source of increased atmospheric CO₂ carbon pool is soil respiration. Although there was a significant increase in carbon storage in the initial apple orchard system, the continuous decrease in soil carbon storage led to a continuous decrease in soil respiration emissions. At the same time, the rate of increase in atmospheric CO₂ carbon storage was slower than the rate of decrease, resulting in a continuous downward trend in atmospheric CO₂ carbon storage in the first 19 years. Twenty years later, the carbon storage of apple orchard and forest systems remains stable, while the carbon storage of grassland system continues to decline. In addition, the total vegetation of the entire ecosystem continues to decline, and the sources of ecosystem carbon sinks decrease. The decline rate of soil carbon storage gradually slows down, and the deceleration rate of ecosystem carbon sources slows down. The reduction rate of carbon sink sources is higher than that of carbon sources, leading to an increasing trend in the atmospheric CO₂ carbon pool, and the growth rate continues to accelerate.

4.2. Simulation of Ecosystem Services Changes in Lvzenong Park

On the basis of the above analysis, further simulation analysis was conducted on the changes in the ecosystem services in Lvzenong Park. The specific results are shown in Figure 4.

As can be seen from Figure 4, the total value of ecosystem services in Lvzenong Park shows an overall downward trend from USD 6.7188 million to USD 1.9286 million from 2015 to 2115, with a decrease of 71.30% and an average annual decrease of 1.24%. After land transfer, the total value of ecosystem services in Lvzenong Park significantly increases in the early stage, reaching a peak of USD 8.2686 million in the fourth year and then rapidly decreasing. After 19 years, the decline rate significantly slows down. The main source of supply services is the output of the apple orchard, so the direction of change is similar to that of carbon storage changes in the apple orchard system. The supply services increase to a peak of USD 0.8771 million in the first four years, and then continue to decrease. After 100 years, the supply services decrease from USD 0.6798 million to USD 0.2350 million, with an average annual decrease of 1.06%. The regulating services, supporting services, and cultural services all show a trend of increasing first and then decreasing, and the turning point time of the curve is consistent with the supply services. Regulating services decrease from USD 3.2598 million to USD 0.9619 million, with an average annual decrease of 0.71%. Supporting services decrease from USD 2.0864 million to USD 0.5907 million, with an average annual decrease of 1.25%. Cultural services decrease from USD 0.6927 million to USD 0.1410 million, with an average annual decrease of 1.58%. The rate of decline in supply services is the slowest, while that in cultural services is the fastest. Lvzenong Park transferred sweet potato planting areas and unused mountainous and wasteland areas into apple orchards through land transfer. Due to the continuous construction of apple orchards, the ecological environment of the park has been damaged, and the rate of soil erosion has accelerated, resulting in a continuous decrease in the total vegetation of the entire ecosystem, ultimately leading to a downward trend in all four services and the total value of ecosystem services. As the carbon storage of the apple orchard system gradually decreases, the ecological environment slowly recovers, and the rate of decline in natural ecosystem vegetation slows down, resulting in a slowdown in the decline rate of the four services and the total value of ecosystem services.

4.3. Simulating the Response of Carbon Storage and Ecosystem Services to Land Transfer Under Multiple Scenarios

The changes in carbon storage and ecosystem services in Lvzenong Park after land transfer were revealed above. In order to further clarify the impact of land transfer behavior on carbon storage and ecosystem services, considering the “dual carbon goals” and the historical development background of the Taihang Mountains, Hebei Province, China, this study proposes two scenarios based on the perspective of land use change to explore the comprehensive management and sustainable development of land transfer in the Taihang Mountains area.

4.3.1. Scenario Settings

Scenario analysis or scenario planning refers to a “structured process of exploring and evaluating alternative futures” [51]. Based on the economic development background of Yi County and the current actual situation, we interviewed the leading official of Lvzenong Park and discussed medium- and long-term development plans. It was decided that 5% values should be determined.

Scenario 1: Economic development scenario. Continue to promote economic development, expand apple orchards, and increase apple planting areas by 5% while reducing grassland planting areas by 5%.

In the past three years, the per capita annual income of employed villagers in Lvzenong Park has increased from less than USD 411 to over USD 822, and poverty alleviation has been achieved in one stroke. With the continuous expansion of Lvzenong Park’s construction scale, the speed at which farmers transform into industrial workers is further accelerated, and more and more farmers are leaving poverty behind and moving towards a moderately prosperous society. In this context, the Yi County government continues to strengthen the construction of apple orchards to ensure the further development of Lvzenong Park. Grasslands within Lvzenong Park are transformed into apple orchards, and carbon elements from the natural ecosystem continuously flow into the apple orchard system.

Scenario 2: Carbon sink protection scenario. Implement carbon sink protection policies, expand grasslands, and increase grassland planting areas by 5% while reducing apple planting areas by 5%.

With the continuous expansion of apple orchards, the potential productivity of the demonstration park continues to decline, the natural ecosystem is continuously damaged, the carbon sink capacity of the ecosystem constantly declines, and various ecological and environmental problems arise that urgently need to be solved. In this context, the Yi County government should implement carbon sink protection policies to enhance the carbon sequestration capacity of the ecosystem and consolidate its carbon sequestration role. Lvzenong Park transforms apple orchards into grassland, and carbon elements within the apple orchard system flow into the natural ecosystem.

4.3.2. Simulation of Carbon Storage Changes in Lvzenong Park Under Different Scenarios

The economic development scenario will expand the apple orchard area, and the carbon elements in the demonstration park will be transferred from the natural ecosystem to the apple orchard system. The carbon sink protection scenario will expand the grassland area and demonstrate the transfer of carbon elements from the park to the natural ecosystem. The carbon storage changes in various carbon pools in Lvzenong Park from 2015 to 2115 under two land use scenarios are shown in Figure 5.

The economic development scenario resulted in a significant increase in the overall carbon storage of the apple orchard system compared to the baseline scenario, with peaks of 1748.21 tC and 1247.75 tC, respectively, which were 1.4 times higher than the baseline scenario. Additionally, the economic development scenario had the longest duration of sustained growth in terms of carbon storage in the apple orchard system. The carbon storage of the apple orchard system reached peaks in the sixth year (baseline scenario), ninth year (economic development scenario), and fourth year (carbon sink protection scenario), respectively. Under both land use scenarios, the carbon storage in the apple orchard system showed a trend of first increasing and then decreasing, slowly recovering, and gradually reaching a stable state after about 20 years. Among them, the stable carbon storage in the apple orchard system was the highest in the economic development scenario, followed by the baseline scenario. Regardless of the land use scenario, the trends and directions of carbon storage changes in the forest system in the first 15 years are consistent, showing a trend of first increasing and then decreasing. The carbon storage of the forest system in the economic development scenario begins to recover after 15 years, and changes steadily around 341.47 tC after 30 years. In the carbon sink protection scenario, the carbon storage in the forest system reaches a valley value after 30 years, and the forest vegetation tends to disappear. The carbon storage in the grassland system, soil carbon storage, and the atmospheric CO₂ carbon pools show completely opposite trends in the two scenarios. The carbon storage in the grassland system in the economic development scenario always maintains a downward trend, reaching a stable state of 313.21 tC after about 50 years, with an average annual decrease of 6.83%. The carbon storage in the grassland system in the carbon sink protection scenario maintains an upward trend for 100 years, rising from 10,740.38 to 133,953.79 tC, with an average annual increase of 2.56% and an accelerated growth rate. The trend of soil carbon storage changes in the economic development scenario is similar to the baseline scenario, but the time to reach the valley value is significantly shortened, from the 51st year to 31st year, with stable values being relatively consistent. In the carbon sink protection scenario, soil carbon storage decreases slowly in the first 20 years and then increases rapidly, with a growth rate that is first fast and then slow. Overall, soil carbon storage shows a fluctuating growth trend, increasing from 15,083.90 to 58,985.12 tC, with an average annual growth rate of 1.37%. The atmospheric CO₂ carbon pool in the economic development scenario is significantly higher than that in the baseline scenario, and the trend of change is consistent with the baseline scenario. The atmospheric CO₂ carbon pool in the carbon sink protection scenario has always shown a downward trend, with a significant fluctuation in the rate of decline, from 74,126.00 to 7062.85 tC, with an average annual decrease of 2.32%.

Based on two land use scenarios and combined with the carbon flow relationship between each component in the carbon flow model, this study selected three time points (year 1, year 20, and year 100) to explore the impact of land transfer behavior on carbon storage. The changes in carbon flow among the carbon pools in the system under different scenarios are shown in

Table 6. Changes in carbon flow among different carbon pools in Lvzenong Park under economic development scenario.

Carbon Flow	The 1st Year	The 20th Year	The 100th Year	Carbon Flow	The 1st Year	The 20th Year	The 100th Year
J0	15.82	2.41	0.23	J11	−46.04	−29.30	−17.17
J1	14.56	4.60	2.57	J12	460.35	292.98	171.75
J2	21.44	2.94	3.83	J13	92.07	58.60	34.35
J3	728.26	111.06	10.37	J14	128.72	40.67	22.74
J4	429.07	135.57	75.80	J15	669.59	184.75	252.85
J5	713.24	97.70	127.53	J16	323.35	44.29	57.82
J6	873.92	133.28	12.44	J17	47.83	13.20	18.06
J7	686.51	216.92	121.28	J18	4.00	16.48	56.52
J8	802.39	109.91	143.47	J19	729.27	224.01	21.92
J9	855.94	469.99	368.38	J20	818.22	124.78	11.65
J10	520.91	160.01	15.66

and

Table 7. Changes in carbon flow among different carbon pools in Lvzenong Park under carbon sink protection scenario.

Carbon Flow	The 1st Year	The 20th Year	The 100th Year	Carbon Flow	The 1st Year	The 20th Year	The 100th Year
J0	17.44	22.75	78.85	J11	42.35	5.50	1.03 × 10−11
J1	13.39	1.04	1.27 × 10−12	J12	423.53	55.02	1.03 × 10−10
J2	21.43	0.83	1.63 × 10−15	J13	84.71	11.00	2.07 × 10−11
J3	802.97	1047.29	3629.61	J14	118.37	9.17	1.12 × 10−11
J4	394.56	30.56	3.73 × 10−11	J15	669.59	43.50	1.32 × 10−13
J5	712.91	27.62	5.43 × 10−14	J16	323.20	12.52	2.46 × 10−14
J6	963.56	1256.75	4355.53	J17	47.83	3.11	9.40 × 10−15
J7	631.30	48.90	5.97 × 10−11	J18	3.33	2.22	1468.06
J8	802.02	31.07	6.11 × 10−14	J19	804.45	1759.56	9376.76
J9	855.94	622.69	3539.11	J20	902.16	1176.66	4077.97
J10	−574.61	−1256.83	−6697.69

.

In the economic development scenario, the apple planting area expands, leading to a significant increase in carbon storage within the apple orchard system and an accelerated rate of soil organic matter absorption and utilization. The ecological environment is continuously damaged, the rate of soil erosion gradually accelerates, and soil carbon storage decreases. Reducing the grassland planting area significantly reduces the total vegetation of the entire ecosystem, leading to an increase in carbon sources and a decrease in carbon sinks, resulting in an increase in atmospheric CO₂ carbon pools. In the carbon sink protection scenario, grassland planting areas are expanded while apple orchard construction is reduced. The initial degradation of grassland litter has a slower rate of supplementing soil carbon elements than the consumption rate of soil organic matter with apple orchard construction, resulting in a slight decrease in soil carbon storage. After 30 years, the carbon storage of the apple orchard system reaches a valley value, and the carbon storage of the grassland system increases significantly. The problem of soil erosion is alleviated, leading to a rapid increase in soil carbon storage. The ecological environment gradually recovers, and the total amount of vegetation in the entire ecosystem significantly increases. The reduction in carbon sources and the increase in carbon sinks leads to a sustained downward trend in the atmospheric CO₂ carbon pools. In summary, land transfer behavior can significantly affect ecosystem carbon storage. The economic development scenario has a positive effect on the carbon storage of the apple orchard system and the atmospheric CO₂ carbon pools, and a negative effect on the carbon storage of the grassland system, resulting in an average annual decrease of 6.83%. The carbon sink protection scenario actively affects the carbon storage of grassland systems and soil, resulting in an average annual growth of 2.56% and 1.37%, while negatively affecting the atmospheric CO₂ carbon pools, resulting in an average annual reduction of 2.32%. The carbon sink capacity of the ecosystem is significantly improved, and the atmospheric CO₂ carbon pool is significantly reduced.

4.3.3. Simulation of Ecosystem Services Changes in Lvzenong Park Under Different Scenarios

To explore the impact of land transfer behavior on ecosystem services, this paper simulates the dynamic changes in ecosystem service values from 2015 to 2115 based on different land use scenarios. The changes in the ecosystem services in Lvzenong Park under two land use scenarios are shown in Figure 6.

The trend of the changes in the total value of ecosystem services in the economic development scenario is similar to the baseline scenario, but the decrease is significantly higher than the baseline scenario, decreasing from USD 6.7188 million to USD 1.8823 million, with an average annual decrease of 1.26%. The total value of ecosystem services in the carbon sink protection scenario shows an overall upward trend, rising from USD 6.7188 million to USD 32.4864 million, with an average annual increase of 1.59%. One hundred years later, the total value of ecosystem services in the carbon sink protection scenario is 17.26 times that of the economic development scenario. The supply and regulating services in the economic development scenario first increase and then decrease to a stable state, while the supply and regulating services in the carbon sink protection scenario show an overall upward trend. The supply services in the economic development scenario significantly increase, which is due to the increase in apple planting areas leading to an increase in apple orchard output, resulting in an increase in supply services. The growth rate of regulating services in the carbon sink protection scenario is the largest, which is because the increase in grassland planting areas promotes the remarkable recovery of the ecological environment, the improvement of soil erosion, increased the total vegetation across the whole ecosystem, and a remarkable improvement in the ecological environment’s adjustment ability. The changing trends of supporting services and cultural services under the two land use scenarios are similar to those of supply services and regulating services. One hundred years later, the supply services, regulating services, supporting services, and cultural services in the economic development scenario decrease by 65.58%, 71.11%, 72.41%, and 81.11%, respectively, while those in the carbon sink protection scenario increase by 193.11%, 356.50%, 396.85%, and 657.34%, respectively. In summary, land transfer behavior can significantly affect ecosystem services. The total value of ecosystem services and the four types of services show a trend of first increasing and then decreasing in the economic development scenario, while they generally show an increasing trend in the carbon sink protection scenario. Moreover, the total value of ecosystem services in the carbon sink protection scenario is much higher than that in the economic development scenario, with the largest increase in regulating services and the fastest growth in cultural services. In the selection of the “dual carbon target” strategy, priority should be given to the carbon sink protection scenario to quickly improve the carbon sink capacity of the ecosystem. In the selection of poverty alleviation strategies, economic development scenarios should be selected to enable rural impoverished people to quickly overcome poverty.

The impact of changes in land use type on ecosystem services is analyzed from the perspectives of the dynamic degree of ecosystem service value and the transformation status of ecosystem services. The specific results are shown in

Table 8. Ecosystem service value dynamic degree and ecosystem service change index.

Time/Year	Ecosystem Service Value Dynamic Degree			Ecosystem Service Change Index
	Benchmark Scenario	Economic Development Scenario	Carbon Sink Protection Scenario	Benchmark Scenario	Economic Development Scenario	Carbon Sink Protection Scenario
0–10	−0.44%	−0.60%	0.95%	−0.45%	−0.62%	0.91%
10–20	−5.00%	−5.89%	−1.77%	−6.70%	−8.51%	−1.92%
20–30	−1.09%	−1.89%	2.44%	−1.15%	−2.08%	2.21%
30–40	−0.90%	−0.49%	3.18%	−0.94%	−0.50%	2.80%
40–50	−0.77%	−0.14%	3.13%	−0.80%	−0.14%	2.76%
50–60	−0.60%	0.00%	2.70%	−0.62%	0.00%	2.42%

. Notably, in the 0–40-year period of the economic development scenario, the absolute values of the dynamic degree of the total ecosystem service value are consistently negative, indicating a faster decline rate compared to the baseline scenario. Conversely, under the carbon sink protection scenario, the dynamic degree of the total ecosystem service value remains positive, except for the 10–20-year period, highlighting a notable enhancement in service value. By measuring the ecosystem service change index to explore the transformation status of ecosystem services, it can be found that carbon sink protection scenarios can accelerate the positive transformation of ecosystem services, manifested as the ecosystem service change index being positive, except for years 10–20. The carbon sink protection scenario promotes significant restoration of the ecological environment by increasing grassland planting areas, improving soil erosion, increasing the total vegetation of the entire ecosystem, and significantly improving the ecological environment’s regulation capacity.

5. Discussion

5.1. Analysis of the Impact of Land Transfer on Carbon Storage and Ecosystem Services

This study simulated the dynamic process of ecosystem service value changes caused by changes in ecosystem functions under an economic development scenario and a carbon sink protection scenario. The research results indicate that changes in land use types can lead to changes in ecosystem services. The scenario of carbon sink protection can significantly enhance the ecological environment’s regulation capacity and promote significant ecosystem restoration by increasing grassland planting areas, improving soil erosion, and expanding the total vegetation of the ecosystem. This is consistent with the results of previous studies [34,36]. The economic development scenario has a positive effect on the apple orchard system, which can effectively improve the supply of services, but has a restraining effect on the grassland system, resulting in the total value of ecosystem services being basically equal to the benchmark scenario, which is similar to the conclusions obtained from references [19,20].

The most significant impact of land transfer on ecosystem services is reflected in carbon storage [6,18]. Research has shown that the grassland system is the key factor influencing changes in ecosystem services. Compared to the apple orchard and the forest systems, the grassland system exhibits a greater degree of carbon storage change in both land use scenarios. The economic development scenario will lead to an average annual reduction of 6.83% in the grassland system, while the carbon sink protection scenario has a significant positive impact on the grassland system. This is because the grassland system has lower evapotranspiration and higher stability in terms of ecosystem services, and can provide higher water production while maintaining a relatively high level of ecosystem services [31]. Therefore, expanding the grassland system area under the carbon sink protection scenario can enhance ecosystem services. The studies by Souza et al. and Gonzalex et al. confirm this conclusion [2,14]. Due to the higher carbon storage value of forest systems, forests usually exist as buffer zones or as transitional land [13], so this article does not discuss in detail the changes in ecosystem service value caused by forest systems.

However, changes in ecosystem structure and ecosystem services are interdependent, which requires weighing different scenarios. Previous studies have validated this conclusion [13,39]. According to the research results, the atmospheric carbon dioxide carbon pool shows opposite directions of change in two scenarios, which also means that the combination of multiple land use types can effectively coordinate carbon sequestration goals [31]. Although the economic development scenario can effectively promote the development of the apple industry and enhance ecosystem supply services in Lvzenong Park, the synergistic effects of the ecosystem should also be considered [18,28]. Especially with the increasing demand for artificial land from stakeholders, some studies have predicted that grassland system coverage will decrease by 2028 [45]. Studies have also confirmed that the expansion of agricultural land poses a threat to long-term environmental sustainability [15,42]. These studies all indicate that the transformation of ecosystem services has become an urgent issue for the development of agricultural parks. Compared to the economic development scenario, the carbon sink protection scenario is more reasonable for achieving ecological service transformation and balancing economic benefits and ecological value in Lvzenong Park. In the long run, it is necessary to integrate the supply of ecosystem services with other services in park management.

5.2. Policy Recommendations

The Chinese government has achieved good implementation results from enhancing the carbon sink capacity of ecosystems. Taking Sichuan Province as an example, by implementing state-owned forest farm (grasslands) carbon sink projects, developing grassland carbon sink projects in western Sichuan, and dynamically managing carbon sink projects, a good carbon sink brand image has been established. Based on the research results of this article, in order to further promote green and low-carbon development in the Taihang Mountains of China, the following policy recommendations are proposed: (1) Strengthen carbon sink construction and enhance the carbon sink capacity of the ecosystem. Promote land greening action by returning farmland to forest and grassland, repair the degraded ecosystem, and stabilize the carbon sequestration effect of the existing forest, grassland, soil, and other natural ecosystems. Strengthen the ecological protection of forests and grasslands, ensure the vegetation restoration of the natural ecosystem, and prevent further damage. (2) In response to the problem of carbon storage decline in the grassland system of Lvzenong Park in Yi County, Taihang Mountains, Hebei Province, it is necessary to protect the original grassland, reduce human damage to grassland, strengthen the construction of artificial grassland, achieve the intensive management of artificial grassland, and improve the carbon absorption capacity of grassland. (3) Improve agricultural land production efficiency, improve farming systems, adopt reasonable land use models, develop efficient and low-carbon agriculture, and increase the carbon sink increment of agricultural ecosystems. On this basis, we will strengthen the total control of construction land, regulate the occupation of arable land by construction land, prevent the expansion of construction land from damaging the original natural ecosystem, and strengthen the construction of intensive land use. (4) Reasonably balance the coordination and unity of long-term carbon peaking, carbon neutrality, and short-term economic development goals. The research results found that the total value of ecosystem services under the carbon sink protection scenario was much higher than that under the economic development scenario. In this regard, local governments, while balancing short-term local economic development with long-term environmental protection and combining existing national policies, such as poverty alleviation and returning farmland to forests and grasslands, strive to further optimize and combine future agricultural green and sustainable development strategies under the guidance of the “dual carbon goals”, standardize and promote agricultural industrial structure adjustment, and guide reasonable and orderly land transfer. The aim is to achieve the maximum improvement of carbon sink capacity at the minimum expense of the short-term economy.

5.3. Limitations

Overall, based on the Odum ESL model and integrating multiple natural ecosystems by building a bridge between natural ecosystems and socio-economic systems, we evaluated the trend of carbon storage and ecosystem services in Lvzenong Park in the Taihang Mountains of Hebei Province. This breaks through the limitations of current research focusing on single systems and makes the evaluation results more scientific. By taking the typical case of the Taihang Mountains in Hebei Province as an example, this study explores the complex carbon flow process within the land transfer system, effectively revealing the energy flow pattern and carbon flow mechanism of each component in the land transfer system. This can provide a reference for land system reform in impoverished areas and lay a solid foundation for the sustainable development of agriculture in mountainous areas of China. However, there are still shortcomings in this study and further improvement is needed in the future. From the perspective of system composition, in order to facilitate model construction, this study did not consider other land use types and crops, but only considered the main land types and crops involved in the land transfer process in the study area. In addition, this study used the equivalent factor method improved by Xie et al. [56] to evaluate the value of ecosystem services. Although the operation is simple, the determination of some equivalent factors lacks sufficient detailed literature and data support. Therefore, Xie et al. [57] did not make a detailed distinction between ecosystem types when calculating these equivalent factors, and their representativeness remains to be verified. The prices of agricultural products in different years and regions may also change, leading to spatial and temporal differences in the assessment of ecosystem service values [10]. In the future, measures such as expanding system boundaries, improving data sources, and introducing local characteristic crops can be taken to further improve the model, explore the impact of more land use types on carbon storage and ecosystem services, analyze the impact of differences in crop planting structure on carbon storage and ecosystem services, and provide a basis for further improving land use efficiency.

6. Conclusions

This study takes Lvzenong Park in Yi County, Taihang Mountains, Hebei Province, as its research object. Taking the land transfer process as an example, a carbon flow model is constructed using the Odum ESL model to reveal the changes in carbon storage in each carbon pool during the land transfer process. The unit area value equivalent factor method is used to evaluate the ecosystem service value. Based on two land use scenarios, the changing trends of carbon storage and ecosystem services from 2015 to 2115 are simulated to explore the pathways and ways in which land transfer behavior affects carbon storage and ecosystem services. The main conclusions are as follows:

(1)

From 2015 to 2115, the carbon storage of apple orchard, forest, and grassland systems shows a trend of first increasing and then decreasing, reaching its peak in the sixth, third, and fifth years, respectively. Soil carbon storage continues to decline, with an average annual decrease of 1.75%. The overall atmospheric CO₂ carbon pool shows an increasing trend, and the total value of ecosystem services decreases by 71.30%, with an average annual decrease of 1.24%. The ecological environment is damaged, and soil erosion accelerated.

(2)

Land transfer behavior can significantly affect the carbon storage of the ecosystem. The economic development scenario has a positive effect on the carbon storage of the apple orchard system and atmospheric CO₂ carbon pool, and a negative effect on the carbon storage of the grassland system. The carbon sink protection scenario positively affects the carbon storage of the grassland system and soil, while negatively affecting the atmospheric CO₂ carbon pools.

(3)

Land transfer behavior can significantly affect ecosystem services. The total value of ecosystem services and the value of the four types of services show a trend of first increasing and then decreasing in the economic development scenario, while they generally show a growth trend in the carbon sink protection scenario. In the selection of the “dual carbon target” strategy, priority should be given to the carbon sink protection scenario to quickly improve the carbon sink capacity of the ecosystem. In the selection of poverty alleviation strategies, the economic development scenario should be selected to enable rural impoverished people to quickly overcome poverty.

The research contribution of this article lies in setting up an economic development scenario and a carbon sink protection scenario, combining energy system language with carbon flow, which helps to explore the complex impact of land use change on ecosystem services under different land use scenarios more reasonably, reveal the carbon flow process within the ecosystem, and provide an effective basis for improving ecosystem services. This can provide valuable reference for promoting green and low-carbon development in the Taihang Mountains of China, and provide a basis for formulating evidence-based land use policies in the future.