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Article

Afforestation Subsidy Determination for Haloxylon ammodendron (C.A.Mey.) Bunge in China Based on Cost–Benefit Analysis

by
Shuyu Song
1,2,†,
Duanyang Xu
1,*,† and
Xiaoyu Zhang
3
1
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
3
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Forests 2022, 13(4), 497; https://doi.org/10.3390/f13040497
Submission received: 29 January 2022 / Revised: 9 March 2022 / Accepted: 21 March 2022 / Published: 23 March 2022
(This article belongs to the Section Forest Economics, Policy, and Social Science)
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Abstract

:
Subsidies are an effective instrument to encourage farmers to engage in afforestation which provides many ecosystem services. A scientific and reasonable subsidy level should reflect the demands of various stakeholders so that the subsidy scheme can be accepted by both farmers and the government. This study aimed to establish a framework for designing an afforestation subsidy to attract voluntary participation in a way that seeks to raise both farmers’ and government’s returns while reducing financial expenditure. The framework determines the optimal subsidy level by integrating direct costs, opportunity costs, and ecological benefits to conduct cost–benefit analysis over the period of afforestation. As a case study, we focus on the planting of Haloxylon ammodendron (C.A.Mey.) Bunge in Alxa, Inner Mongolia. The results show that the subsidy level required to motivate farmers is lower than the subsidy level according to the government’s willingness to pay. Under the optimal subsidy level, the government and farmers can reach a balance point that provides effective incentives for afforestation without requiring unreasonable spending. Additionally, the current subsidy is substantially lower than the recommended subsidy; there is still room for improvement in the subsidy policy. The research framework developed herein can help policy and decision makers to design afforestation subsidy schemes and contribute to ecological restoration in the future.

1. Introduction

Afforestation is an effective tool for realizing ecological restoration and desertification control, as forests provide multiple ecosystem services, such as sand fixation, soil conservation, and climate regulation [1,2]. However, ecological programs are often hampered by market failures [3]. A typical policy instrument used by governments is to offer subsidies in afforestation programs; indeed, this is becoming increasingly popular in forest management [4,5]. By making afforestation financially more attractive to farmers than other options, afforestation subsidies offer a way to enhance farmers’ motivation to undertake afforestation, and thus help achieve a desired ecological restoration goal [6,7]. The determination of the subsidy level is the core component of subsidy policy design. To improve the effectiveness, efficiency, and feasibility of policy interventions, it is vital to know how large subsidies should be to enhance participants’ enthusiasm for afforestation while reducing the government’s financial burden [8].
In the administration of afforestation programs, governments provide subsidies mainly to reduce the costs of afforestation and management [9]. However, the subsidy level based on direct costs is generally low, thus influencing the effect of compensation [10]. Moreover, the opportunity costs and external ecological values of afforestation are often not fully considered when designing subsidy policies [11]. Afforestation conducted by individuals or firms provides ecosystem services that are public goods and thus significant positive externalities [12]. Therefore, estimating the value of forest ecosystem services is critically needed as a reference for formulating subsidy policies. However, subsidy levels proposed based on service provision pay little attention to governmental budget constraints [13], which thus has ramifications in terms of the cost-effectiveness of afforestation programs. Furthermore, the major economic precondition for the implementation of subsidy policy is that the value of the services should exceed the provider’s profit loss with associated costs usually being ignored [14,15]. Hence, understanding the whole array of economic and ecological components from the perspective of farmers as well as the government is useful for guiding the design of effective subsidy policies [16].
In this paper, we established an analytical framework to determine the subsidy level by comprehensively quantifying farmers’ willingness to accept and government’s willingness to pay based on a cost–benefit analysis of planting trees over the period of afforestation. The planting of Haloxylon ammodendron (C.A.Mey.) Bunge was selected as the case study, as it is one of the most widely used tree species in afforestation programs in arid regions, and has both ecological and economic value. Through theoretical analysis and a field survey, combined with model simulation, we explored the appropriate afforestation subsidy in Alxa League (hereafter called Alxa), a typical arid region in Inner Mongolia, China. The objectives of this study are to (1) create a research framework for afforestation subsidy level determination, based on cost–benefit analysis; (2) test the framework and design an afforestation subsidy policy by balancing farmers’ direct costs and opportunity costs, and the government’s benefits from ecosystem services in afforestation. It is hoped that this study will support policymaking vis-a-vis afforestation subsidies in ecological restoration contexts.

2. Research Framework

Historically, the government has been the main actor overseeing the supply of forest ecosystem services, and public sector agencies have dominated forest plantation development [17]. Due to various reasons including limited resources and the broad spectrum of forest management, the government expects the private sector to get involved in afforestation to help with the provision of ecosystem services. Since private net benefits are often lower than social benefits, incentives should be offered to address the divergence between public and private goals [18]. To encourage farmers to participate voluntarily in afforestation, the government must offer incentives to solve the problems of recovering the costs of afforestation and make the returns from afforestation exceed those from other options. Meanwhile, because of budget constraints, a cost-effective program should focus on raising government returns from its support for afforestation with minimal costs [19]. Hence, the design of the subsidy policy should reflect the demands of both farmers and the government and be sensitive to the interests of different stakeholders [20].
Afforestation requires long-term efforts aimed at realizing both economic and ecological benefits [21]. A large proportion of the overall investment is used in the initial stage of afforestation, while the major share of revenue is generated during the final stage [22]. Therefore, to reduce the investment risk of afforestation, subsidies should be offered to recover the direct costs in the first few years. Farmers are profit seekers with goals to maximize their revenues, thus they will weigh the benefits of afforestation and other labor activities before making decisions [23]. Specifically, they will choose to plant trees if and only if the sum of net benefits from afforestation and the subsidy is greater than the revenues from other options. From the viewpoint of the government, the aim of introducing the subsidy is to optimize the trade-off between obtaining the greatest possible ecological benefits while minimizing financial expenditure [24]. A rational government would offer subsidies that are less than the value of forest ecosystem services.
On the basis of the foregoing, we establish a research framework for determining the afforestation subsidy level (Figure 1). In theory, the subsidy needs to cover farmers’ direct costs and opportunity costs [25,26], and should not exceed the government’s ecological benefits [27]. The lower limit of the subsidy acceptable to farmers was determined based on the direct costs and opportunity costs of plantation. The upper limit of the subsidy that the government would be willing to pay can be calculated as the value of ecosystem services achieved by afforestation. All subsidies between these two limits can be regarded as feasible in that they would not only motivate the farmers to participate in the afforestation program, but also enable the government to achieve the ecological restoration goal for less cost. The optimal subsidy was calculated as the average of the lower and upper limits.

3. Materials and Methods

3.1. Study Area

Alxa is located in the western part of Inner Mongolia, China (37°24′–42°47′ N and 97°10′–106°53′ E) with a total area of approximately 2.70 × 105 km2 (Figure 2). Alxa is a representative arid region with a vulnerable ecological environment and has long been suffering from desertification and grassland degradation [28]. The region has a temperate continental climate that is characterized by strong winds, drought, and intense evaporation, with an average annual temperature of −0.6–10.8 °C and an average annual precipitation of 40–200 mm that declines along a gradient from southeast to northwest. The average annual evaporation is above 3500 mm, and the average annual wind speed is 2.9–5 m/s, which mainly occurs in winter and spring. Available land resources are scarce in this region: desert, bare land, and degraded grassland account for approximately 90% of Alxa’s total area.
Since the 1990s, many afforestation programs have been implemented in Alxa for the purpose of ecological protection and degraded land restoration. H. ammodendron is one of the dominant species in Alxa, and it is the host plant of Cistanche deserticola Ma. Due to the ecological function of H. ammodendron and economic value of C. deserticola, the two species were widely planted during the process of ecological restoration in this region. At present, the average annual area of artificially planted H. ammodendron is 32,667 ha, and the inoculation area of C. deserticola is 12,333 ha.

3.2. Data Collection and Processing

Data used in this study spanned climate, vegetation, soil, topography, and socioeconomic variables, along with cost and benefit data of H. ammodendron planting. Meteorological data including temperature, precipitation, wind speed, and sunshine duration were acquired from the China Meteorological Data Service Center (http://data.cma.cn, accessed on 17 May 2021). Vegetation, soil, land use maps, and a Digital Elevation Model (DEM) with a 1-km resolution were obtained from the Resource Environmental Data Centre of the Chinese Academy of Sciences (http://www.resdc.cn, accessed on 17 May 2021). Socioeconomic data, such as consumer price index, price index of agricultural production materials, income from other labor activities from 2014 to 2019, were collected from the Statistics Yearbooks of China and Inner Mongolia, and the Migrant Workers Monitoring Survey Report released by the National Bureau of Statistics (http://www.stats.gov.cn, accessed on 17 May 2021). To collect information about the planting of H. ammodendron and C. deserticola, a face-to-face group interview was conducted in Alxa Left Banner in August 2018 by using a semi-structured method. We randomly selected seven representatives of big specialized households from the largest farming cooperative that plants H. ammodendron and C. deserticola in Alxa. In addition, managers of four ecological technology companies that specialize in the production of C. deserticola were invited to participate in the interview. Through the interview, we knew the specific process of the planting period, obtained the data of plantation, and investigated the potential barriers or problems in afforestation. According to the consensus reached by interviewees, we set some key parameters, including planting area, water demand, and planting density. At the end, records were returned to the participants for comment and correction. Meanwhile, we performed a review of the literature using the CNKI database to find publications that provided the cost and benefit data of H. ammodendron plantation [29,30,31,32,33]. Furthermore, data on the distribution of H. ammodendron were obtained from the Alxa Bureau of Statistics (http://tjj.als.gov.cn, accessed on 17 May 2021). To facilitate spatial analysis, all raster data were uniformly resampled to a resolution of 1 km.

3.3. Methods

We assessed the afforestation subsidy over a planting period. According to the field survey, after H. ammodendron is planted, C. deserticola can be inoculated in the third year and harvested in years 6–8, and the output would decline significantly afterwards. Therefore, an 8-year planting period was chosen. Since farmers can only earn income in years 6–8, we assumed that the implementation period of the subsidy is the first 5 years and the subsidy is issued at the end of every year, with a one-off subsidy for preparation costs in the first year and equal subsidy for management costs in years 2–5 [34].

3.3.1. Direct Costs

We analyzed the costs and benefits of H. ammodendron plantations by using the net present value (NPV) method. The equations for the annual costs and benefits of plantation are as follows:
N P V C i = ∫ i − 1 i C t 1 + r t d t
N P V B i = ∫ i − 1 i B t 1 + r t d t
where C(t) is the costs of plantation at time t, including preparation, management, inoculation, and harvest costs; B(t) is the benefits of plantation at time t; r is the annual discount rate, which was specified as 1.63% according to the average consumer price index of Inner Mongolia.
According to the interview with households and managers, the per-capita planting area of H. ammodendron was set to 1 ha, the density of H. ammodendron was set to 525 plants/ha, and the density of C. deserticola was set to 1200 plants/ha. The composition and description of planting costs are shown in Table 1 and Table 2. Planting benefits only consider the benefits of C. deserticola, the yield was set to 4 kg/plant [29], and the sale price was set to 35 RMB/kg [30]. With reference to the price index of agricultural production materials of Inner Mongolia, considering that the planting costs may change with market price fluctuations in the future, the planting costs were adjusted according to the rate of change in the cost of production materials (−0.06%) and labor costs (5.89%).

3.3.2. Opportunity Costs

Opportunity costs of afforestation refer here to the forgone benefit that would be derived by other most profitable labor activities. Each farmer has a fixed labor endowment at a given time and has to decide whether to plant trees or choose other labor activities. In China, farming, raising livestock, and out-migration employment are the most fundamental and common options adopted by rural farmers [35]. Therefore, the farmer’s other labor activity set can be defined as L = {A, H, E}, where A, H, E denote the decision to engage in agriculture, husbandry, and out-migration employment, respectively. The NPV of planting H. ammodendron and other labor activities over the planting period can be calculated as follows:
N P V P = ∫ 0 T B t − C t 1 + r t d t
N P V A = ∫ 0 T B A t 1 + r t d t
N P V H = ∫ 0 T B H t 1 + r t d t
N P V E = ∫ 0 T B E t 1 + r t d t
where BA(t), BH(t), and BE(t) are the benefits of farming, raising livestock, and out-migration employment, respectively.
For farmers who choose to plant H. ammodendron, the opportunity cost is the maximum benefits of other labor activities, and is expressed as follows:
O C = M A X N P V A , N P V H , N P V E
According to the per capita disposable income of farmers and herdsmen of Inner Mongolia, and the average monthly income of migrant workers employed in the western region of China, the income from other labor activities and their rates of change are set as shown in Table 3.

3.3.3. Ecological Benefits

As one of the dominant plant types in deserts, H. ammodendron mainly provides sand fixation and carbon sequestration services. It can not only reduce the amount of soil loss by increasing the surface roughness and decreasing the wind speed [36], but also sequester CO2 from the atmosphere through photosynthesis [37], which is of significance to ecological restoration and environmental protection in drylands. Therefore, based on the characteristics of dryland ecosystems, we finally selected sand fixation and carbon sequestration services provided by H. ammodendron to estimate the maximum subsidy the government is willing to offer.
1.
Sand fixation service
The value of sand fixation was estimated using the shadow project approach and market value approach with the following equation:
V S = Q × P S + Q × ∑ i = 4 4 S i × P i K i
where Q is the amount of sand fixation; PS is the cost of digging and transporting the soil, which was specified as 13.86 RMB/t; i = 1, 2, 3, 4 represent nitrogen, phosphorus, potassium, and organic matter, respectively; Si is the content of substance i in soil, which was assigned to 0.03%, 0.05%, 2.1%, and 0.9%, respectively; Pi is the market price of fertilizer, based on the national average retail price, the price of diamine phosphate, potassium chloride, and organic matter were set to 2928.7 RMB/t, 2257.2 RMB/t, and 415.71 RMB/t, respectively; Ki is the content of substance i in fertilizer, the content of nitrogen and phosphorus in diamine phosphate fertilizer are 14% and 15%, and the content of potassium in potassium fertilizer is 50%.
The Revised Wind Erosion Equation (RWEQ) was used to estimate the amount of sand fixation, which fully considered factors including climate, soil erodibility, soil crust, surface roughness, and vegetation [38,39]. The regional average value was calculated as the amount of sand fixation per unit area of H. ammodendron for each year. The amount of sand fixation in each year during the planting period was simulated by the model variable control method that inputs the vegetation coverage of H. ammodendron in the corresponding year and the average climatic conditions from 2001 to 2016. The aboveground biomass estimation model [40,41] is combined with an age estimation model [42] to calculate the vegetation coverage at time t using the following equation:
V C = 0.295 t 1.861
2.
Carbon sequestration service
The value of carbon sequestration was estimated using the carbon tax approach, as shown in the following equation:
V C = Δ C × P C
where ΔC is the annual increment of carbon sequestration; PC is the carbon price, which is specified as 1034 RMB/t (150 USD/t) according to the internationally accepted Swedish carbon tax rate.
The amount of carbon sequestered in each year is equal to the increment of biomass multiplied by the carbon transfer factor. According to the biomass estimation model [41,43], age estimation model [42], and the carbon transfer factor, the carbon sequestration of a single tree at time t can be calculated as follows:
C = 0.037 t 2.111

4. Results

4.1. Lower Limit of Subsidy Based on Farmers’ Direct Costs

The costs and benefits of planting H. ammodendron in each year are shown in Figure 3. In years 1–5, although the planting costs are relatively low, including the expenses of preparation, management, and inoculation, since the C. deserticola cannot be harvested during this period, there would be no benefits from planting without subsidies. In years 6–8, the costs include management and harvest expenses, and the benefits derive from income from selling C. deserticola. The annual benefits are much greater than the costs, therefore the net benefits are considerable. From the perspective of farmers, afforestation subsidies are supposed to cover both preparation costs and management costs. The first-year subsidy should exceed the preparation costs, and the subsidy in years 2–5 should exceed the management costs. Through calculation, the lower limit of the subsidy for the first year is 3892.06 RMB/ha, and the lower limit for years 2–5 is 1577.97 RMB/ha.

4.2. Lower Limit of Subsidy Based on Farmers’ Opportunity Costs

The average annual NPV of each option over the planting period is shown in Table 4. The total benefits of planting are 451,035.84 RMB/ha and the total costs are 47,537.31 RMB/ha, thus the average annual NPV of planting H. ammodendron is 50,437.32 RMB/ha. If farmers choose to plant trees, the opportunity costs in terms of out-migration employment are 52,875.05 RMB/year. To motivate farmers to participate in afforestation, the sum of subsidies and planting benefits should exceed the opportunity costs of planting. Assuming that the government grants certain subsidies on the basis of direct costs, the lower limit of the subsidy for the first year is 6047.21 RMB/ha and the lower limit for years 2–5 is 3733.12 RMB/ha.

4.3. Upper Limit of Subsidy Based on Government’s Ecological Benefits

We estimated the amount of sand fixation and carbon sequestration per unit area of H. ammodendron as a function of tree age, and finally calculated the value of ecosystem services provided by afforestation in each year (Figure 4). The value of sand fixation and carbon sequestration both show a significant upward trend with the increase in tree age. The value of sand fixation and carbon sequestration provided by H. ammodendron over the planting period are 57,583.41 RMB/ha and 1620.69 RMB/ha, respectively. The total value of ecosystem services is 59,204.09 RMB/ha. The maximum amount of subsidy the government is willing to pay is the ecological benefits obtained from afforestation. Assuming that the subsidies would be provided as fixed annuity over the implementation period of the subsidy scheme, the upper limit of the subsidy for years 1–5 is 12,415.19 RMB/ha.

4.4. Determination of Afforestation Subsidy from Multiple Perspectives

Based on the analysis of direct costs and opportunity costs from the perspective of farmers, the minimum subsidy expected by farmers is 6047.21 RMB/ha in year 1 and 3733.12 RMB/ha in years 2–5. From the perspective of the government, the maximum subsidy the government is willing to pay is 12,415.19 RMB/ha in years 1–5. Taking the average of the lower limit and upper limit of the subsidy, the optimal subsidy is 9231.20 RMB/ha in year 1 and 8074.16 RMB/ha in years 2–5.
Under the implementation of the above afforestation subsidy scheme, the NPV of planting H. ammodendron with the subsidy is greater than that without the subsidy (Table 5). In years 1–5, subsidies can cover the direct costs of planting and ensure that farmers have certain net benefits every year, which greatly reduces investment risks and avoids the restriction of a large amount of capital investment in the early planting period on farmers’ afforestation activities. For the government, during the planting period, the NPV of the subsidy issued to farmers is 39,641.91 RMB, while the government’s benefit from ecosystem services is 59,204.09 RMB. The total subsidy accounts for 66.96% of the ecological benefits. Overall, the optimal afforestation subsidy proposed in this study fully considers farmers’ demands for subsidies and the government’s willingness to pay, which is acceptable from the perspectives of both farmers and the government, and is conducive to the realization of a win–win outcome.

5. Discussion

Although afforestation is promoted worldwide to restore degraded environments, economic problems often occur over the short run, and their implementation may not be feasible at the regional level without subsidies provided to participants. Similar to other studies [44,45], the case of H. ammodendron plantation in Alxa again shows the importance of subsidies because the net benefit obtained from afforestation is less than that from other labor activities. Apart from making afforestation programs feasible, subsidies are expected to improve people’s livelihoods by elevating farmers’ income, particularly in the poor regions. However, afforestation subsidies also increase a government’s financial burden, and cannot be long lasting. Therefore, the selection of tree species that will generate sufficient economic return in the long run are more encouraged. In the case of H. ammodendron plantation, our analysis indicates that even without incentives in the later planting period, the financial situations of the farmers will not be altered in the future, which makes it possible to realize the risk aversion by granting subsidies in the early stage.
To implement flexible and feasible subsidies in afforestation programs, it is of great importance to focus on farmers’ interests and precisely estimate their participation costs [46]. Our study suggests that a large amount of capital investment is required in the initial stage of afforestation, which is a major factor restricting farmers’ participation in afforestation. The current afforestation subsidy policy in Alxa is to issue 1500 RMB/ha in the first year and third year, which is much lower than the optimal subsidy level presented in this study. Therefore, it is crucial to promote the subsidy level, which was consistent with the conclusions of previous studies [47,48,49]. The current subsidy cannot offset the direct costs of planting, so for farmers with insufficient funds for afforestation, the limited access to capital and long delay before an economic return may cause farmers to face funding shortages. According to our field survey, many farmers pointed out that they are reluctant to ask for loans because of low quotas and one-year maturities, which contradict the slow returns from afforestation. From the perspective of opportunity costs, the scale of planting has a direct impact on the actual benefits of farmers. According to cost–benefit analysis of afforestation, the NPV of afforestation covering large areas will be significantly higher than the NPV of other options. However, for farmers with small holdings, if the subsidies are not sufficient to make up for the gap between net benefits and opportunity costs, they would tend to choose other labor activities to earn more money, which would reduce the number of people involved in afforestation. While opportunity costs were estimated based on three other labor activities’ benefits, the actual opportunity costs depend on the farmers’ labor allocation, as farmers may be not only engaged in a single livelihood. Detailed data on labor allocation can be used to calculate opportunity costs precisely in the future.
The key to formulating a subsidy policy based on the government’s ecological benefits is the selection of ecosystem services for valuation [50]. Service metrics should be selected according to the types and functions of the regional ecosystem to meet the needs of subsidy research [51,52]. Compared with the compensation standard proposed by other scholars [11,34], the subsidy level in this study is higher, which may be attributed to the difference in the selection of ecosystem services. Based on the characteristics of dryland ecosystems, we selected sand fixation and carbon sequestration for valuation, but forests also provide other ecosystem services such as hydrological regulation and water purification, which have been commonly selected for valuation to establish ecological compensation mechanisms in previous studies [53,54]. Therefore, the ecological benefits of afforestation may be underestimated to a certain extent, resulting in an underestimation of the subsidy that the government is willing to pay. The value of more ecosystem services needs to be further assessed in future research. Ecosystem services have a spatial flow effect, and the supply and use of ecosystem services is often inconsistent in space [55]. Liu et al. [56] and Pei et al. [57] proposed cross-regional ecological compensation schemes based on the theory of ecosystem service flow. However, due to the difficulty of analyzing mechanisms of ecosystem service flows, the valuation methods adopted in this study did not take into account the radiation benefit of ecosystem services and residents’ willingness to pay in beneficiary areas. Doing so thus represents important terrain for future research. In addition, the determination of optimal subsidies should be improved by measuring the likelihood of farmers participating in afforestation under different incentives and the corresponding ecosystem services provided, thereby selecting the subsidy level with the highest cost-effectiveness.
Based on our analysis, we propose several suggestions for improvement. First, the design of afforestation subsidy policies should fully consider the heterogenous demands of different stakeholders. The government should enhance public participation, especially farmers’ participation. The subsidy level should be jointly determined by both sides with the aim of balancing the interests of the government and farmers. Second, the subsidy policy could be improved by raising the subsidy level appropriately to increase the enthusiasm of farmers to participate in afforestation and give more consideration to the costs and benefits of afforestation in different periods. Furthermore, a forest management subsidy should be established that can realize cost savings to alleviate the financial pressure on farmers before afforestation creates economic benefits. Third, other measures should be adopted to collect afforestation funds and offer help to farmers. For example, local governments should develop green finance and improve the green financial product system based on ecological rights to broaden the financing channels for afforestation. Furthermore, developing innovative agricultural insurance for characteristic plants and agricultural resources in drylands can offset the risk of unforeseen monetary loss in afforestation. Financial and technical barriers can be overcome if farmers form professional cooperatives and establish stable collaborative relations with enterprises, so that they can get help in terms of technical training and accessing afforestation funds.

6. Conclusions

This study developed a framework for determining the optimal subsidy level that takes into account the demands of different stakeholders, based on analysis of farmers’ direct costs and opportunity costs, and the government’s ecological benefits. The theoretical framework was complemented by a case study of H. ammodendron plantation in Alxa, Inner Mongolia. The findings demonstrated that the magnitude of the afforestation subsidy differs depending on the stakeholders which are being considered. The subsidy the government would be willing to provide is substantially higher than the subsidy that farmers would be willing to accept. Therefore, a compromise can be reached which induces farmers to participate in afforestation without requiring excessive financial outlays by the government. Since the current subsidy is lower than the optimal subsidy proposed in this study, efforts is needed by the government to adjust subsidy policy and develop other instruments to guarantee farmers’ interests. Through information collection, valuation of ecosystem services, and cost–benefit analysis, the framework can be applied to design an afforestation subsidy policy for different tree species in other regions. However, there still exist some uncertainties in the determination of subsidy level; future research is required to consider the labor allocation of farmers, incorporate more ecosystem services and analyze their flows effects.

Author Contributions

Conceptualization, D.X. and S.S.; methodology, S.S. and D.X.; formal analysis, D.X. and S.S.; investigation, D.X.; data curation, S.S. and X.Z.; writing—original draft preparation, S.S. and D.X.; supervision, D.X.; funding acquisition, D.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was jointly funded by National Natural Science Foundation of China (41971253), and National Program on Key Research Project of China (2017YFC0506704).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Meteorological data are available at http://data.cma.cn (accessed on 17 May 2021). Vegetation, soil, land use maps, and a Digital Elevation Model (DEM) can be obtained from http://www.resdc.cn (accessed on 17 May 2021). Socioeconomic data are available at http://tj.nmg.gov.cn and http://www.stats.gov.cn (accessed on 17 May 2021). Data on the distribution of H. ammodendron can be obtained from http://tjj.als.gov.cn (accessed on 17 May 2021).

Conflicts of Interest

The authors declare no conflict of interest.

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Forests 13 00497 g001 550
Figure 1. Research framework for determining the afforestation subsidy level.
Figure 1. Research framework for determining the afforestation subsidy level.
Forests 13 00497 g001
Forests 13 00497 g002 550
Figure 2. (a) Distribution of H. ammodendron (C.A.Mey.) Bunge in the study area; (b) H. ammodendron; (c) C. deserticola Ma.
Figure 2. (a) Distribution of H. ammodendron (C.A.Mey.) Bunge in the study area; (b) H. ammodendron; (c) C. deserticola Ma.
Forests 13 00497 g002
Forests 13 00497 g003 550
Figure 3. Annual costs and benefits of planting H. ammodendron.
Figure 3. Annual costs and benefits of planting H. ammodendron.
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Forests 13 00497 g004 550
Figure 4. Values of ecosystem services provided by afforestation.
Figure 4. Values of ecosystem services provided by afforestation.
Forests 13 00497 g004
Table
Table 1. Preparation costs for planting H. ammodendron (C.A.Mey.) Bunge [31].
Table 1. Preparation costs for planting H. ammodendron (C.A.Mey.) Bunge [31].
ItemDescriptionYearCost (RMB/ha)
Land leveling5 ha of land can be leveled in 12 h, 50 RMB/h1120
IrrigationWater consumption 1500 t/ha, 0.1 RMB/t150
Irrigation equipmentPipes, joints, and pumps1800
H. ammodendron seedlings0.1 RMB/seedling52.5
Planting of seedlings1 ha of land can be planted in 12 h, 50 RMB/h600
FertilizerNitrogen fertilizer 5.2 g/plant, 2928.7 RMB/t; Potassium fertilizer 77 g/plant, 2257.2 RMB/t99
Table
Table 2. Management, inoculation, and collection costs for planting H. ammodendron [30,31,32,33].
Table 2. Management, inoculation, and collection costs for planting H. ammodendron [30,31,32,33].
ItemDescriptionYearCost (RMB/ha)
IrrigationWater consumption 900 t/ha in year 1 and 450 t/ha in year 2–8, 0.1 RMB/t190
2–845
WeedingWeeding 3 times per annum in years 1–3 and once per annum in years 4–8, 300 RMB/ha1–3900
4–8300
C. deserticola Ma seeds0.2 RMB/seed4105
C. deserticola inoculation30 pits can be dug in 1 h, 50 RMB/h4875
C. deserticola harvest2 RMB/kg6–89600
Table
Table 3. Income from other labor activities and their rates of change.
Table 3. Income from other labor activities and their rates of change.
Other Labor ActivitiesAgricultureHusbandryOut-Migration Employment
Income (RMB/year)11,87318,05844,676
Change rate (%)10.187.535.89
Table
Table 4. Benefits of each option.
Table 4. Benefits of each option.
H. ammodendron Plantation (RMB/ha·Year)Agriculture (RMB/Year)Husbandry (RMB/Year)Out-Migration Employment (RMB/Year)
Benefits50,437.3216,684.9522,822.5852,875.05
Table
Table 5. Benefits of planting H. ammodendron with and without the afforestation subsidy.
Table 5. Benefits of planting H. ammodendron with and without the afforestation subsidy.
Time (Year)With Subsidy (RMB)Without Subsidy (RMB)
Yearly BenefitsCumulative BenefitsYearly BenefitsCumulative Benefits
1−3829.64−3829.645256.185256.18
2−1001.56−4831.206820.3012,076.48
3−1041.27−5872.486657.4118,733.89
4−1479.15−7351.626098.3024,832.18
5−403.23−7754.857054.8831,887.06
6140,018.90132,264.04140,018.90171,905.96
7137,079.36269,343.40137,079.36308,985.32
8134,155.13403,498.53134,155.13443,140.45
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Song, S.; Xu, D.; Zhang, X. Afforestation Subsidy Determination for Haloxylon ammodendron (C.A.Mey.) Bunge in China Based on Cost–Benefit Analysis. Forests 2022, 13, 497. https://doi.org/10.3390/f13040497

AMA Style

Song S, Xu D, Zhang X. Afforestation Subsidy Determination for Haloxylon ammodendron (C.A.Mey.) Bunge in China Based on Cost–Benefit Analysis. Forests. 2022; 13(4):497. https://doi.org/10.3390/f13040497

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Song, Shuyu, Duanyang Xu, and Xiaoyu Zhang. 2022. "Afforestation Subsidy Determination for Haloxylon ammodendron (C.A.Mey.) Bunge in China Based on Cost–Benefit Analysis" Forests 13, no. 4: 497. https://doi.org/10.3390/f13040497

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