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Procedia Environmental Sciences
Procedia Environmental Sciences 8 (2011) 2471–2476 Procedia Environmental Sciences 13 (2012) 2445 – 2450
www.elsevier.com/locate/procedia
The 18th Biennial Conference of International Society for Ecological Modelling
Economic Valuation of Forest Ecosystem Services in Heshui Watershed using Contingent Valuation Method Zhang Tao, Haiming Yan, Jinyan Zhan a
State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
Abstract
We attempted to estimate the economic value of forest ecosystem services in a typical deforestationafforestation area represented by the Heshui watershed in Jiangxi province. Environment services provided by restored forest ecosystem in Heshui would include basic goods supply, soil-water conservation, climate regulation, environment purification and biological habitats. A contingent valuation survey in 200 households in three typical counties, Anfu, Yongxin and Lianhua, was administered to estimate values of forest ecosystem. Respondents were given a current situation and hypothetical scenario to ask their willingness to pay to restore and protect the forest in this area. Analysis results from 170 valid questionnaires and 80 WTPs indicated that respondents would pay for the forest restoration and protection 238 yuan per mu yearly. And WTP was found related to basic social-economic variables: income, education level, household population, off-farm work members. This paper will give a brief guide of CVM application and allow decision makers to manage forest ecosystem for sustainable development in comparing different situations.
© 2011 Published by Elsevier B.V. Selection and/or peer-review under responsibility of School of © 2011 Published by Elsevier Ltd. Environment, Beijing Normal University. Open access under CC BY-NC-ND license. Keywords: Forest ecosystem services; Contingent valuation method; Willingness to pay; Jiangxi
1. Introduction The objective of this study is to estimate the economicvalue of the forest in Heshui watershed, Jiangxi province, China, based on the Contingent Valuation Method (CVM). The Heshui watershed, consists of
Corresponding author. E-mail address:
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1878-0296 © 2011 Published by Elsevier B.V. Selection and/or peer-review under responsibility of School of Environment, Beijing Normal University. Open access under CC BY-NC-ND license. doi:10.1016/j.proenv.2012.01.233
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Anfu, Yongxin counties, Ji’an city and Lianhua county, Pingxiang city, located in the middle west of Jiangxi within area of 9103km2. The predominant climate is subtropical moist monsoon featured by mild, rainy, and sunny weather; the average annual temperature, relative moisture, and rainfall is 17.5℃, 82% and 1570 mm. Heshui watershed is within high forest coverage and biodiversity. Unfortunately during the ―Great leap forward‖ period, national steel-making fever drove most of farmers to turn farming to logging and mineextracting, which aimed to meet the country’s raw material needs [1]. The environmental concerns—with resources over exploitation—were cultivated land desertification, yield reduction, and forest coverage contraction. And now, most areas of the forest ecosystem are in different stages of inverse ecological succession. A series of forest land management policies were implemented throughout China at the beginning of the 1970s to transform the wood supply to ecological reconstruction, commercial investment oriented wood supply, environmental conservation and poverty reduction [1-3]. With the purpose of taking full use of forest ecosystem functioned soil-water conservation, climate regulation, environment purification, China came up with the worldwide spotlight policy-―Grain for Green‖-which was prompted by the Yellow River cutoff in 1997 and unprecedented floods of the Yangtze River basin in 1998 [2, 3]. Jiangxi province responded with a forest rights reform policy in 2003, but that resulted in biodiversity change and forest quality descent due to the simple structure of tree species [1]. The rest of this paper is organized in the following order. First we give a brief literature review that focuses on contingent valuation method (CVM). Then series of steps were followed in CVM studies to design our survey questionnaire. And at last preliminary analysis on our elicited information will be briefly described. 2. Literature review Ecosystem services are public goods, essential to the support of life, but there are no relevant markets where these values are expressed [4]. Due to the public attributes, a non-market economic valuation method was required to estimate their non-use values to avoid ―The Tragedy of the Common.” Based on previous studies, non-market valuation methods can be divided into two categories: revealed preference and stated preference methods [5]. The former is represented by the travel cost method (TC) and the hedonic pricing method (HPM), which has been principally applied to the actual market valuation characterized by exchanging market goods/services and economic currency. On the contrary, stated preference methods mainly consist of conjoint method; choice experiment and contingent valuation method (CVM), were commonly used to value non-market sources and services, and the last one was also used to estimate the total ecosystem services value [8-10]. Irreplaceable merits inherited from CVM studies showed that it doesn’t require an explicit linkage between the economic market price and non-market goods. All researchers have to do is to set up a hypothetical situation and find the truth by which they can present the respondents’ value on services or goods [11]. Consequently, researchers can discover the maximum willingness of respondents to pay for improvement of environmental quality and conservation of natural resources which can indirectly reflect the values placed on the resources. 3. Survey design and data handling The data come from the investigation based on peasant households in the Heishui watershed carried out in October 2010. The questionnaire was designed with CVM and DC (Single-bound Dichotomous Choice, i.e. the answer is yes or no), and the investigation was mainly carried out by interview [12].
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There are four parts in the questionnaire. The ecosystem services involved in current PES projects can be summarized into the followings: watershed water resource protection, forest carbon sequestration, biodiversity conservation and landscape culture. Then the contents were readjusted into the following sectors according to the research purposes: (1) the general condition of the peasant household. Representative socioeconomic indicators were selected to measure the peasant household background such as the education level, number of children under 15 years of age, household income, all of which influences the individual’s consciousness of ecological environment expressed by WTP. (2) Consciousness of ecological environment, which mainly aims to make the peasants deeply understand the forest ecosystem services and estimate their WTP more accurately. (3) WTP of peasants. In view of the great difference of local household socioeconomic background, we used the method of DC format to elicit their max WTP. Some other methods were used when processing the WTP data [13]. (1) The WTP will be considered to be invalid if it is too high; in this study the threshold was set to be 5% of the household income. (2) The zero WTP will be considered to be invalid when it is identified as the protest zero. The protest zero means that people believe it is the duty of the government or other organizations to pay for the ecosystem services and environmental goods while enjoying the resources, or they do not trust the related organization or government. (3) Exclude the real zero WTP. It will be regarded as the hypothetically bias between the virtual and real market due to the low education level in the interview processing; (4) Exclude the interviewees that are not familiar with the questions at all. After pretreatment, 80 valid WTP were obtained in this investigation, which met the requirement of effectiveness for the total questionnaire. Since the questionnaire was designed with CVM-DC, the answer of peasant household was the noncontinuous variable, for which the linear regression is not suitable, so binary logistic nonlinear regression was used to process and analyze the investigation data in this study. 4. Results and discussion 4.1. Demographic information and respondents’ environment consciousness After being emended by a pre-survey, 200 questionnaires were surveyed in Heshui watershed with 10 percent of the households in each village to ensure the survey’s representativeness. 170 questionnaires were available in the retrieved 186 surveys, including the 80 reliable WTP within the primarily analysis. The basic social-demographic information is presented in Table 1. Farming households make up the largest percentage in Heshui watershed, and the land management is aging due to out-migration of many young laborers; together with a low education level and not enough income to renew the facilities, labor capacity in this area has dropped rapidly over time. Theoretically, all of these will influence the respondents’ willingness to pay for the forest ecosystem services. Most results from surveys and face-to-face interviews have been formed into a binary number format in Table 2, which would feed to binary logistic analysis which aimed to determine the important driving forces of respondents’ willingness. Data show that most respondents are familiar with forest resources in the Heshui watershed and know that they are important to the ecological civilization construction and healthy life conservation, even though they don’t know exactly what ecological services in the watershed offers except for provision functions in terms of firewood, timber, and fruit supply. Many farmers pay increasing attention to other services when they have suffered from natural disasters, such as drought, floods, ice-snow disasters and landslides, and some of them would take varieties of measures, or follow the government policies to protect the forest ecosystem, especially within the activities of planting economic tress to maximize their profit in constructed situations. Almost 61.8% of respondents show a willingness to pay for the forest recovery and construction.
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Table 1 Basic social-economic background environmental consciousness of respondents Survey data Respondent households (hu)
170
Gender proportion
116/54
Average population (hu) Off-farm work population per hu
5.55 1.89
Per personal capita (1000 yuan) Per household capita （1000 yuan）
3.84 21.32
Average educational level（year）
7.57
Table 2 environmental consciousness of respondents Question/ information Whether is familiar with forest in Heshui watershed（CON1） Whether the forest is important to this area (IMP) Whether the forest area changed in the past decades (FAC) Whether took some measures to protect forest ecosystem (PRO) Whether is willing to contract plots to plant trees (AFF) Whether suffered from natural disasters (DIS) Whether abandoned some cultivated land (DES) Whether is willing to pay for the forest ecosystem (WTP)
Frequency(yes/no)
Proportion (%)
142/28 165/5 49/121 48/122 55/115 40/130 56/114 105/65
83.5/16.5 97.1/2.9 28.8/71.2 28.2/71.8 32.4/67.6 23.5/76.5 32.9/67.1 61.8/38.2
4.2. WTP distribution Following the pretreatment steps, 80 maximum WTP were available to generate the lognormal distribution curve above the frequency bar chart. Furthermore, K-S test confirmed that the data fit lognormal distribution very well. The distribution of WTP obtained from the survey is presented in Fig.1. The expected results showed that most WTPs located in the low area of the bid amount. The mean WTP was 238 yuan per year per mu, which was located in the range of 95% confidence interval with uncertainty analysis.
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Fig.1 WTP distribution
4.3. Driving force analysis Responses of participants were taken as the dependent variable, and independent variables were described as follows: Gender, Age, Education level, Occupation, Household population, Children under 15 years old, Off-farm work population, Cropland area, Household income, Forest area and whether the area changed or not, Forest ecosystem importance, Cropland desertification, Precipitation, Temperature, Disasters suffered or not, which was shorted to the variable name- GEN, AGE, EDU,OCU, POP, CHI, OW, CRO, INCOME,FOR, FAC,IM, DES, PRE, TEM, DIS . The conceptual model can be built to analyze the consciousness and socio-economic driving factors: Yi=f(GEN, AGE, EDU,OCU, POP, CHI, OW, CRO, INCOME,FOR, FAC,IM, DES, PRE, TEM, DIS) Yi represents the respondents’ environmental consciousness and willingness to pay in binary number (Table 2). A Binary Logistic regression method was used to determine the dominances of respondents’ willingness. Results presented in Table 3 indicate that the most important determinants influencing whether the respondents’ WTP or not for the forest protection were educational level, income, forest land area and area changed or not and if they suffered from the natural disasters in terms of drought, flood, slope slide, which were mentioned mostly in face-to-face interview. Table 3 Regression results of conceptual model Whether or not WTP Driving force AGE EDU OCU POP OW CROP INCOME FAC DIS FOR F-statistic R2 Number of observations
Coefficient -0.064 0.108 0.022 0.028 -0.011 0.008 0.043 0.033 0.043 0.112
t 0.117 0.026** 0.499 0.192 0.692 0.467 0.024* 0.702* 0.627** 0.698* 3.284 0.443 170
5. Conclusion A contingent valuation method was used to design a questionnaire to estimate the willingness to pay for forest ecosystem services including provision of timber, firewood, fruit and habitats, climate regulation concerned with temperature and precipitation, environment purification of water and air, soilwater and biodiversity conservation. The most acceptable services to farmers were provision function with the purpose of maximizing household income under the low income, energy crisis and outdated consumption patterns. Single-bound dichotomous choice format was applied to elicit the respondents’
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maximum WTP. And 80 valid WTP values derived from the questionnaire survey indicate the average WTP is 238 yuan per mu yearly in cash. In order to determine the major driving factors of whether respondents are willing to pay for forest ecosystem service conservation, a conceptual model between the social-economic and WTP was established and analyzed by a binary logistic regression model. The results indicated that the WTP was significantly impacted by several factors: age, education level, occupation, household population, offfarm work members, income, forest area and whether respondents suffered from natural disasters. Acknowledgements This research was supported by the National Basic Research Program of China (973 Program) (2010CB950904); National Scientific Foundation of China (40801231; 41071343) is also appreciated. This study was conducted with support from Beijing Normal University for their help during the questionnaire design and pre-survey, Dong Surui, Rong Lei. We also thank Lin Yingzhi, Ke Xinli, Zhu Wenwu, Fan Xiang for helping with survey adjustment and field work. Certainly we appreciate other group members in the whole process of this study. All errors will be the responsibility of the authors. References [1] QiuXuehong, Yang Jie. Investigation and measures of forest land and soil erosion of JiangXi province. Subtropic Soil and Water Conservation, 2007, 19(4): 35-7. [2] Uchida E, Xu Jintao, Rozelle S. “Grain for Green‖ Policy in China: Cost-effectiveness and Sustainability of a Conservation Set-aside Program. Land Economics, 2005, 81(15):247-64. [3] Xu Jintao, Tao Ran, XuZhigang. Sloping land conversion program: cost-effectiveness structural effect and economic sustainability. China Economic Quarterly. 2004, 4(1):139-62. [4] Robert Costanza, Ralph d’Arge, Rudolf G, et al. The value of the world’s ecosystem services and natural capital [J].Nature, 1997, 387:253-60. [5] Monica I O, Alex S M, Barry D S. Economic valuation of environmental services sustained by water flows in the Yaqui River Delta [J]. Ecological Economics, 2008, 65:155-66. [6] Bateman I J, Langford I H, Turner R K, et al. Elicitation and truncation effects in contingent valuation studies [J]. Ecological Economics, 1999, 12: 161-79. [7] Bateman I J, Langford I H, Jones A P, et al. Bound and path effects in double and triple bounded dichotomous choice contingent valuation [J]. Resources and Energy Economics, 2001, 23: 191-13. [8] Loomis J B. measuring the economic benefits of removing dams and restoring the Elwha river: Results of a contingent valuation survey [J]. Water Resources Research, 1996, 32(2):441-7. [9] Loomis J B, Kent P, Strange L, et al. Measuring the total economic value of restoring ecosystem services in an inpaired river basin: Results from a contingent valuation survey [J]. Ecological Economics, 2000, 33:103-17. [10] Zhang Zhiqiang, XuZhongming, Cheng Guodong. The updated development and application of contingent valuation method [J].Advance in Earth Sciences, 2003, 18(3): 454-63. [11] Venkatachalam L. The contingent valuation method: a review.Environmental Impact assessment Review, 2004,24 :89–124. [12] Zhang Zhiqiang, XuZhongming, LongAihua, et al. Measuring the economic value of restoring ecosystem services in Zhangye city of Heihe river basin-Comparison and application of continuous and discrete contingent valuation survey. Journal of Natural Resources, 2004,19(2):230-9. [13]Monica I O, Alex S. M, Barry D. S. Economic valuation of environmental services sustained bywater flows in the Yaqui River Delta. Ecological Economics,2008,65: 155 – 66.
