Cultural ecosystem services valuation and its multilevel drivers: A case study of Gaoqu Township in Shaanxi Province, China

Ecosystem Services 41 (2020) 101052

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Cultural ecosystem services valuation and its multilevel drivers: A case study of Gaoqu Township in Shaanxi Province, China

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Qinqin Shia,b, Hai Chena,b, , Xiaoying Lianga,b, Hang Zhanga,b, Di Liua,b a b

College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi’an 710127, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Cultural ecosystem services Multilevel drivers Social preference method Gaoqu Township

Understanding residents’ preferences for cultural ecosystem services (CES) will provide reference for targeted ecological management. The purpose of this study was to evaluate the preferences for CES and to determine their multilevel drivers in Gaoqu Township in Mizhi County, China. A social preference method (questionnaire) was used to quantitatively assess the CES preferences. The respondents in Gaoqu Township perceived the importance of all eight types of CES, and aesthetic and sense of place services were the two most prevalent CES categories in the study area. Woodlands and grasslands, cave dwellings, terraces, temples and theaters played a significant role in providing diverse CES, and each type of environmental space was important for at least four types of CES. We also used multilevel models to detect the individual and environmental variables that affect the CES preferences. The results showed that gender, age, health, and annual per capita income did not have a significant effect on preferences for any of the eight types of CES. Community safety was identified as an important environmental variable that explained the preferences for educational, social relations, therapeutic and recreation services. The preferences for sense of place services were driven by per capita living space, population density and road network density, and migrant works had higher preferences for sense of place services than did farmers in the study area. This study verified the validity of multilevel model to quantitatively identify the nested drivers of CES. These outcomes can contribute to improving our understanding of the importance of CES and may assist in developing relevant policy for the transformation from traditional living functions to cultural and ecological functions in Gaoqu Township.

1. Introduction The Millennium Ecosystem Assessment (MA) can be regarded as a milestone in ecosystem services (ES) research (Ma et al., 2017), and the ES concept is rapidly drawing the attention of scientists, stakeholders, policy makers and society (Fisher et al., 2009; Lamarque et al., 2011; Ciftcioglu, 2017a). Cultural ecosystem services (CES) have been defined as “the non-material benefits that people derive from ecosystems through spiritual satisfaction, cognitive development, thinking, entertainment, and aesthetic experiences (including knowledge systems, social relationships, and aesthetic values)” (MA, 2005). In a specific valuation, CES cannot be quantified independently of human existence (Nahuelhual et al., 2014; Assandri et al., 2018) due to their characteristics of subjectivity and intangibility (Milcu et al., 2013; Peña et al., 2015; Willcock et al., 2017). Integrating them into the current evaluation framework of ES poses challenges (Small et al., 2017; Loc et al., 2018). Hence, systematic evaluations of CES and their integration

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into decision-making lag far behind other tangible services (Nahuelhual et al., 2014; Darvill and Lindo, 2016; Ma et al., 2017; Peng et al., 2017; Hanaček and Rodríguez-Labajos, 2018). However, CES often shape societies, cultures, and welfare and drive environmental change (Small et al., 2017), and the literature has also shown that the human demand for CES will increase with the growth of a national economy (Guo et al., 2010). Thus, it is necessary to take into account CES to achieve sustainable environment management and to meet human needs (Lan et al., 2017). Current CES researches have largely been limited to market services such as tourism and entertainment that can be evaluated using a monetary estimation (Hernández-Morcillo et al., 2013; Tratalos et al., 2015; Cheng et al., 2019). Chiesura and Groot (2003) support the concept that people’s choices of social and cultural values are based on moral, ethical and cultural principles rather than merely utilitarian standards. Hence, the assessment of CES cannot regard them as purely a market phenomenon. In recent years, an increasing number of scientists

Corresponding author at: College of Urban and Environmental Sciences, Northwest University, Xue fu Ave. 1, Xi’an 710127, China. E-mail address: [email protected] (H. Chen).

https://doi.org/10.1016/j.ecoser.2019.101052 Received 13 November 2018; Received in revised form 30 October 2019; Accepted 4 December 2019 2212-0416/ © 2019 Elsevier B.V. All rights reserved.

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(1) Are CES important to the residents of rural communities in ecologically vulnerable and poverty-stricken areas in China? Which services are the most prevalent in the study area? Which environmental spaces are important for the provision of CES? (2) Can a multilevel modeling approach be used to quantify the role of individual and environmental variables in CES preferences?

have begun to evaluate CES using nonmonetary valuation methods. For example, the social preference method (Ciftcioglu, 2017b; Bryce et al., 2016; Schmidt et al., 2016), retrospective trend analysis (Szücs et al., 2015) and the ES matrix method (Burkhard et al., 2012) have been used to value CES. Among them, the social preference method allows respondents to clarify their true perceptions of and preferences for such services, and it makes it possible to comprehensively analyze every aspect of CES, such as aesthetics, sense of place, education, and spiritual and religious aspects, to reveal the values obscured by monetary methods (Phillipson et al., 2009; Chan et al., 2012; Christie et al., 2012; Cheng et al., 2019). Furthermore, this method can resolve the issue of the lack of reliable biophysical and social data in research areas (Ciftcioglu, 2017a). A comparative study by Willcock et al. (2017) further confirms the effectiveness of the social preference method in collecting data on CES. Thus, the social preference method has attracted increasing attention and has become the most frequently used method to value CES in a nonmonetary way (Cheng et al., 2019). Based on CES evaluation, studies have begun to examine the variables that affect the preferences for CES. Previous studies have mainly used a single-level model to study the impact of different variables on CES preferences (Martín-López et al., 2012; Beichler, 2015; Ciftcioglu, 2017b). The results show that both individual variables (e.g., the level of formal education and gender) and environmental variables (e.g., infrastructure and accessibility) have an impact on these preferences (Martín-López et al., 2012; Ala-Hulkko et al., 2016; Bullock et al., 2018). However, individuals are an inseparable part of the environment (Levin, 1998), and the effect of individual variables on CES preferences depends on the environment to which they belong (Small et al, 2017; Teixeira et al., 2018). Further research is needed to better understand the impacts on CES preferences by placing individual variables and environmental variables in a single framework (Li et al., 2011; Hernández-Morcillo et al., 2013). Multilevel modeling is a statistical technique that uses multilevel data to illustrate the relationships between different levels, typically the individual level and the environmental level to which individuals belong (Qiu et al., 2019). This approach is designed to solve the limitations of traditional single-level models in processing nested data and is suitable for analyzing systems with complex hierarchical structures. Compared with single-level models, multilevel models provide more accurate inferences, and they are widely used in social science research (Fang et al., 2011; Liu et al., 2017). Using a multilevel model to nest individual variables into environmental variables to distinguish the impact and to calculate the contributions of different geographical hierarchical variables to CES is relatively novel. Research on CES must consider not only the services provided by an ecosystem but also the relationship between human and ecosystem, including individual and environmental variables that influence the CES preferences (Hernández-Morcillo et al., 2013). Rural areas in China face the challenge of recession (Liu and Li, 2017; Liu, 2018). Ecological and cultural functions constitute the unique charm of rural ecosystems, which are different from cities. The revitalization of rural areas needs to explore the path of rural transformation from the traditional living functions to cultural and ecological functions (Long and Tu, 2017). CES provide an important link between humans and the ecosystem (Bryce et al., 2016), and understanding the CES preferences of rural residents, which environmental spaces provide these CES, and which variables affect the preferences for CES, will help protect rural environmental spaces and purposefully maintain traditional culture, which in turn will contribute to rural revitalization. In this study, we integrated individual and environmental variables as two-level drivers into the CES framework provided by Fish et al. (2016) for a holistic understanding of CES. Then, a social preference method was used to study the CES preferences, and multilevel models were used to quantitatively analyze the drivers of these preferences in Gaoqu Township. The main research questions of this study are as follows:

2. Materials and methods 2.1. Study area: Gaoqu Township Mizhi County is located in northeastern Shaanxi Province. The county is between 109°49′-110°29′E and 37°39′-38°5′N (Liang et al., 2016), and it has a semiarid climate typical of the middle temperate zone. There is a low annual rainfall, and the climate is dry (Liu et al., 2018b). The county belongs to the hilly-gully region of the Loess Plateau and is a typical ecologically vulnerable area with severe soil erosion and barren land (Chen et al., 2016). In this area, 30.1% of the land experienced severe erosion before the 1999 implementation of the “Grain for Green” (GFG) project, which aimed to promote socioeconomic development and to reduce the soil erosion caused by cultivation on steep hillside slopes (Liang et al., 2016). This area is also known as “the hometown of culture,” “the hometown of small drama” and “the hometown of terraced fields.” The integration of nature and culture forms unique environmental spaces. Gaoqu Township (a rural administrative unit) is located 10 kilometers north of the county and has 20 administrative villages (note that in China, the hierarchy of administrative units from high to low is province, county, township, and village (Chen et al., 2018)) (Fig. 1). The township’s environmental spaces and regional culture are similar to those of Mizhi County. Gaoqu Township began to implement the GFG project in 1999 and has experienced the largest increase in forest area of any region in the county (Chen et al., 2016), with the rate of forest coverage reaching 48.5% in 2017 (SBMC, 2018). To conserve water and soil and to increase the grain yield, Gaoqu Township took the lead in building terraces as early as 1952, and terraces accounted for 9.3% of all arable land (MCCCC, 1993). As a result of the vertical characteristics of the loess and the “warm in winter and cool in summer seasons,” cave dwellings became the most popular residential landscape in the region. These cave dwellings are known as one of the living fossils of Chinese cultural heritage. Temples and theaters as well as cave dwellings are important parts of Chinese intangible cultural heritage. There are 39 temples and 9 theaters in Gaoqu Township, with an average of two temples per village and one theater for every two villages. In 2017, there were 3116 households and 10,542 residents in Gaoqu Township (SBMC, 2018); the majority of the local people were traditionally engaged in agriculture. Currently, however, 33.5% of rural households have migrated to cities due to the limited employment opportunities in the region, and 9.8% of the households are engaged in multiple occupations to make a living (SBMC, 2018). Moreover, individuals aged 65 years and older account for 20.6% of the population (SBMC, 2018). Migrations, the expansion of social activity spaces and the aging trend have had a large impact on traditional rural lifestyles. Nevertheless, the productive ecosystem and idiosyncratic landscapes that have been shaped over the centuries are still maintained.

2.2. Methods The research method of this paper consists of three parts: constructing a conceptual framework for evaluating CES and their multilevel drivers, evaluating CES using the social preference method and a relevant tool (questionnaire), and evaluating the drivers of CES preferences using a multilevel model.

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Fig. 1. Map of the study area: (a) location of Shaanxi Province, China, (b) location of the Gaoqu Township in Mizhi County, (c) 20 villages of the Gaoqu Township.

2014). At the bottom of Fig. 2, the drivers are individual and environmental variables that affect the CES preferences that arise from the interaction between environmental spaces and cultural practices. Referring to the existing literature, we chose the variables that affect CES. A plethora of studies have shown that individual variables such as gender, age, education level (Martín-López et al., 2012; Ciftcioglu, 2017b; Dou et al., 2019), residence status, income (Beichler, 2015; Zhang et al., 2019) and health (Aguado et al., 2018) have impacts on CES preferences. These studies have shown that the impacts of individual variables on CES preferences vary from region to region, which fully proves the complexity of individuals’ preferences and their dependence on the environment. Recently, although some studies have attempted to investigate the impacts of environmental variables on CES preferences, such as accessibility (which often depends on the road network) (Ala-Hulkko et al., 2016; Bullock et al., 2018), and the forest coverage rate (Brown, 2013) have been proved to have impacts on CES preferences, the impacts of more environmental variables on CES preferences require further attention. In this study, for the other three environmental variables, area poverty, community safety and population density, we referred to the environmental variables that affect residents’ well-being (Ettema and Schekkerman, 2016; Liu et al., 2017). The final individual and environmental variables selected are shown in Fig. 2, and the relevant descriptions are presented in Table 3.

2.2.1. Development of a conceptual framework for an evaluation of CES and their drivers in Gaoqu Township The conceptual framework of this study was developed based on the CES frameworks proposed by Fish et al. (2016) and Bryce et al. (2016), whose frameworks provide an innovative perspective for assessing CES. Fig. 2 shows that the conceptual framework for evaluating CES and their drivers in Gaoqu Township is composed of four domains (CES, environmental spaces, cultural practices and drivers). At the top of Fig. 2, the classification of CES is based mainly on the most widely cited typology of the MA (2005). Gaoqu Township is a rural area with clean air that has higher therapeutic value than cities have. The therapeutic category is based on the study by Sherrouse et al. (2011). The CES categories and corresponding statements in the study are described in Table 1. Notably, the respondents did not clearly understand the concept of educational services. In view of the traditional agricultural society of the research area, educational services here refer to the agricultural skills passed down from generation to generation. The transformation from ecosystem functions to ES is the process of interaction between humans and natural environment (Andersson et al., 2007). At the center of Fig. 2, environmental spaces are understood as the places, localities, landscapes and seascapes in which individuals interact with each other and the natural environment, and cultural practices are understood as expressive, symbolic and interpretive interactions between individuals and the natural environment (Church et al., 2014; Fish et al., 2016). In this study, woodlands and grasslands, cave dwellings, terraces, temples and theaters were selected as the five environmental spaces where cultural practices in Gaoqu Township take place. Cultural practices are the relational processes in which people actively gather, play, express, consume, etc. through interactions with environmental spaces, as when the residents of Gaoqu Township gather together and worship the gods on the days of the “temple fair.” In short, as Fig. 2 conveys, environmental spaces both enable and are shaped by cultural practices; that is, environmental spaces provide the material carrier for cultural practices and enable cultural practices to occur; however, they are also reconstructed through cultural practices, such as the protection and maintenance of environmental spaces (Li et al.,

2.2.2. Using a social preference method for interpreting CES preferences How much people value ES is based on their preferences (Daily, 1997). The social preference method is a direct consultative approach for proving the social importance of ES by analyzing the social perceptions of ES (Ciftcioglu, 2017b), and it is an effective method for understanding which services respondents consider to be the most important (Castro et al., 2011). In this study, we defined “preference” as the perceived importance of CES by respondents of the study area and used a questionnaire tool to determine the social preference. Data collection: Relevant data was collected from 24 July 2018 to 24 August 2018 in 20 villages of Gaoqu Township. The data collection 3

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Fig. 2. The conceptual framework for evaluating the CES and their drivers of the Gaoqu Township (Modified from Fish et al., 2016; Bryce et al., 2016).

(from 0: not at all to 5: very high important). The respondents were asked to indicate the relative perceived importance of each type of CES to represent their CES preferences. (3) The third part addressed the importance of environmental spaces for CES provision. The respondents were asked to select all of the environmental spaces (Fig. 2) that provided each service. The total number of times that each type of environmental space was selected provided an indication of the importance of that environmental space for the service provision.

tools included a questionnaire and semi-structured interviews. The questionnaire consisted of three parts. (1) The first part addressed the profile of the respondents: age, gender, education level, occupation, family income sources, residence status, family population and health status (physical and mental health) (Fig. 2). (2) The second part addressed the respondents’ preferences for CES. The preferences for eight types of CES (Table 1) obtained from the ecosystem of the village in which the respondents live were evaluated on a 6-point Likert scale

Table 1 The CES categories, examples of the statements of each CES in the survey, and the mean values of each CES for the entire samples. CES

Examples of the statements of each CES

Mean

S.D.

Aesthetic Educational Sense of place

I value these sites because I enjoy the scenery, sights, colors, sounds, smells, etc. I value the terraces because I learned a lot knowledge of farming (both formally and informally) when I grew up I value these sites because I feel safest when I stay here, or they are the most comfortable place for me, or I have strong feelings of belonging I value these sites because they serving as meeting points with friends I value these sites because they are related to local history and culture I value these sites because they make me feel better, physically and/or mentally I value these sites because they are a sacred, religious, or spiritually special place to me or I believe I will be blessed when I visit them I value these sites because they provide a place for me to spend leisure time, walking, dog walking, playing with kids, dancing, etc.

4.30 3.35 4.10

1.01 1.31 1.24

4.21 2.97 3.71 3.09 2.86

0.85 1.39 1.14 1.31 1.45

Social relations Cultural heritage Therapeutic Spiritual and religious Recreation

Mean value: the average of entire samples; S.D. refers to standard deviation. 4

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etc. during these activities. These contents provided information to qualitatively analyze of the relationship between cultural practices and environmental spaces in Gaoqu Township. Date valuation: The mean values of the CES were calculated by dividing the total score by the total number of respondents (Table 1). An independent-samples t test was used to analyze the effect of gender on the preferences for CES, and one-way ANOVA was used to analyze the effects of education level and age on the preferences for CES by running the Statistical Package for Social Sciences (SPSS) version 16.0 (Table 4).

Table 2 Population profile of the respondents in Gaoqu Township. Population profile

Characteristics of the population profile

Number of respondents

Percentage of respondents

Gender

Female Male

36 168

17.6 82.4

Education level

Illiteracy Primary school High school College

38 86 78 2

18.6 42.2 38.2 1

Occupation

Farmer Migrant worker Multiple occupations Housewife Government employees

96 11 70 6 21

47.1 5.4 34.3 2.9 10.3

20–49 50–59 60–69 ≥70

30 58 75 41

14.7 28.4 36.8 20.1

Age range

2.2.3. Multilevel models This research treated the preferences for the eight types of CES in our case as functions of their individual and environment variables (Table 3). First, for a better comparison of the coefficients of the independent variables, we normalized the initial values by a logarithmic method (Wu et al., 2018). Second, we conducted a variance inflation factor (VIF) test to justify the multicollinearity of the independent variables, and the results (VIF < 5) showed that the correlations between independent variables had no significant effect on the parameter estimation of the models. Third, we employed multilevel linear models to quantify the effects of individual and environment variables on the CES using the Software for Statistics and Data Science (STATA) version 12.0. In the model, individuals (204 respondents) belong to the environment (20 villages); individual variables are level 1, and environmental variables are level 2. Thus, 204 respondents at level 1 were nested within 20 villages at level 2. The models are specified as follows:

To proceed, we explained the concepts of the CES, and the purpose and content of the questionnaire. Then, we conducted face-to-face interviews to complete the questionnaires. The respondents were randomly selected from the local residents with the aim of coving different backgrounds. A total of 204 questionnaires (Table 2) were finally obtained and processed by two PhD students and six master’s students on the research team. Importantly, because most of the decision-making in local families was male dominated, we had to interview the heads of household (males) to obtain more information, and although we repeatedly stressed that everyone has different preferences for CES, most females still rejected our questionnaire. For this reason, we had more males than females in our sample. Furthermore, the GFG project converted arable land to woodland by providing subsidies to local residents rather than providing employment opportunities, leading to a considerable amount of migration of young people in search of jobs and the elderly individuals staying home (Dou et al., 2019). Therefore, the higher proportion of the elderly individuals in our sample was consistent with the actual situation of the study area. Two other master’s students on the research team conducted the semi-structured interviews, and approximately 2–3 leaders from each village participated in each semi-structured interview. The contents of the interviews consisted of two parts: (1) data to facilitate the quantitative analysis of the drivers of the preferences for CES, including the number of residents receiving minimum living standard support, the total population of the village, traffic conditions, and the area of various land-use types (Table 3); and (2) the cultural activities engaged in by residents every year and how people gather, play, express, consume,

ln Ynij = α + β ln Xij + γ ln Zij + μj + εij where ln Ynij represents the normalized values of different types of CES for respondent i in village j . n = 1 refers to the preferences for aesthetic services, n = 2 refers to the preferences for educational services, n = 3 refers to the preferences for sense of place services, n = 4 refers to the preferences for social relations services, n = 5 refers to the preferences for cultural heritage services, n = 6 refers to the preferences for therapeutic services, n = 7 refers to the preferences for spiritual and religious services, and n = 8 refers to the preferences of recreation services. ln Xij denotes a set of normalized individual variables related to the individual level, while lnZij represents a set of normalized environmental variables related to the village level. α refers to fixed-effect; β refers to coefficients of individual variables; λ refers to coefficients of environmental variables; μj denotes the differences between village j’s mean and the overall mean; and εij represents individual residuals.

Table 3 Descriptions of individual and environment variables. Dimension

Independent variables

Description

Individual variables

Gender Age Education Occupation Physical health Mental health Per capita living space Annual per capita income

Sex of respondents: male = 1, female = 0 Age of respondents The educational level of respondents: illiteracy = 0, primary school = 1, high school = 2, and college = 3 Occupations of respondents: housewife = 0, farmer = 1, migrant worker = 2, multiple occupations = 3, and government = 4 Physical health state of respondents: 1–5 Likert scale, 1 unhealthy, 5 very healthy Mental state of respondents: 1–5 Likert scale, 1 very unhealthy, 5 very healthy The ratio of total housing area and total number of households. Units: m2/per The ratio of household agricultural, migrant workers and other income (including government subsidies) and the total number of households in the last year. Units: CNY

Environmental variables

Area poverty Community safety Population density Road network density Forest coverage rate

Ratio of residents receiving minimum living standard support The degree of safety of villages: 1–5 Likert scale, 1 very unsafe, 5 very safe The ratio of total population and total area of villages. Units: people/km2 The ratio of total road length and total area of villages. Units: km/km2 The ratio of forest area and total area of villages

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Table 4 Results of the effect of gender, education level and age on preferences for CES in Gaoqu Township. Aesthetic

Educational

Sense of place

Social relations

Cultural heritage

Therapeutic

Spiritual and religious

Recreation

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

Mean

S.D.

Gender

Female Male p value

4.14 4.34 0.40

1.36 0.93

3.44 3.33 0.63

1.36 1.31

4.00 4.12 0.60

1.29 1.24

4.28 4.19 0.58

0.74 0.88

2.97 2.96 0.98

1.42 1.40

3.67 3.72 0.80

1.22 1.13

2.89 3.13 0.32

1.39 1.30

2.50 2.93 0.10

1.40 1.46

Education level

Illiteracy Primary High College p value

4.24 4.17 4.47 4.50 0.28

1.26 1.06 0.80 0.71

3.34 3.16 3.54 4.00 0.28

1.30 1.30 1.34 1.41

4.13 4.00 4.18 4.50 0.78

1.14 1.34 1.21 0.71

4.21 4.07 4.35 4.50 0.21

0.84 0.88 0.82 0.71

2.63 3.02 3.01 5.00 0.08

1.38 1.36 1.42 0.00

3.76 3.62 3.77 4.50 0.61

1.22 1.20 1.04 0.71

2.79 3.15 3.12 5.00 0.09

1.44 1.22 1.33 0.00

2.37 3.00 2.88 5.00 0.02*

1.26 1.44 1.50 0.00

Age range

20–49 50–59 60–69 ≥70 p value

4.30 4.38 4.27 4.27 0.93

0.65 1.02 1.11 1.07

3.17 3.45 3.33 3.37 0.82

1.29 1.29 1.30 1.44

4.23 3.88 4.23 4.08 0.40

1.07 1.24 1.25 1.37

4.33 4.16 4.19 4.22 0.82

0.71 0.89 0.85 0.91

2.77 2.95 2.93 3.20 0.63

1.52 1.32 1.43 1.38

3.83 3.79 3.59 3.73 0.67

1.02 0.97 1.23 1.29

3.27 2.93 3.12 3.12 0.70

1.41 1.42 1.19 1.33

3.03 2.64 2.81 3.12 0.37

1.47 1.42 1.44 1.52

Mean value: 0-not at all to 5-very high importance; S.D. refers to standard deviation and* denotes statistical significance at 5%.

3. Results

played the most important roles in local people’s valuation of aesthetic services (n = 170), followed by sense of place (n = 125), therapeutic (n = 54) and social relations (n = 31) services. Cave dwellings played an important role in local people’s sense of place services (n = 159), followed by aesthetic (n = 106), therapeutic (n = 74) and recreation (n = 61) services. Terraces played an important role in local people’s sense of place (n = 110), followed by aesthetic (n = 105), educational (n = 103) and social relations (n = 36) services. Temples were considered the most important environmental spaces for spiritual and religious service (n = 101), followed by cultural heritage (n = 85), recreational (n = 54), and aesthetic (n = 51) services. Theaters played an important role in delivering the service of cultural heritage services (n = 62), followed by recreation (n = 52), spiritual and religious (n = 47), and therapeutic (n = 1) services.

3.1. Characteristics of the respondents Table 2 shows that the number of male respondents was 4.67 times higher than the number of female respondents. Regarding the education level, primary school accounted for the largest proportion at 42%, with only two university graduates accounting for the smallest proportion. In terms of age, respondents aged 60–69 accounted for the largest proportion (36.8%), followed by those 50–59 years old, 70 and over, and 20–49 years old. According to income sources and the actual situation of the study area, the respondents were divided into five types: farmers, migrant workers, multiple occupations, housewives and government employees. Among them, farmers engage in farming only; migrant workers are those who do not cultivate land and for whom going out to work is their main source of income; the term multiple occupations refers to being engaged in two or more types of livelihood at the same time, such as farming and feeding livestock, farming and planting economic forests (apple and apricot trees), or farming and working in another capacity; housewives are women who do not have any occupation; and government employees consist of local leaders such as accountants, secretaries, and village heads. The proportions of farmers (47.1%) and multiple occupations (34.3%) among the respondents were the highest.

3.4. Evaluation of the multilevel drivers of the preferences for CES in Gaoqu Township We further examined the multilevel drivers that influence the preferences for eight types of CES in our work via a series of multilevel models. Eight outcome variables were introduced into the multilevel models, and the results are shown in Table 5. As seen in Table 5, the estimated results of the individual variables showed no evidence that gender, age, health or annual per capita income were significantly related to CES in Gaoqu Township. Regarding the other individual variables, education level revealed a significant difference in terms of the residents’ preferences for therapeutic services (coefficient = 0.21, p < 0.05). With respect to different occupations, we set the occupation of farmers as the reference group, and the results showed that migrant workers had higher preferences for sense of place (coefficient = 0.83, p < 0.05), spiritual and religious (coefficient = 1.12, p < 0.05), and recreation (coefficient = 0.99, p < 0.05) services than farmers had. Moreover, government employees had a higher preference for recreation services (coefficient = 0.74, p < 0.05) than farmers had. Furthermore, per capita living area was positively associated with sense of place services (coefficient = 0.30, p < 0.05). The estimated results of the environmental variables showed that area poverty had a positive impact on aesthetic services (coefficient = 0.34, p < 0.05). Additionally, community safety was significantly associated with educational (coefficient = 1.47, p < 0.05), social relations (coefficient = 0.82, p < 0.05), therapeutic (coefficient = 0.97, p < 0.05) and recreation (coefficient = 1.58, p < 0.05) services. Regarding the other environmental variables, population density was negatively associated with sense of place services (coefficient = −0.71, p < 0.05) and positively associated with cultural

3.2. The preferences for CES in Gaoqu Township Table 1 presents the mean perceived values of each CES of the total sample. The CES with the highest value in Gaoqu Township was aesthetic services (mean = 4.30; S.D. = 1.01). Social relations services (mean = 4.21; S.D. = 0.85) and sense of place services (mean = 4.10; S.D. = 1.24) were other important services. Therapeutic (mean = 3.71; S.D. = 1.14), educational (mean = 3.35; S.D. = 1.31), and spiritual and religious (mean = 3.09; S.D. = 1.31) services had moderate values. Cultural heritage (mean = 2.97; S.D. = 1.39) and recreation (mean = 2.86; S.D. = 1.45) services had the lowest values. According to the independent-samples t test and the one-way ANOVA, no demographic variables influenced the preferences for CES, with the exception of the education level had a significant effect on the values of recreation services (p < 0.05) (Table 4). 3.3. Importance of environmental spaces for CES provision in Gaoqu Township Environmental spaces were important for at least four types of CES in Gaoqu Township (Fig. 3). Concretely, woodlands and grasslands 6

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Fig. 3. The total number of times that each type of environmental space was selected provided an indication of the importance of that environmental space for the service provision.

are regarded as daily living and cultivation spaces; however, their cultural heritage services were ignored by the residents of Gaoqu Township. Therefore, managers should publicize the importance of local cultural heritage and awaken residents’ sense of cultural heritage. The environmental spaces in Gaoqu Township were the result of the long-term interaction between human beings and the ecosystem, and each type of environmental space mentioned served multiple roles. Gaoqu Township belongs to the hilly-gully region of the Loess Plateau, which is one of the most eroded areas in the world (Chang et al., 2011; Jiang et al., 2016). To conserve water and soil, Gaoqu Township has experienced a series of ecological restoration projects, such as the transformation of slope land into terraces and the GFG project. Our results found that terraces and woodlands and grasslands also provided multiple CES. For example, terraces provided educational services because they were the results of the harmonious coexistence between humans and nature; additionally, they represented ancestral wisdom and agricultural civilization. Moreover, Gaoqu Township has relied on farming for many generations. The residents were born and grew up here and had deep feelings of affiliation with this place, and when they engaged in agricultural activities, they simultaneously appreciated the growth of their crops (Dou et al., 2019). Therefore, terraces also delivered sense of place and aesthetic services. Woodlands and grasslands provided aesthetic services and, at the same time, provided therapeutic services by reducing sandstorms and purifying the air (the Loess Plateau has loose soil and frequent sandstorms in spring (Wang, 2008); the respondents mentioned that the GFG project reduced the frequency of sandstorms). In short, managers need to make full use of the multiple services of environmental spaces to provide more well-being for humans.

heritage (coefficient = 0.89, p < 0.01) and recreation (coefficient = 1.39, p < 0.01) services. Road network density was positively related to sense of place services (coefficient = 0.89, p < 0.01), and respondents whose village had a higher road network density had higher preferences for sense of place services.

4. Discussion 4.1. Preferences for CES and the multiple roles of environmental spaces in CES provision Rural residents can recognize more diverse ES because their own well-being is more closely linked to the ecosystem that they depend on (Martín-López et al., 2012; Aguado et al., 2018). There is mounting evidence demonstrating the importance of CES to rural areas (AngaritaBaéz et al., 2017; Kandel et al., 2018). We also found that the respondents from Gaoqu Township perceived the importance of all eight types of CES. Consistent with previous findings (Plieninger et al., 2013; Martínez Pastur et al., 2016; Ciftcioglu, 2017a,b), our research found that aesthetic services had the highest value and that most of the respondents in Gaoqu Township acknowledged the aesthetic services of woodlands and grasslands. On the one hand, this result could be explained by the fact that the GFG project, with the primary goal of soil conservation, has produced beneficial spillover effects, including nonmaterial human benefits. On the other hand, our research occurred during the summer season, when the woodlands and grasslands in the study area presented lush green scenes; thus, our study may have overestimated their aesthetic value. Therefore, the selection of appropriate temporal assessment scales must be carried out very carefully (Burkhard et al., 2014). In contrast to the study by Hartel et al. (2014), recreation services had the lowest value; on the one hand, after working a long day to earn a living, most residents had little energy remaining for recreation (Dou et al., 2019); on the other hand, there was a lack of recreational facilities, and cave dwellings were the most common environmental spaces in Gaoqu Township where residents’ recreational activities took place. In addition, consistent with previous findings (Angarita-Baéz et al., 2017; Kandel et al., 2018), the value of cultural heritage services was at a low level. In fact, cave dwellings and terraces are important part of Chinese cultural heritage, probably because they

4.2. The role of individual and environmental variables in the preferences for CES Our research shows that the use of a relatively novel multilevel model was effective in nesting individual variables into environmental variables and in exploring their effects on the preferences for CES. There are many interesting findings. The individual variables had no effect on the preferences for aesthetic, educational, social relations and cultural heritage services, which could be explained by the fact that the 7

8

0.17 −0.08 −0.21 −0.09 0.03 −0.07 −0.01 −0.04

0.34* 0.09 0.14 −0.03 0.11 1.98 1.02 0.01 204 −285.72

Occupation (ref: Farmer) Housewife Worker Multiple occupations Government employee Physical health Mental health Per capita living space Annual per capita income

Environmental variables Area poverty Community safety Population density Road network density Forest coverage rate Constant Within area variance Between area variance Sample N Log likelihood

0.14 0.45 0.25 0.27 0.10 3.01

0.43 0.34 0.18 0.26 0.05 0.06 0.10 0.06

0.20 0.37 0.09

0.06 1.47* −0.06 0.46 0.02 −1.85 1.73 0.00 204 −333.42

−0.70 −0.73 0.00 0.17 0.04 −0.03 0.05 −0.08

0.43 −0.37 −0.07

0.18 0.57 0.32 0.34 0.12 3.81

0.54 0.44 0.22 0.33 0.07 0.07 0.13 0.08

0.25 0.46 0.11

S.E.

* and ** denote statistical significance at 5% and 1%, respectively.

−0.01 0.10 −0.10

Individual variables Gender (ref: Male) Age Education

Estimates

Estimates

S.E.

Educational

Aesthetic

Table 5 Multilevel modeling on preferences for CES in Gaoqu Township.

−0.19 0.75 −0.71* 0.89** 0.09 0.21 1.47 0.07 204 −318.57

−0.03 0.83* −0.03 0.18 −0.10 0.03 0.30* −0.01

0.09 0.69 −0.01

Estimates

Sense of place

0.17 0.53 0.30 0.32 0.12 3.54

0.50 0.40 0.21 0.30 0.06 0.07 0.12 0.07

0.23 0.43 0.10

S.E.

−0.13 0.82* −0.28 0.42 −0.02 1.65 0.67 0.05 204 −249.88

−0.06 0.17 0.11 −0.01 0.00 −0.04 0.08 −0.06

0.02 0.14 −0.04

Estimates

Social relations

0.12 0.38 0.21 0.23 0.08 2.53

0.36 0.29 0.15 0.22 0.05 0.05 0.08 0.05

0.17 0.31 0.07

S.E.

0.31 1.11 0.89** −0.64 0.17 −10.14 1.83 0.12 204 −343.36

0.56 0.80 0.14 0.44 0.12 0.03 0.02 0.12

0.05 0.20 0.17

Estimates

0.19 0.60 0.34 0.36 0.13 4.00

0.57 0.46 0.24 0.34 0.07 0.08 0.13 0.08

0.26 0.48 0.12

S.E.

Cultural heritage

0.15 0.97* −0.19 0.12 0.18 −3.49 1.29 0.00 204 −301.35

−0.46 0.43 −0.08 0.32 −0.02 −0.15 −0.14 0.07

−0.04 0.65 0.21*

Estimates

Therapeutic

0.15 0.49 0.28 0.29 0.11 3.25

0.46 0.37 0.19 0.28 0.06 0.06 0.11 0.07

0.21 0.39 0.10

S.E.

0.30 1.10 0.28 −0.36 0.25 −5.35 1.63 0.08 204 −333.36

0.23 1.12* −0.02 0.36 −0.01 −0.04 −0.07 0.07

−0.04 0.06 0.09

Estimates

0.18 0.57 0.32 0.34 0.12 3.80

0.54 0.43 0.22 0.33 0.07 0.07 0.13 0.08

0.25 0.46 0.11

S.E.

Spiritual and religious

0.27 1.58* 1.39** −0.55 0.03 −14.15 1.64 0.42 204 −349.00

−0.11 0.99* −0.03 0.74* 0.02 −0.11 0.04 0.05

−0.22 0.46 0.11

Estimates

Recreation

0.20 0.62 0.35 0.37 0.13 4.11

0.58 0.47 0.24 0.35 0.07 0.08 0.13 0.09

0.27 0.50 0.12

S.E.

Q. Shi, et al.

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research. In addition, the drivers of the preferences for CES come from the natural ecosystems and socioeconomic systems. Natural ecosystems affect CES by changing the structure and function of ecosystems, and the diversification of socioeconomic systems leads to preferences for different types of CES (Andersson et al., 2007; Zhao et al., 2018). Due to the small scale of this research, we considered that the natural ecosystem was similar throughout the research area, and the impact of environmental variables on CES was not fully considered. The limitation of the sample data was also a prominent weakness in our research. First, most of the decision-making in local families is male dominated, and more males were interviewed to obtain more information, as a result of which the proportion of males and females in the sample was unbalanced, leading to the underrepresentation of females’ perceptions of CES. However, males’ and females’ preferences for CES seemed quite similar, alleviating some of the concerns. Second, the evaluation of aesthetic services during a single season may have overestimated or underestimated the ability of environmental spaces to deliver CES. Third, the education services in our study referred to the agricultural culture provided by terraces; thus, the education services provided by other environmental spaces were ignored.

preferences that we hold as individuals are influenced by socialization within a particular society (Irvine et al., 2016), and the residents of Gaoqu Township have formed homogeneous values with these services through a long-term process of socialization (Kenter, 2016). Additionally, in our work, males accounted for 4.67 times more respondents than females, and older men (≥60) accounted for 56.9% of the total sample. It seems that with respect to gender and age, are sample is biased, making it difficult to compare our study with other studies that are gender and age balanced. In fact, no significant differences in CES preferences according to gender and age were found in our study; thus, these results alleviate some of the concerns about sample bias. Surprisingly, annual per capita income did not have a significant effect on any of the eight types of CES, but this result is consistent with the study of Aguado et al. (2018), who showed that economic variables alone did not explain the CES preferences. Most likely, different cultural backgrounds, such as the degree of participation in the market economy, affect how people perceive the role of the economy in their preferences for CES. The importance of community safety is likely based on avoiding negative emotions, and it will lead to a better conscious evaluation of life circumstances. The positive impact of community safety on human well-being has been proven by relevant studies (Ettema and Schekkerman, 2016; Liu et al., 2017). Our study provided a first assessment of the relationship between community safety and CES preferences, and an interesting finding was that the preferences for four types of CES were affected in the same direction by community safety. Apparently, community safety is the basic condition for people to live and work in harmony, and it will lead to better experiences of CES. However, this study shows that there was only a positive correlation between community safety and CES, which does not mean that people cannot enjoy CES without community safety. Per capita living area was a positive factor of the preferences for sense of place services. One possible explanation is that an estate is one of the main fixed assets of local residents and determines the psychological stability of individuals. In addition, in the township we investigated, it was a local tradition that harvesting crops, building cave dwellings and performing many other activities must be completed collectively by all villagers in a village with a small population density; thus, the smaller the population is, the higher the cohesion and the stronger the sense of place among the residents. The result of a positive correlation between road network density and the preferences for sense of place services further demonstrates that the realization of CES often hinges on perfect infrastructure (Bullocket al., 2018). Furthermore, the research area is located in an ecologically vulnerable region, and the frequent occurrence of natural disasters has a great impact on the promotion of regional sustainable development. Farmers face many livelihood risks that reduce their sense of place (Liu et al., 2018b). In contrast, when migrant workers go out to work, they compare their hometown with the outside world, finding the uniqueness of their hometown and strengthening their attachment to their hometown (Ye et al., 2015). This phenomenon indicates that people’s direct experience plays an important role in shaping their sense of place (Zhang et al., 2019), and the different direct experiences of farmers and migrant workers in their hometown lead to different sense of place.

4.4. Implications for policy making and rural revitalization CES are directly experienced and intuitively appreciated by people; thus, they are the motivators for ecosystem protection (Plieninger et al., 2013). CES preferences can shape people’s attitudes and behavioral intentions, influencing the way they use environmental spaces (Poppenborg and Koellner, 2013). In this paper, the study of residents’ preferences for CES in Gaoqu Township will contribute to improving managers’ awareness of the importance of CES in the region and to integrating the demand of local residents into the policy making of environmental space management. In addition, for some CES that are important but that were not recognized by people in Gaoqu Township, such as cultural heritage services, managers should strengthen residents’ awareness by providing guidance and then cultivate their deepseated motivation for environmental space protection. Rural areas in China face the challenge of recession, and problems such as population outflows, land abandonment and ecological destruction have arisen in rural areas (Liu and Li, 2017). Cultural revitalization and ecological revitalization are important components of rural revitalization (Long et al., 2018). First, activating “nostalgia” and promoting the return of population are the key steps in cultural revitalization. This study shows that the residents of Gaoqu Township, especially migrant workers, have a strong sense of place, and per capita living space and road network density are the environmental variables that affect residents’ sense of place. Therefore, the government should not only develop rural industry to provide employment opportunities for more residents but also pay attention to their living conditions and strengthen road construction so that rural areas will become space carriers to retain “nostalgia” (Ye et al., 2015) and ultimately promote population return. Second, improving the livable environment is the content of ecological revitalization. Each kind of environmental space in our study can provide a variety of CES. For example, in the process of terrace management, managers should beautify the terrace and improve the sightseeing and leisure functions of the terraces so that they give full pay to aesthetic and recreation services while inheriting the agricultural cultural. In addition, managers should carry out effective social governance to ensure community safety and make residents better enjoy CES.

4.3. Limitations of the study Our research integrated individual and environmental variables into the CES frameworks proposed by Fish et al. (2016) and Bryce et al. (2016), and it mainly discussed the preferences for CES and their drivers in Gaoqu Township in rural China. The explanation of the interaction between environmental spaces and cultural practices was not exhaustive; to provide a more detailed understanding, we will increase the frequency of activities held in various environmental spaces and the types of CES the residents obtained from these activities in future

5. Conclusion The Gaoqu Region is a loess hilly gully region of the Loess Plateau, the vulnerable ecological environment restricts its development and makes it one of the poverty-stricken area of China. This study focused on evaluating the preferences for CES and their drivers in Gaoqu 9

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Township. Through a detailed case study, the results revealed that the residents in Gaoqu Township perceived the importance of all eight types of CES and that aesthetic and sense of place services were the two most prevalent CES categories in the study area. Environmental spaces, including woodlands and grasslands, cave dwellings, terraces, temples and theaters, played a significant role in delivering diverse CES, and each type of environmental space was important for at least four types of CES. From the results of the multilevel models, we concluded that depending upon the CES in question, individual and environmental variables played more or less significant roles. No significant differences in the preferences for any of the eight types of CES according to gender, age, health or annual per capita income were found. Community safety was key to enjoying educational, social relations, therapeutic and recreation services. The preferences for sense of place services were driven by per capita living space, population density and road network density, and migrant works had higher preferences for sense of place services than did farmers in the study area. Identifying the drivers of CES based on individuals and environmental variables can clarify the coupling relationship between the ecosystems and the socioeconomic systems and can also provide a reference for measures to realize the maximum potential of CES, such as improving road construction and strengthening community safety.

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