1. Introduction
As one of the most important and widely distributed types of terrestrial ecosystems [
1], the grassland ecosystem represents approximately 26% of the total land area [
2]. This ecosystem not only serves as the natural resource carrier of animal husbandry [
3] but also offers a variety of ecosystem services, such as water conservation, climate regulation, soil conservation, and biodiversity maintenance [
4,
5]. With the gradual formation of the international carbon trading market, grassland, as an important carbon sink, may also produce more economic value [
6]. However, grassland ecosystems are very fragile. Once the vegetation within them is degraded, their natural recovery will take a long time [
7].
Livestock is part of a production system that attempts to balance stock size and supporting crop production, as the livestock nutrient intake must be based primarily on home-grown feed [
8]. As part of the concept of a ‘natural environment’, animals should also be kept on pasture in the summer season and fed a high proportion of roughage. For dairy cows, this constitutes a minimum of 60% of their daily dry matter intake. On larger and more specialized livestock farms in many countries, grassland plays a lesser role in livestock production [
9]. However, from production oriented toward the market to farms where market-orientation integrated with crop selection is linked to its added value, grassland has the opportunity to regain its importance in the livestock sector [
10]. Increasing grazing activities and climate change have a considerable impact on the structure, productivity, carbon storage, and flux of grassland ecosystems [
11,
12]. Although there are great differences in the grassland resource endowments worldwide, the state of grassland resources in most areas has deteriorated to varying degrees [
13]. According to a survey, nearly half of the grassland in the world has been degraded [
14], resulting in a series of negative effects, such as livestock production reduction, sand storms, and carbon absorption capacity decline [
15], exposing humans to significant social, ecological and environmental problems.
In addressing grassland degradation, many countries and regions have adopted different policies or management systems. For example, in developed countries, the loss, fragmentation, and degradation of lowland semi-natural grassland has been largely attributed to agricultural intensification [
16,
17,
18]. In response to this threat, the UK, for example, has introduced a variety of policies, such as agri-environment (AE) schemes [
19]. On the one hand, the AE schemes include the maintenance of existing high-biodiversity-value, semi-natural grassland, while on the other hand, they can improve grassland that has been degraded by agricultural improvement works or neglect [
20]. In EU member states, the target for the proportion of permanent grassland in the total agricultural area should not be reduced below 10% of the area in 2003. If this threshold is exceeded, preventive measures must be implemented. Some member states have also implemented controls for the protection of permanent grassland. For example, Greece, Italy, and Spain have banned the conversion of permanent grassland, and Austria does not allow conversion on steep hills or along watercourses [
21]. Cropland agriculture is typically more profitable than grassland agriculture, and the demands to increase profitability accelerate grassland conversion [
22]. In the 2014 U.S. Farm Bill, one program that seeks to directly ameliorate this effect is “Sodsaver”, which reduces crop insurance subsidies during the first four years on any cropland converted from prairies. This protection applies to Plains and Prairie Potholes Ecoregion states, which include Iowa, Minnesota, Montana, Nebraska, North Dakota, and South Dakota [
23,
24,
25].
Grassland degradation is also a problem in developing countries. For instance, China includes approximately 4 × 10
6 km
2 of natural grassland, accounting for 41.7% of the total land area [
26], and is the country with the second most grassland resources in the world [
27]. Approximately 80% of its grassland is concentrated in the arid and semiarid areas of China [
28]. Grasslands play a very important role in ecosystem services, ensuring national food security, maintaining social and economic harmony and stability, etc. However, the proportion of degraded grassland in northern China’s total grassland area has gradually increased to approximately 90% [
29]. To reduce the grassland degradation area, China has introduced a number of grassland protection systems and policies, striving to protect the ecological security of grassland while ensuring the living standards of herders.
China implemented the Returning Grazing Land to Grassland Project (RGLGP) in Inner Mongolia, Gansu, and Ningxia starting in 2003. The RGLGP (a program to convert grazing land back to grassland) aims to (i) restore grassland vegetation; (ii) improve grassland ecological environments; (iii) accelerate the transformation of modes of animal husbandry and production; and (iv) promote the sustainable development between grassland and animal husbandry by establishing pasture fences, improving grass seed banks, and restricting access to certain pastures [
30]. From 2003 to 2018, China invested 29.57 billion yuan (around USD 4.54 billion) in the RGLGP, increasing the fresh grass production by 830 million tons [
31].
The Grassland Law of the People’s Republic of China clearly states in Article 45 that state practices must manage livestock through grass and forage-livestock balance regulation (Quoted from the Grassland Law of the People’s Republic of China:
http://www.gov.cn/gongbao/content/2003/content_62420.htm accessed on 22 February 2021). Forage-livestock balance regulation is a regulation of grassland protection adopted in China and focuses on maintaining a dynamic balance between the amount of forage provided by grassland and by other means and the amount of forage needed for livestock in a certain area and at a given time [
32]. Article 46 of the same law stipulates a grazing prohibition and resting institution implements on grasslands that are seriously degraded, desertified, salinized, rocky, desertificated, or ecologically fragile (Quoted from the Grassland Law of the People’s Republic of China:
http://www.gov.cn/gongbao/content/2003/content_62420.htm accessed on 22 February 2021). A grazing prohibition generally forbids grazing for more than one year on grasslands with fragile ecological systems, serious levels of soil erosion, or special uses. Rest grazing forbids grazing at a certain time of the year [
33]. ‘Rest grazing’ refers to a short-term ban of grazing on steppes for a limited period of time. It is a key method for the recovery of degraded steppes [
34]. Its aim is to realize sustainable utilization of natural grasslands by providing time for rest and recovery [
35].
To reduce the grazing pressure and restore grassland productivity, the Chinese government launched a large-scale production compensation program, namely the Grassland Ecological Protection Subsidies and Reward Policy (GEPSRP). Its aim is to encourage herders to comply with grassland protection measures through subsidies [
15]. The GEPSRP was officially launched in 2011 with a five-year cycle. The main measures adopted are as follows. The first measure involves grazing prohibition, and subsidies should be implemented in the areas with poor environments, serious degradation, and or those which are not suitable for grazing. The second measure is to strictly implement forage-livestock balance regulation and allocate corresponding compensation to grassland that is not seriously degraded. The policy is implemented in Inner Mongolia, Xinjiang, Tibet, Qinghai, Sichuan, Gansu, Ningxia, and Yunnan, the eight major grassland and pastoral provinces. In its early years, the central government allocated 13.6 billion yuan (around USD 2.08 billion) to the policy. In 2012, the investment was increased to more than 15 billion yuan (around USD 2.30 billion), and the policy was extended to 36 pasture and farming pastoral areas in Hebei, Jilin, Shanxi, Liaoning, and Heilongjiang. By the end of the first round of the GEPSRP, the central government had invested 77.4 billion yuan (around USD 11.84 billion) in total.
From a review of grassland protection policies in China, we found the current attitudes of herders toward grassland protection to be one of the reasons for the success or failure of grassland management and protection policies [
26]. Therefore, to improve China’s grassland management and protection policies and provide a reference for other countries and regions, this paper aims to explore the herders’ willingness and attitudes about protecting grasslands and summarizes the practical experiences and existing problems.
2. Theoretical Framework and Research Hypothesis
Grassland protection policies generally affect herders’ interests. The willingness and attitude of herders should be considered in the implementation of these policies. Based on the extended framework of Ostrom’s Institutional Analysis and Development Framework model and the 453 herders’ responses, we used a binary logistic regression model to study the herders’ willingness to protect grasslands. On this basis, the work summarizes the problems and shortcomings of China’s grassland protection policy and provides suggestions for improving the grassland protection policy.
A new institutional economics model called the Institutional Analysis and Development (IAD) framework has been widely employed in the research on the local management of common resources [
36,
37,
38]. The original purpose is to explain why exogenous variables such as application rules affect the self-governance of public resources to provide resource users with a set of institutional design schemes and evaluation criteria that can enhance trust and cooperation [
39]. The IAD framework is unique in that it can systematically and theoretically focus on the influence of rules and norms on individual incentives of complex systems of ecological economics [
38].
As shown in
Figure 1, the IAD framework consists of exogenous variables, an action stage, an interactive mode, results, and evaluation criteria for the results. Exogenous variables include the biophysical conditions and attributes of community and the rules-in-use, which can affect the action stage. The action stage is composed of action situations and actors, and it is the unit of institutional analysis. The rules-in-use refer to a series of formal and informal institutional arrangements, and institutions mainly influence the action stages through the structural framework of the action situation. The biophysical conditions can be regarded as the attributes of things, and the strategy choice of actors in the action stage will be influenced by the attributes of nature and the material world. The attributes of community play an important role in constructing the structure of the action stage. They include the behavioral norms generally accepted by members of a community, the common understanding levels of potential participants regarding the structure of an action stage, the level of preference homogeneity among members of a community, and the resource allocation among community members [
40]. Within the IAD framework, the rules are the basic determinants of the formation of a social accumulation structure. Under the influence of exogenous variables, all actors in an action stage will establish the interaction mode and results that can be evaluated by certain standards under this mode. These results will affect the action stage and, sometimes, the external variables. In recent years, coastal and marine ecosystem governance [
41], integrated forest management decisions [
42], and work focused on farmers’ willingness to participate in cultivated land recuperation [
43] based on the IAD framework and related extended models have been applied in integrated management, management decision making, and studies of farmers’ interests and behavior.
The Participants Intellectual Decision Model is the core focus of the action stage. The central premise is as follows: the decision-making willingness of participants is affected not only by their own situation, level of control, net income expectations, and perceptions of action status information but also by their expectations, the final situation before action, and the actual results of the final action in addition to the impact of the natural material and institutional environment [
44]. In this study, we used a participant intelligence decision model extended from the IAD framework to divide the process of herders’ willingness (decision) to engage in grassland protection into four main parts. At the same time, the participants’ background information, the market environment, the grassland protection rules, and the herders’ views of grassland protection policies were combined under a unified logical framework (
Figure 2). To demonstrate the applicability of the IAD extended decision model, Hypothesis 1 was proposed: the herders’ willingness to protect grassland is affected by state variables, protection rule variables, market environment variables, and state perception variables.
More importantly, the herders’ perceptions of the final actual results and income predictions made before decision making serve as the basis for making a final decision. An important criterion for judging whether the rights and interests of herders have been protected through grassland protection policy implementation concerns whether herders can obtain reasonable compensation after participating in grassland protection. Therefore, Hypothesis 2 was proposed: under the current grassland protection and management system, herders will tend to participate in grassland protection if the ecological compensation is more reasonable.
Combined with the research content of this paper, the characteristics of the heads of the households and basic family conditions were used to represent the participants’ status and condition control; policy implementation environment and market variables were used to represent the natural environment and social attributes; grassland protection rule variables were used to represent the action rules of the action stage; and cognitive reform variables were used to represent the herders’ perceptions and income judgments with regard to the grassland protection results.
4. Empirical Results
4.1. Interpretation of the Model’s Results
SPSS 20.0 software was used to conduct a binary logistic regression analysis of the regression elements and regressors. As shown in
Table 3, the overall regression results of the model show that all four categories of indicators had significant variables, proving the validity of hypothesis 1. According to the results of the model, among the variables reflecting the characteristics of the household head and the family profiles, the household income was significant at the level of 0.1. Although the regression coefficient was 0.000, it still had economic value, as the change range of household income is more than 1 yuan normally (around USD 0.15). The grassland area variable reached the 95% significance level in explaining the dependent variables. The coefficient of grassland area was 0.001, which indicates that when other conditions remain unchanged, if more than 1 mu (around 0.06 hm²) of grassland is owned, the probability of herders agreeing to protect the grassland is twice that of herders disagreeing to protect grassland. This result indicates that the more grassland area herders own, the more compensation they may obtain under grassland ecological compensation policy and the more likely they are to protect the grassland.
Among the variables reflecting the rules of grassland protection, the compensation level has a significant impact on whether grassland protection is supported. This is the case because the compensation amount adopted in Qinghai Province was higher than that adopted in Gansu Province in terms of grazing prohibition and livestock reduction or the balance between grassland and livestock. This result shows that, in terms of grassland management, the amount of ecological compensation provided by the government plays a significant role in decision-making for grassland protection.
Regarding the policy implementation environment and market variables, the distance from the county was significant at the level of 0.01 and showed a negative correlation, indicating that the farther an area is from a county and the more remote an area is, the more likely it is that herders would not support grassland protection, which also reflects the higher dependence of herders in remote areas on grassland production and grazing. In addition, for the past two years, the sales price of livestock explained the dependent variable with a significance level of 95%, and its coefficient was negative, indicating that the higher the price of livestock, the more income herders earn through animal husbandry, the greater their dependence on grazing becomes, and the less inclined they are to support grassland protection.
Among the variables reflecting herders’ cognitive reform, whether herders pay attention to grassland ecological protection, their understanding of the effects of management on grassland restoration, their understanding of grassland ecological compensation, and their views on the reasonableness of ecological policy compensation had a significant influence on whether herders support grassland protection. Among these variables, the coefficient of views of grassland restoration was negative, which indicates that herders may think that grassland is best protected through government management and that they do not need to participate in grassland protection. The coefficient for whether herders pay attention to grassland ecological protection and the coefficient of their understanding of grassland ecological compensation were negative, indicating that herders may not be satisfied with the grassland ecological compensation policy or think that the policy is unreasonable to some extent. Therefore, the more attention that was given to grassland protection and the more the policy was understood, the less willing herders were to participate in grassland protection. The positive coefficient of the reasonableness of ecological policy compensation also happened to explain this result; that is, the more reasonable an ecological compensation policy was, the more willing herders were to participate in grassland protection. Thus, hypothesis 2 holds.
4.2. Model Verification and Explanation
Table 4 shows the chi-square test results demonstrating that the equation was generally significant at the significance level of 0.01, and the significance of the Hosmer-Lemeshow test presented in
Table 5 was 0.397, which was greater than 0.05, showing that the goodness of fit was strong. However, the reasoning behind decisions of herders who had participated in livestock reduction and those who had not differed. For example, the ecological compensation of herders who had participated in grazing prohibition and livestock reduction may differ from that of herders who had not due to family income, the impact of grassland ecological compensation policy on total family income, and their views of the reasonableness of grassland ecological compensation. For herders who had participated in the policy, their expectations of family benefits were based on comparisons drawn to the reality before they participated in the policy. Herders who had not participated in the policy were more likely to compare themselves to those who had participated. When herders who had participated in the grassland management policy were compared to those who had not, they may prefer to support grassland protection only if grassland protection led to positive changes in their income when long-term variables, such as the household head and family characteristics, the grassland management policy implementation environment and market, and cognitive reform features show no significant changes. Therefore, conducting a respective regression analysis of the herders who had participated in grazing prohibition and livestock reduction and those who had not is of great significance to further address the herders’ willingness to protect grassland.
4.3. Comparative Regression Analysis
To verify whether herders who had participated in grazing prohibition and livestock reduction would make different choices in a similar action stage, we conducted a difference analysis of the herders who had participated in livestock reduction and those who had not to test for potentially significant differences in the values of each variable for the two groups. The results, which are shown in
Table 6, demonstrate that the education background, household income, livestock quantity, grassland area, compensation region, distance from the county seat, attention to grassland ecological protection, understanding of the effects of management on grassland restoration, and understanding of grassland ecological compensation policy significantly differed between herders who had participated in grazing prohibition and livestock reduction and those who had not at the level of 0.01. Clearly, the null hypothesis can be rejected. Thus, we performed a further classified regression analysis of herders who had participated in grazing prohibition compensation and those who had not.
As shown in
Table 7, for the herders who had participated in grazing prohibition and livestock reduction, age and education background were significant at the 0.1 level. The family population and distance to the county were significant at the 0.05 significance level. When the age increased by one year, the probability of supporting grassland protection was 1.04 times that of opposing the policy. When the education level was higher, the probability of opposing grassland protection was 1.51 times that of supporting the policy. When the family population increased by 1 person, the probability of opposing grassland protection was 1.32 times that of supporting the policy. When the distance from the county increased by 1 km, the probability of opposing grassland protection was 1.05 times that of supporting the policy.
For the herders who had not participated in grazing prohibition and livestock reduction, the grassland area owned by the householder, the compensation region, the distance from the county seat, the livestock sales price of the past two years, the attention to grassland ecological protection, and the views of the effects of grassland management on grassland restoration were significant. The larger the area of grassland owned by the householder, the more likely the householder was to agree to grassland protection. For herders living in Qinghai Province, who received more ecological compensation for grassland protection, the probability of supporting grassland protection was 5.62 times that of opposing the policy. At a far distance from the county seat, the probability of not agreeing to protect grassland was 1.06 times that of agreeing. At a high selling price for livestock products, the probability of not agreeing to protect grassland was 2.02 times that of supporting the policy. When herders paid more attention to the issues of grassland ecological protection, the probability of not agreeing to protect grassland was four times that of supporting the policy. When herders believed that grassland management can improve grassland restoration, the probability of opposing grassland protection was 1.86 times that of supporting grassland protection.
For herders who had participated in grazing prohibition and livestock reduction, the higher the age was, the less grazing behavior was involved. The lower the education level of herders, the stronger the willingness to protect grassland in order to obtain more compensation. The smaller the family population was, the lower living expenses were. At the same time, the closer households were to a county, the easier it was to find other income opportunities in the market and lessen their dependence on grazing. Therefore, it can be inferred that the willingness of herders who had participated in grazing prohibition and livestock reduction to participate in grassland protection was more affected by their families’ economic conditions.
For herders who had not participated in the prohibition of grazing and livestock reduction, their willingness to participate in grassland protection was affected not only by their families’ economic conditions but also by the features of grassland protection policy. These herders expect to obtain reasonable subsidies through grassland ecological compensation to reduce the impact of grassland protection on their animal husbandry income.
The results of the chi square test presented in
Table 8 show that the two equations testing involvement and noninvolvement in livestock reduction were significant at 0.05. The significance values of the Hosmer–Lemeshow test presented in
Table 9 were 0.465 and 0.419, respectively, which were both greater than 0.05, showing that the overall fitting effect of the model was ideal.
6. Conclusions
Based on the theory of the IAD extended decision model, through a comparative binary logistic regression analysis of a sample of 453 herders and explanation test of the model parameters, the following conclusions are drawn.
First, our overall regression model for herders showed that the household and family characteristics, grassland protection rules, policy implementation environment, and market and cognitive reform variables were significant at the 0.1 level, which proves the validity of hypothesis 1. Among these variables, when herders thought that the ecological compensation policies were reasonable, they were more inclined to carry out grassland protection, which proves the validity of Hypothesis 2.
Second, our difference analysis of herders who had participated in livestock reduction and those who had not shown significant differences in four respects. Therefore, it is of great theoretical and practical significance to divide herders into those who had participated in grazing prohibition and the reduction of livestock and those who had not. The regression results of the herders classification model showed no significant differences in the distances from counties between herders who had participated in livestock reduction and those who had not; however, significant differences were found for the family population, grassland area, compensation region, the livestock sales price for the last two years, attention to grassland ecological protection, and the role of governance in grassland restoration.
Third, China’s current grassland management system has achieved certain results. However, an analysis of the herders’ willingness to protect the grassland also shows some problems with the grassland management in China, including a lack of comprehensive grassland ecological compensation publicity policies, implementation, and supervision rules for grassland management policies and supporting social system guarantees for policy implementation. According to these results, we must build a diversified grassland protection mechanism, flexibly adjust grassland ecological compensation modes, and moderately adjust the production structure of pastoral areas to solve these problems.
Due to the research capacities and conditions, this paper has the following shortcomings. The design of variables can be further refined to consider factors, such as different types of grassland, grassland quality, spatial locations, and types of livestock raised, which may also lead to differences in the herders’ willingness to protect the grassland. In addition, there may be differences in the spatial characteristics of the herders’ decision-making between southern and northern China, which will require more in-depth research.