Study on Chinese herders’ preference for grassland ecological compensation and its impact factors — Based on the survey of two counties in Qinghai Province
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China's Grassland covers an area of 390 million hectares, accounting for more than 40% of the total land area. It is the largest terrestrial ecosystem in China. After the institutional reform of the State Council, the State Forestry and Grassland Administration (NFGA) became the department in charge of grassland and forest. NFGA began to explore the long-term mechanism for Grassland Ecological Compensation (GEC). Qinghai Province is the main pastoral region in China, and it is also the water source of Yangtze River, Yellow River and Lantsang River (Mekong River), where there are different herders with different Religious Belief and Minority. It is of great significance for the formulation of long-term GEC mechanism and the implementation of precise policies to study the local herders’ preference for GEC and its influencing factors. Based on 340 questionnaires from Qilian County and Menyuan County in Qinghai Province, this study selects three compensation methods, fund compensation (FC), policy compensation (PC) and substantial compensation (SC), as dependent variables, and takes demographic characteristics, family characteristics, grassland characteristics, policy cognition and other factors as independent variables. Disordered Multiple Logistic Regression Analysis was used in this study. The results show that 69.71% of respondents prefer FC, 20.29% prefer PC, and 10% prefer MC. The impact of some independent variable involved county, demographic characteristics, Family characteristics, grassland characteristics on herders’ preference for GEC means is significant. It is found that policy cognition has no significant to the preference. Therefore, the study believes that FC is still the main compensation method for a period of time, but it should be more diversified and detailed for different groups and their demands in the sustainable compensation mechanism and policy design.
Keywords: Agriculture, Governance, Policies, Research
ID: 3486732