Study On Pastoral Livestock Production And Multidimensional Poverty Of The Households In Qilian Mountain

In the "Thirteen-five years" plan in 2016 government work report, the focus of the next five years including the deepening of rural collective property rights reform, the implementation of projects tackling poverty, strengthen ecological security barrier construction which solidarity content with the development of animal husbandry. The research area, part of the Qinghai-Tibetan Plateau, has fragile grassland ecosystem and livestock is the main source of income for local residents. Grazing behavior of the households in Qilian Mountain is not only affect the herders’ livelihoods, but also affect the performance of services function of the Tibetan Plateau grassland ecosystems. Therefore, the Tianzhu Tibetan Autonomous County and Sunan Yugu Autonomous County, both located in the Qilian Mountains, Gansu Province, were selected to analyze the livestock production efficiency and multidimensional poverty. Twenty-five households have been selected in each of the two counties. In Sunan County, the use of the pasture is allocated to households. Each household has its pastures for summer, autumn and winter. In Tianzhu County, summer and autumn pastures are common. Their use is collective at the village scale. Through DEA model(the Model of Data Envelopment Analysis), inputs and outputs data within each farm of the sample were fully collected, such as the size of pasture,feeding supply, number of breeding females and family labor, the income of selling livestock,wool, milk and other products, to get the mean and distribution of production efficiency under different land ownership and the factors which affect production efficiency. Through multidimensional poverty model, data like household income, education level, health condition,living standards and so on were selected to analyze similarities and differences of households under single and multiple factors and the contribution of each factor data to multidimensional poverty. The main conclusions are given as:1.The income of most herdsman in Sunan County and Tianzhu County is at middle level or less, overall level of income needs to be improved. The proportion of herdsman in Sunan County which in the higher income group was higher than that of Tianzhu County. Average income ofherdsman in Tianzhu County is higher than Sunan County in the higher income group.2. Income and invest of herdsman are basically positively correlated, in a certain level, the more the grassland area, number of breeding females owned by herdsman, the higher the income they have. But to achieve a high income, we need more labor. Labor and feeding supply is more in high-income groups and similar in other groups. This shows that if the investment funds is limited, herdsman can increase the input of labor and feeding supply appropriately, in order to obtain a higher price.3. By DEA model, 46% of surveyed herders reached a high level of productivity in the current climate and pasture condition. Specifically, 66% of surveyed herders reached an effective use of resources in current level of technology and management. 30% of surveyed herders whose scale efficiency is 0.5 or less. Scale efficiency is the main reason for the lower comprehensive efficiency.4. 74% of surveyed herders are under condition of increasing returns to scale, 24% of surveyed herders are under condition of constant returns to scale, 2% of the herders are under condition of decreasing returns to scale. Most herders’ output could be increased by the increase of input. There is potential to expand production. 24% of surveyed herders are in the best production scale, only 2% of the surveyed herders need to narrow the scale of production.5. Average production efficiency of Tianzhu is larger than Sunan County(0.69> 0.59)(P<0.05), and distribution of production efficiency in Tianzhu County is better than Sunan County.Verify the difference of grassland ownership will affect the production efficiency. Further analysis shows that the factors which contribute to the redundancy of input is similar under different grassland ownership. The redundancy of feeding supply and breeding females.6. Under the influence of single factor, drinking water, fuel for life, property, education level are the main factors in poverty. Under the influence of multiple factors, the number of poor herders accounted for 96% in two dimensions. The indexes such as drinking water(0.28), living fuel(0.26), educational level(0.22),assets(0.22) have most contributions to the multidimensional poverty. From the county level, in single-dimensional poverty, Tianzhu County has higher levels of asset and water poverty, and income poverty exists; Sunan County has higher levels of water and living fuel poverty, and healthy poverty exists. In multidimensional poverty,the major factors of poverty coincides with the factors in one-dimensional poverty, but the degree of contribution is slightly different, which is related to specific development situation.