Ecological Vulnerability Assessment And Application In Fund Optimal-allocation For Road Ecological Restoration In Eastern Inner Mongolia

A healthy and sustainable ecosystem is responsible for human existence and development. The ecological vulnerability is increasing gradually with the rapid economic development, population growth and excessive exploitation of natural resources. Assessing ecological vulnerability scientifically can facilitate taking effective measures to prevent ecological degradation and conduct ecological restoration activities.In this study, a new method that combined Monte Carlo simulation with geographic information system (GIS) technology was proposed to assess the ecological vulnerability and to analyze the uncertainty originating from weight assignments from different experts’experience. A case study of eastern Inner Mongolia was used to illustrate the capacity of this method. According to the conceptual model of sensitivity-resilience-pressure for ecological vulnerability assessment, an index system was established, covering overall13factors of soil erosion sensitivity, desertification risk, animal diversity, plant diversity, net primary productivity (NPP), population, GDP, grain output, livestock number, comprehensive land-use degree index, acid rain intensity, fire risk and earthquake frequency. Supported by the ecological vulnerability assessment, a funding decision on road ecological restoration was made to identify the roads for restoration corresponding to specific optimal fund allocation. The results have been summarized as follows.(1) Comprehensively affected by regional climate and natural physical factors, the ecological vulnerability in the southern study area is higher than that in the northern, especially in the counties of Sonid Left Banner and Sonid Right Banner. They are located in the southwest of the study area facing with the most serious ecological predicament as a result of higher ecological sensitivity and lower ecological resilience simultaneously.(2) Monte Carlo method can simulate the accumulation of uncertainty from the index weights to ecological assessment results. By combining Monte Carlo with GIS technology, the probability distribution of ecological vulnerability index was obtained in each cell of the study area, and the uncertainty of assessment result caused by different index weights was also quantified. (3) Based on the assessment result, the road ecological vulnerability index was further extracted. Combining this index with the estimation standard of road ecological restoration fund, the "EVI-Cost" curve was created to facilitate decision-making on optimal fund allocation for road ecological restoration with limited fund. Then the road-determinant fund was reasonably allocated to each administrative unit to ensure that the ecological restoration fund would be effectively used.