锡林郭勒盟生态脆弱性

以锡林郭勒盟为研究区,分析植被覆盖变化,辨析出影响暴露敏感性的主要因素,结合社会经济统计资料,构筑起以暴露敏感性和适应性能力为基础的生态脆弱性评价体系,分别借助空间主成分分析方法和主成分分析方法构建了暴露敏感性指数和适应性能力指数,获得生态脆弱性及其空间格局。结果显示:锡林郭勒盟暴露敏感性指数以西北部为中心,向四周辐射状递增,各旗县市的适应性能力指数从东北向西南递减,二者呈负相关关系。锡林郭勒盟生态脆弱性自东北向西南递增,东北部地区由于草地资源状况较好,经济发展水平相对较高,暴露敏感性较低而适应性能力较高;西南部地区因环境相对恶劣,经济发展落后,暴露敏感性较高而适应性能力较低。通过叠加分析,将研究区划分为8个生态脆弱性区域。

Ecological vulnerability research for Xilingol League, Northern China

Environmental change will affect the sustainability of human-environmental systems with natural and anthropogenic driving forces, especially in the ecologically vulnerable dryland, where the loss of biological and economic productivity hinders the prospects of poverty reduction. To adapt to a complicated changing environment, human society has to respond with various adaptive management and human behavior adjustments. The environmental state variance is greatly dependent on the system vulnerability, which was defined as the balance between exposure to physical threats to human well-being and the capacity of people and communities to cope with those threats. Vulnerability research can help to identify coping strategies for dryland regions. The present study provides a vulnerability assessment for the semiarid grasslands of the Xilingol League, Northern China. The grassland cover change of Xilingol is computed using the AVHRR NDVI data for 2000, by comparing it to the NDVI background from 1981 to 2006. The driving forces of grassland cover change are investigated by correlation analysis between grassland cover change and its potential climatic, topographic and anthropogenic drivers. An combined exposure-sensitivity index was calculated across the region using Spatial Principal Component Analysis (SPCA) for climate and anthropogenic indicators that had a strong correlation with the observed grassland cover change. This indicator was compared with an adaptive capacity index, constructed using principal component analysis (PCA) for relevant variables from aspects of location, economic development level, natural resource availability and administrative efficiency. As the relationships between exposure, sensitivity and adaptive capacity are not clearly understood, A vulnerability map was constructed by classifying and overlaying the spatial distributions of exposure-sensitivity and adaptive capacity. The results show that in Xilingol, the exposure-sensitivity index increases in a radial pattern with the valley in the northwest and the adaptive capacity index decreases from northeast to the southwest; the two indices are negatively correlated with each other, showing that harsher environmental conditions leading to higher exposure-sensitivity which failed in supporting the socio-economic and ecological infrastructure require a greater adaptive capacity. Combining exposure-sensitivity and adaptive capacity, the northeast part of Xilingol is identified to be least vulnerable due to a more favorable resource status and greater economic development. By contrast, the counties in the southwest, with harsh environmental conditions and a poor socio-economic infrastructure, have the greatest vulnerability and are in dire need of targeted adaptation measures to avoid a further decline in human well-being. The vulnerability of Xilingol decreases from southwest to northeast, which is opposite to the trend of annual mean precipitation, which indicates that the drier areas are more vulnerable than others. Based on the combination of exposure-sensitivity and adaptive capacity, Xilingol can be divided into eight sub-regions and the results of SPCA and PCA help in pinpointing the source of exposure-sensitivity and the advantages of adaptive capacity, which gives clues to find out a specific way for each county to reduce vulnerability by alleviating exposure-sensitivity and improving adaptive capacity. This paper demonstrated a straightforward approach to regional vulnerability assessment that can be readily applied in other dryland regions.