蒙古国植被自然恢复潜力

植被自然恢复能力评估是生态恢复实践的重要内容。基于蒙古国的MODIS EVI植被指数产品、气象数据及土壤数据，依据相似生境原则，构建了植被恢复潜力计算模式，计算得到蒙古国植被恢复潜力值（VRP，可代表在自然条件下区域植被能够恢复到的最佳状况）及植被恢复潜力指数（VRPI，代表植被生长现状与最大潜力之间的差距），并用蒙古国纵贯铁路沿线长期围封区的采样分析数据进行了验证。结果表明：（1）蒙古国整体上具有较高的植被恢复潜力，植被自然恢复潜力值0.6—0.9；（2）受降水、气温、土壤等自然要素组配的空间分异影响，蒙古国植被自然恢复潜力具有较大的空间差异性，其中北部及东部地区为VRP高值区和VRPI低值区，植被轻度退化，且较容易恢复；南部及西部地区为VRP中低值区和VRPI高值区，植被退化程度较重，恢复难度相对较大。

Natural restoration potential of vegetation in Mongolia

Assessment of natural restoration capacity of vegetation is an important part of ecological restoration practice. This article， based on the MODIS Enhanced Vegetation Index （EVI）， meteorological data and soil data of Mongolia， build the vegetation restoration potential calculation model on the “similar habitat”， calculate the Mongolia vegetation restoration potential value （VRP， representative in the area under the condition of natural vegetation to restore to the best condition） and vegetation restoration potential index （VRPI， on behalf of the vegetation growth status and potential difference between the largest）. And use the sampling analysis data from Mongolian through long-term enclosure along the railway area to verify the research findings. The results showed that ：（1） There is a high vegetation restoration potential in Mongolia， and the natural vegetation restoration potential value is mostly between 0.6 and 0.9. （2） Under the influence of spatial differentiation of natural factors such as precipitation， air temperature and soil， the natural restoration potential of vegetation in Mongolia has great spatial differences. The northern and eastern regions are the regions with high VRP value and low VRPI value. Suggest that the vegetation was slightly degraded and easy to recover. In the southern and western regions， there are middle and low values of VRP and high values of VRPI. The degree of vegetation degradation is severe and the restoration is relatively difficult. The results of this study can provide scientific reference for the restoration of degraded vegetation in Mongolia according to local conditions.