中文摘要：

研究了科尔沁沙地6个典型生境类型的沙质草地群落物种多样性与生产力的变化，分析了植物群落格局、物种多样性、生产力与土壤特性的关系．结果表明，从湿草甸向干草甸、固定沙丘、半固定沙丘、半流动沙丘和流动沙丘退化过程中，群落生产力逐渐下降；群落物种多样性先增加后减小，表现出由湿生化和土壤贫瘠化生境向中生、中旱生生境逐渐增加的趋势；土壤极细沙和粉粒含量逐渐递减，土壤有机碳和全氮含量、电导率逐渐递减．典范对应分析（CCA）表明，土壤有机碳、全氮、有效氮、有效钾、土壤含水量、酸碱度和盐分含量的变化共同影响植物群落分布格局，其解释总方差为40％，其中土壤养分梯度是沙质草地群落分布格局的主要土壤限制因子．沙质草地植物群落的生态优势度、物种多样性指数分别与土壤养分梯度和水盐及酸碱因子二元指标之间存在显著的二元线性关系．沙质草地群落物种多样性变化受土壤养分、水盐及酸碱度因子的共同影响．多元回归模型分析表明，土壤养分对生物量的贡献率为86．73％，明显大于水盐及酸碱度对群落生产力的影响．

英文摘要：

This study provided the analysis of changes of species diversity and productivity in relation to soil properties in six typical habitats （wet meadow, dry grassland, fixed dune, semi-fixed dune, semi-shifted dune, and shifted dune） in Horqin Sand Land. The changes of vegetation and soil properties, following the degraded process of sandy grassland, show the following trends： ① productivity decreases gradually, ② species diversity changes in a pattern of near-formal distribution, firstly increases from wet meadow, dry grassland, to fixed dune （at the peak）, and then decreases from semi-fixed dune, semi-shifted dune, to shifted dune, while ③ contents of soil fine sand, silt, soil organic carbon, total nitrogen, and electrical conductivity, decrease consistently. Ordination technique of canonical correspondence analysis （CCA） was used to examine the relationship between the vegetation pattern and soil parameters. Results show that soil organic carbon, total nitrogen, available nitrogen, available potassium, soil water content, pH and electrical conductivity are main factors of vegetation pattern in this area. These factors are closely related to the first two canonical axes, accounting for 40% of the species-soil properties relationship, and soil nutrient is the key factor for determining the distributions of the major vegetation type and pattern. Furthermore, the correlation between species diversity or ecological dominance of the communities and gradient of soil factors is significant, shows that changes of species diversity and productivity are affected by soil nutrients, soil water content, pH and electrical conductivity. The regression model of productivity and soil property reveals that soil nutrient is the key factor to community productivity, accounting for 86.73 % of the relationship between productivitysoil properties.