通过在高寒草甸设置研究样地、进行植物群落特征观测、土壤样品采集、土壤主要物理化学性质分析测定, 利用退化草地群落特征和土壤因子数据进行冗余分析, 对高寒草甸土壤因子与草地退化之间的关系进行探讨.结果表明:不同退化程度草地沿冗余分析排序图第一排序轴分布, 第一排序轴反映草地退化程度的变化;草地植物群落特征中与第一排序轴负相关且按相关程度大小排序的指标为植被覆盖度＞地上生物量＞多样性指数＞均匀性指数;第一、第二排序轴能够解释90.3%的草地退化与土壤因子关系;土壤温度、容重与第一排序轴正相关, 土壤含水量、全氮、有效氮、全磷、土壤有机碳与第一排序轴负相关, 有效钾、粘粒占比与第二排序轴负相关;第一排序轴及所有排序轴所反映的土壤因子均与草地退化样地之间呈极显著相关关系(P＜0.01);不同土壤因子与草地退化之间关系密切程度不同, 土壤温度(r = 0.929)、容重(r = 0.915)、土壤含水量(r = -0.916)、全氮(r = -0.907)、有效氮(r = -0.859)、全磷(r = -0.809)、土壤有机碳(r =-0.662)等与高寒草甸退化相关程度更高且相关关系极显著(P＜0.01);土壤因子中筛选出土壤温度、全氮等 9 个敏感性土壤指标, 能够解释 93.3%的草地退化与土壤因子关系.利用退化草地群落特征和土壤因子数据矩阵进行冗余分析能够综合反映土壤因子与草地退化之间的关系及相关程度, 筛选后的土壤因子能够作为高寒草甸草地退化的敏感性指示指标.%Through setting up research sample plots on the alpine meadow, observation of plant community characteristics, collection of soil samples, analysis of soil physical and chemical properties, and use of the community characteristics of degraded grassland and soil factor data for redundancy analysis, we discussed the relationship between soil factors and grassland degradation in alpine meadows. The results showed that the redundancy analysis ordination diagram first sorting axis showed the distribution of different degradation degrees grassland, and the first sorting axis reflected the degree of grassland degradation. The grassland plant community was negatively correlated with the first sorting axis and correlation degree was vegetation coverage, above-ground biomass, diversity index and evenness index successively. The first and second sorting axes were able to explain 90.3% relationship between grassland degradation and soil factors. Soil temperature and bulk density were positively correlated with the first sorting axis. Soil water content, total nitrogen, available nitrogen, total phosphorus and soil organic carbon were negatively correlated with the first sorting axis, and available potassium and the ratio of clay were negatively correlated with the second sorting axis. The relationship between soil factors and grassland degradation was different and extremely significant correlation in first sorting axis and all sorting axis (P＜0.01), and the relationships between soil temperature(r = 0.929), bulk density (r = 0.915), soil water content (r = -0.916), total nitrogen (r = -0.907), available nitrogen (r = -0.859), total phosphorus (r = -0.809) and soil organic carbon (r = -0.662) and so on with alpine meadow degradation were extremely significant correlation(P＜0.01). Soil sensitivity indexes were selected from soil factors and could explain 93.3% the relationship between grassland degradation and soil factors. Redundancy analysis of degraded grassland community characteristics and soil factors data matrix could comprehensively reflect the relationship between soil factors and grassland degradation and the degree of correlation. Screened soil factors can be used as a sensitive indicator of alpine meadow degradation.
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