不同尺度下内蒙古河套灌区有机质空间变异

Spatial variability of soil organic matter at different sampling scales in Inner Mongolia Hetao irrigation area

以内蒙古河套灌区为研究对象,利用经典统计学与地统计学相结合的方法,对1、4、8 km 3个样点间距下不同土层（0~20、20~40、40~70与70~100 cm）有机质含量的空间变异及尺度效应进行分析。经典统计结果表明,不同尺度下有机质含量均值的变异程度均随着土层深度的增加而增加,其在0~20和20~40 cm土层随着尺度的增加而变大。地统计分析结果显示,不同尺度不同土层有机质含量均具有强烈的空间自相关,且其空间分布主导影响因子为土壤类型。各尺度不同土层有机质空间分布均存在一定程度的方向性,其在小尺度（1 km）表现为东西方向上的条状变异;在中尺度（4 km）及大尺度（8 km）均在土壤表层的东-西和西北-东南方向存在强烈的空间变异性。各尺度下有机质的普通克里格插值交叉验证的均方根误差均小于1,说明样本的空间变异均被高估。研究结果对于理解土壤有机质空间分布具有重要意义,为农业技术研究中野外采样系统设计提供一定的参考。

Taking the Hetao irrigation region in Inner Mongolia as the research subject,with methods of classical statistics and geo-statistics,we analyzed the spatial variability and scale effect of soil organic matter at different soil layers（ 0-20,20-40,40-70 and 70-100 cm） and sampling scales（ 1,4 and 8 km）. The results of classical statistics showed that the variation of mean organic matter contents increased with the increase of soil depth at all sampling scales; the coefficients of variations of organic matter contents at soil depths of 0-20 cm and 20-40 cm increased with increasing the sampling scale. Geo-statistics indicated that there existed strong spatial autocorrelations in soil organic matter contents in different soil layers and at different sampling scales,and soil type was the dominant factor influencing its spatial distribution. There were certain anisotropic effects in the spatial patterns of organic matter content at different soil layers at all sampling scales. At small scale（ 1 km）,this anisotropic effect presented a strip variation on eastwest direction at each soil layer. At moderate（ 4 km） and large scale（ 8 km）,corresponding spatial variability was intensive in terms of east-west and northwest-southeast gradients at the top soil layer. The cross validation of ordinary Kriging applied on organic matter at the three scales showed that the root mean square errors were less than 1,indicating that the spatial variability of samples was overestimated. Our results highlight great significance for understanding the spatial distribution of soil organic matter,providing a scientific basis for sampling system design in agricultural technology research.