黄土高原盆地土壤有机质与影响因子的空间多尺度关系

不同影响因子对土壤有机质含量的影响存在尺度依赖性。以太原盆地土壤有机质为研究对象,于盆地上、中、下部分别设置采样带,应用多元经验模态分解(multivariate empirical mode decomposition,MEMD),分析了盆地内不同部位土壤有机质与影响因子(高程、坡度、地形湿度指数、土壤容重、砂粒、壤粒、黏粒和光谱主份等)在表征尺度的相关性,并预测了采样尺度上土壤有机质含量,旨在研究黄土高原盆地区内土壤有机质与相关因子的空间多尺度关系。研究结果表明:(1)利用MEMD法可将盆地内不同部位处的土壤有机质空间序列分解为不同表征尺度,盆地上、中和下部的表征尺度分别为6、8和7个。研究区域内,尺度约1000 m处是土壤有机质的主要表征尺度,且盆地内垂直河流方向的有机质序列主要表征尺度沿河流方向表现分散。(2)土壤有机质和影响因子的空间多尺度关系表明,高程与土壤有机质的关系主要表现在大尺度,而坡度、地形湿度指数与盆地中、下部土壤有机质的关系较明显。土壤容重与有机质在不同位置的不同表征尺度存在显著差异。土壤质地中,壤粒含量与有机质的多尺度关系最为明显。光谱主份1在全部样带中所有表征尺度上均与有机质显著相关。(3)采用MEMD法对有机质的预测精度高于基于原始数据的逐步多元回归结果。综上,研究结果可为黄土高原盆地区内土壤数字制图、土壤田块的合理设计与有机质的精确预测提供理论依据。

Multi-scale spatial relationships between soil organic matter and influencing factors in basins of the Chinese Loess Plateau

Soil organic matter (SOM) content is affected by a variety of factors that operate at different scales. The purpose of the present study was to investigate the multi-scale spatial relationships between SOM content and influencing factors, including elevation, slope, topographic wetness index, soil bulk density, sand content, silt content, clay content, and soil spectral components. Soil samples were collected from the Taiyuan basin, a typical area of the Chinese Loess Plateau, by establishing sampling transects at the upper, middle, and lower parts of the basin. At different locations in the basin, the multi-scale correlations of SOM content with the influencing factors were analyzed, and the SOM contents at the sampling scale were predicted using the multivariate empirical mode decomposition. The results showed that (1) the multivariate empirical mode decomposition method could separate the transects of SOM content into six, eight, and seven intrinsic mode functions for the upper, middle, and lower parts of the basin, respectively. A scale of 1000 m was the main representative scale for SOM content in the entire basin, and the number of representative scales increased along the river. (2) In contrast to the correlation at the sampling scale, the multi-scale spatial correlation between SOM content and the influencing factors revealed that the correlation of elevation and SOM content was dominant at larger scales. Meanwhile, the correlation of slope and SOM content was significant for the middle part of the basin, and the relationship between the topographic wetness index and SOM content was significant for both the middle and lower parts. However, the correlation between soil bulk density and SOM content was much more complex and differed at the various scales and locations; in the upper part of the basin, the relationship between the silt and SOM contents was more apparent than that of the sand and clay contents. In addition, spectral component 1 was significantly correlated with SOM content in the entire basin. (3) The multivariate empirical mode decomposition method was more accurate at predicting SOM content than the stepwise multiple linear regression. Therefore, taken together, the results of the present study provide a basis for soil digital mapping, dimension design of farmland, and SOM content prediction on the Chinese Loess Plateau.