Scale effects of spatial variations in SOM and STN in semi-arid regions: A case study of Yan'an
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摘要: 以高密度采样数据为数据集,经重采样分析,模拟不同尺度的采样空间分布场景,采用莫兰指数、半方差函数值和分形维数FD等空间分析方法,探讨土壤有机质和全氮空间变异的尺度效应特征,并分析其影响因素的尺度间转换关系。结果表明:随着尺度增大,空间集聚性降低,有机质和全氮含量空间总变异先增大后趋于稳定,但随机性变异逐渐减少,结构性变异先增大后减少。小尺度产生的空间变异中的随机变异占比较多,结构变异占比较少,而大尺度则相反。不同的影响因素对有机质和全氮空间变异具有不同的区分度,高程的区分度最小;土壤类型、植被指数、年均气温、湿度等影响因素的区分度次之;降水量的区分度最大。有机质和全氮空间变异影响因素具有尺度特征,随着尺度增大,小尺度因素引起的随机变异逐渐减少,而大尺度因素引起的结构性变异先增大后减弱,直至转换为相对的小尺度因素;各影响因素对土壤有机质和全氮含量的影响协同机制在尺度间差异较大,引起随机变异和结构变异出现尺度间消长,导致空间变异呈现出先减少后趋于平稳的变化规律。Abstract: Taking high-density sampling data as a dataset, the sampling spatial distribution scenarios on different scales were simulated through resampling analysis. Spatial analysis methods, such as Moran's I index, semi-variance function value, and fractal dimension FD, were used to explore the scale effects of spatial variations in soil organic matter (SOM) and soil total nitrogen (STN) and to analyze the conversion of influencing factors between different scales. The results are as follows. With an increase in scale, the spatial agglomeration decreased, and the spatial variation of SOM and STN in general increased first and then tended to be stable. By contrast, the random variation decreased gradually and the structural variation increased first and then decreased as the scales increased. The spatial variation generated on small scales consisted of a large proportion of random variation and a small proportion of structural variation, while the opposite is true on large scales. Different influencing factors had different distinguishing degrees for the spatial variations in SOM and STN. Their distinguishing degrees were in the order of height
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Key words:
- sampling scale /
- spatial variation /
- fractal dimension /
- semi-variance function /
- SOM /
- STN /
- semi-arid regions
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