广东山区土壤有机碳空间变异的尺度效应

Abstract

研究土壤有机碳的尺度效应能够为区域生态环境保护和确定合理的土壤取样间距提供科学依据。采用土壤类型法估算了广东山区表层(0-20 cm)和全剖面(0-100 cm)土壤有机碳密度,选择4条采样带,获取采样间距为250 m的土壤有机碳密度序列,并利用离散小波变换工具对其进行多尺度分解,得到2×250 m、2²×250 m、2³×250 m、2⁴×250 m、2⁵×250 m和2⁶×250 m 6个分解尺度上的小波信息,计算小波信息方差。结果表明:土壤有机碳密度具有较强的空间异质性,其空间异质性的大小受控于不同尺度下土壤有机碳密度分布格局的主导因子影响程度;整体上在大于等于1 km的尺度,其空间异质性较强;各个样带特征尺度的差异与各样带的土壤和植被类型、地貌特征以及土地利用方式、耕作管理方式等人类活动干扰强度有关。;Understanding the scaling effect on the spatial variation of soil organic carbon (SOC) is necessary for regional eco-environmental protection and for determination of reasonable soil sampling intervals. The objective of this study was to characterize the scaling effect on the spatial variation of SOC using wavelet multi-analysis techniques. This study was based on data from 223 typical soil profiles that were derived from the second national soil survey data from Guangdong Province. The soil profile data included soil types, soil organic matter (SOM) content, soil bulk density, soil depth and area. We estimated SOC density from depths of 20 cm and 100 cm in mountainous areas of Guangdong Province, and then developed an SOC density map with a grid size of 250 m by using the soil type map (1:200000). In detail, we selected four spatial sampling transects, which comprised two horizontal transects with a grid size of 250 m from 24° 50' N to 24° N latitude, and two left-oblique transects with a grid size of 250 m from 111° E to 114° E longitude, and from 115° E to 116° E longitude. These four transects reflect the general characteristics of the study area. By using the method of discrete wavelet transform (DWT) on the spatial sampling data of SOC density along the above four transects, we derived wavelet approximate information and wavelet detailed information over six different scales of 2×250 m (0.5 km), 2²×250 m (1 km), 2³×250 m (2 km), 2⁴×250 m (4 km), 2⁵×250 m (8 km) and 2⁶×250 m (16 km) respectively. The descriptive statistical characteristics of SOC density were tabulated, and then we calculated the variance of the wavelet detailed information of SOC density, which can then represent the magnitude of variation in SOC density. The results showed the following. (1) On the whole, the spatial heterogeneity of SOC density was strong and varied with different transects and soil depth, which was controlled by dominant influence factors on different scales. (2) The overall optimum scale of grid size on which SOC had the maximum spatial heterogeneity was equal to or greater than 1 km. (3) The variation of different scales of each transect varied with soil type and vegetation type, geomorphologic characteristics, human activities(e.g. land use, cultivation management) and other influencing factors. In summary, this study provided a reference for the application of discrete wavelet transform to the spatial variation of SOC density on large regional scales, and made the analysis of SOC variation patterns more convenient.