[Spatial heterogeneity of soil organic matter and its response to disturbance in karst peak cluster depressions].
摘要
By using geostatistic methods, this paper studied the spatial variation and distribution of soil organic matter as well as its ecological processes and related mechanisms in four typical disturbed areas (cropland, man-made forest, secondary forest, and primary forest) of karst peak cluster depressions in northwest Guangxi of China. Eighty soil samples (0-20 cm) were collected from an aligned grid of 10 m x 10 m for the analysis of soil organic matter. The soil organic matter content increased significantly (P < 0.05) with the decrease of disturbance and the vegetation succession from crop to man-made forest to secondary forest to primary forest. Soil organic matter content had good spatial autocorrelation in all of the four typical disturbed areas, but its spatial heterogeneity differed. Gaussian model fitted best to the semivariance functions of soil organic matter content in the study areas except secondary forest area where exponential model fitted well. In cropland area, the spatial autocorrelation of soil organic matter was at medium level, with the C0/(C0 + C) being 26.5%; while in the other three areas, the spatial autocorrelation was at high level, with the C0/(C0 + C) being 9.0%-22.6%. The range and scale of the spatial autocorrelation of soil organic matter in cropland and man-made forest areas were larger than those in the other two areas, possibly due to the strong human disturbance and the homogeneity of low energy. The range of the spatial autocorrelation of soil organic matter in primary forest area was large due to the high vegetation coverage, while that in secondary forest area was the lowest due to the diverse vegetation communities and their uneven distribution. The low fractal value (D) of semivariance functions of soil organic matter in man-made forest and primary forest areas suggested that a strong spatial dependence existed, while the high D in cropland and secondary forest areas suggested a great random variance of spatial distribution of s