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Spatial heterogeneity of soil nutrients in Liaocheng, Shandong Province.

Jinping Zhang, Baohua Zhang, Yaochen Qin

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Abstract

Based on data from field survey of arable soil by the end of 2008, spatial heterogeneity and distribution patterns of soil nutrients in Liaocheng City, Shandong Province were studied in this paper. By 8 km×8 km grid, the land was divided into 136 sampling points, and the contents of soil organic matter, total N, total P and total K were monitored. The combination of GIS, spatial autocorrelation analysis and geostatistical analysis was used to analyze the spatial features of soil nutrients. Traditional statistical analysis shows that, after decades of farming, the variation of soil nutrient content in the measurement scale has the increasing trend. Geostatistical analysis shows that, the changes of spatial heterogeneity of four kinds of soil nutrient are not identical in the entire region. The changes of organic matter and total N are irregular, while the spatial variability of total P is more random. The spatial heterogeneities of soil nutrients change mainly by random factors. Human activities, such as irrigation, fertilization, cultivation measures, cropping systems, etc, are major factors. The spatial correlations of four soil nutrients are very weak. On the whole, there is an obvious spatial distribution of the four soil nutrients which gradually declines from the eastern and southern to the western and northern part of Liaocheng City. Spatial autocorrelation analysis shows that, as the scale increases, spatial autocorrelation decreasing trends of four soil nutrients are similar, but the overall response on the scale is hardly evident. In the scope of the 40 km, Moran's I coefficients of four kinds of soil nutrients are positive which shows a positive spatial correlation. The response of organic matter on the scale is more sensitive than that of other three nutrients. The change of Moran's I of total N and total P is similar. But Moran's I coefficient of total K outside the scope of 64 km performs the volatility in the vicinity of 0, which may be related to the local agricultural activities.

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What this paper is about

Based on data from field survey of arable soil by the end of 2008, spatial heterogeneity and distribution patterns of soil nutrients in Liaocheng City, Shandong Province were studied in this paper. By 8 km×8 km grid, the land was divided into 136 sampling points, and the contents of soil organic matter, total N, total P and total K were monitored. The combination of GIS, spatial autocorrelation analysis and geostatistical analysis was used to analyze the spatial features of soil nutrients. Traditional statistical analysis shows that, after decades of farming, the variation of soil nutrient content in the measurement scale has the increasing trend. Geostatistical analysis shows that, the changes of spatial heterogeneity of four kinds of soil nutrient are not identical in the entire region. The changes of organic matter and total N are irregular, while the spatial variability of total P is more random. The spatial heterogeneities of soil nutrients change mainly by random factors. Human activities, such as irrigation, fertilization, cultivation measures, cropping systems, etc, are major factors. The spatial correlations of four soil nutrients are very weak. On the whole, there is an obvious spatial distribution of the four soil nutrients which gradually declines from the eastern and southern to the western and northern part of Liaocheng City. Spatial autocorrelation analysis shows that, as the scale increases, spatial autocorrelation decreasing trends of four soil nutrients are similar, but the overall response on the scale is hardly evident. In the scope of the 40 km, Moran's I coefficients of four kinds of soil nutrients are positive which shows a positive spatial correlation. The response of organic matter on the scale is more sensitive than that of other three nutrients. The change of Moran's I of total N and total P is similar. But Moran's I coefficient of total K outside the scope of 64 km performs the volatility in the vicinity of 0, which may be related to the local agricultural activities.

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Available abstract

Based on data from field survey of arable soil by the end of 2008, spatial heterogeneity and distribution patterns of soil nutrients in Liaocheng City, Shandong Province were studied in this paper. By 8 km×8 km grid, the land was divided into 136 sampling points, and the contents of soil organic matter, total N, total P and total K were monitored. The combination of GIS, spatial autocorrelation analysis and geostatistical analysis was used to analyze the spatial features of soil nutrients. Traditional statistical analysis shows that, after decades of farming, the variation of soil nutrient content in the measurement scale has the increasing trend. Geostatistical analysis shows that, the changes of spatial heterogeneity of four kinds of soil nutrient are not identical in the entire region. The changes of organic matter and total N are irregular, while the spatial variability of total P is more random. The spatial heterogeneities of soil nutrients change mainly by random factors. Human activities, such as irrigation, fertilization, cultivation measures, cropping systems, etc, are major factors. The spatial correlations of four soil nutrients are very weak. On the whole, there is an obvious spatial distribution of the four soil nutrients which gradually declines from the eastern and southern to the western and northern part of Liaocheng City. Spatial autocorrelation analysis shows that, as the scale increases, spatial autocorrelation decreasing trends of four soil nutrients are similar, but the overall response on the scale is hardly evident. In the scope of the 40 km, Moran's I coefficients of four kinds of soil nutrients are positive which shows a positive spatial correlation. The response of organic matter on the scale is more sensitive than that of other three nutrients. The change of Moran's I of total N and total P is similar. But Moran's I coefficient of total K outside the scope of 64 km performs the volatility in the vicinity of 0, which may be related to the local agricultural activities.

Key concepts: Environmental science, Nutrient, Geostatistics, Arable land, Spatial variability, Spatial distribution, Spatial analysis, Spatial heterogeneity

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