Accessibility to organic carbon(OC) budget is required for sustainable agricultural development and ecosystem preservation and restoration. Using geostatistical models to describe and demonstrate the spatial variabili...Accessibility to organic carbon(OC) budget is required for sustainable agricultural development and ecosystem preservation and restoration. Using geostatistical models to describe and demonstrate the spatial variability of soil organic carbon(SOC) will lead to a greater understanding of this dynamics. The aim of this paper is to present the relationships between the spatial variability of SOC and the topographic features by using geostatistical methods on a loess mountain-slope in Toshan region, Golestan Province, northern Iran. Hence, 234 soil samples were collected in a regular grid that covered different parts of the slope. The results showed that such factors as silt, clay, saturated moisture content, mean weighted diameter(MWD) and bulk density were all correlated to the OC content in different slope positions, and the spatial variability of SOC more to slope positions and elevations. The coefficient of variation(CV) indicated that the variability of SOC was moderate in different slope positions and for the mountain-slope as a whole. However, the higher variability of SOC(CV = 45.6%) was shown in the back-slope positions. Also, the ordinary cokriging method for clay as covariant gave better results in evaluating SOC for the whole slope with the RMSE value 0.2552 in comparison with the kriging and the inverse distance weighted(IDW) methods. The interpolation map of OC for the slope under investigation showed lowering SOC concentrations versus increasing elevation and slope gradient. The spatial correlation ratio was different between various slope positions and related to the topographic texture.展开更多
There are various occasions where simple, ordinary, and universal kriging techniques may find themselves incapable of performing spatial prediction directly or efficiently. One type of application concerns quantificat...There are various occasions where simple, ordinary, and universal kriging techniques may find themselves incapable of performing spatial prediction directly or efficiently. One type of application concerns quantification of cumulative distribution function (CDF) or probability of occurrences of categorical variables over space. The other is related to optimal use of co-variation inherent to multiple regionalized variables as well as spatial correlation in spatial prediction. This paper extends geostatistics from the realm of kriging with uni-variate and continuous regionalized variables to the territory of indicator and multivariate kriging, where it is of ultimate importance to perform non-parametric estimation of probability distributions and spatial prediction based on co-regionalization and multiple data sources, respectively.展开更多
Soil organic carbon (SOC) plays a key role in the global carbon cycle.In this study,we used statistical and geostatistical methods to characterize and compare the spatial heterogeneity of SOC in soils of Jiangsu Provi...Soil organic carbon (SOC) plays a key role in the global carbon cycle.In this study,we used statistical and geostatistical methods to characterize and compare the spatial heterogeneity of SOC in soils of Jiangsu Province,China,and investigate the factors that influence it,such as topography,soil type,and land use.Our study was based on 24 186 soil samples obtained from the surface soil layer (0-0.2 m) and covering the entire area of the province.Interpolated values of SOC density in the surface layer,obtained by kriging based on a spherical model,ranged between 3.25 and 32.43 kg m 3.The highest SOC densities tended to occur in the Taihu Plain,Lixia River Plain,along the Yangtze River,and in high-elevation hilly areas such as those in northern and southwest Jiangsu,while the lowest values were found in the coastal plain.Elevation,slope,soil type,and land use type significantly affected SOC densities.Steeper slope tended to result in SOC decline.Correlation between elevation and SOC densities was positive in the hill areas but negative in the low plain areas,probably due to the effect of different land cover types,temperature,and soil fertility.High SOC densities were usually found in limestone and paddy soils and low densities in coastal saline soils and alluvial soils,indicating that high clay and silt contents in the soils could lead to an increase,and high sand content to a decrease in the accumulation of SOC.SOC densities were sensitive to land use and usually increased in towns,woodland,paddy land,and shallow water areas,which were strongly affected by industrial and human activities,covered with highly productive vegetation,or subject to long-term use of organic fertilizers or flooding conditions.展开更多
基金Gorgan University of Agricultural Sciences and Natural Resources for the support of this study
文摘Accessibility to organic carbon(OC) budget is required for sustainable agricultural development and ecosystem preservation and restoration. Using geostatistical models to describe and demonstrate the spatial variability of soil organic carbon(SOC) will lead to a greater understanding of this dynamics. The aim of this paper is to present the relationships between the spatial variability of SOC and the topographic features by using geostatistical methods on a loess mountain-slope in Toshan region, Golestan Province, northern Iran. Hence, 234 soil samples were collected in a regular grid that covered different parts of the slope. The results showed that such factors as silt, clay, saturated moisture content, mean weighted diameter(MWD) and bulk density were all correlated to the OC content in different slope positions, and the spatial variability of SOC more to slope positions and elevations. The coefficient of variation(CV) indicated that the variability of SOC was moderate in different slope positions and for the mountain-slope as a whole. However, the higher variability of SOC(CV = 45.6%) was shown in the back-slope positions. Also, the ordinary cokriging method for clay as covariant gave better results in evaluating SOC for the whole slope with the RMSE value 0.2552 in comparison with the kriging and the inverse distance weighted(IDW) methods. The interpolation map of OC for the slope under investigation showed lowering SOC concentrations versus increasing elevation and slope gradient. The spatial correlation ratio was different between various slope positions and related to the topographic texture.
基金Supported by the National 973 Program of China (No. 2007CB714402-5)
文摘There are various occasions where simple, ordinary, and universal kriging techniques may find themselves incapable of performing spatial prediction directly or efficiently. One type of application concerns quantification of cumulative distribution function (CDF) or probability of occurrences of categorical variables over space. The other is related to optimal use of co-variation inherent to multiple regionalized variables as well as spatial correlation in spatial prediction. This paper extends geostatistics from the realm of kriging with uni-variate and continuous regionalized variables to the territory of indicator and multivariate kriging, where it is of ultimate importance to perform non-parametric estimation of probability distributions and spatial prediction based on co-regionalization and multiple data sources, respectively.
基金Supported by the National Social Science Foundation of China (Nos. 10ZD & M030)the Non-Profit Industry Financial Program of the Ministry of Land and Resources of China (No. 200811033)+1 种基金the Foundation of Philosophy and Social Sciences Research of Jiangsu Higher Education Institutions,China (No. 2010ZDAXM008)the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions,China
文摘Soil organic carbon (SOC) plays a key role in the global carbon cycle.In this study,we used statistical and geostatistical methods to characterize and compare the spatial heterogeneity of SOC in soils of Jiangsu Province,China,and investigate the factors that influence it,such as topography,soil type,and land use.Our study was based on 24 186 soil samples obtained from the surface soil layer (0-0.2 m) and covering the entire area of the province.Interpolated values of SOC density in the surface layer,obtained by kriging based on a spherical model,ranged between 3.25 and 32.43 kg m 3.The highest SOC densities tended to occur in the Taihu Plain,Lixia River Plain,along the Yangtze River,and in high-elevation hilly areas such as those in northern and southwest Jiangsu,while the lowest values were found in the coastal plain.Elevation,slope,soil type,and land use type significantly affected SOC densities.Steeper slope tended to result in SOC decline.Correlation between elevation and SOC densities was positive in the hill areas but negative in the low plain areas,probably due to the effect of different land cover types,temperature,and soil fertility.High SOC densities were usually found in limestone and paddy soils and low densities in coastal saline soils and alluvial soils,indicating that high clay and silt contents in the soils could lead to an increase,and high sand content to a decrease in the accumulation of SOC.SOC densities were sensitive to land use and usually increased in towns,woodland,paddy land,and shallow water areas,which were strongly affected by industrial and human activities,covered with highly productive vegetation,or subject to long-term use of organic fertilizers or flooding conditions.
