Relation between Soil Order and Sorptive Capacity for Dissolved Organic Carbon

Soil Science Society of America Journal(2012)

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摘要
Soils have historically been considered a temporary sink for organic C, but deeper soils may serve as longer term C sinks due to the sorption of dissolved organic C (DOC) onto Fe- and clay-rich mineral soil particles. This project provides an improved understanding and predictive capability of the physical and chemical properties of deep soils that control their sorptive capacities for DOC. Two hundred thirteen subsurface soil samples (72 series from five orders) were selected from the eastern and central United States. A characterized natural DOC source was added to the soils, and the Langmuir sorption equation was fitted to the observed data by adjusting the maximum DOC sorption capacity (Q{sub max}) and the binding coefficient (k). Different isotherm shapes were observed for Ultisols, Alfisols, and Mollisols due to statistically significant differences in the magnitude of k, while Q{sub max} was statistically invariant among these three orders. Linear regressions were performed on the entire database and as a function of soil order to correlate Langmuir fitted parameters with measured soil properties, e.g., pH, clay content, total organic C (TOC), and total Fe oxide content. Together, textural clay and Fe oxide content accounted for 35% of the variation in Q{sub max}more » in the database, and clay was most important for Alfisols and Ultisols. The TOC content, however, accounted for 27% of the variation in Q{sub max} in Mollisols. Soil pH accounted for 45% of the variation in k for the entire database, 41% for Mollisols, and 22% for Alfisols. Our findings demonstrate that correlations between Langmuir parameters and soil properties are different for different soil orders and that k is a more sensitive parameter for DOC sorption than is Q{sub max} for temperate soils from the central and eastern United States.« less
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关键词
chemical properties,dissolved organic carbon,soil ph,statistical significance,linear regression
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