Lunan stone forest is a kind of typical karst in China, which is mainly developed under red soil. In the winter of 1999, three study sites were chosen in stone forest national park according to veget...Lunan stone forest is a kind of typical karst in China, which is mainly developed under red soil. In the winter of 1999, three study sites were chosen in stone forest national park according to vegetation cover, geomorphologic location and soil types. CO 2 concentration was measured with Gastec pump at different depths of soil (20, 40, 60 cm) and at the same time soil samples were gathered and soil properties such as soil moisture, pH, soil organic content were analyzed and the total number of viable microbes were counted in laboratory. In the study, dependent variable was chosen as the mean soil log (PCO 2 ), and soil properties were chosen as the independent variables. Multiple stepwise regression analysis showed that the total amount of microbes and soil moisture are the best indicators of the CO 2 production, with the equation LOG(PCO 2 ) = - 0.039(TNM) - 0.056(Mo) + 1.215 accounting for 86% of the variation of the soil CO 2 concentration, where TNM is the total number of microbes in the soil and Mo is the moisture of soil sample.展开更多
基金National Natural Science Foundation of China No.40071017+2 种基金 No.90202017 The Shilin Research Foundation of China No.199903
文摘Lunan stone forest is a kind of typical karst in China, which is mainly developed under red soil. In the winter of 1999, three study sites were chosen in stone forest national park according to vegetation cover, geomorphologic location and soil types. CO 2 concentration was measured with Gastec pump at different depths of soil (20, 40, 60 cm) and at the same time soil samples were gathered and soil properties such as soil moisture, pH, soil organic content were analyzed and the total number of viable microbes were counted in laboratory. In the study, dependent variable was chosen as the mean soil log (PCO 2 ), and soil properties were chosen as the independent variables. Multiple stepwise regression analysis showed that the total amount of microbes and soil moisture are the best indicators of the CO 2 production, with the equation LOG(PCO 2 ) = - 0.039(TNM) - 0.056(Mo) + 1.215 accounting for 86% of the variation of the soil CO 2 concentration, where TNM is the total number of microbes in the soil and Mo is the moisture of soil sample.
