Soil respiration (SR) Wis one of the largest contributors of terrestrial CO_2 to the atmosphere.Environmental as well as physicochemical parameters influence SR and thus, different land use practices impact the emissi...Soil respiration (SR) Wis one of the largest contributors of terrestrial CO_2 to the atmosphere.Environmental as well as physicochemical parameters influence SR and thus, different land use practices impact the emissions of soil CO_2. In this study, we measured SR, bi-monthly, over a one-year period in a terrace tea plantation, a forest tea plantation and a secondary forest, in a subtropical mountain area in Xishuangbanna, China. Along with the measurement of SR rates, soil characteristics for each of the land use systems were investigated. Soil respiration rates in the different land use systems did not differ significantly during the dry season, ranging from2.7±0.2 μmol m^(-2) s^(-1) to 2.8±0.2 μmol m^(-2) s^(-1). During the wet season, however, SR rates were significantly larger in the terrace tea plantation(5.4±0.5 μmol m^(-2)s^(-1)) and secondary forest(4.9±0.4 μmol m^(-2)s^(-1)) than in the forest tea plantation(3.7±0.2 μmol m^(-2) s^(-1)).This resulted in significantly larger annual soil CO_2 emissions from the terrace tea and secondary forest,than from the forest tea plantation. It is likely that these differences in the SR rates are due to the 0.5times lower soil organic carbon concentrations in thetop mineral soil in the forest tea plantation, compared to the terrace tea plantation and secondary forest.Furthermore, we suggest that the lower sensitivity to temperature variation in the forest tea soil is a result of the lower soil organic carbon concentrations. The higher SR rates in the terrace tea plantation were partly due to weeding events, which caused CO_2 emission peaks that contributed almost 10% to the annual CO_2 flux. Our findings suggest that moving away from heavily managed tea plantations towards low-input forest tea can reduce the soil CO_2 emissions from these systems. However, our study is a casestudy and further investigations and upscaling are necessary to show if these findings hold true at a landscape level.展开更多
Soil organic carbon(SOC) is an important component of farming systems and global carbon cycle. Accurately estimating SOC stock is of great importance for assessing soil productivity and modeling global climate change....Soil organic carbon(SOC) is an important component of farming systems and global carbon cycle. Accurately estimating SOC stock is of great importance for assessing soil productivity and modeling global climate change. A newly built 1:50 000 soil database of Zhejiang Province containing 2 154 geo-referenced soil profiles and a pedological professional knowledge-based(PKB) method were used to estimate SOC stock up to a depth of 100 cm for the Province. The spatial patterns of SOC stocks stratified by soil types,watershed(buffer analysis), topographical factors, and land use types were identified. Results showed that the soils in Zhejiang covered an area of 100 740 km2 with a total SOC stock of 831.49 × 106 t and a mean SOC density of 8.25 kg m-2, excluding water and urban areas. In terms of soil types, red soils had the highest SOC stock(259.10 × 106t), whereas mountain meadow soils contained the lowest(0.15 × 106t). In terms of SOC densities, the lowest value(5.11 kg m-2) was found in skel soils, whereas the highest value(45.30 kg m-2) was observed in mountain meadow soils. Yellow soils, as a dominant soil group, determined the SOC densities of different buffer zones in Qiantang River watershed because of their large area percentage and wide variation of SOC density values.The area percentages of various soil groups significantly varied with increasing elevation or slope when overlaid with digital elevation model data, thus influencing the SOC densities. The highest SOC density was observed under grassland, whereas the lowest SOC density was identified under unutilized land. The map of SOC density(0–100 cm depth) and the spatial patterns of SOC stocks in the Province would be helpful for relevant agencies and communities in Zhejiang Province, China.展开更多
基金financially supported by the Yunnan Department of Sciences and Technology of China (Grant No. 2012EB056)Further support was supplied by the CGIAR Research Program 6: Forests, Trees and Agroforestry
文摘Soil respiration (SR) Wis one of the largest contributors of terrestrial CO_2 to the atmosphere.Environmental as well as physicochemical parameters influence SR and thus, different land use practices impact the emissions of soil CO_2. In this study, we measured SR, bi-monthly, over a one-year period in a terrace tea plantation, a forest tea plantation and a secondary forest, in a subtropical mountain area in Xishuangbanna, China. Along with the measurement of SR rates, soil characteristics for each of the land use systems were investigated. Soil respiration rates in the different land use systems did not differ significantly during the dry season, ranging from2.7±0.2 μmol m^(-2) s^(-1) to 2.8±0.2 μmol m^(-2) s^(-1). During the wet season, however, SR rates were significantly larger in the terrace tea plantation(5.4±0.5 μmol m^(-2)s^(-1)) and secondary forest(4.9±0.4 μmol m^(-2)s^(-1)) than in the forest tea plantation(3.7±0.2 μmol m^(-2) s^(-1)).This resulted in significantly larger annual soil CO_2 emissions from the terrace tea and secondary forest,than from the forest tea plantation. It is likely that these differences in the SR rates are due to the 0.5times lower soil organic carbon concentrations in thetop mineral soil in the forest tea plantation, compared to the terrace tea plantation and secondary forest.Furthermore, we suggest that the lower sensitivity to temperature variation in the forest tea soil is a result of the lower soil organic carbon concentrations. The higher SR rates in the terrace tea plantation were partly due to weeding events, which caused CO_2 emission peaks that contributed almost 10% to the annual CO_2 flux. Our findings suggest that moving away from heavily managed tea plantations towards low-input forest tea can reduce the soil CO_2 emissions from these systems. However, our study is a casestudy and further investigations and upscaling are necessary to show if these findings hold true at a landscape level.
基金supported by the National Natural Science Foundation of China(No.30771253)the Key Project of Science Technology Department of Zhejiang Province,China(No.2006C22026)
文摘Soil organic carbon(SOC) is an important component of farming systems and global carbon cycle. Accurately estimating SOC stock is of great importance for assessing soil productivity and modeling global climate change. A newly built 1:50 000 soil database of Zhejiang Province containing 2 154 geo-referenced soil profiles and a pedological professional knowledge-based(PKB) method were used to estimate SOC stock up to a depth of 100 cm for the Province. The spatial patterns of SOC stocks stratified by soil types,watershed(buffer analysis), topographical factors, and land use types were identified. Results showed that the soils in Zhejiang covered an area of 100 740 km2 with a total SOC stock of 831.49 × 106 t and a mean SOC density of 8.25 kg m-2, excluding water and urban areas. In terms of soil types, red soils had the highest SOC stock(259.10 × 106t), whereas mountain meadow soils contained the lowest(0.15 × 106t). In terms of SOC densities, the lowest value(5.11 kg m-2) was found in skel soils, whereas the highest value(45.30 kg m-2) was observed in mountain meadow soils. Yellow soils, as a dominant soil group, determined the SOC densities of different buffer zones in Qiantang River watershed because of their large area percentage and wide variation of SOC density values.The area percentages of various soil groups significantly varied with increasing elevation or slope when overlaid with digital elevation model data, thus influencing the SOC densities. The highest SOC density was observed under grassland, whereas the lowest SOC density was identified under unutilized land. The map of SOC density(0–100 cm depth) and the spatial patterns of SOC stocks in the Province would be helpful for relevant agencies and communities in Zhejiang Province, China.
