The study of the critical zones(CZs) of the Earth link the composition and function of aboveground vegetation with the characteristics of the rock layers, providing a new way to study how the unique rock and soil cond...The study of the critical zones(CZs) of the Earth link the composition and function of aboveground vegetation with the characteristics of the rock layers, providing a new way to study how the unique rock and soil conditions in karst regions affect the aboveground vegetation. Based on survey results of the rocks, soils and vegetation in the dolomite and limestone distribution areas in the karst area of central Guizhou, it was found that woody plant cover increases linearly with the number of cracks with a width of more than 1 mm, while the cover of herbaceous plants shows the opposite trend(p<0.01). The dolomite distribution area is characterized by undeveloped crevices, and the thickness of the soil layer is generally less than 20 cm, which is suitable for the distribution of herbaceous plants with shallow roots. Due to the development of crevices in the limestone distribution area, the soil is deeply distributed through the crevices for the deep roots of trees, which leads to a diversified species composition and a complicated structure in the aboveground vegetation. Based on moderate resolution imaging spectroradiometer(MODIS) remote sensing data from 2001 to 2010, the normalized differentiated vegetation index(NDVI) and annual net primary productivity(NPP) results for each phase of a 16-day interval further indicate that the NDVI of the limestone distribution area is significantly higher than that in the dolomite distribution area, but the average annual NPP is the opposite. The results of this paper indicate that in karst CZs, the lithology determines the structure and distribution of the soil, which further determines the cover of woody and herbaceous plants in the aboveground vegetation. Although the amount of soil in the limestone area may be less than that in the dolomite area, the developed crevice structure is more suitable for the growth of trees with deep roots, and the vegetation activity is strong. At present, the treatment of rocky desertification in karst regions needs to fully consider the rock-s展开更多
Development of a quantitative understanding of soil organic carbon （SOC） dynamics is vital for management of soil to sequester carbon （C） and maintain fertility, thereby contributing to food security and climate c...Development of a quantitative understanding of soil organic carbon （SOC） dynamics is vital for management of soil to sequester carbon （C） and maintain fertility, thereby contributing to food security and climate change mitigation. There are well-established process-based models that can be used to simulate SOC stock evolution; however, there are few plant residue C input values and those that exist represent a limited range of environments. This limitation in a fundamental model component （i.e., C input） constrains the reliability of current SOC stock simulations. This study aimed to estimate crop-specific and environment-specific plant-derived soil C input values for agricultural sites in France based on data from 700 sites selected from a recently established French soil monitoring network （the RMQS database）. Measured SOC stock values from this large scale soil database were used to constrain an inverse RothC modelling approach to derive estimated C input values consistent with the stocks. This approach allowed us to estimate significant crop-specific C input values （P 〈 0.05） for 14 out of 17 crop types in the range from 1.84 =h 0.69 t C ha-1 year-1 （silage corn） to 5.15 =k 0.12 t C ha-1 year-1 （grassland/pasture）. Furthermore, the incorporation of climate variables improved the predictions. C input of 4 crop types could be predicted as a function of temperature and 8 as a function of precipitation. This study offered an approach to meet the urgent need for crop-specific and environment-specific C input values in order to improve the reliability of SOC stock prediction.展开更多
基金supported by National Natural Science Foundation of China (Grant Nos. 41571130044 & 41325002)111 Plan (B14001)Peking University Undergraduate Talents Training Program
文摘The study of the critical zones(CZs) of the Earth link the composition and function of aboveground vegetation with the characteristics of the rock layers, providing a new way to study how the unique rock and soil conditions in karst regions affect the aboveground vegetation. Based on survey results of the rocks, soils and vegetation in the dolomite and limestone distribution areas in the karst area of central Guizhou, it was found that woody plant cover increases linearly with the number of cracks with a width of more than 1 mm, while the cover of herbaceous plants shows the opposite trend(p<0.01). The dolomite distribution area is characterized by undeveloped crevices, and the thickness of the soil layer is generally less than 20 cm, which is suitable for the distribution of herbaceous plants with shallow roots. Due to the development of crevices in the limestone distribution area, the soil is deeply distributed through the crevices for the deep roots of trees, which leads to a diversified species composition and a complicated structure in the aboveground vegetation. Based on moderate resolution imaging spectroradiometer(MODIS) remote sensing data from 2001 to 2010, the normalized differentiated vegetation index(NDVI) and annual net primary productivity(NPP) results for each phase of a 16-day interval further indicate that the NDVI of the limestone distribution area is significantly higher than that in the dolomite distribution area, but the average annual NPP is the opposite. The results of this paper indicate that in karst CZs, the lithology determines the structure and distribution of the soil, which further determines the cover of woody and herbaceous plants in the aboveground vegetation. Although the amount of soil in the limestone area may be less than that in the dolomite area, the developed crevice structure is more suitable for the growth of trees with deep roots, and the vegetation activity is strong. At present, the treatment of rocky desertification in karst regions needs to fully consider the rock-s
基金Supported by the Soil Scientific Interest Group (GIS Sol) of Francefinanced by the "Groupement d'Intrêt Scientifique Sol". Jeroen Meersmans' postdoctoral position was funded by the French Environment and Energy Management Agency (ADEME)funded by the EU projects "Greenhouse gas management in European land use systems (GHG-Europe)" (FP7-ENV-2009-1-244122) and "CARBO-Extreme" (FP7-ENV-2008-1-226701)
文摘Development of a quantitative understanding of soil organic carbon （SOC） dynamics is vital for management of soil to sequester carbon （C） and maintain fertility, thereby contributing to food security and climate change mitigation. There are well-established process-based models that can be used to simulate SOC stock evolution; however, there are few plant residue C input values and those that exist represent a limited range of environments. This limitation in a fundamental model component （i.e., C input） constrains the reliability of current SOC stock simulations. This study aimed to estimate crop-specific and environment-specific plant-derived soil C input values for agricultural sites in France based on data from 700 sites selected from a recently established French soil monitoring network （the RMQS database）. Measured SOC stock values from this large scale soil database were used to constrain an inverse RothC modelling approach to derive estimated C input values consistent with the stocks. This approach allowed us to estimate significant crop-specific C input values （P 〈 0.05） for 14 out of 17 crop types in the range from 1.84 =h 0.69 t C ha-1 year-1 （silage corn） to 5.15 =k 0.12 t C ha-1 year-1 （grassland/pasture）. Furthermore, the incorporation of climate variables improved the predictions. C input of 4 crop types could be predicted as a function of temperature and 8 as a function of precipitation. This study offered an approach to meet the urgent need for crop-specific and environment-specific C input values in order to improve the reliability of SOC stock prediction.
