Soil organic matter （SOM） plays an important role in maintaining vegetation cover and thus mitigating land erosion of fragile terrestrial ecosystems such as in the Northern Ordos Plateau of China （NOPC）. However, ...Soil organic matter （SOM） plays an important role in maintaining vegetation cover and thus mitigating land erosion of fragile terrestrial ecosystems such as in the Northern Ordos Plateau of China （NOPC）. However, little information is available on whether and how SOM varies spatially as an intrinsic characteristic of landform in NOPC. The objective of this study was to examine the spatial associations of SOM with landform and vegetation cover. The study was conducted in a 23,000-km2 area within NOPC because this area has landforms of mobile dunes （MD）, flat dunes （FD）, grassy sandy land （GSL）, flat sandy bedrocks （FSB）, and swamps and salt lakes （SW）, which are typical landforms in semiarid ecosystems. SOM was determined using a standard laboratory analysis method for 5 cm topsoil samples collected at 72 locations across the study area. In addition, the 250 m Multitem- poral Moderate Resolution Imaging Spectroradiometer （MODIS） imageries taken in the period from August 2006 to August 2010 were used to extract Normalized Difference Vegetation Index （NDVI） which in turn was used as the surrogate of vegetation cover. Classic and geostatistical methods were used to compare SOM concentration across different landforms. The results indicated that an area with a greater value for NDVI （i.e. better vegetation cover） tended to have a higher SOM concentration regardless of the landform types. However, the association between SOM and NDVI varied from one landform to another. The SW and GSL had a highest SOM concentration, while MD had a lowest concentration. For the study area as a whole and the FD, GSL, and MD, SOM was found to be the sole function of NDVI, whereas, for the FSB, SOM was influenced by several intrinsic variables, namely ground surface altitude, slope, and aspect, as well as NDVI. SOM for the SW landform was found to be a function of NDVI. Furthermore, SOM and NDVI exhibited a consistent spatial pattern of increasing from north to south and from west to east. The highest SOM concentration of 3.5% occurred along an east-westward belt, which is adjacent to water pathways, in the mid part of the study area.展开更多
Landform classification is commonly done using topographic altitude only. However practice indicates that locations at a same altitude may have distinctly different landforms, depending on characteristics of soils und...Landform classification is commonly done using topographic altitude only. However practice indicates that locations at a same altitude may have distinctly different landforms, depending on characteristics of soils underneath those locations. The objectives of this study were to： 1） develop a landform classification approach that is based on both altitude and soil characteristic; and 2） use this approach to determine landforms within a watershed located in northern Ordos Plateau of China. Using data collected at 134 out of 200 sampling sites, this study determined that D10 （the diameter of soil particles 10% finer by weight） and long-term average soil moisture acquired in 2010, which can be estimated at reasonable accuracy from remote sensing imagery, can be used to represent soil characteristics of the study watershed. Also, the sampling data revealed that this watershed consists of nine classes of landforms, namely mobile dune （MD）, mobile semi-mobile dune （SMD）, rolling fixed semi-fixed dune （RFD）, flat sandy land （FD）, grassy sandy land （GS）, bedrock （BR）, flat sandy bedrock （FSB）, valley agricultural land （VA）, and swamp and salt lake （SW）. A set of logistic regression equations were derived using data collected at the 134 sampling sites and verified using data at the remaining 66 sites. The verification indicated that these equations have moderate classification accuracy （Kappa coefficients K 〉 43%）. The results revealed that the dominant classes in the study watershed are FD （36.3%）, BR （27.0%）, and MD （23.5%）, while the other six types of landforms （i.e., SMD, RFD, GS, FSB, VA, and SW） in combination account for 13.2%. Further, the landforms determined in this study were compared with the classes presented by a geologically-based classification map. The comparison indicated that the geologically-based classification could not identify multiple landforms within a class that are dependent upon soil characteristics.展开更多
基金supported by the National Natural Science Foundation of China(51139002 and 51069005)the Inner Mongolia Agricultural University Innovation Team Building Program (NDTD 2010-6)+1 种基金the Inner Mongolia Scientific and Technology Bureau (20090516)the Chinese Ministry of Science and Technology (2010DFA71460)
文摘Soil organic matter （SOM） plays an important role in maintaining vegetation cover and thus mitigating land erosion of fragile terrestrial ecosystems such as in the Northern Ordos Plateau of China （NOPC）. However, little information is available on whether and how SOM varies spatially as an intrinsic characteristic of landform in NOPC. The objective of this study was to examine the spatial associations of SOM with landform and vegetation cover. The study was conducted in a 23,000-km2 area within NOPC because this area has landforms of mobile dunes （MD）, flat dunes （FD）, grassy sandy land （GSL）, flat sandy bedrocks （FSB）, and swamps and salt lakes （SW）, which are typical landforms in semiarid ecosystems. SOM was determined using a standard laboratory analysis method for 5 cm topsoil samples collected at 72 locations across the study area. In addition, the 250 m Multitem- poral Moderate Resolution Imaging Spectroradiometer （MODIS） imageries taken in the period from August 2006 to August 2010 were used to extract Normalized Difference Vegetation Index （NDVI） which in turn was used as the surrogate of vegetation cover. Classic and geostatistical methods were used to compare SOM concentration across different landforms. The results indicated that an area with a greater value for NDVI （i.e. better vegetation cover） tended to have a higher SOM concentration regardless of the landform types. However, the association between SOM and NDVI varied from one landform to another. The SW and GSL had a highest SOM concentration, while MD had a lowest concentration. For the study area as a whole and the FD, GSL, and MD, SOM was found to be the sole function of NDVI, whereas, for the FSB, SOM was influenced by several intrinsic variables, namely ground surface altitude, slope, and aspect, as well as NDVI. SOM for the SW landform was found to be a function of NDVI. Furthermore, SOM and NDVI exhibited a consistent spatial pattern of increasing from north to south and from west to east. The highest SOM concentration of 3.5% occurred along an east-westward belt, which is adjacent to water pathways, in the mid part of the study area.
基金Foundation： National Natural Science Foundation of China, No.51139002 No.51069005+1 种基金 Inner Mongolia Agricultural University Innovation Team Building Program Cold-Arid Region Water Resources Utilization, No.NDTD2010-6 Inner Mongolia Scientific and Technology Bureau, No.20090516, Project of the Ministry of Science and Technology of China, No.2010DFA71460
文摘Landform classification is commonly done using topographic altitude only. However practice indicates that locations at a same altitude may have distinctly different landforms, depending on characteristics of soils underneath those locations. The objectives of this study were to： 1） develop a landform classification approach that is based on both altitude and soil characteristic; and 2） use this approach to determine landforms within a watershed located in northern Ordos Plateau of China. Using data collected at 134 out of 200 sampling sites, this study determined that D10 （the diameter of soil particles 10% finer by weight） and long-term average soil moisture acquired in 2010, which can be estimated at reasonable accuracy from remote sensing imagery, can be used to represent soil characteristics of the study watershed. Also, the sampling data revealed that this watershed consists of nine classes of landforms, namely mobile dune （MD）, mobile semi-mobile dune （SMD）, rolling fixed semi-fixed dune （RFD）, flat sandy land （FD）, grassy sandy land （GS）, bedrock （BR）, flat sandy bedrock （FSB）, valley agricultural land （VA）, and swamp and salt lake （SW）. A set of logistic regression equations were derived using data collected at the 134 sampling sites and verified using data at the remaining 66 sites. The verification indicated that these equations have moderate classification accuracy （Kappa coefficients K 〉 43%）. The results revealed that the dominant classes in the study watershed are FD （36.3%）, BR （27.0%）, and MD （23.5%）, while the other six types of landforms （i.e., SMD, RFD, GS, FSB, VA, and SW） in combination account for 13.2%. Further, the landforms determined in this study were compared with the classes presented by a geologically-based classification map. The comparison indicated that the geologically-based classification could not identify multiple landforms within a class that are dependent upon soil characteristics.
