Spatial Variation Of Soil Organic Carbon Of Croplands On The Loess Plateau

With the increasing concern of the ecological environmental problems, carbonrelated scientific questions have been becoming the research focus of scientists all overthe world. As the biggest carbon pool on the terrestrial ecosystem, soil carbon pool is amain research field for soil scientists. For an accurate estimation of soil carbon storage, itis critical to understand soil carbon spatial variation at a specific scale. The Loess Plateauof China is characterized for its diverse landforms induced by serious soil erosion. It is achallenging work to estimate soil carbon storage on the Loess Plateau, especially the soilcarbon storage in farmland with a mosaic distribution on the region. So far, mostresearches on soil carbon spatial variability were focused on field and small watershedscale on the Loess Plateau. Fresh work has been done on regional scale as well asdifferent scales. In this thesis soil carbon spatial variability at regional scale and countyscale on the Loess Plateau were studied using a geo-statistics method combined withGeographic Information System (GIS).The main content of the thesis include the spatialvariability of soil organic carbon and its influencing factors, a reasonable number ofsamples and differences of sampling methods about organic carbon, which may provide ascientific basis for the calculation model of organic carbon storage and accuratelyunderstanding the current situation of farmland soil organic matter and nutrient foragricultural departments. The main conclusions are as following:(1) Variability of soil organic carbon had scale effect in different scales and different landscape types on the Loess Plateau, and the scale effect was obviousabout the SOC and coefficient variation in Loess Hilly Region. The SOC in the Plainswas the highest, followed by Plateau Area and the Loess Hilly Region on regional scale,but the variation of SOC was in contrast. On the country scale, the highest of SOC was inthe Plains, followed by the Loess Hilly Region and Plateau Area, and the order ofvariation was the Plains, the Plateau Area and the Loess Hilly Region. Therepresentativeness of SOC in Zhuanglang county was relatively poor in the Loess HillyRegion, and the other two areas were representative. On the whole, the study areacorrelation distance shown that the greater area, greater distance. The SOC have showeda strongly spatial self-relativity either country scale or regional scale in the Loess HillyRegion; Randomness were strengthened with increased the area in the plains, whileshowed nugget effect in Plateau Area.(2) The rule about contribution of different factors to SOC variation on theLoess Plateau was as follows: Main influencing factors for SOC on regional scalewas complex and covered the country scale in the same landforms except the plains.On regional scale, soil erosion degree could explain29.7%of variability, soil type26.3%and altitude29.6%in the Loess Hilly Region; Cropping system could explain57.4%ofvariability, soil type15.3%and soil texture12.3%in the Plains; Soil texture couldexplain66.6%of variability, field surface slope16.7%and Aspect16.7%in Plateau Area.On the country scale, altitude could explain86.5%of variability, soil type13.5%in theLoess Hilly Region; Cropping system could explain51.2%of variability, altitude29.9%in the plains; No influencing factors was noted in Plateau Area.(3) The results indicated that main influencing factors for the SOC variationwere altitude and soil type in Zhuanglang county, and difference about SOCvariability was significant in different scales and different landscape types in LoessHilly Region. There are statistically significant differences in every increase of200melevation group. Dark loessial soils, red clay soils and Cultivated loessial soils had astatistically significant effect on SOC. The impact of natural factor on the variance ofSOC did not significantly change in high mountain region, and the others had obviousscale effect. With the narrowing of spatial scale, SOC variation effect of altitude and soiltype began to lessen. In gully region, all the factors were not significant between the complete geomorphic units and the town scale. In the hilly region, the main factors werethe altitude and the soil type in the complete geomorphic unit scale, but in town scalewas the slope gradient of field surface. In the high mountain region, the main controllingfactor was soil type in the geomorphic unit scale, but the town scale was the soil erosiondegree.(4) Classical statistics and Geostatistics were different in sampling. Thereasonable sampling number in combine unit stationing was less than the randomsmooth stationing. It showed fully representativeness among different sample sizesand the uncertainty of combine unit stationing was slightly larger than the randomsmooth stationing. Classical statistics showed reasonable sampling number was64inrandom smooth stationing and61in combine unit stationing, which expressed thesmaller difference. Based on the Geostatistics, we concluded that reasonable samplingnumber of SOC was respectively about903and454in random smooth stationing andcombine unit stationing, which had great difference. Consequently, both combine unitstationing and random smooth stationing can be applied when studied the overall trendand characteristics by classical statistics, and the combine unit stationing was best whenstudied precision distribution of nutrient by Geostatistics.