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以江西省2012年测土配方施肥项目采集的16 582个耕地表层(0~20 cm)土壤样点数据,运用普通克里格和回归分析方法,对江西省土壤碳氮比(C/N)空间变异特征及其影响因素进行分析.结果表明江西省土壤C/N在2.98~52.67之间,平均值为11.72,变异系数为25.17%,呈中等变异性.经半方差分析,土壤C/N的块金效应为88.44%,其空间变异受结构性和随机性因素共同影响,但随机性因素的影响更大.土壤C/N空间分布较为平滑,高值区主要分布在九江市彭泽县、萍乡市上栗县和抚州市乐安县.地形因子、耕地利用方式、成土母质、土壤类型和氮肥施用量对土壤C/N空间变异影响均显著(P<0.05),但影响程度不一.地形因子可解释0.3%的土壤C/N空间变异,耕地利用方式的独立解释能力为1.4%,成土母质的独立解释能力为2.4%,土类、亚类和土属的独立解释能力分别为2.7%、3.6%、5.5%.氮肥施用量对土壤C/N空间变异的独立解释能力最高,为33.4%,是引起江西省土壤C/N空间变异最主要的因素.
Based on the soil sample data of 16 582 cultivated land (0 ~ 20 cm) collected by Jiangxi Province Soil Testing and Fertilization Project in 2012, the soil carbon and nitrogen ratio (C / N) in Jiangxi Province was calculated using ordinary Kriging and regression analysis. Spatial variability and its influencing factors were analyzed.The results showed that soil C / N was between 2.98 and 52.67 in Jiangxi Province, with an average of 11.72 and a coefficient of variation of 25.17%, showing a medium variability.The soil C / N , The bulk gold effect is 88.44%, and its spatial variation is affected by both structural and random factors, but it is more influenced by random factors. The spatial distribution of soil C / N is relatively smooth, and the high values are mainly distributed in Pengze County, Jiujiang , Shangli County of Pingxiang City and Le’an County of Fuzhou City.The topographical factors, the ways of arable land utilization, parent materials, soil types and nitrogen application rates had significant effects on spatial variability of soil C / N (P <0.05), but with different degrees of influence. The topographic factors can explain 0.3% of soil C / N spatial variability, the independent interpretation ability of cultivated land use pattern is 1.4%, the independent interpretation ability of soil parent material is 2.4%, the independent interpretation ability of soil, sub-category and soil are 2.7%, 3.6%, 5.5%. Spatial variability of soil C / N with different N rates Independent highest explanatory power, was 33.4%, which is caused by soil Jiangxi C / N spatial variability of the most important factors.