引用本文:陈洋,齐雁冰,王茵茵,张亮亮,刘姣姣,等.秦巴中部山区耕地土壤速效钾空间变异及其影响因素[J].环境科学研究,2017,30(2):257-266.
CHEN Yang,QI Yanbing,WANG Yinyin,ZHANG Liangliang,LIU Jiaojiao,et al.Spatial Variability and Factors Affecting Soil Available Potassium in the Central Qinling-Daba Mountain Area[J].Reserrch of Environmental Science,2017,30(2):257-266.]
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秦巴中部山区耕地土壤速效钾空间变异及其影响因素
陈 洋1, 齐雁冰1,2, 王茵茵1,3, 张亮亮1, 刘姣姣1
1.西北农林科技大学资源环境学院, 陕西 杨陵 712100 ;2.农业部西北植物营养与农业环境重点实验室, 陕西 杨凌 712100 ;3.中国科学院教育部水土保持与生态环境研究中心, 陕西 杨凌 712100
摘要:
为探究土壤速效钾空间异质性及其影响因素,以秦巴中部山区的碑坝镇、福成乡、白玉乡为研究区,基于104个耕层土壤采样点,运用经典统计学和地统计学方法揭示速效钾的空间变异特征,并利用相关分析、方差分析、冗余方差分解法研究不同因素对其空间变异的影响.结果表明:研究区土壤中w(速效钾)为55~156 mg/kg,平均值为125.99 mg/kg,表现出中等程度变异性(变异系数为14.07%).地统计分析显示,各理论模型中以高斯模型对w(速效钾)的拟合效果最佳,块金效应为16.95%,变程达1 454 m,具有强烈空间自相关性,其空间变异中结构变异占优、随机成分较少;速效钾呈地带性分布,自中部河谷低地向东西部山地丘陵呈增加趋势.定量分离结果表明,各类因子总体解释了48.67%的变异信息,土壤因子(土壤类型、土壤质地、成土母质、pH)、地形水文因子(海拔、坡度、地下水深度、地表产水量)、人为因素(施钾量、种植制度、耕层厚度、到村中心距离)的综合解释能力依次为35.39%、17.14%、9.96%;就单因子而言,施钾量、土壤类型、海拔、pH、土壤质地、成土母质的解释能力达35.35%、31.02%、28.39%、26.23%、21.96%、20.74%,并在P<0.001水平上表现出强烈显著性,是土壤速效钾变异的主要因素.
关键词:  空间变异  速效钾  影响因素  变量分解  秦巴中部山区
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基金项目:国家科技基础性工作专项(2014FY110200A08)
Spatial Variability and Factors Affecting Soil Available Potassium in the Central Qinling-Daba Mountain Area
CHEN Yang1, QI Yanbing1,2, WANG Yinyin1,3, ZHANG Liangliang1, LIU Jiaojiao1
1.College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China ;2.Key Laboratory of Plant Nutrition and the Agri-Environment in Northwest China, Ministry of Agriculture, Yangling 712100, China ;3.Research Center of Soil and Water Conservation and Ecological Environment, Chinese Academy of Sciences, Yangling 712100, China
Abstract:
Abstract: The soil available potassium in Beiba, Fucheng and Baiyu towns in the central Qinling-Daba Mountain area was measured, and its spatial variability and affecting factors were analyzed based on 104 samples with the geostatistical classical statistics methods, as well as the correlation analysis, analysis of variance and canonical redundancy analysis. The results showed that soil available potassium ranged from 55 to 156 mg/kg, with the average mean value of 125.99 mg/kg. The coefficient of variation was 14.07%, which suggested soil available potassium had moderate variability. Geostatistical analysis indicated that the soil available potassium had strong spatial autocorrelation, and the semi-variogram was best fitted by the Gaussian model. Soil available potassium showed significant anisotropy, with the nugget-to-sill ratio being 16.95%, and the spatial autocorrelation ranges was 1454 m. Soil available potassium in this area was mainly affected by structural factors, while the influence of random factors was weak. Soil available potassium showed zonal distribution with gradual increase from valley to hilly. Quantitative analysis of the relationship between soil available potassium and influencing factors showed that all factors could explain 48.67% of spatial variability in this nutrient, 35.39% of which was explained by soil related factors(e.g., soil type, soil parameter matter, soil texture and pH), 17.14% by topographical and hydrological factors(e.g., altitude, slope, depth of ground water and surface water yield), and 9.96% by human factors(potassium application amount rotation system, topsoil thickness and distance to village). In terms of single influencing factor, potassium application rate, soil type, soil texture and soil parameter matter were able to explain 35.35%, 31.02%, 28.39%, 26.23%, 21.96% and 20.74% of available potassium variability, respectively. The factors were significantly correlated with soil available potassium at P<0.001 level, which were the main factors affecting the spatial distribution of soil available potassium in the central region of Qinling-Daba Mountain area.
Key words:  spatial variability  soil available potassium  influencing factors  variance partitioning procedure