Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264003, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.
Environ Sci Pollut Res Int. 2018 Jan;25(1):52-63. doi: 10.1007/s11356-016-7882-8. Epub 2016 Oct 31.
Mapping the spatial distribution of available copper (A-Cu) in orchard soils is important in agriculture and environmental management. However, data on the distribution of A-Cu in orchard soils is usually highly variable and severely skewed due to the continuous input of fungicides. In this study, ordinary kriging combined with planting duration (OK_PD) is proposed as a method for improving the interpolation of soil A-Cu. Four normal distribution transformation methods, namely, the Box-Cox, Johnson, rank order, and normal score methods, were utilized prior to interpolation. A total of 317 soil samples were collected in the orchards of the Northeast Jiaodong Peninsula. Moreover, 1472 orchards were investigated to obtain a map of planting duration using Voronoi tessellations. The soil A-Cu content ranged from 0.09 to 106.05 with a mean of 18.10 mg kg, reflecting the high availability of Cu in the soils. Soil A-Cu concentrations exhibited a moderate spatial dependency and increased significantly with increasing planting duration. All the normal transformation methods successfully decreased the skewness and kurtosis of the soil A-Cu and the associated residuals, and also computed more robust variograms. OK_PD could generate better spatial prediction accuracy than ordinary kriging (OK) for all transformation methods tested, and it also provided a more detailed map of soil A-Cu. Normal score transformation produced satisfactory accuracy and showed an advantage in ameliorating smoothing effect derived from the interpolation methods. Thus, normal score transformation prior to kriging combined with planting duration (NSOK_PD) is recommended for the interpolation of soil A-Cu in this area.
在农业和环境管理中，绘制果园土壤中可利用铜（A-Cu）的空间分布图谱非常重要。然而，由于杀菌剂的持续投入，果园土壤中 A-Cu 的分布数据通常高度可变且严重偏态。在本研究中，提出了普通克里金法结合种植年限（OK_PD）作为改进土壤 A-Cu 插值的方法。在插值之前，利用了四种正态分布转换方法，即 Box-Cox、Johnson、秩次和正态得分方法。共采集了 317 个果园土壤样本，利用 Voronoi 图对 1472 个果园进行了种植年限的调查，获得了一张种植年限图。土壤 A-Cu 含量范围为 0.09-106.05，平均值为 18.10mgkg，反映了土壤中 Cu 的高生物有效性。土壤 A-Cu 浓度具有中等空间依赖性，且随种植年限的增加而显著增加。所有正态转换方法均成功降低了土壤 A-Cu 的偏度和峰度以及相关残差，并计算出更稳健的变差函数。对于所有测试的转换方法，OK_PD 都可以比普通克里金（OK）生成更好的空间预测精度，并且可以提供更详细的土壤 A-Cu 图。正态得分转换在改善插值方法带来的平滑效应方面表现出优势，因此在该地区，建议在克里金结合种植年限（NSOK_PD）之前进行正态得分转换，以用于土壤 A-Cu 的插值。
