宁夏中宁枸杞林地粉壤土阳离子交换量空间分布预测方法对比  

Predicting spatial distribution of cation exchange capacity in silt loam soil under Lycium barbarum of Zhongning,Ningxia

作　　者：包维斌 白一茹[1,2] 杨帆 钟艳霞[1,2] 夏子书[1,2] 王幼奇[1,2] BAO Wei-bin;BAI Yi-ru;YANG Fan;ZHONG Yan-xia;XIA Zi-shu;WANG You-qi(College of Resources and Environment,Ningxia University,Yinchuan 750021,China;Arid Area Characteristic Resources and Environmental Governance Department of Education International Cooperation Joint Laboratory,Yinchuan 750021,China)

机构地区：[1]宁夏大学资源环境学院,银川750021 [2]旱区特色资源与环境治理教育部国际合作联合实验室,银川750021

出　　处：《生态学杂志》2020年第4期1377-1386,共10页Chinese Journal of Ecology

基　　金：国家自然科学基金项目(41867003和41761049);宁夏高等学校科研项目(NGY2017015);宁夏回族自治区科技重大专项(2018BFG02016);宁夏自然科学基金项目(2018AAC03027);宁夏青年科技人才托举工程项目;宁夏环境保护科学技术研究项目(2018-07)资助。

摘　　要：土壤阳离子交换量(CEC)是土壤施肥、改良的主要依据和土壤质量的评价指标,研究土壤CEC的空间分布及模型预测可为土壤养分监测、管理及精准农业实施提供科学依据。本研究以中宁枸杞林地粉壤土为对象,在自相关、交互相关等分析基础上,采用协同克里格(CoKriging)、普通最小二乘法(OLS)、地理加权回归(GWR)和随机森林(RF)模型对土壤CEC进行回归分析,比较了制图效果及模型预测精度。结果表明:中宁枸杞林地粉壤土CEC平均值为13.12 cmol·kg^-1,属中等肥力;土壤CEC的空间分布具有自相关性,并与土壤pH、有机质、黏粒和电导率在不同滞后距离上存在不同的空间相互关系;RF模型预测图避免了CoKriging、OLS和GWR模型预测图中土壤CEC图斑边界两侧破碎程度大、突变明显的缺陷,使土壤CEC在空间变化上表现为自然、平缓的过渡;RF模型RMSE值分别比CoKriging、OLS和GWR模型减少33.82%、20.55%和19.81%,R^2分别提高8.84%、51.92%和7.69%。RF模型考虑了样点空间位置,明显提高了插值精度且制图效果更加平缓。Soil cation exchange capacity(CEC)is the basis for soil fertilization and improvement,and thus an evaluation index of soil quality.Studies on the spatial heterogeneity of soil CEC can provide scientific basis for soil nutrient monitoring,management,and precision agriculture implementation.Spatial distribution of CEC in silt loam soil of Lycium barbarum in Zhongning was investigated based on the analysis of autocorrelation and interaction correlation.The CoCriging,ordinary least squares(OLS),geographically weighted regression Kriging(GWR)and Random Forest(RF)models were applied to perform regression analysis.After that,spatial interpolation mapping effect and the accuracy of the models were compared.The results showed that the average silt loam soil CEC in L.barbarum was 13.12 cmol·kg^-1,belonging to moderately fertility.The distribution of soil CEC had spatial autocorrelation.There were different spatial relationships among CEC,pH,soil organic matter,clay and electrical conductivity in different lag distances.The prediction map of RF model avoided the large fragmentation and obvious mutations which occurred on both sides of the CEC map boundary in the prediction maps of CoKriging,OLS and GWR models.Consequently,soil CEC appeared as a natural and gentle transition in the spatial variation map.The RMSE of the RF model was 33.82%,20.55%and 19.81%lower than that of Co Kriging,OLS and GWR models,and R^2 was increased by 8.84%,51.92%and7.69%,respectively.The RF model considered the location of sample space,and obviously improved the accuracy of interpolation,making the mapping more smooth.

关 键 词：阳离子交换量 协同克里格 普通最小二乘法 地理加权回归 随机森林 

分 类 号：S714[农业科学—林学]