陕西黄土区农田土壤主要养分特征及影响因素
收稿日期: 2023-06-06
修回日期: 2023-09-11
网络出版日期: 2023-12-18
基金资助
国家自然科学基金项目(41901034);国家自然科学基金项目(42001033);陕西省哲学社会科学研究专项(2022HZ1859)
Main nutrient characteristics and influencing factors of farmland soil in the Loess Plateau of the Shaanxi Province
Received date: 2023-06-06
Revised date: 2023-09-11
Online published: 2023-12-18
为了探究陕西黄土区农田主要土壤养分特征及其影响因素,基于研究区5096个农田0~20 cm耕层采样点数据,利用GIS与地统计学方法对有机质(SOM)、全氮(TN)、有效磷(AP)和速效钾(AK)含量进行空间分析,并应用地理探测器模型探究18种影响因素对养分空间变异的解释程度。结果表明:SOM、TN、AP和AK含量均值分别为14.43 g·kg-1、0.92 g·kg-1、18.21 mg·kg-1和190.28 mg·kg-1,呈现中等程度变异;4种养分最佳拟合模型均为指数模型,各养分呈现中等程度空间相关性,结构性与随机性因素的共同作用导致了养分含量的空间差异;养分全局空间相关性大小表现为:TN>SOM>AK>AP;养分含量区域差异明显,呈现由北向南逐渐递增的趋势;年日照时长、年均气温、化肥用量和地貌类型等单因子作用对各养分含量空间变异具有更强的解释力,两因子交互作用对养分的解释力强于其单因子解释力。研究表明,陕北地区宜适当增加肥料投入,关中地区宜进行精耕细作,农田建设应考虑多方面因素。
贺军奇 , 拜寒伟 , 徐轶玮 , 倪莉莉 . 陕西黄土区农田土壤主要养分特征及影响因素[J]. 干旱区研究, 2023 , 40(12) : 1907 -1917 . DOI: 10.13866/j.azr.2023.12.04
To explore the main soil nutrient characteristics and influencing factors of farmland in the Loess Plateau of Shaanxi, spatial analysis was conducted on the content of SOM, TN, AP, and AK using GIS and geostatistics methods based on the data from 5096 farmland sampling points with a depth of 0-20 cm in the study area. A geographic detector model was used to explore the degree to which 18 influencing factors explained the spatial variation of nutrients. The results showed that the average contents of SOM, TN, AP, and AK were 14.43 g·kg?1, 0.92 g·kg?1, 18.21 mg·kg?1, and 190.28 mg·kg?1, respectively, showing moderate variation. The four best-fit models for nutrients were all exponential models, with moderate spatial correlation among each nutrient. The combined effect of structural and random factors causes spatial differences in the nutrient content. The global spatial correlation of nutrients is TN > SOM > AK > AP. The regional differences in nutrient content are significant, indicating a gradually increasing trend from north to south. The single-factor effects of annual sunshine duration, annual average temperature, fertilizer use, and geomorphic type have stronger explanatory power for spatial variation in nutrient content but lesser than that of the interaction between the two factors. Research has shown that it is necessary to increase fertilizer input in the northern Shaanxi region, perform intensive cultivation in the Guanzhong region, and consider multiple factors in farmland construction.
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