基于Geo-D的陕西省STN空间变异因子交互影响
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中央高校基本科研业务费专项资金项目(2452017108)和国家高技术研究发展计划(863计划)项目(2013AA102401-2)


Driving Factors and Interaction of STN Spatial Variation in Shaanxi Province Based on Geo-D
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    摘要:

    以陕西省为研究区,应用地理探测器模型,揭示了不同气候区域土壤全氮(STN)空间变异与自然、人文环境的内在联系。结果表明:陕西省STN表现出中等变异强度,平均含量为0.91g/kg。STN含量总体呈现南高北低的特性,秦巴区STN平均含量最高,为1.40g/kg;蒙中区最低,为0.37g/kg。整体上,STN含量变异受自然因素影响程度高于人文因素。其中,土壤有机质含量的单因子影响力最大(q为0.63~0.86),其次为县级行政区划(q为0.13~0.67)。其它因素中,陕西省市级行政区划、日照时长单因子影响力较大,q均达到0.50以上;秦巴区与蒙中区土壤亚类影响力最大(q为0.22~0.30);渭河区市级行政区划单因子影响程度最高(q为0.31);晋陕甘区与蒙东区影响力最大因子分别为化肥施用量(q为0.47)、有效磷含量(q为0.26)。各因子对STN含量变异存在交互作用,交互影响力较单因子有所提升,表现出互相增强或非线性增强效应。

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    The relationship between the spatial variation of soil total nitrogen (STN) and the natural and human environment in different climatic regions was revealed by using geographic detector model,a method of spatial counting to detect spatial variation and identify the driving factors, in Shaanxi Province. The results showed that the STN content was generally high in the south and low in the north, and presented a moderate intensity of variation in the 2020s, with an average content of 0.91g/kg. The average STN content in Qinba District was the highest (1.40g/kg), and the lowest (0.37g/kg) in Central Mongolia. On the whole, STN variation was more affected by natural factors than human factors, and influenced by the single factor of soil organic matter content (q value of 0.63~0.86) mainly, and secondly the county-level administrative divisions (q value of 0.13~0.67). Among other factors, the city-level administrative division and the duration of sunshine were more influential in Shaanxi Province, q-value both reached more than 0.50;in Qinba District and Central Mongolia District, the higher driving factor was the soil subtypes (q value of 0.22~0.30);the degree of influence of municipal administrative division was the highest (q value of 0.31) in Weihe District;the fertilizer application in Shanxi-Shaanxi-Gansu had the greatest influence (q value of 0.47);and the available phosphorus content (q value of 0.26) in the eastern Inner Mongolia was the higher driving factor on STN variation. The influence of factors was interactive on the variation of STN, the synergistic effect of the STN showed mutual enhancement or non-linear enhancement and the interaction of the two factors enhanced the influence of the single factor on STN.

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王琦,常庆瑞,黄勇,史博太,落莉莉.基于Geo-D的陕西省STN空间变异因子交互影响[J].农业机械学报,2021,52(11):161-169. WANG Qi, CHANG Qingrui, HUANG Yong, SHI Botai, LUO Lili. Driving Factors and Interaction of STN Spatial Variation in Shaanxi Province Based on Geo-D[J]. Transactions of the Chinese Society for Agricultural Machinery,2021,52(11):161-169.

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  • 收稿日期:2020-11-20
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  • 在线发布日期: 2021-11-10
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