引用本文:王萍萍,段英华,徐明岗,张水清,王小利.不同肥力潮土硝化潜势及其影响因素[J].土壤学报,2019,56(1):124-134.
WANG Pingping,DUAN Yinghua,XU Minggang,ZHANG Shuiqing,WANG Xiaoli.Nitrification Potential in Fluvo-aquic Soils Different in Fertility and its Influencing Factors[J].Acta Pedologica Sinica,2019,56(1):124-134
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不同肥力潮土硝化潜势及其影响因素
王萍萍,段英华,徐明岗,张水清,王小利
贵州大学;中国农业科学院农业资源与农业区划研究所,中国农业科学院农业资源与农业区划研究所,中国农业科学院农业资源与农业区划研究所,河南省农业科学院植物营养与资源环境研究所,贵州大学
摘要:
依托河南郑州潮土长期定位施肥试验,探索不同肥力土壤的硝化潜势(NP)及其主要影响因素。采集高肥力土壤(有机机肥配施)、中肥力土壤(化肥平衡施用)和低肥力土壤(不施肥或不施氮肥),分析土壤NP、全氮(TN)、铵态氮(NH4+-N)、硝态氮(NO3--N)、微生物生物量碳(MBC)和微生物生物量氮(MBN),并通过逐步回归、路径分析和方差分解分析(VDA)等统计分析方法,明确不同肥力潮土NP的主要影响因素,量化各主效应因子对NP的贡献率。结果表明:潮土NP为0.3~1.1 mg•kg-1•h-1,在不同肥力梯度土壤中差异显著(P<0.05),其中高肥力较中肥力平均提高7.9%;中肥力较低肥力平均提高162.5%。在各项土壤指标中,MBC、NO3--N、TN、MBN是土壤NP变化的主要影响因素,其中,MBC、NO3--N和MBN与NP为直接效应,TN与NP为间接效应大于直接效应,微生物生物量碳、氮(MBC和MBN)、NO3--N和TN对NP变异的贡献率分别为24.3%、18.9%和13.7%,而4个主效应因子交互作用对硝化潜势变异的贡献率达52.8%,各变量及其交互作用对硝化潜势变异的总贡献率达92.9%。可见,高肥力土壤上硝化作用较强,铵态氮很容易被硝化成为硝态氮,硝态氮累积和淋洗的可能性较大,应通过改善水肥条件适当降低其土壤硝化强度,进而达到构建氮素养分库和减少氮素损失的目的。
关键词:  土壤肥力  微生物生物量  全氮  硝化作用
DOI:10.11766/trxb201804080533
分类号:
基金项目:国家重点研发计划项目(2016YFD0200301)、国家重点基础研究发展规划(973)项目(2015CB150505)和国家自然科学基金项目(41471247)
Nitrification Potential in Fluvo-aquic Soils Different in Fertility and its Influencing Factors
wangpingping,duanyinghua,xuminggang,zhangshuiqing and wangxiaoli
Guizhou University; Institut of Agricultural Resources and Regional Planning of CAAS,Institut of Agricultural Resources and Regional Planning of CAAS,Institut of Agricultural Resources and Regional Planning of CAAS,Institute of Plant Nutrition and Environmental Resources Science, Henan Academy of Agricultural Sciences,Guizhou University
Abstract:
【Objective】soil nitrification potential (NP) and its main influencing factors in fluvo-aquic soils were studied based on a long-term fluvo-aquic soil fertilization experiment in Zhengzhou, Henan Province. 【Method】Three tracts of farmlands of fluvo-aquic soil different in fertility level, i.e. High (applied with chemical fertility plus organic manure); Moderate ( applied with balanced chemical fertilizers); and Low (applied with no fertilizer or no N fertilizer), were selected for soil sampling for analysis of total N (TN), ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3--N), microbial biomass C (MBC) and microbial biomass N (MBN). And stepwise regression analysis, path analysis and variance decomposition analysis (VDA) were performed to define main influencing factors in fluvo-aquic soil relative to soil fertility and quantify contribution of each factor to NP. 【Result】Results show that NP in the fluvo-aquic soils varied in the range of 0.3 mg•kg-1•h-1~1.1 mg•kg-1•h-1, and differed significantly between the soils. It was 7.9% higher in the soil high in fertility than in the soil moderate in fertility, and 162.5% higher in the soil moderate in fertility than in the soil low in fertility. Among all the soil fertility indices, MBC, NO3--N, TN and MBN were found to be the main influencing factors of soil NP. MBC, NO3--N and MBN affected NP directly, while TN did more indirectly. The contribution rate of microbial biomass (MBC and MBN), NO3--N and TN to NP variation is worked out to be 24.3%, 18.9% and 13.7%, respectively. The contribution of four main influencing factors’ interaction effects to the variation of soil nitrification potential has reached to 52.8%, while the total contribution of each variant and its interaction effects amounted to 92.9%. Therefore, it can be concluded that nitrification is much stronger in soils of high fertility than in soils low and moderate in fertility. 【Conclusion】As result of strong nitrification, ammonium nitrogen is nitrified into nitrate nitrogen, which is readily accumulated and/or leached. It is, therefore, essential to regulate soil water and nutrient regimes to a proper level so as to reduce soil nitrification intensity and eventually achieve the target of constructing a nitrogen nutrient pool and reducing nitrogen loss in fluvo-aquic soils.
Key words:  Soil fertility  Microbial biomass  Total N  Nitrification