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Predicting soil N mineralization: Relevance of organic matter fractions and soil properties

机译:预测土壤氮矿化度:有机物含量与土壤性质的相关性

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Distinct extractable organic matter (EOM) fractions have been used to assess the capacity of soils to supply nitrogen (N). However, substantial uncertainty exists on their role in the N cycle and their functional dependency on soil properties. We therefore examined the variation in mineralizable N and its relationship with EOM fractions, soil physical and chemical properties across 98 agricultural soils with contrasting inherent properties and management histories. Mineralizable N was determined by aerobic incubation at 20 degrees C and optimum moisture content for 20 weeks. We used multivariate statistical modelling to account for multi-collinearity, an issue generally overlooked in studies evaluating the predictive value of EOM fractions. Mineralization of N was primarily related to the size of OM pools and fractions present; they explained 78% of the variation in mineralizable N whereas other soil variables could explain maximally 8%. Both total and extractable OM expressed the same soil characteristic from a mineralization perspective; they were positively related to mineralizable N and explained a similar percentage of the variation in mineralizable N. Inclusion of mineralizable N in fertilizer recommendation systems should be based on at least one OM variable. The most appropriate EOM fraction can only be identified when the underlying mechanisms are known; regression techniques are not suitable for this purpose. Combination of single EOM fractions is not likely to improve the prediction of mineralizable N due to high multi-collinearity. Inclusion of texture-related soil variables or variables reflecting soil organic matter quality may be neglected due to their limited power to improve the prediction of mineralizable N
机译:不同的可萃取有机物(EOM)馏分已用于评估土壤提供氮(N)的能力。但是,它们在氮循环中的作用及其对土壤特性的功能依赖性存在很大的不确定性。因此,我们研究了98种农业土壤中可矿化氮的变化及其与EOM分数,土壤理化性质的关系,并对比了固有性质和管理历史。可矿化的氮是通过在20摄氏度和最佳水分含量下进行20周的有氧培养确定的。我们使用多元统计模型来解释多重共线性,这在评估EOM分数的预测价值的研究中通常被忽略。氮的矿化主要与OM池的大小和存在的馏分有关。他们解释了可矿化氮变化的78%,而其他土壤变量最多解释了8%。从矿化的角度来看,总有机质和可萃取有机质都表现出相同的土壤特性。它们与可矿化氮成正相关,并解释了可矿化氮变化的相似百分比。在肥料推荐系统中包括可矿化氮应至少基于一个OM变量。仅当已知基本机制时,才能确定最合适的EOM分数;回归技术不适合此目的。由于高多重共线性,单个EOM馏分的组合不太可能改善可矿化N的预测。可能会忽略与纹理相关的土壤变量或反映土壤有机质质量的变量,因为它们在改进可矿化氮预测方面的能力有限

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