Compositional analysis of plant nutrients and soil P pools

目前的模型使用限于单一形式的成分数据，例如植物和土壤分析，忽视了组件必须在封闭的信息空间内相互作用的事实。由于在一个封闭的系统中，一个成分的任何变化都必须伴随着其他成分的变化，因此系统的组织模式可能会被虚假的相关性所破坏。成分分析考虑了单纯形内各组件之间的所有可能的相互作用。成分数据分析已经成功地应用于许多科学领域，最近还被应用于许多作物的营养诊断和解释土壤中的磷转化。作为偏离目标成分的一种衡量标准，马氏距离被发现是将营养不平衡的玉米植株检测为“异常值”。另一方面，土壤、作物残体和有机产品的磷分级程序允许区分不稳定的和不稳定的磷库。利用扰动向量、单纯度量和马氏距离等形式，可以通过成分分析来模拟不稳定和非不稳定池塘中的P对驱动变量(时间、轮作、土壤保持措施、添加的P)的响应。土壤磷缓冲能力是一项重要的土壤功能，它可以防止土壤中可溶性磷的流失，并控制向根系的磷供应，这一功能可以与简单度量或马氏距离有关。Mehlich-III磷饱和度是土壤磷缓冲能力的可靠指标。Mehlich-III指数与活性磷库和非活性磷库之间的关系可以支持目前矿物土壤和有机土壤的环境阈值。我们的主要目标是建立土壤-植物系统中作物养分和土壤磷的组成模型。在这个项目中，我们将把成分马哈拉诺比斯的概念应用到魁北克和巴西的十种作物上。此外，我们将对土壤、有机投入和作物残体中的磷进行分级，并使用成分分析和土壤磷缓冲能力的指标来分析磷的组分。从长远来看，我们将根据土壤和植物的组成模式对其进行分类，以响应驱动变量。

Present models using compositional data constrained to a simplex such as plant and soil analyses disregard the fact that components must interact within a closed information space. Since any change in one constituent must be accompanied by a change in other constituents by resonance in a closed system, system patterns of organization may be spoiled by spurious correlations. Compositional analysis takes into account all possible interactions among components within a simplex. Compositional data analysis has been successfully applied in many scientific fields and, more recently, for nutrient diagnosis of many crop species and interpreting phosphorus transformations in soils. As a measure of deviation from targeted composition, the Mahalanobis distance was found to detect nutritionally imbalanced corn plants as 'outliers'. On the other hand, the phosphorus fractionation procedures for soils, crop residues, and organic products allow distinguishing between labile and non labile P pools. The P in labile and non labile pools in response to a driving variable (time, crop rotation, soil conservation practice, added P) can be modelled by compositional analysis using formalisms such as the perturbation vector, the simplicial metric, and the Mahalanobis distance. Soil P buffering capacity that protects the soil against soluble P loss and controls the P supply to roots is an important soil function that can be related to either the simplicial metric or the Mahalanobis distance. The Mehlich-III P saturation ratio proved to be a reliable indicator of soil P buffering capacity. The relationships between Mehlich-III indexes and labile and non labile pools of P could support the present environmental thresholds for both mineral and organic soils. Our main objective is to develop compositional models for crop nutrients and soil P in soil-plant systems. In this project, we will apply the compositional-Mahalanobis concept to ten crops in Quebec and Brazil. In addition, we will fractionate the P in soils, organic inputs, and crop residues and analyze P fractions using compositional analysis as well as indexes of soil P buffering capacity. On the long run, we will classify soils and plants according to their compositional patterns in response to driving variables.