The characterisation of the spatial and temporal distribution of the root system in a cultivated field depends on the soil volume occupied by the root systems (the scatter), and the local intensity of the root colonisation in the field (the intensity). We introduce a multivariate generalised linear mixed model for simultaneously describing the scatter and the intensity using data obtained with minirhizotrons (i.e., tubes with observation windows, which are inserted in the soil, enabling to observe the roots directly). The models presented allow studying intricate spatial and temporal dependence patterns using a graphical model to represent the dependence structure of latent random components. The scatter is described by a binomial mixed model (presence of roots in observation windows). The number of roots crossing the reference lines in the observational windows of the minirhizotron is used to estimate the intensity through a specially defined Poisson mixed model. We explore the fact that it is possible to construct multivariate extensions of generalised linear mixed models that allow to simultaneously represent patterns of dependency of the scatter and the intensity along with time and space. We present an example where the intensity and scatter are simultaneously determined at three different time points. A positive association between the intensity and scatter at each time point was found, suggesting that the plants are not compensating a reduced occupation of the soil by increasing the number of roots per volume of soil. Using the general properties of graphical models, we identify a first-order Markovian dependence pattern between successively observed scatters and intensities. This lack of memory indicates that no long-lasting temporal causal effects are affecting the roots' development. The two dependence patterns described above cannot be detected with univariate models.
翻译:种植场根系统的空间和时间分布特性取决于根系统( 散落) 所占用的土壤数量( 散落), 以及野外根结结结结的当地强度( 强度) 。 我们采用了多变的常规线性混合模型, 用于同时描述散落量和强度, 使用以微型顺差体获得的数据( 即带有观测窗口的管子, 插入土壤, 能够直接观察根) 。 模型显示的是, 使用图形模型来研究复杂的空间和时间依赖模式, 以代表潜在随机组成部分的依附性结构。 散落由一种二元混合模型描述( 观察窗口中根的直径直线性趋势) 。 我们采用了一种多变的直线性模型, 通过一个特别定义的Poisson 混合模型来估计其强度 。 我们发现, 普通的线性混合模型可以同时代表散分布的依附时间和空间的依附性模式。 我们展示了一个示例是, 在三个不同时间点上同时确定强度和分散性模型的强度和分散性, 显示的是, 测量的土壤的直径直径的根部之间的直径和直径 。