Département de biologie, Laboratoire d'Écologie Fonctionnelle, Université de Sherbrooke, Sherbrooke, Quebec, J1K 2R1, Canada.
Ecology. 2019 Jan;100(1):e02549. doi: 10.1002/ecy.2549.
We propose an operational definition of soil "fertility" that is applicable to plant community ecology and develop a method of measuring and quantifying it, using structural equations modeling, that is generalizable to soils in different regions whose fertility has different causes. To do this, we used structural equation modeling (SEM). The measurement submodel predicts the latent "generalized fertility," F , of a soil using four indicator variables: the relative growth rates of Festuca rubra, Trifolium pratense, Triticum aestivum, and Arabidopsis thaliana. The direct causes of F in this study were the supply rates of NO , P, and K as well as three indirect causes consisting of three physical soil properties, but these can change between studies. The model was calibrated using 76 grassland soils from southern Quebec, Canada and independently tested using aboveground net primary productivity (NPP) of the natural vegetation over two growing seasons. Both the measurement submodel and the full SEM fit the data well. The F values predicted 51% of the variance in NPP and were a better predictor than any other single variable, including the actual nutrient flux rates. Furthermore, this model can be applied to grassland soils anywhere because of its modular nature in which the causes and effects of soil fertility are clearly separated.
我们提出了一个适用于植物群落生态学的土壤“肥力”操作定义，并开发了一种使用结构方程模型来测量和量化它的方法，该方法适用于具有不同肥力成因的不同地区的土壤。为此，我们使用了结构方程模型（SEM）。测量子模型使用四个指示变量预测土壤的潜在“广义肥力”F：红羊茅、三叶草、普通小麦和拟南芥的相对生长率。在本研究中，F 的直接原因是 NO3-、P 和 K 的供应率以及由三个物理土壤特性组成的三个间接原因，但这些原因在不同的研究中可能会发生变化。该模型使用来自加拿大魁北克省南部的 76 个草原土壤进行校准，并在两个生长季节的自然植被地上净初级生产力（NPP）上进行了独立测试。测量子模型和完整的 SEM 都很好地拟合了数据。F 值预测了 NPP 的 51%方差，并且比任何其他单个变量（包括实际养分通量率）都更好地预测了 NPP。此外，由于该模型具有明确分离土壤肥力的原因和影响的模块化性质，因此可以应用于任何地方的草原土壤。
