Global distribution pattern in characteristics of gross primary productivity response to soil water availability

作者：Shanning Bao, Nuno Carvalhais, Jian Xu, J.M. Chen, Yang Lei, Gegen Tana, Changgui Lin, Jiancheng Shi · 发表于：Agricultural and Forest Meteorology · 年份：2025 · DOI：10.1016/j.agrformet.2025.110701 · 被引用次数：2 · 研究领域：Plant Water Relations and Carbon Dynamics、Environmental and Agricultural Sciences、Hydrology and Watershed Management Studies

Understanding how carbon assimilation rates respond to water availability is crucial for diagnosing global carbon and water cycles. This study aims to investigate characteristics and drivers of gross primary productivity (GPP) responses to soil water availability using three parameters from a light-use-efficiency (LUE) model: W I , k W and α W , representing the inflection point, slope and lag effect of GPP response to soil water availability changes, respectively. We followed a hybrid modeling approach coupling an artificial neural network with the LUE model to derive model parameters and examine intricate relationships between these parameters and features characterizing climate, vegetation, nutrient deposition, soil properties and elevation across 196 eddy covariance sites. Relationships between the LUE model parameters and observed ecosystem properties were analyzed using partial dependence plots and Shapley additive explanation dependence plots. Our results revealed significant statistical differences in parameters across plant functional types. Specifically, forests exhibited lower inflection points, responding more steeply and immediately to water availability changes, contrasting with smoother and lagged responses from open shrubs. Vegetation seasonality, represented by variability of enhanced vegetation index (EVI) and seasonal EVI, was the most influential noncategorical factor, followed by soil properties. Notably, the relationships were predominantly nonlinear. Ad...