A general model for the seasonal to decadal dynamics of leaf area

Seasonal changes in leaf display, indicated by variations in leaf area index (LAI), play a crucial role in influencing the exchange of CO₂ and energy between terrestrial ecosystems and the atmosphere. Accurate simulation of leaf phenology is essential for both land surface models (LSMs) and dynamic global vegetation models (DGVMs). But there is no agreement on how leaf phenology should be modelled. A common approach invokes specific physiological triggers for budburst and senescence, but the domain of application of such models is restricted to specific plant types and/or climatic zones. Recent theoretical advances suggest the existence of a more general relationship between gross primary production (GPP) and the seasonal variation of ‘steady-state LAI’ (i.e., the LAI that would be supported if environmental conditions were held constant). The dynamics of LAI can then be predicted from the time course of potential GPP, given their interdependence through Beer's law and the necessity for GPP to support LAI development. We have developed a model based on this principle in two steps. First, the principle was implemented using the P model, a universal first-principles light use efficiency (LUE) model for GPP. Second, we used a simple moving average method to represent the time lag between leaf allocation and steady-state LAI. The model requires a prediction of annual peak LAI, which we simulate based on the energy and water requirements of GPP. The model captures satellite-derived LAI dynamics across biomes at both site and global levels, except for some remaining problems in arid biomes. The model outperforms 15 DGVMs participating in the TRENDY project. This study thus provides a prognostic vegetation leaf phenology model that can be used to forecast the seasonal dynamics of LAI under climate change in LSMs and DGVMs.