Modeling the seasonal dynamics of leaf area index based on environmental constraints to canopy development

Leaf area index (LAI) is an important variable for understanding land-surface atmosphere flux dynamics and a key biophysical variable included in terrestrial biosphere models. Because of its influence on resource cycling and atmospheric feedbacks it is necessary to have a model that can accurately predict the seasonal progression of canopy development. The goal of this study is to use a simple function to modify a prognostic phenology model, based on the influence of environmental factors on limiting foliar phenology, into a model capable of predicting the seasonal course of LAI. Model performance was assessed by comparison to a time-series of LAI measurements derived from gap fraction theory at five deciduous sites selected from the FLUXNET database. The model was assessed in terms of its ability to predict the magnitude of LAI as well as phenological transition dates. The results show a strong correlation between predicted LAI and gap fraction derived estimates (r = 0.94, RMSE = 0.45). The accuracy of the model varied among sites at predicting transition dates but remained consistently high at predicting the continuous seasonal progression of LAI. Our results demonstrate that a simple prognostic phenology model can be rescaled to predict the seasonal course of LAI in deciduous forests.