Monitoring and Modeling of Large-Scale Pattern of Forest Height and Biomass based on the Metabolic Scaling Theory and Water-Energy Balance Equation

Abstract:

This study applies the metabolic scaling theory (MST) and water-energy balance equation (PM: Penman-Monteith) to monitor and model the large-scale pattern of forest height and biomass. The WBE and PM theories grant a generalized mechanistic understanding of relationships between the forest structure and multiple geospatial predictors including topography and climatic variables. We successfully expanded the average trend and predictions of the MST and PM by including eco-regional and plant functional type variations. Our model now accounts for plant interaction, self-competition and disturbance effects to alleviate known limitations of the MST. The topographic heterogeneity and climate seasonality are additionally incorporated in the model predictions. A simple and clear mechanistic understanding in the model is promising for prognostic applications in contrast to conventional black-box approaches. This study provides baseline maps (circa 2005; 1-km² grids) of the maximum forest canopy heights and aboveground biomass over the continental USA. Their future projections are also delivered using various climate scenarios. The NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) dataset is used in this task.