A method for scaling vegetation dynamics: The ecosystem demography model (ED)

The problem of scale has been a critical impediment to incorporating import ant fine-scale processes into global ecosystem models. Our knowledge of fin e-scale physiological and ecological processes comes from a variety of meas urements, ranging from forest plot inventories to remote sensing, made at s patial resolutions considerably smaller than the large scale at which globa l ecosystem models are defined. In this paper, we describe a new individual -based, terrestrial biosphere model, which we label the ecosystem demograph y model (ED). We then introduce a general method for scaling stochastic ind ividual-based models of ecosystem dynamics (gap models) such as ED to large scales. The method accounts for the fine-scale spatial heterogeneity withi n an ecosystem caused by stochastic disturbance events, operating at scales down to individual canopy-tree-sized gaps. By conditioning appropriately o n the occurrence of these events, we derive a size-and agc-structured (SAS) approximation for the first moment of the stochastic ecosystem model. With this approximation, it is possible to, make predictions about the large sc ales of interest from a description of the fine-scale physiological and pop ulation-dynamic processes without simulating the fate of every plant indivi dually. We use the SAS approximation to implement our individual-based bios phere model over South America from 15 degrees N to 15 degrees S, showing t hat the SAS equations are accurate across a range of environmental conditio ns and resulting ecosystem types. We then compare the predictions of the bi osphere model to regional data and to intensive data at specific sites. Ana lysis of the model at these sites illustrates the importance of fine-scale heterogeneity in governing large-scale ecosystem function, showing how popu lation and community-level processes influence ecosystem composition and st ructure, patterns of aboveground carbon accumulation, and net ecosystem pro duction.