Biome-BGC is a biogeochemical and ecophysiological model that uses general stand information and daily meteorological data to simulate energy, carbon, water and nitrogen cycling. Biome-BGC emphasizes leaf area index (LAI) as a key structural attribute with substantial control on ecosystem processes. Numerous studies have shown that gross primary production (GPP) and net primary production (NPP) are positively correlated to LAI because it controls the amount of incident radiation absorbed and converted into photosynthate. Therefore, there is a sound physiological basis for LAI being an important ecosystem attribute. Moreover, LAI can be remotely sensed and used as a spatial input in Biome-BGC to conduct regional to global C simulations (Ahl et al. 2004, 2005, Bond-Lamberty et al. 2007).

Respiration components such as heterotrophic, autotrophic growth and autotrophic maintenance are treated separately and governed by temperature and water limitations. NPP is partitioned into biomass compartments following dynamic allocation patterns that reflect N limitations.


The strong linkage between the water cycle and forest carbon cycles in Biome-BGC is a strong advantage of this model for examining the long-term effects of biomass removal on soil organic matter and N dynamics.