Modeling forest carbon and nitrogen cycles based on long term carbon stock field measurement in the Delaware River Basin

Abstract:

Process-based models are a powerful approach to test our understanding of biogeochemical processes, to extrapolate ground survey data from limited plots to the landscape scale and to simulate the effects of climate change, nitrogen deposition, elevated atmospheric CO₂, increasing natural disturbances and land use change on ecological processes. However, in most studies, the models are calibrated using ground measurements from only a few sites, though they may be extrapolated to much larger areas. Estimation accuracy can be improved if the models are parameterized using long-term carbon stock data from multiple sites representative of the simulated region. In this study, vegetation biomass and soil carbon stocks, and changes in these stocks over a recent decade, were measured in 61 forested plots located in three small watersheds in the Delaware River Basin (DRB). On average, total vegetation biomass was 160.2 Mg C ha^-1 and the soil carbon stock was 76.6 Mg C ha^-1, measured during 2012-2014. The biomass carbon stock increased by 2.45 Mg C ha^-1 yr^-1 from 2001-2003 to 2012-2014. This dataset was subsequently used to parameterize the PnET-CN model at the individual plot basis, and averaged parameters among plots were then applied to generate new watershed-scale model parameters for each of the three watersheds. The parameterized model was further validated by the field measurements in each of the major forest types. The spatial distribution of forest carbon pools and fluxes in three watersheds were mapped based on the simulation results from the newly parameterized PnET-CN model. The model will also be run under different scenarios to test the effects of climate change, altered atmospheric composition, land use change, and their interactions within the three watersheds and across the whole DRB.