Simulations and Analysis of Net Primary Productivity in Quercus liaotungensis Forest of Donglingshan Mountain Range in Response to Different Climate Change Scenarios

摘要

An ecosystem process model, BIOME-BGC, was used to explore the sensitivity of net primary productivity (NPP) of an oak (Quercus liaotungensis Koidz) forest ecosystem in Beijing area to global climate changes caused by increasing atmospheric CO_2 concentrations. Firstly we tested the model, and validated the modeled outputs using observational data; the outputs of BIOME-BGC model were consistent with observed soil water content and annual NPP. Secondly the potential impacts of climate change on the oak forest ecosystem were predicted with BIOME-BGC model. We found that the simulated NPP was much more sensitive to a 20% precipitation increase or a doubling of atmospheric CO_2 from 355 to 710 μmol/ mol than to a 2℃ temperature increase. Our results also indicated that the effects of elevated CO_2 and climate change on the response of NPP were not interactive.