Evaluating Spatial-Temporal Dynamics of Net Primary Productivity of Different Forest Types in Northeastern China Based on Improved FORCCHN

An improved individual-based forest ecosystem carbon budget model for China (FORCCHN) was applied to investigate the spatial-temporal dynamics of net primary productivity of different forest types in northeastern China. In this study, the forests of northeastern China were categorized into four ecological types according to their habitats and generic characteristics (evergreen broadleaf forest, deciduous broadleaf forest, evergreen needleleaf forest and deciduous needleleaf forest). The results showed that distribution and change of forest NPP in northeastern China were related to the different forest types. From 1981 to 2002, among the forest types in northeastern China, per unit area NPP and total NPP of deciduous broadleaf forest were the highest, with the values of 729.4 gC/(m(2)•yr) and 106.0 TgC/yr, respectively, followed by mixed broadleaf- needleleaf forest, deciduous needleleaf forest and evergreen needleleaf forest. From 1981 to 2002, per unit area NPP and total NPP of different forest types in northeastern China exhibited significant trends of interannual increase, and rapid increase was found between the 1980s and 1990s. The contribution of the different forest type’s NPP to total NPP in northeastern China was clearly different. The greatest was deciduous broadleaf forest, followed by mixed broadleaf- needleleaf forest and deciduous needleleaf forest. The smallest was evergreen needleleaf forest. Spatial difference in NPP between different forest types was remarkable. High NPP values of deciduous needleleaf forest, mixed broadleaf- needleleaf forest and deciduous broadleaf forest were found in the Daxing’anling region, the southeastern of Xiaoxing’anling and Jilin province, and the Changbai Mountain, respectively. However, no regional differences were found for evergreen needleleaf NPP. This study provided not only an estimation NPP of different forest types in northeastern China but also a useful methodology for estimating forest carbon storage at regional and global levels.