Calculating net primary productivity of forest ecosystem with G4M model: case study on South Korea

Abstract:

Net primary productivity (NPP) is considered as an important indicator for forest ecosystem since the role of forest is highlighted as a stepping stone for mitigating climate change. Especially rapidly urbanizing countries which have high carbon dioxide emission have large interest in calculating forest NPP under climate change. Also maximizing carbon sequestration in forest sector has became a global goal to minimize the impacts of climate change. Therefore, the objective of this research is estimating carbon stock change under the different climate change scenarios by using G4M (Global Forestry Model) model in South Korea. We analyzed four climate change scenarios in different Representative Concentration Pathway (RCP). In this study we used higher resolution data (1kmx1km) to produce precise estimation on NPP from regionalized four climate change scenarios in G4M model. Finally, we set up other environmental variables for G4M such as water holding capacity, soil type and elevation. As a result of this study, temperature showed significant trend during 2011 to 2100. Average annual temperature increased more than 5℃ in RCP 8.5 scenario while 1℃ increased in RCP 2.6 scenario. Each standard deviation of the annual average temperature showed similar trend. Average annual precipitation showed similarity within four scenarios. However the standard deviation of average annual precipitation is higher in RCP8.5 scenario which indicates the ranges of precipitation is wider in RCP8.5 scenario. These results present that climate indicators such as temperature and precipitation have uncertainties in climate change scenarios. NPP has changed from 5-13tC/ha/year in RCP2.6 scenario to 9-21 tC/ha/year in RCP8.5 scenario in 2100. In addition the spatial distribution of NPP presented different trend among the scenarios. In conclusion we calculated differences in temperature and precipitation and NPP change in different climate change scenarios. This study can be applied for maximizing carbon seqestration of vegetation.