Estimating Net Primary Productivity under Climate Change by Application of Global Forest Model (G4M)

Sung, S., Forsell, N., Kindermann, G. ORCID:, & Lee, D.K. (2016). Estimating Net Primary Productivity under Climate Change by Application of Global Forest Model (G4M). Journal of the Korean Society People, Plants, and Environment 19 (6) 549-558. 10.11628/ksppe.2016.19.6.549.

Estimating Net Primary Productivity under Climate Change by Global Forest Model.pdf - Published Version
Available under License Creative Commons Attribution.

Download (4MB) | Preview


Net primary productivity (NPP) is considered as an important indicator for forest ecosystem since the role of the forest is highlighted as a key sector for mitigating climate change. The objective of this research is to estimate changes on the net primary productivity of forest in South Korea under the different climate change scenarios. The G4M (Global Forest Model) was used to estimate current NPP and future NPP trends in different climate scenarios. As input data, we used detailed (1 km × 1 km) downscaled monthly precipitation and average temperature from Korea Meteorological Administration (KMA) for four RCP (Representative Concentration Pathway) scenarios (2.6/4.5/6.0/8.5). We used MODerate resolution Imaging Spectroradiometer (MODIS) NPP data for the model validation. Current NPP derived from G4M showed similar patterns with MODIS NPP data. Total NPP of forest increased in most of RCP scenarios except RCP 8.5 scenario because the average temperature increased by 5°C. In addition, the standard deviation of annual precipitation was the highest in RCP8.5 scenario. Precipitation change in wider range could cause water stress on vegetation that affects decrease of forest productivity. We calculated future NPP change in different climate change scenarios to estimate carbon sequestration in forest ecosystem. If there was no biome changes in the future NPP will be decreased up to 90%. On the other hand, if proper biome change will be conducted, future NPP will be increased 50% according to scenarios.

Item Type: Article
Uncontrolled Keywords: climate change adaptation, forest biome change, forest carbon sequestration, forest ecosystem productivity, Representative Concentration Pathway (RCP) scenarios
Research Programs: Ecosystems Services and Management (ESM)
Depositing User: Luke Kirwan
Date Deposited: 01 Feb 2017 07:39
Last Modified: 27 Aug 2021 17:28

Actions (login required)

View Item View Item

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313