Detecting Climate-Driven Increases in Interannual Net Primary Productivity of Forest Ecosystems

Under Paris Agreement, carbon sink at the national level has been reported to the international community. There are various attempts to improve the accuracy of reporting on the national carbon sink. Especially, IPCC has discussed the necessity of reports distinguished by artificial and natural factors’ effects on the carbon sink based on the Interannual variability (IAV) (IPCC, 2019). However, there are no clear methods to identify the effect of artificial factors. The forest, which has a high density of vegetation, is important as the place that absorbs carbon. The accelerated photosynthesis process of forests by climate change can lead to changes in vegetation productivity and carbon sink. Forest net primary productivity is representative of carbon sink in vegetation which retains the amount of carbon based on aboveground biomass.

The main purpose of this study is to suggest a method to extract climate-driven changes in the carbon sink of forest ecosystems in order to increase the accuracy of carbon sink reported to the international community. The suggested method is composed of three steps: 1) This study estimated annual forest net primary productivity change due to climate change using the Carnegie-Ames-Stanford Approach (CASA) model. 2) The variability of FPAR and temperature affected by climate change was extracted through the Empirical mode decomposition (EMD) algorithm, which decomposes a time-series signal. Then, this value was applied to the CASA model to estimate the change in the net primary production of forest ecosystems. 3) The forest productivity due to the climate effect was derived by comparing the above two results.

This assessment approach is expected to understand the variability of forest carbon sink and to support the decision-making of the greenhouse gas reduction report system by assessing climate-driven changes in forest net primary productivity.