Prediction of the productivity of cedar plantation in Japan under changing climate

The prediction of the productivity of tree plantation in changing climate is becoming important in capturing the flow of material and energy in terrestrial ecosystems, along with the expansion of planted forest worldwide. The ecosystem model is a useful tool for this purpose and its parameterization is the key step for the better prediction. For modeling and predicting the productivity of Japanese cedar (Cryptomeria japonica) which is most common planted tree species in Japan, we parameterized Biome-BGC using the plant-trait database of Japanese cedar and the Bayesian optimization scheme with flux data (gross primary production and ecosystem respiration) of two sites in warm and cool temperate regions in Japan. The climate change scenarios for RCP2.6 and RCP8.5 of MIROC5 and MRI-CGCM3, downscaled into a resolution of 1-km, were used. In general, the results suggested that the warming climate decreased net primary production (NPP) in summer in the western part of Japan, and the increase in NPP in winter compensated for it in most cases. The sensitivity of changed parameters and the uncertainty of the model are also discussed.