16:15 〜 16:30
[ACG39-10] Effects of soil properties in estimating soil respiration and methane absorption
キーワード：土壌呼吸、メタン吸収、土壌特性、炭素14、機械学習
Soil exchanges greenhouse gases (GHGs) such as CO2 and CH4 with near-surface atmosphere, and these exchanges are one of the essential components of soil CO2 and CH4 cycles. In general, forest soils act as a CO2 source via emission through soil respiration and CH4 sink via absorption by the soil. Various efforts have been made to observe soil CO2/CH4 fluxes, analyze their mechanisms, and upscale them. However, due to insufficient observation and understanding, significant uncertainties remain in their spatio-temporal variations and their underlying mechanisms. For example, various efforts on upscaling soil respiration have been conducted using machine-learning models or semi-empirical models, and further improvements were expected by denser observation networks and/or adding parameters relating to soil characteristics.
In this study, we analyzed the effects of observed soil properties on explaining spatio-temporal variations in observed soil respiration and CH4 absorption. With the largest soil respiration observation network across Asia developed and maintained by National Institute for Environmental Studies (NIES) and several observed soil properties such as 14C, organic matter properties, and mineral properties by Japan Atomic Energy Agency (JAEA), we estimated soil respiration and methane absorption across Japan based on random forest regression. Adding 14C data to the explanatory variables for CO2 estimation improved the accuracy of the estimation compared to the model based on meteorological data only. Mineral properties data were important for CH4 estimation, and the importance of mineral properties data as explanatory variables was greater than those of soil meteorological data such as temperature and soil moisture. We revealed that soil properties, in addition to meteorological data, are essential for estimating soil CO2/CH4 fluxes.
In this study, we analyzed the effects of observed soil properties on explaining spatio-temporal variations in observed soil respiration and CH4 absorption. With the largest soil respiration observation network across Asia developed and maintained by National Institute for Environmental Studies (NIES) and several observed soil properties such as 14C, organic matter properties, and mineral properties by Japan Atomic Energy Agency (JAEA), we estimated soil respiration and methane absorption across Japan based on random forest regression. Adding 14C data to the explanatory variables for CO2 estimation improved the accuracy of the estimation compared to the model based on meteorological data only. Mineral properties data were important for CH4 estimation, and the importance of mineral properties data as explanatory variables was greater than those of soil meteorological data such as temperature and soil moisture. We revealed that soil properties, in addition to meteorological data, are essential for estimating soil CO2/CH4 fluxes.