Updated data-driven estimation of soil respiration in Japan; Development and intercomparison

日本における土壌呼吸のモデル推定; 開発と相互比較

山貫 緋称*; 市井 和仁*; 山本 雄平*; 小槻 峻司*; 寺本 宗正*; Sun, L.*; 永野 博彦*; 平野 高司*; 高木 健太郎*; 石田 祐宣*; 高木 正博*; 安立 美奈子*; 近藤 俊明*; 小嵐 淳   ; 安藤 麻里子  ; 高橋 善幸*; Liang, N.*

Yamanuki, Hina*; Ichii, Kazuhito*; Yamamoto, Yuhei*; Kotsuki, Shunji*; Teramoto, Munemasa*; Sun, L.*; Nagano, Hirohiko*; Hirano, Takashi*; Takagi, Kentaro*; Ishida, Sachinobu*; Takagi, Masahiro*; Adachi, Minaco*; Kondo, Toshiaki*; Koarashi, Jun; Atarashi-Andoh, Mariko; Takahashi, Yoshiyuki*; Liang, N.*

Soil respiration (SR) is one of the most essential components of soil carbon cycles. However, large uncertainties remain in its temporal and spatial variations. In this study, we updated our data-driven estimation of SR across Japan with observation data (eight sites across Japan), remote sensing data (MODIS land products), and random forest regression. We used soil temperature and moisture by a process-based model, the Simple Biosphere model including Urban Canopy (SiBUC). Our estimation shows a reasonable performance with R=0.70 for the best model. Based on the established model, we estimated SR across Japan with a spatial resolution of 4 km from 2006 to 2018. Intercomparison of our estimation with other available datasets was also conducted to confirm consistent observation approach is important to upscale SR.