National-scale 3D mapping of soil organic carbon in a Japanese forest considering microtopography and tephra deposition

Abstract Geographic information on soil organic carbon (SOC) is important for climate change research and understanding the global carbon cycle. At present, this information is limited for forest soils in mountainous regions that have complex topographies and are affected by tephra deposition. This study predicted the SOC concentration (OC), bulk density (BD), apparent rock coarse fraction (CF), and SOC stock (OCS) at 0–5, 5–15, and 15–30 cm in the soil horizon for the forested areas (ca. 230 000 km2) of Japan. This was carried out with a 10 m grid resolution using a digital soil mapping (DSM) approach. To determine the appropriate spatial prediction model, we evaluated the accuracy of a two dimensional approach for ordinary kriging (OK) and regression kriging (RK), and a three dimensional approach for random forest model (RF). The RF was based on topography, climate and vegetation factors (RFenv), distance and direction from 152 volcanos (RFenv+vol), distance from survey points (RFenv+sp); these factors were also combined (RFall) as explanatory attributes. The results demonstrated an improvement in the average root mean square errors (RMSEs) of RFenv+vol, RFenv+sp, and RFall by approximately 12%, 14%, 5%, and 21% for OC, BD, CF, and OCS using 10-fold cross-validation on a site-by-site basis, respectively, compared with OK. Based on the relatively small difference in improvement among RFenv+vol, RFenv+sp, and RFall (