Soil Organic Carbon Stock Prediction: Fate under 2050 Climate Scenarios, the Case of Eastern Ethiopia

Soil Organic carbon (SOC) is vital to the soil’s ecosystem functioning as well improving soil fertility. Slight variation in C has significant potential be either a source of CO2 atmosphere or sink stored form organic matter. However, modeling SOC spatiotemporal changes was challenging due lack data represent high spatial heterogeneity properties. Less expensive techniques, digital mapping (DSM) combined with space-for-time substitution (SFTS), were applied predict present and projected stock for temperature rainfall projections under different climate scenarios represented by four Representative Concentration Pathways (RCPs): RCP2.6, RCP4.5, RCP6, RCP8.5). The relationship between environmental covariates (n = 16) measured (148 samples) developed using random forest model. Then, temporal over baseline top 30 cm depth selected districts (Chiro Zuria, Kuni, Gemechis Mieso) West Hararghe Zone at m resolution. model validation sample 20% showed that explained 44% variance (R2) root mean square error (RMSE) 8.96, (ME) 0.16, Lin’s concordance correlation coefficient (CCC) 0.88. Temperature most important predictor factor influencing distribution stock. An overall net gain expected study area 2050. areas lower counterbalanced loss higher depended on land use cover (LULC), type, agro-ecological zones. By 2050, cropland supposed lose its all RCPs; therefore, appropriate decisions are crucial compensate C.