Climate change effect on soil carbon stock in different land use types in eastern Rajasthan, India

Global change in climate might have potential effect on both SOC stock and carbon sequestration capacity in soil. Predicting soil carbon stock in future climate scenarios is crucial for implementation of adaptation methods to mitigate influence of climate change. In the current study, multiple linear regression analysis was performed to determine relationship between climatic variables and soil carbon stock under land use types. To project the impact of climate change on SOC stock, we applied CarboSOIL model. Baseline and future climate data are acquired using spatial analyst tool in ArcGIS. Three global circulation models of fifth phase of the coupled model intercomparison project driven by four representative concentration pathway scenarios were selected for projecting future climate data. Time periods selected were baseline (1970–2000), 2050 (2041–2060) and 2070 (2061–2080). Six land use classes were obtained, i.e. dry deciduous forest, tropical thorn forest, scrubland, cropland, plantation and fallow land from analysis of satellite images. Regression analysis revealed that the temperature has significant influence on the variation of SOC stock under all land use types. Under dry deciduous forest and plantation, there is no significant influence of rainfall variable, whereas under other land use pattern, there is significant influence on SOC stock. Predicted vs. actual soil value showed that overall regression model was significant under all land use types. Altogether, findings from CarboSOIL model indicate that the future climate change will have an adverse impact on SOC stock in 0–30 cm of soil depth.