Modelling Soil Organic Carbon as a Function of Topography and Stand Variables

Abstract

Soil organic carbon (SOC) plays a crucial role in global carbon cycling. The amount of SOC is influenced by many factors (climate, topography, forest type, forest disturbance, etc.). To investigate this potential effect, we performed a multiple regression model using six different predictor variables in the third national-level forest resource assessment data of Nepal. We found a significant correlation between the SOC and altitude (r = 0.76) followed by crown cover and slope. The altitude alone explains r2 = 58 percent of the variability of the SOC and shows an increasing rate of change of SOC with the increase of altitude. Altitude was identified as a suitable predictor of SOC for large areas with high altitudinal variation followed by crown cover and slope. Increasing amounts of SOC with increasing altitude shows the significance of high-altitude forests in the perspective of climate change mitigation. Altitude, a proxy of temperature, provides insights into the influence of changing temperature patterns on SOC due to future climate change. Further study on forest types and SOC along the altitudinal gradient in Nepal is recommended to deal with the climate change problem in the future.