SOIL ORGANIC CARBON DYNAMICS IN AGRICULTURE: MODEL DEVELOPMENT AND APPLICATION FROM DAILY TO DECADAL TIMESCALES

Soil carbon (C) is the largest terrestrial C pool globally, containing more C than the atmosphere and biosphere. Soil organic carbon (SOC) is a source and sink of CO2 emissions to and from the atmosphere, thus influencing future climate change. Understanding SOC dynamics is also important for maintaining C stocks to sustain and improve crop yields. An existing model to estimate changes in SOC due to respiration was modified to operate in three computational platforms: MS Excel, MS Excel with Visual Basic for Applications, and supercomputing. This model was validated against CO2 flux data from a 9-year field experiment at Mead, NE, and was found to predict CO2 flux to within ±10% of measured values. The model was used to estimate agricultural SOC change from 1960 to 2008 for 11 counties in Nebraska and Iowa. On average, agricultural land under corn, soybean, and wheat was estimated to lose 22% of SOC due to respiration from 1960 to 2008; regressions were developed for subsequent economic modeling of trade-offs in agricultural systems. Using projections of temperature increase from climate change from 2010 to 2060, the model estimated that SOC under corn would decline by 8.4%, in contradiction to USGS projections of SOC gain in the region in the future. The modeling platforms developed, validated, and demonstrated here are shown to be useful research tools for estimating SOC and CO2 dynamics due to temperature and crop yield. Advisor: Adam J. Lisk