Improving representation of Soil Carbon Dynamics in Earth System ModelI am developing an open source MIR spectroscopy based system to predict a range of soil properties that are essential to improving representation of soil carbon dynamics in earth system models. Currently, I am using various multivariate and machine learning techniques to predict organic carbon, clay, CEC, pH, bulk density and exchangeable of Ca, Fe and Al using MIR spectra (> 50000 samples) avaiable through NSSC-KSSL library across the US. Later, we will use these predicted soil properties to improve SOC estimates in earth system models and simulate the impact of climate and land use scenarios on SOC change through 2100.
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Land Use Change and DisturbancesI have used a biogeochemical model (TEM-Hydro) to look at the effects of agriculture and timber harvest on carbon sequestration in the Eastern US forests. The Eastern US forests have been recovering from past land use changes, particularly agricultural abandonment since the mid-20th century. Our results showed that forests in the eastern US are still recovering from the past disturbance indicating increased carbon sequestration.
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Herbivory effect on grassland carbon dynamics
I am using a highly integrated daily time step ecosystem model (The Dynamic Land Ecosystem Model) to quantify the response of grassland to increased herbivory pressure using Mongolia as a case study. The purpose of this study is to identify tradeoffs and synergies associated with climate and herbivory in a region where livestock husbandry is an important component of the national economy.
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