North-Central Section - 50th Annual Meeting - 2016

Paper No. 11-5
Presentation Time: 8:00 AM-12:00 PM

A REACTIVE TRANSPORT MODEL OF SOIL RESPIRATION INFLUENCED BY DIFFERENT MOISTURE CONTENT


LIU, Yuchen, Geology Department, THE SCHOOL OF EARTH, SOCIETY & ENVIRONMENT, UIUC, 1719 MELROSE VILLAGE CIR APT 1521, URBANA, IL 61801, SANFORD, Robert A., Department of Geology, University of Illinois Urbana-Champaign, 1301 W. Green St, Urbana, IL 61801 and DRUHAN, Jennifer L., Geology, University of Illinois at Urbana-Champaign, 156 Computing Applications Building, 605 E. Springfield Ave, Champaign, IL 61820, liu305@illinois.edu

Carbon dioxide is one of the most important gases related to global warming. Soils represent a large reservoir of terrestrial carbon, and emit carbon to the atmosphere during decomposition and heterotrophic respiration. Research has shown that soil respiration processes are highly sensitive to the soil moisture. However, a consistent, mechanistic model for this relationship has yet to be produced. In this work, soil samples collected from the East River watershed in Colorado are used for incubation experiments to quantitatively determine the effect of moisture on microbial oxidation of organic carbon. CO2 concentration and carbon isotopes are measured in time series with different soil moisture in a series of incubation experiments. Preliminary results show respiration rate can range between 0.03 to 5.31 umol CO2/g soil/day as a function of soil moisture. For saturations between 0 and 66%, the respiration rate increases with increasing soil moisture, though from 66 – 100% this relationship reverses. We relate respiration rates at lower soil moisture contents to the portion of total biomass that is active through measurement of the rRNA over DNA ratio as an indicator of changes of biomass activity. These data will be used to parameterize a process-based relationship for the percentage of total microbial biomass that is actively contribution to soil carbon respiration in a reactive transport model framework. This capability will support improved predictions of carbon cycling in response to climate change.