Project Number: 3070-13000-012-13-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Mar 1, 2016
End Date: Feb 28, 2019
Objective #1: Quantify the dynamics of microbial community structure, diversity, and function to better understand their roles in determining CO2, N2O, and CH4 Objective #2: Improve biogeochemical models (DNDC) by incorporating the measured microbial dynamics into the model framework to describe the interactions among the soil climate, soil nutrient status, microbial activity, and GHG fluxes for the grasslands and croplands. Objective#3: Apply the developed plant-soil-microbe modeling system to model and predict potential of alternative management practices on mitigating CO2, N2O, and CH4 emissions from grasslands and croplands across landscape and watershed scales. The ARS investigator will be primarily responsible for conducting research under objective 1 and 3, with contributions to objectives 2.
ARS investigators will continue to utilize stationary chamber techniques to monitor greenhouse gas (GHG) flux from native prairie, improved pasture and winter wheat, monitoring for methane, carbon dioxide and nitrous oxide. Concurrently, soil samples will be obtained for assessment of soil carbon (C) and nitrogen (N) along with microbial carbon and nitrogen. Three times a season microbial community work will be assessed using poly lipid fatty acid (PLFA) profiling. The GHG, soil C and N data, along with microbial C and N and microbial community information will be correlated with on site automated greenhouse gas chambers that will also have microbial information associated with them. Processing of soil, analysis and archiving of soil will occur at ARS, along with microbial PLFA work. Stationary chambers and soil samples will be taken biweekly during the growing season in native prairie and improved pasture and winter wheat. During dormant months sampling will be decreased to monthly, however, soil work will continue throughout dormancy. This is a group of measurements that will help to understand the microbial population and their association with management practice, livestock grazing and crop cover to close the soil carbon and nitrogen budgets. Ideally there will be enough climatic variability to correlate seasonal and temporal indices with the generated data. This data will be given to UNH for use in the DNDC model.