Ogle, Stephen: Colorado State University (Project Lead)
Breidt, F.: (Co-Investigator)
Conant, Rich: (Co-Investigator)
Klooster, Steven: NASA Ames Research Center - Cal State Univ Monterey Bay (Co-Investigator)
Paustian, Keith: (Co-Investigator)
Potter, Christopher: NASA ARC (Institution Lead)
Brenner, John: (Participant)
Goebel, Jeff: (Participant)
Spencer, Shannon: Colorado State University (Participant)
Project Funding:
2005 - 2007
NRA: 2004 NASA: Carbon Cycle Science
Funded by USDA, NASA
Abstract:
Quantifying CO2 fluxes between agricultural lands and the atmosphere is important for basic scientific understanding of the terrestrial carbon cycle. Historically, agriculture has been a major source of CO2 emissions, but changes in management during the latter of the l900s are believed to have slowed soil carbon losses, and moreover, recent policy is encouraging producers to adopt conservation practices that are known to sequester carbon in soils. Determining the change in CO2 fluxes associated with adoption of new management practices is needed for evaluating the factors regulating current terrestrial carbon sources and sinks. In addition, policymakers need this information to determine the contribution of agricultural management for mitigation of greenhouse gas emissions as they deal with climate change and air quality issues in the US.
Our objective is to make a major advancement in current inventory assessments for agricultural CO2 fluxes by incorporating remote sensing products. Specifically, we plan to use vegetation products from the NASA MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensor with climate, soil property, and management data to compute cropland NPP, and then integrate this information into an existing assessment tool that is based on the Century Model. With the latest land use and management activity data and more detailed climate data, this tool will produce the most complete accounting of US agricultural management impacts on soil organic carbon storage of any current or past assessments. Uncertainty will be quantified for the inventory utilizing a set of new ground-based observations and an existing network of agricultural experiments. Uncertainty imparts an additional and arguably critical piece of information for comparison of fluxes among different terrestrial sources and sinks. In addition uncertainty is required for reporting purposes to assess the risks involved with using agricultural carbon sequestration for mitigation of greenhouse gas emissions relative to other carbon sinks or direct emission reductions. Incorporation of remote sensing products into a modeling framework is expected to reduce those uncertainties and therefore the associated risks. In addition to assessing recent trends in CO2 fluxes, the potential for carbon sequestration in the future will be evaluated based on simulations of management scenarios from current baseline conditions.
Publications:
Ogle, S. M., Breidt, F. J., Easter, M., Williams, S., Paustian, K. 2007. An empirically based approach for estimating uncertainty associated with modelling carbon sequestration in soils. Ecological Modelling. 205(3-4), 453-463. DOI: 10.1016/j.ecolmodel.2007.03.007
Gurung, R. B., Breidt, F. J., Dutin, A., Ogle, S. M. 2009. Predicting Enhanced Vegetation Index (EVI) curves for ecosystem modeling applications. Remote Sensing of Environment. 113(10), 2186-2193. DOI: 10.1016/j.rse.2009.05.015
OGLE, S. M., BREIDT, F. J., EASTER, M., WILLIAMS, S., KILLIAN, K., PAUSTIAN, K. 2010. Scale and uncertainty in modeled soil organic carbon stock changes for US croplands using a process-based model. Global Change Biology. 16(2), 810-822. DOI: 10.1111/j.1365-2486.2009.01951.x
More details may be found in the following project profile(s):
