49-8 An Integrative Approach to Carbon, Nitrogen, and Greenhouse Gas Accounting and Management in Corn Production Systems.
See more from this Division: Agriculture and Natural Resources Science for Climate Variability and Change: Transformational Advancements in Research, Education and ExtensionSee more from this Session: Carbon, Nitrogen, Energy and Water Footprints In Agriculture Production: Changing Practices and Opportunities
Monday, October 22, 2012: 3:30 PM
Duke Energy Convention Center, Junior Ballroom B, Level 3
Our project focuses on three regions of the U.S. (NY, IA, CO) with distinct climate, soil, and corn management systems. Our approach integrates: strategic soil sampling for C assessment; biogeochemical models that predict yield, greenhouse gas (GHG) losses, and soil C change; regionally downscaled climate projections; and policy evaluation with an economic equilibrium model. A low-cost soil C assessment tool involving remote sensing, use of soil and land-use databases, and geostatistical models is being developed. In 2011 we collected over 1500 soil samples stratifying across soil types and management systems and measured these for soil characteristics including percent organic matter (OM), percent C and N, active C (permanganate oxidation), bulk density (BD), and visible to near-infrared (VNIR) and mid-infrared (MIR) spectroscopy. Preliminary analyses indicate a tendency for soil database (SSURGO) estimates of OM to be higher than measured OM above 30 cm, and lower than measured OM at lower depths. We built and field-tested a diamond-tipped rotary corer for more accurate BD determination at depth on rocky soils. For one intensively sampled site in NY we found lower variability in BD than percent C, suggesting a smaller sample number requirement for BD. Also at this site we found that soil C at 20-40 cm was best for estimating soil C stocks for the entire soil profile. We are evaluating the use of on-the-go VNIR for characterizing field variability and sampling requirements. Our DayCent biogeochemical model has a new subroutine for ammonia volatilization, recognizes black C pools, and can assimilate remotely sensed data to improve the plant growth submodel. A method has been developed to estimate soil moisture retention curve parameters from SSURGO for “Adapt-N” (a N management tool). Beta testing of “COMET-Farm”, a web-based C and GHG accounting and management tool, is planned for 2012.
See more from this Division: Agriculture and Natural Resources Science for Climate Variability and Change: Transformational Advancements in Research, Education and ExtensionSee more from this Session: Carbon, Nitrogen, Energy and Water Footprints In Agriculture Production: Changing Practices and Opportunities