320-7 Estimating Soil Carbon in Loess Veneered Landscapes in the Central US.

Poster Number 1033

See more from this Division: S05 Pedology
See more from this Session: Digital Soil Assessment for Ecosystem Modeling: II
Wednesday, November 3, 2010
Long Beach Convention Center, Exhibit Hall BC, Lower Level
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Stephanie Frank1, Phillip Owens1, Zamir Libohova2, Samuel Indorante3, Michael Wilson4, Brad Lee5, Steve Blanford6 and Travis Neely7, (1)Purdue University, West Lafayette, IN
(2)National Soil Survey Center, USDA-NRCS, Lincoln, NE
(3)USDA-NRCS, DuQuoin, IL
(4)Rm. 152, MS 41, USDA-NRCS, Lincoln, NE
(5)University of Kentucky, Lexington, KY
(6)Suite 210, USDA-NRCS, Lexington, KY
(7)USDA-NRCS, Indianapolis, IN
Carbon dioxide emissions continue to increase and society continues to seek solutions for carbon sequestration. Carbon accounting and prediction in the soil is crucial for managing landscapes for carbon sequestration. Currently, no high-resolution maps of soil carbon and soil carbon recalcitrance are available on a regional level in the United States.  Such maps would be useful for refining estimates of regional carbon stocks and gas exchange as well as for estimating how quickly carbon could be sequestered, and how much carbon could be stored, in managed landscapes. This study is part of a regional project between Indiana, Illinois and Kentucky to focus on soil-landscape relationships in loess veneered landscapes. Loess soils make up approximately 10% of the terrestrial surface of the earth and approximately 4.2 million km2 in the central US. The study sites have loess that ranges from 0.5 to 3 m over residuum from sandstone and shale on bedrock controlled landscapes. Soils were sampled at key landscape positions (summit, shoulder, middle backslope, lower backslope, and footslope) of a paired pasture and forest watershed. Data indicate landuse and landscape position through digital soil mapping can be used to improve carbon predictions across a regional scale.
See more from this Division: S05 Pedology
See more from this Session: Digital Soil Assessment for Ecosystem Modeling: II