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ARS Home » Plains Area » Lincoln, Nebraska » Agroecosystem Management Research » Research » Publications at this Location » Publication #320483

Title: Observations from the field: further developing linkages between soil C models with long-term bioenergy studies

Author
item Schmer, Marty
item Jin, Virginia
item Wienhold, Brian

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 8/4/2015
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Biofuel feedstocks are being developed and evaluated in the United States and Europe to partially offset petroleum transport fuels. Accurate accounting of upstream and downstream greenhouse gas (GHG) emissions is necessary to measure the overall carbon intensity of new biofuel feedstocks. Changes in direct soil organic carbon (SOC) can have a major impact on estimating overall greenhouse gas (GHG) emissions from biofuels when using life-cycle assessment (LCA). Estimating changes in SOC, when accounted for in a LCA, is largely derived from near-surface soil depths , typically to a depth of 30 cm or less. The majority of soil models do not model SOC changes below near-surface soil depths. Perennial herbaceous roots often extend much deeper than 30 cm and changes in cumulative SOC stocks may not be fully accounted for. Further, there is limited empirical data to validate SOC changes at soil depth from bioenergy crops with soil C models. Further calibration, validation, and intercomparisons of soil C models with long-term, field-based bioenergy studies are needed to accurately predict SOC stock changes at depth under variable soil types, climates, and cropping systems. From a LCA perspective, determining SOC stock changes at sub-surface depths would be a logical step to accurately quantify biofuel GHG emissions especially in bioenergy cropping systems with high potential for soil C storage. Presentation objectives will look at developing linkages and determining research needs from field-based SOC changes to modeling and looking at future landscapes with increased bioenergy feedstocks.