|Douglas Jr, Clyde|
Submitted to: Journal of Soil and Water Conservation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/15/2000
Publication Date: N/A
Interpretive Summary: Atmospheric carbon dioxide (CO2) concentration has been increasing at an accelerating rate for several decades. Average global air temperature appears to be rising. Carbon dioxide is known as a greenhouse gas, which transmits visible light energy from the sun and inhibits the loss of heat from the earth by radiation into space. This stores heat in the atmosphere, just as heat is stored in a glass-roofed greenhouse on a sunny day. Several processes occurring on the earth may be accelerated or aggravated by increasing the heat load on our atmosphere. In addition to increasing air temperature there could be problems from melting icefields and sea level rise, weather pattern shifts contributing to flooding and drought, and an increase in the number and intensity of extreme weather events. Human activity releases large amounts of CO2. It should be possible to reduce that human contribution. There is an immediate need to predict how agricultural management systems effect organic carbon storage in soils. These predictions could be provided by a field level carbon sequestration model that is sensitive to local soils, climate, tillage, crop rotations, cover crops, and organic amendments. The Agricultural Research Service staff at Pendleton is currently developing such a model, named CQESTR, that will compute decomposition rate and residence time in the soil of carbon from antecedent organic matter, crop residues, roots, and organic carbon containing amendments (compost, manure, sewage sludge, or other biosolids). This model will use data sets that are available nationally. It will help both at the farm level and for policy and program development for national carbon sequestration policy objectives.
Technical Abstract: The residue decomposition model D3R is to be used as the core of a model "CQESTR" for the prediction of carbon sequestration in agricultural soils. D3R has been tested and found to successfully predict residue decomposition nationally in the USA. Input data for CQESTR will be obtained from existing data files that have been created and used for the Revised Universal Soil Loss Equation (RUSLE), from national soil surveys, and from plant properties databases like the FAO Tropical Feed database. Output from CQESTR will include short term and long term trends in surface and buried residue and soil organic matter content.