Colunga-Garcia, Manuel (Michigan State University, 209 Manly Miles Bldg., 1405 S. Harrison Rd., East Lansing, MI, 48824; Phone: 517-432-4463; Fax: 517-432-9415; Email: colungag@msu.edu)

 

Urbanization and its Impact on the Carbon Sequestration Potential of Agroecosystems in the North Central Region

 

M. Colunga-Garcia *, P.R.Grace, S.H. Gage, G.P. Robertson, G.R. Safir, S. Rowshan

 

Current estimates of terrestrial carbon sequestration potential across the landscape are constrained by our present knowledge of land use distribution within a region. With an exponential growth in population worldwide, there is an increasing demand on rural lands to accommodate urban development. Whilst the identification of high potential regions and management strategies for sequestration of carbon in agroecosystems is an important policy objective in the mitigation of global climate change, we may be losing as much carbon in terms of productive lands as we hope to gain with conservation tillage practices. Regional and sub-regional assessments of terrestrial carbon storage over the next century which include estimates of land use change will allow us to provide policy makers with more realistic information on the impact of greenhouse gas mitigation strategies.†† The North Central Region (NCR) of the United States comprises the 12 states of the greater Midwest and is the major producer of corn and soybeans in the country, as well as producing half of the nationís wheat. The potential impact of urbanization in this region was estimated using a combined analysis of urban influence buffers and urban-patch distribution for the major urbanized areas. Estimation of changes in soil organic carbon and associated greenhouse gas emissions within agricultural soils in response to management and climatic changes were conducted using a process based simulation model -SOCRATES- to rapidly integrate spatially explicit climate, soil and terrestrial ecosystem characterization data. The main considerations in using SOCRATES is its ability to accurately predict carbon and associated greenhouse gas emissions using non-site specific concepts of carbon cycling and biogeochemistry, its relative ease of use and minimal data input requirements. In its simplest form, SOCRATES uses annual precipitation, mean annual temperature, and soil clay content or CEC. More detailed climate inputs can be used for refining non-CO2emissions.