Great Plains Population and Environment Data: Biogeochemical Modeling Data, 1860-2003 [United States] (ICPSR 31681)
Principal Investigator(s): Parton, William J., Colorado State University. Natural Resource Ecology Laboratory; Gutmann, Myron P., National Science Foundation, and University of Michigan. Institute for Social Research; Hartman, Melannie D., Colorado State University. Natural Resource Ecology Laboratory; Merchant, Emily R., University of Michigan. Institute for Social Research; Lutz, Susan M., Colorado State University. Natural Resource Ecology Laboratory
This study is part of a series of studies assembled by an interdisciplinary research team led by Myron Gutmann of the University of Michigan between 1995 and 2004, as part of a research project funded by the National Institute of Child Health and Human Development (Grant Number R01 HD33445 to the University of Michigan). The goal of the project was to amass information about approximately 500 counties in 12 states of the Great Plains of the United States, and then to analyze those data in order to understand the relationships between population and environment that existed between the years of 1860 and 2003. The data distributed as part of this series are all data about counties. They fall into four broad categories: information about the counties, about agriculture, about demographic and social conditions, and about the environment. The information about counties (name, area, identification code, and whether the project classified the county as part of the Great Plains in a given year) is embedded in each of the other data files, so that there will be three series of data (agriculture, demographic and social conditions, and environment), containing individual data files for each year for which data are available.
Specifically, this study contains environmental data and is meant to aid the modeling of the biogeochemical effects of cropping in the Great Plains region. These data were generated by the Daycent ecosystem model, which has been used extensively to simulate soil biogeochemical dynamics from agricultural systems throughout the United States. Variables include information on above-ground production, soil and system carbon, evaporation and transpiration data, soil temperature, nitrogen mineralization, and fluxes of various chemical compounds.
These data are freely available.
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