Great Plains Population and Environment Data: Biogeochemical Modeling Data, 1860-2003 [United States] (ICPSR 31681)
Published: Oct 4, 2012
Principal Investigator(s):
William J. Parton, Colorado State University. Natural Resource Ecology Laboratory;
Myron P. Gutmann, National Science Foundation, and University of Michigan. Institute for Social Research;
Melannie D. Hartman, Colorado State University. Natural Resource Ecology Laboratory;
Emily R. Merchant, University of Michigan. Institute for Social Research;
Susan M. Lutz, Colorado State University. Natural Resource Ecology Laboratory
Series:
https://doi.org/10.3886/ICPSR31681.v1
Version V1
Summary
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 R01HD033554 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.
Citation
Export Citation:
Funding
United States Department of Health and Human Services. National Institutes of Health. Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD033554)
Subject Terms
Geographic Coverage
Smallest Geographic Unit
county
Study Design
To simulate soil biogeochemistry in the Great Plains of the United States, 21 counties were selected to represent the ecosystem diversity and variety of cropping practices in the region. For each of these counties, a set of schedule files was compiled from historical data and documentary sources to detail daily agricultural events for all of the major dryland and irrigated cropping systems. These schedules represent historical changes in land use -- such as initial plowout and the introduction of fertilizer, irrigation, and new crop rotations -- as well as daily management activities, such as planting, cultivating, and harvesting. For each major land-use trajectory, replicate schedules were used to simulate both gradual plowout of native grassland and crop rotation, such that each crop in the rotation is grown in each year. Additional schedules represent land never cropped (pasture), land removed from cropping (return), and cropland enrolled in the Conservation Reserve Program after 1985. Schedule files were calibrated by running the Daycent model and iteratively altering schedule parameters (within historically realistic limits) to match the simulated yields of major crops to yields reported in the United States Department of Agriculture (USDA) Census of Agriculture and the USDA National Agricultural Statistics Service database over the simulation period.
Each of the remaining 455 counties were linked to one of the 21 representative counties, so that the schedule files of the representative county could be used as the basis for simulating the agricultural histories of the counties. The assignment was made by identifying agro-ecological patterns through an average means cluster analysis and adjusting the results to produce 21 contiguous clusters with similar ecological characteristics and agricultural practices, each containing one of the 21 representative counties. The schedule files for the 21 representative counties were extended to each of the other counties in the cluster, and the land in each county divided among those files, based on historical agricultural data for that county.
Universe
All the counties in the 12 Great Plains states of the United States (Colorado, Iowa, Kansas, Minnesota, Montana, Nebraska, New Mexico, North Dakota, Oklahoma, South Dakota, Texas, and Wyoming).
Unit(s) of Observation
county
Data Source
HISTORICAL, DEMOGRAPHIC, ECONOMIC, AND SOCIAL DATA: THE UNITED STATES, 1790-1970 (ICPSR 0003).
Census volumes for pertinent years by the United States Bureau of the Census.
Census volumes for pertinent years by the United States Department of Agriculture.
aggregate data
Mode of Data Collection
record abstracts
Description of Variables
The 24 variables in the study include grain harvest data, irrigation data, above-ground net primary production of carbon data, non-grain harvest data, fertilizer use data, and agricultural production data, mean soil carbon data, precipitation data, maximum and minimum air temperature data, soil temperature data, transpiration by plants data, soil evaporation data, total emissions of various chemical compounds, and data regarding the amount of carbon removed by fire or grazing.
Response Rates
not applicable
Presence of Common Scales
none
Original Release Date
2012-10-04
Version Date
2012-10-04
Notes
The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.
This study was originally processed, archived, and disseminated by Data Sharing for Demographic Research (DSDR), a project funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD).