CROP PRODUCTIVITY
For more information on Crop Productivity Modeling research at
MSU, please contact
Stuart Gage.
Crop Productivity Modeling research at MSU is supported by the Upper
Midwest RESAC. We wish to acknowledge partial support for this effort
from the NSF Long Term Ecological Research program at Michigan State
University and the Michigan Agricultural Experiment Station. We
acknowledge the effort that the USDA Regional Project NC94 made
in assembling the weather data sets. Finally, we wish to thank Dr.
T. Sinclair for providing the QBMaize model code.
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Project Overview
Our objectives include the analysis of historical crop productivity patterns in the Upper Midwest to explore future scenarios using a modeling and analysis framework. |
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Agricultural ecosystems affect biophysical and socioeconomic systems and thus constitute a primary example of human impact on the Biosphere. The drivers and impacts of agroecosystems change with spatial scale. A regional scale analysis requires an equivalent expansion in the scope of the temporal scale. Long-term analysis is achieved by the integration of historical data and modeling.
We have integrated a relational database containing county maize yield for the 266 counties in this region from 1972-1999, and daily weather information from 1972-1995. We are evaluating the regional variability of corn productivity in the context of historical climatic fluctuations.
To facilitate the ability to develop future scenario, we have integrated a physiological corn model into a modeling applications system framework interface. This interface allows for data management and visualization of model inputs/outputs and facilitates the use of GIS and statistical analysis.
In addition, it permits the integration of satellite imagery as a means to achieve real-time model calibration. In this website we present the results of modifying the MAIZE model for use in cold climates and the implications of using variable soil water availability.
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