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Title: Use of GIS to Define Agro-ecosystems & Climate Change

item White, Jeffrey

Submitted to: International Wheat Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 1/15/2006
Publication Date: 3/24/2006
Citation: Hodson, D.P., White, J.W. 2006. Use of GIS to Define Agro-ecosystems & Climate Change. In: International Wheat Conference Proceedings, CIMMYT, Ciudad Obregon, Sonora, Mexico, March 19-24, 2006.

Interpretive Summary:

Technical Abstract: Bread wheat and durum wheat occupy an estimated 200 million ha globally, are grown from sea-level to over 3500 masl, and from the equator to above 60N latitude in Canada, Europe & Asia. For an organization like CIMMYT, charged with improving wheat for the entire developing world, an understanding of wheat production environments is crucial for international priority setting, collaboration, and targeting germplasm to specific environments. Increasingly important is information on how those environments and associated biotic and abiotic stress patterns, and hence required traits or management, may shift with changing climate patterns. There is also an increasing need to classify production environments, not just solely in biophysical terms but also with respect to socio-economic factors. Geospatial technologies, especially GIS, are playing a role in each of these areas. Use of GIS is described using illustrative examples based on CIMMYT experiences. Since the 1980’s, the CIMMYT wheat program has classified production regions into mega-environments based on climatic, edaphic and biotic constraints. Advances in spatially disaggregated datasets and GIS tools provide an opportunity for characterizing and mapping mega-environments in a much more quantitative manner – current progress is outlined. In parallel, advances are also being made in the describing the spatial distribution of major crops, including wheat. The combination of improved crop distribution data and key biophysical data at high spatial resolutions also permit the exploration of scenario models for disease epidemics – the example of a stem rust is given. Availability of GIS data describing future climate scenarios may provide insights into potential changes in wheat production environments in the coming decades – selected examples are given. Despite progress in characterizing wheat environments, there is a pressing need to advance beyond static definitions of environments and incorporate temporal aspects to define locations or regions in terms of probability or frequency of occurrence of different environment types. Progress in this aspect is being made for other crops, and increased availability of nearly real-time daily weather data derived from remote sensing offers opportunities to further improve environment characterization as well as to produce regional-scale models of dynamic processes such as disease progression or crop water balance.