Submitted to: Meeting Abstract
Publication Type: Abstract only
Publication Acceptance Date: 4/1/2009
Publication Date: N/A
Citation: Interpretive Summary:
Technical Abstract: Most of the earth’s carbon-based products, such as food, fiber, fuel, and petrochemicals and fresh water come from the terrestrial ecosystem. This is a thin living skin covering the earth’s land surface. The earth’s thin mantel of soil, a major component of this ecosystem captures, stores, and releases water to vegetation, aquifers, streams, and lakes, and provides the major portion of the world’s fresh water supply. Within the next fifty years, human population is projected to double, and economic buying power for carbon-based products could triple. As there are no more unexplored frontiers, this increased demand from our terrestrial ecosystem will have to be met with the existing natural resource base. Added to this is the uncertainty introduced by the future global environmental changes. Potential global environmental changes include atmospheric carbon dioxide concentration, temperature, rainfall, and ultraviolet radiation intensity. Extreme weather events such as floods, drought, and heat waves are expected to be more common in the changed global climate of the future. In addition, regional increases in soil erosion and atmospheric pollution could also have negative impacts on crop productivity and the natural resource base of the planet. With existing scientific knowledge it is impossible to predict how these changes in the global climate may change the productivity of various crops worldwide and overall productivity of the terrestrial ecosystem. It is also difficult to determine how policy decisions by government agencies to address a changing resource base will impact agriculture in future. One way to deal with the complexity of the system and its impact on crop productivity is to develop and use mechanistic, process level computer models both at the field level and at the ecosystem level. Simulations by the cotton model CALGOS and the soybean model GLYCIM for example, showed that there would be large changes to regional patterns in the distribution of increased root growth due to elevated CO2 and increased temperature. This may have implications for long term soil quality changes as affected by global climate. Simulations with the rice model ORYZA1 and the wheat model WTGROW were used to analyze tradeoffs among water use and farm income in India. The results quantified the increased risk to growers as water/energy pricing policies were used to reduce water use. These and other examples of the development and use of the crop models for various applications to increase productivity and to mitigate the harmful effects of adverse environmental variables on natural resources both in the current and in the future changing environment are discussed in the paper.