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Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time. [ABSTRACT FROM AUTHOR]

The development and application of cropping system simulation models for cotton production has a long and rich history, beginning in the southeastern U. S. in the 1960s and now expanded to major cotton production regions globally. This paper briefly reviews the history of cotton simulation models, examines applications of the models since the turn of the century, and identifies opportunities for improving models and their use in cotton research and decision support. Cotton models reviewed include those specific to cotton (GOSSYM, Cotton2K, COTCO2, OZCOT, and CROPGRO-Cotton) and generic crop models that have been applied to cotton production (EPIC, WOFOST, SUCROS, GRAMI, CropSyst, and AquaCrop). Model application areas included crop water use and irrigation water management, nitrogen dynamics and fertilizer management, genetics and crop improvement, climatology, global climate change, precision agriculture, model integration with sensor data, economics, and classroom instruction. Generally, the literature demonstrated increased emphasis on cotton model development in the previous century and on cotton model application in the current century. Although efforts to develop cotton models have a 40-year history, no comparisons among cotton models were reported. Such efforts would be advisable as an initial step to evaluate current cotton simulation strategies. Increasingly, cotton simulation models are being applied by nontraditional crop modelers, who are not trained agronomists but wish to use the models for broad economic or life-cycle analyses. Although this trend demonstrates the growing interest in the models and their potential utility for a variety of applications, it necessitates the development of models with appropriate complexity and ease-of-use for a given application, and improved documentation and teaching materials are needed to educate potential model users. Spatial scaling issues are also increasingly prominent, as models originally developed for use at the field scale are being implemented for regional simulations over large geographic areas. Research steadily progresses toward the advanced goal of model integration with variable-rate control systems, which use real-time crop status and environmental information to spatially and temporally optimize applications of crop inputs, while also considering potential environmental impacts, resource limitations, and climate forecasts. Overall, the review demonstrates a languished effort in cotton simulation model development, but the application of existing models in a variety of research areas remains strong and continues to grow. [ABSTRACT FROM AUTHOR]

AbstractSpring wheat [Triticum aestivum (L). cv. Yecora Rojo] was grown from December 1992 to May 1993 under two atmospheric CO2 concentrations, 550 μmol mol–1 for high-CO2 plots, and 370 μmol mol–1 for control plots, using a Free-Air CO2 Enrichment (FACE) apparatus. In addition to the two levels of atmospheric CO2, there were ample and limiting levels of water supply through a subsurface trip irrigation system in a strip, split-plot design. In order to examine the temporal and spatial root distribution, root cores were extracted at six growth stages during the season at in-row and inter-row positions using a soil core device (86 mm ID, 1.0 m length). Such information would help determine whether and to what extent root morphology is changed by alteration of two important factors, atmospheric CO2 and soil water, in this agricultural ecosystem. Wheat root growth increased under elevated CO2 conditions during all observed developmental stages. A maximum of 37% increase in total root dry mass in the FACE vs. Control plots was observed during the period of stem elongation. Greater root growth rates were calculated due to CO2 enhancement until anthesis. During the early vegetative growth, root dry mass of the inter-row space was significantly higher for FACE than for Control treatments suggesting that elevated CO2 promoted the production of first-order lateral roots per main axis. Then, during the reproductive period of growth, more branching of lateral roots in the FACE treatment occurred due to water stress. Significant higher root dry mass was measured in the inter-row space of the FACE plots where soil water supply was limiting. These sequential responses in root growth and morphology to elevated CO2 and reduced soil water supports the hypothesis that plants grown in a high-CO2 environment may better compensate soil-water-stress conditions. [ABSTRACT FROM AUTHOR]

Pinus eldarica L. trees, rooted in the natural soil of an agricultural field at Phoenix, Arizona, were grown from the seedling stage in clear-plastic-wall open-top enclosures maintained at four different atmospheric CO2 concentrations for 15 months. Light response functions were determined for one tree from each treatment by means of whole-tree net CO2 exchange measurements at the end of this period, after which rates of carbon assimilation of an ambient-treatment tree were measured across a range of atmospheric CO2 concentrations. The first of these data sets incorporates the consequences of both the CO2- induced enhancement of net photosynthesis per unit needle area and the CO2-induced enhancement of needle area itself (due primarily to the production of more needles), whereas the second data set reflects only the first of these effects. Hence the division of the normalized results of the first data set by the normalized results of the second set yields a representation of the increase in whole-tree net photosynthesis due to enhanced needle production caused by atmospheric CO2 enrichment. In the solitary trees we studied, the relative contribution of this effect increased rapidly with the CO2 concentration of the air to increase whole-tree net photosynthesis by nearly 50% at a CO2 concentration approximately 300 μmol mol-1 above ambient. [ABSTRACT FROM AUTHOR]