2010 Annual Report
1a.Objectives (from AD-416)
Objective 1. Assess the relative utility of experimental approaches such as FACE, SPAR, OTC and T-FACE for estimating impacts of climate change factors on plant responses.
Objective 2. Strengthen physiological and genetic assumptions of ecophysiological models used for climate change research.
Sub-objective 2.A: Compare and refine ecophysiological models that differ in the level of complexity used to represent key processes.
Sub-objective 2.B: Refine and apply approaches for gene-based modeling of ecotypic adaptations to factors relevant to climate change research.
Objective 3. Predict likely impacts of climate change and potential for adaptation of cropping systems.
1b.Approach (from AD-416)
Assess and strengthen existing process-based plant growth models for their ability to simulate interacting effects of CO2 and temperature on crop growth, water use, soil carbon storage, and trace gas emissions and then utilize the models to predict likely effects of global change on agriculture. Also evaluate effectiveness and costs of technolgocial methods of manipulating temperature in open-field, free-air plots at a specific location for validating the models and studying underlying processes, and appraise whether natural temperature variations due to season, elevation, and latitude can be utilized for similar lines of research. Replacing 5347-11000-008-00D (2/10).
This project, which builds upon findings from the older project (5347-11000-008-00D), started in February, 2010. With the shift in emphasis from field experimentation to simulation modeling, our initial work has emphasized training, data organization and literature review. One such effort was a meta-analysis of over 160 research papers where simulation models were used to predict potential impacts of climate change or explore adaptation. The review identified numerous areas for improvement, especially highlighting the need for testing more physiologically detailed models against the relatively simple radiation use efficiency models that have predominated in impact research. Another line of work involves developing software to facilitate inter-conversion of datasets stored in spreadsheets for use in simulation models. Among test datasets are data from GRACEnet and our recently completed T-FACE experiments. The first output format being tested is for the DSSAT4.5 modeling software, which is expected to be used extensively in our upcoming simulation studies.
Improved climate data sources for modeling. Use of ecophysiological models for climate change research and other agricultural decision support applications is often constrained by lack of quality weather datasets. Two promising sources, NASA/POWER and VEMAP, were assessed for suitability in modeling by ARS scientists in Maricopa, AZ. The NASA/POWER data on solar radiation are available on a 1° grid globally, are updated to within a week of the current date, and were found to accurately reproduce daily variation. The VEMAP data are available on a 0.5° grid for the US, include temperature, precipitation and solar radiation, and were found to provide results similar to those for conventional weather stations from associated grid cells. Both data sources thus can be used in simulation studies, allowing researchers to focus on scientific issues rather than data acquisition and quality control. This should ultimately lead to better information on potential impacts of climate change and potential for adaptation, especially at regional to global scales.
Effects of elevated CO2 on crop yield. In order to determine how the increasing concentration of CO2 in the atmosphere will likely affect crop yields in the future, at least nine research groups from around the world have conducted many FACE (free-air CO2 enrichment) experiments on at least ten crops over the last two decades. An ARS scientist from the U.S. Arid-Land Agricultural Research Center analyzed all these experiments, and the results showed yields of a so-called C4 crop, sorghum, were unaffected, whereas yields of C3 crops were increased about 16 to 40% at CO2 concentrations of about 550 ppm. Yields of C3 grain crops (wheat, rice, barley, soybean) were increased about 17% on average, but especially noteworthy are recent results from the China FACE Rice Project finding about 32% increases for some hybrid rice varieties. These results show C3 (but not C4) crop yield will increase in the future due to the direct effects of elevated CO2 on plants if the effects of climatic change are small, or if such climatic changes are detrimental, these direct CO2 effects will tend to mitigate the harm.
Infrared Heater Arrays for Warming Field Plots Scaled from 1 to 100 Meters. There is a need to study the likely effects of global warming on ecosystems in field plots larger than the standard 3-m diameter plot sizs. By nesting hexagonal arrays in a honeycomb pattern, ARS scientists from the U.S. Arid-Land Agricultural Research Center, Maricopa, AZ and a collaborator from Brookhaven National Laboratory, Upton, NY showed that excellent uniformity of the warming treatment can theoretically be achieved across the plots. Switching to the honeycomb pattern and to larger heaters increased overall efficiency from about 26% to 70% at wind speeds of 4 m s-1. For 4°C of warming and electricity costs of US $0.1 per kWh, under Kansas prairie conditions, annual energy costs would be about $8,500 for a 3-m-diameter plot and $3,300,000 for a 100-m-diameter plot. However, there is an economy of scale such that the costs would be about $1,200 and $410 per square meter for the 3- and 100-m plots, respectively. These procedures enable the costs to be estimated for potential new warming experiments and have already been used in collaborations with four groups.
Meta-analysis of protocols for modeling impacts of climate change. Ecophysiological models are widely used to assess impacts of climate change on agroecosystems and to examine options for adaptation, but protocols for such assessments vary to such an extent that they constrain cross-study syntheses and increase the potential for unintentional biases. ARS scientists from the U.S. Arid-Land Agricultural Research Center, Maricopa, AZ and cooperator from the University of Georgia reviewed 163 peer-reviewed papers dealing with climate change and agriculture, considering six main topics: target crops and regions; the crop model(s) used and their characteristics; sources and application of data on [CO2] and climate; adaptation strategies; impact parameters evaluated; and assessment of variability or risk. The review identified numerous aspects of the protocols that could be improved including: assessment of the appropriate level of model complexity, selection of baseline periods that are much closer to current conditions, more realistic treatment of sources of variability such as from soils and management, and more realistic representation of options for adaptation. Our recommendations should strengthen studies on potential impacts of climate change, leading to more robust overall assessments and hence more accurate information for stakeholders.
Delacy, I.H., Fox, P.N., Mclaren, G., Trethowan, R., White, J.W. (2009). A Conceptual Model for Describing Processes of Crop Improvement in Database Structures. Crop Science, 49:2100-2112.
Thorp, K.R., Hunsaker, D.J., French, A.N., White, J.W., Clarke, T.R., Pinter Jr, P.J. 2010. Evaluation of the CSM-CROPSIM-CERES-Wheat Model as a Tool for Crop Water Management. Transactions of the ASABE. 53(1):87-102.
Boone, K.J., Jones, J.W., Hoogenboom, G., White, J.W., 2010. The Role of Crop Systems Simulation in Agriculture and Environment. International Journal of Agricultural and Environmental Information Systems 1, 41-54.
White, J.W., Jones, J.W., Porter, C., Mcmaster, G.S., Sommer, R., 2009. Issues of Spatial and Temporal Scale in Modeling the Effects of Field Operatiions on Soil Properties. Operational Research International Journal (ORIJ). DOI:10.1007/s12351-009-0067-1.
Wua, W., Liu, H., Hoogenboom, G., White, J.W., 2009. Evaluating the accuracy of VEMAP daily weather data for application in crop simulations on a regional scale. European Journal of Agronomy 32, pp. 187-194.