Location: Plant Physiology and Genetics Research2010 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).
3. Progress Report
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.
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.