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United States Department of Agriculture

Agricultural Research Service

Research Project: IMPACTS OF RISING ATMOSPHERIC CARBON DIOXIDE AND TEMPERATURE ON CROP GROWTH, REPRODUCTIVE PROCESSES, YIELD, AND SEED QUALITY

Location: Chemistry Research Unit

Title: Testing effects of climate change in crop models

Authors
item Boote, K -
item Allen, Leon
item Prasad, P -
item Jones, J -

Submitted to: Book Chapter
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 22, 2010
Publication Date: January 1, 2011
Citation: Boote, K.J., Allen Jr, L.H., Prasad, P.V., Jones, J.W. 2011. Testing effects of climate change in crop models. In: Hillel, D., Rosenzweig, C. Handbook of climate change and agroecosystems. Volume 1. Covent Garden, London: Imperial College Press.109-129.

Interpretive Summary: Crop simulation models can be used for evaluating the consequences of climate change on production and shifts in species, sowing date, cultivars, irrigation, and fertility management for adapting to climate change. The models should be accurately structured and tested for CO2 and temperature effects on crop growth and development. Most models can simulate photosynthesis, dry matter growth, reproductive processes, and seed-grain yield responses to rising CO2 and temperatures; however, too frequently, model developers have accepted that past relationships are accurate, and insufficient effort has been made to improve or test those relationships relative to the latest scientific findings. Rigorous improvement of the climate change sensitivities of crop models has been sidetracked frequently by the demand for immediate use of models for impact assessments, and steps for adaptation or mitigation of climate change. University of Florida scientists and an ARS scientist at Gainesville, Florida: 1) characterized types of data needed for evaluating crop models for response to climate change, and 2) presented approaches and methods for testing crop models for sensitivity to CO2 and temperature at the levels of theory, processes, intermediate outcomes, and end-of-season predictions. From this characterization of types of data needed for a more reliable underpinning of model structures, in the future model predictions should be more sensible for applying to evaluation of strategies for evaluation of responses of crops to climate change and development of adaptation and mitigation options.

Technical Abstract: Climate change induced by increased atmospheric carbon dioxide (CO2) is expected to increase temperature, alter rainfall patterns, and extended growing seasons in many regions. Crop simulation models can be used as a tool for evaluating effects of climate change on production, as well as for evaluating potential shifts in species, sowing date, cultivars, irrigation, and fertility management for adapting to climate change. Before models can be used as such a tool, they must be accurately parameterized and tested for CO2 and temperature effects on crop growth and development. Most crop growth models simulate photosynthesis, dry matter growth, reproductive processes, and seed-grain yield responses to rising CO2 and temperatures; however, too often model developers have accepted that past relationships are accurate, and insufficient effort has been made to improve or test those relationships based on the latest scientific findings. Rigorous improvement of the climate change sensitivities of crop models has sometimes been supplanted by the demand for immediate use of models for strategy evaluation, climate adaption, and climate mitigation, with insufficient concern for the reliability of the responses to CO2 and temperature. The goals of this paper were to: 1) characterize types of data needed for evaluating crop models for response to climate change factors, and 2) discuss approaches and methods for testing crop models for sensitivity to CO2 and temperature, spanning theory, processes, intermediate outcomes, and end-of-season predictions. From this characterization of information needed for a more reliable underpinning of model structures, future model predictions should be more realistic for evaluation of responses of crops to climate change factors and for development of adaptation and mitigation options.

Last Modified: 9/1/2014
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