Submitted to: Field Crops Research
Publication Type: Peer reviewed journal
Publication Acceptance Date: 7/4/2011
Publication Date: 12/20/2011
Citation: White, J.W., Hoogenboom, G., Kimball, B.A., Wall, G.W., 2011. Methodologies for simulating impacts of climate change on crop production. Field Crops Research. 124:357-368. Interpretive Summary: In order to understand how climate change might affect agriculture, researchers use computer-based models combined with climate change projections. These studies have seen wide use by the Intergovernmental Panel on Climate Change (IPCC) and other groups. Although one would like to compare studies across crops and regions, the diversity of modeling approaches has made it difficult to conduct such comparisons. We reviewed 139 publications dealing with climate change and agriculture, considering six main topics: target crops and regions; the model(s) used and their characteristics; sources and application of data for future CO2 levels or climate change; strategies farmers might use to adapt to climate change; which variables related to impact were evaluated; and whether variability or risk was considered. Over 30 crops were represented, including wheat, maize, soybean and rice, in approximately 111 papers. The USA and Europe were the dominant regions studied. More than 50 crop simulation models were used. Most models responded to CO2 by adjusting radiation use efficiency (RUE) and transpiration, which precludes consideration of interacting effects of CO2, stomatal conductance, and canopy temperature. The assumed current or historic baseline CO2 levels often corresponded to conditions 10 or more years earlier than the publication date, which would exaggerate relative impacts of increasing CO2. Furthermore, few papers explained whether variation in CO2 was synchronized between the simulation model and historic or GCM-modeled weather datasets. Potential farmer adaptations predominantly involved planting dates and cultivars, whereas tillage or crop rotations only appeared in 17 papers. Economic yield was considered in 116 papers while only five papers considered impacts on soil carbon levels or greenhouse gas emissions. Strengthening the assessment process would improve the reliability and comparability of studies. A coordinated data resource would allow researchers to focus on underlying science instead of dataset assembly, ultimately leading to more useful projections on impacts and insights into how agriculture might best adapt to climate change.
Technical Abstract: Ecophysiological models of crop growth have seen wide use in IPCC and related assessments. However, the diversity of modeling approaches constrains cross-study syntheses and increases potential for bias. We reviewed 139 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 CO2 or climate change data; adaptation strategies; impact parameters evaluated; and assessment of variability or risk. Wheat, maize, soybean and rice were considered in approximately 111 papers, and over 30 crops were represented. The USA and Europe were the dominant regions studied. Of the more than 50 simulation models used, most models responded to CO2 by adjusting radiation use efficiency (RUE) and transpiration, which precluded consideration of interacting effects of CO2, stomatal conductance and canopy temperature. Assumed baseline CO2 levels often corresponded to conditions 10 or more years earlier than the publication date, exaggerating relative impacts of increasing CO2. Furthermore, few papers explained whether variation in [CO2] was synchronized between the crop model and historic or future weather data. Adaptations predominantly involved planting dates and cultivars; 17 papers tested different tillage or crop rotations. Economic yield was considered in 116 papers vs. only five papers assessing soil carbon or greenhouse gas fluxes. A coordinated crop, climate and soil data resource would allow researchers to focus on underlying science and facilitate development of more uniform assessment protocols, ultimately allowing for more robust and intercomparable studies of climate change impacts and potential for adaptation. [GRACEnet Publication].