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http://dx.doi.org/10.7465/jkdi.2015.26.2.355

A meta analysis of the climate change impact on rice yield in South Korea  

Shin, Deok Ha (Department of Statistics, Dongguk University)
Lee, Mun Su (Department of Energy Science, Sungkyunkwan University)
Park, Ju-Hyun (Department of Statistics, Dongguk University)
Lee, Yung-Seop (Department of Statistics, Dongguk University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.2, 2015 , pp. 355-365 More about this Journal
Abstract
As the global climate has dramatically changed over the past decades, there has been active research on evaluating its effects on food security, which has been recognized as one of the most important issues in the field. In this study, we analyzed the impact of the climate change on the Korean agriculture using meta-analysis methods. Especially, our research focus is on estimating the effect of CO2 concentration and two adaptations (planting-date and cultivar adjustments)on rice that accounts for a larger proportion of the Korean domestic agriculture. Unlike traditional general meta-analysis methods that use summary statistics of effects of interest, meta analysis specific to the agriculture literature was conducted by integrating the data on rice yield that were generated under various CO2 emission scenarios and general circulating models of the 6 collected individual studies. As a modeling approach, the rice yield change ratio was set as the dependent variable and the main and interaction effects of CO2 concentration and adaptation were considered as independent variables in a regression model, As a result, CO2 is estimated to have opposite effects on rice yield depending on whether any of the two adaptations is applied or not; decreasing effect without adaptation and increasing effect with adaptation. In addition, it turns out that the cultivar adjustment has a higher increasing effect on rice yield than the planting-date adjustment. The results of the study are expected to be used as basic quantitative data for establishing responsive polices to the future climate changes.
Keywords
Climate change; greenhouse gas emission scenario; meta analysis; regression analysis;
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Times Cited By KSCI : 6  (Citation Analysis)
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