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Estimation of the carbon dioxide (CO 2 ) fertilization effect using growth rate anomalies of CO 2 and crop yields since 1961
Author(s) -
LOBELL DAVID B.,
FIELD CHRISTOPHER B.
Publication year - 2008
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/j.1365-2486.2007.01476.x
Subject(s) - yield (engineering) , crop , carbon dioxide , crop yield , environmental science , climate change , co occurrence , carbon dioxide in earth's atmosphere , estimation , atmospheric sciences , agronomy , econometrics , mathematics , economics , chemistry , ecology , computer science , geology , materials science , management , artificial intelligence , organic chemistry , metallurgy , biology
The effect of elevated carbon dioxide (CO 2 ) on crop yields is one of the most uncertain and influential parameters in models used to assess climate change impacts and adaptations. A primary reason for this uncertainty is the limited availability of experimental data on CO 2 responses for crops grown under typical field conditions. However, because of historical variations in CO 2 , each year farmers throughout the world perform uncontrolled yield ‘experiments’ under different levels of CO 2 . In this study, measurements of atmospheric CO 2 growth rates and crop yields for individual countries since 1961 were compared to empirically determine the average effect of a 1 ppm increase of CO 2 on yields of rice, wheat, and maize. Because the gradual increase in CO 2 is highly correlated with major changes in technology, management, and other yield controlling factors, we focused on first differences of CO 2 and yield time series. Estimates of CO 2 responses obtained from this approach were highly uncertain, reflecting the relatively small importance of year‐to‐year CO 2 changes for yield variability. Combining estimates from the top 20 countries for each crop resulted in estimates with substantially less uncertainty than from any individual country. The results indicate that while current datasets cannot reliably constrain estimates beyond previous experimental studies, an empirical approach supported by large amounts of data may provide a potentially valuable and independent assessment of this critical model parameter. For example, analysis of reliable yield records from hundreds of individual, independent locations (as opposed to national scale yield records with poorly defined errors) may result in empirical estimates with useful levels of uncertainty to complement estimates from experimental studies.

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