Submitted to: Annals of Botany
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/30/2013
Publication Date: 6/19/2013
Citation: Kimball, B.A. 2013. Comment on "improving ecophysiological simulation models to predict the impact of elevated CO2 concentration on crop productivity" by X. Yin. Annals Of Botany. 112:477-478.
Interpretive Summary: Crop growth simulation models are used to predict the likely effects of the increasing atmospheric CO2 concentration and global warming on future crop productivity. In the paper listed in the title, Yin describes an improved modeling strategy, and to prove his point, he does a comparison with data we published two decades ago based on free-air CO2 enrichment (FACE) methodology. Unfortunately, we subsequently found a flaw in our methodology for the particular growing seasons on which he based his paper. This "Comment" states this deficiency and provides some subsequent data, as well as perspectives about the FACE method. This research benefits all consumers of food and fiber.
Technical Abstract: The paper listed in the title by Yin (2013) provides an excellent review of modeling approaches to predict the impact of elevated CO2 on crop productivity, as well as on the controversy regarding whether yield responses observed in free-air CO2 enrichment (FACE) experiments are indeed lower than those from chamber-based experiments. I do not disagree with Yin's main thesis that nitrogen-based functional relationships are a robust way to simulate many growth processes. However, as a leader of the Arizona FACE wheat project, I feel a responsibility to point out that our 1992-1993 and 1993-1994 FACE wheat experiments in the example of Fig. 1 by Yin (2013) had a flaw. Unfortunately, for those two cropping seasons, our control plots lacked blowers that were in the FACE plots which warmed the FACE plots at night and hastened plant development (Pinter et al., 2000). Therefore, our measured CO2 response ratios in those two experiments must have been underestimated, so for the models to be correct, we should expect higher response ratios from them than were measured for those two crops. The measured average wheat yield response ratio for those two seasons was 1.08 under ample water and nitrogen. In contrast, for the same ample water and nitrogen conditions, when we had proper controls (i.e., plots at ambient CO2, but with blowers) in 1995-96 and 1996-97 our measured yield response ratios were 1.15 and 1.17, respectively (Kimball et al., 2002) , which are closer to what several of the models predicted (Yin, 2013, Fig. 1) and higher than GECROS, Yin and van Laar's (2005) model. The range in crop response to elevated CO2 in FACE and especially in chamber-based experiments is rather large (e.g. Kimball, 2011, Fig. 9), so it is unclear whether there is a distinct difference in crop responses between the two approaches. Moreover, differences in CO2 response exist among varieties within a species. Recent reports of responses of hybrid rice to elevated CO2 from the Chinese FACE project (Liu et al., 2008; Yang et al., 2009a,b) were about 1.32 or more than double the 1.12 increase observed for non-hybrid rice in prior FACE experiments. Such varietal differences also need to be addressed by the modelers, and researchers need to be searching for more high-CO2-responsive varieties. Even though there appears to be no consistent difference between FACE and enclosure experiments in their relative yield responses to elevated CO2 and although fluctuating CO2 concentrations in FACE experiments can reduce responses (e.g., Holtum and Winter, 2003; Bunce, 2012), the FACE approach still offers distinct advantages. The generally larger plot sizes enable more extensive robust multidisciplinary experiments (e.g., Ainsworth et al., 2008). Kimball et al. (1997) showed that plants often do not grow by the same absolute amounts inside open-top chambers (OTCs) as they do outside, even though relative responses to elevated CO2 may be similar. Because a very important objective of much global change research is to obtain data suitable for validating crop growth models, therefore, a very important advantage of the FACE approach is that such data can be obtained under conditions with greater realism -- for both absolute and relative responses. At the same time, however, enclosure experiments also can continue to contribute valuable data about physiological mechanisms because they enable greater control of individual environmental variables over much larger ranges than are possible in field experiments.