Evaluation of cropland maximum light use efficiency using eddy flux measurements in North America and Europe

Abstract

[1] Croplands cover 12% of the ice-free land surface and play an important role in the global carbon cycle. Light use efficiency (LUE) models have often been employed to estimate the exchange of CO 2 between croplands and the atmosphere. A key parameter in these models is the maximum light use efficiency ("*), but estimates of "* vary by at least a factor 2. Here we used 12 agricultural eddyflux measurement sites in North America and Europe to constrain LUE models in general and "* in particular. We found that LUE models could explain on average about 70% of the variability in net ecosystem exchange (NEE) when we increased the "* from 0.5 to 0.65-2.0g C per MJ Photosynthetic Active Radiation (PAR). Our results imply that croplands are more important in the global carbon budget than often thought. In addition, inverse modeling approaches that utilize LUE model outputs as a-priori input may have to be revisited in areas where croplands are an important contributor to regional carbon fluxes. Citation: Chen, T., G. R. van der Werf, A. J. Dolman, and M. Groenendijk (2011), Evaluation of cropland maximum light use efficiency using eddy flux measurements in North

Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States

“…Though different from early studies using AVHRR data (Bradford et al, 2005;Lobell et al, 2002), our findings show agreement with recent studies (Bandaru et al, 2013;Chen et al, 2011;Guanter et al, 2014) and indicate that the field-derived ε * GPP values should be consistently used for large-scale modeling. In our results (Figures 2 and 5), it is clear that the underestimated MODIS GPP is largely due to the underestimated ε * GPP .…”

“…Most validation efforts for MODIS GPP have been made using eddy covariance data from flux tower measurements, and some studies suggest increasing the ε * GPP values in models to estimate cropland GPP (Chen et al, 2011;Zhang et al, 2008). On the other hand, some large-scale modeling studies identified overestimations of crop productivity in comparison with statistical inventory data when applying field-derived ε * GPP values (Lobell et al, 2002;Ruimy et al, 1994;Turner et al, 2006).…”

“…Typical ε * GPP in site-scale studies range from 2.40 to 4.24 gC MJ −1 for C4 crops and 1.41 to 1.96 gC MJ −1 for C3 crops (Chen et al, 2011;Kalfas et al, 2011;Lindquist et al, 2005;Singer et al,2011;Turner et al, 2002), while ε * GPP in many large-scale modeling efforts are about 0.604-1.08 gC MJ −1 for croplands (Bradford et al, 2005;Heinsch et al, 2003;Lobell et al, 2002;Zhao and Running, 2010). Note that the ε * GPP values prescribed in many large-scale biogeochemical models are only approximately half of those in a number of small-scale studies.…”

Estimating global cropland production from 1961 to 2010

“…European crop yields today would be more than 16 % lower without access to improved varieties (the British Society of Plant Breeders, BSPB). The 2003 drought and heat in Europe reduced the terrestrial gross primary productivity (GPP) by 30 % (Ciais et al, 2005), while it was decreased by 15 % for cropland NPP in this study (Fig. 5i).…”

“…The importance of parameter calibration has been recognized and addressed by numerous modeling studies Chen et al, 2011;Crowther et al, 2016;Luo et al, 2016;Ogle et al, 2010;Peng et al, 2013). In addition, regional calibrated parameters are critical for global-scale modeling (Le Quéré et al, 2016).…”