Impacts of diffuse radiation fraction on light use efficiency and gross primary production of winter wheat in the North China Plain

Publication Type:
Journal Article
Agricultural and Forest Meteorology, 2019, 275 pp. 233 - 242
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© 2019 Elsevier B.V. The increase of diffuse radiation fraction (kd) has been reported to significantly impact light use efficiency (LUE) and carbon uptake in terrestrial ecosystems. The impact of kd on LUE should be considered in crop models to accurately evaluate the effect of radiation changes on crop production. However, the magnitude of the kd effect is difficult to quantify because of the complicated interacting relationships among all of the meteorological parameters, as well as the changing effects for various ecosystem types and research sites. Eight site-years of flux data and two years of diffuse radiation data from two field ecosystems in the North China Plain were used to (1) compare the performance of five kd models, (2) explore the impacts of environmental factors on LUE and gross primary production (GPP) of winter wheat (Triticum aestivum L.), and (3) quantify the relationships between kd and both LUE and GPP of winter wheat. Comparison results showed that the kd model developed by Boland et al. performed the best of the five models evaluated. This model was chosen to calculate kd in this research. Path analysis show that kd was the main factor affecting LUE of winter wheat, explaining up to 55% of the variability in LUE. The relationship between kd and LUE was significantly linear (slope of about 0.326 g C mol−1). GPP initially increased and then decreased with increasing kd. A moderate radiation condition (kd = 0.53) was favorable for increasing GPP. The effect of kd on LUE should be added in the LUE module of APSIM-Nwheat to improve simulation accuracy. The results of this study highlight the importance of kd in correctly modeling LUE for winter wheat with a crop model and provide quantitative relationships between these two parameters. These relationships will be helpful in improving crop model simulation accuracy under changed climate conditions.
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