Integration and Comparison of Multiple Two-Leaf Light Use Efficiency Models Across Global Flux Sites
文献类型: 外文期刊
第一作者: Zhou, Haoqiang
作者: Zhou, Haoqiang;Bao, Gang;Tong, Siqin;Huang, Xiaojun;Guo, Enliang;Bao, Yuhai;Rina, Wendu;Zhou, Haoqiang;Bao, Gang;Tong, Siqin;Huang, Xiaojun;Guo, Enliang;Bao, Yuhai;Rina, Wendu;Li, Fei;Chen, Jiquan
作者机构:
关键词: Biological system modeling; Atmospheric modeling; Data models; Ecosystems; Remote sensing; Forestry; Vegetation mapping; Eddy covariance (EC); gross primary productivity (GPP); light intensity; model integration; topography; two-leaf LUE model
期刊名称:IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING ( 影响因子:5.5; 五年影响因子:5.5 )
ISSN: 1939-1404
年卷期: 2023 年 16 卷
页码:
收录情况: SCI
摘要: Accurate estimation of gross primary productivity (GPP) from the regional to global scale is essential in modeling carbon cycle processes. The recently-developed two-leaf light use efficiency (TL-LUE) model and its revised versions based on different concepts have significantly improved the underlying mechanisms between model assumptions and photosynthetic processing. Yet few studies have compared the advantages of the various two-leaf LUE models for their practical applications. Here, an integrated model referred to as a three-parameter radiation-constrained mountain TL-LUE (RMTL3-LUE) is proposed by combining the radiation scalar of the [radiation-constrained TL-LUE model] and the topographic parameters of the [mountainous TL-LUE model]. In this way, the importance of light intensity and topography on vegetation photosynthesis is integrated. Our calibration and validation of RMTL3-LUE were carried out for 11 ecosystems with in situ eddy covariance measurements around the globe. This indicates that the model can effectively improve the GPP estimates compared with its predecessors. At the landscape scale, RMTL3-LUE can also realistically quantify topographic effects on photosynthesis, with topographic sensitivities of decreasing (increasing) with the slope on the unshaded (shaded) terrain. Furthermore, RMTL3-LUE displays an asymmetric sensitivity to PAR variability, with a low sensitivity to PAR compared with other models under high PAR conditions and a similar sensitivity to PAR in low PARs. Altogether, it is clear that the integration of the merits of multiple TL-LUE models can further improve the photosynthetic processes for various conditions amid more challenges in constructing more complex models.
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