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| Main Author: | |
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| Format: | Dataset Open Access |
| Language: | en |
| Published: |
PANGAEA
2020
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| Subjects: | |
| Online Access: | https://doi.org/10.1594/PANGAEA.911385 |
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Table of Contents:
- Light use efficiency models are commonly applied to simulate global terrestrial gross primary production (GPP)- carbon uptake by terrestrial vegetation through photosynthesis. However, some key parameters within this model, including the optimum growth temperature for vegetation (T_opt) and the maximum light use efficiency (ε_max), which represents the potential light energy conversion ability for plants without heat or water stresses, remain rather uncertain. In this study, we spatially mapped these two parameters at the global scale. The methods can be divided into four steps. First, the existing LUE equations are compared and adjusted to devise an optimized LUE model (the prerequisite of T_opt and ε_max mapping). Second, the T_opt values at 115 flux sites are fitted under the optimized LUE model and then extrapolated to the global scale by exploring the relationship between T_opt and local climate conditions as well as vegetation composition. Third, by integrating the slope of the regression between SIF and the simulated GPP with ε_max=1 and the extrapolated map of the regression coefficient between SIF and actual GPP, ε_max values are estimated at the global scale. Finally, we calculated global GPP during 2001~2016 based on the revised LUE model and with the T_opt and ε_max maps incorporated. The resulting maps can indicate the strong interaction between plants and the living environment, while the global GPP simulation accuracy can be improved significantly by incorporating the maps of T_opt and ε_max (R2 =0.83, RMSE =1.38 g C m-2 d-1 against flux observations)). Upon analysis, we distinguished a faster GPP rising rate and a stronger positive impact of human activities on global GPP during 2001~2016 than most previous studies.