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Improved Global Maps of the Optimum Growth Temperature, Maximum Light Use Efficiency, and Gross Primary Production for Vegetation
Author(s) -
Chen Yongzhe,
Feng Xiaoming,
Fu Bojie,
Wu Xutong,
Gao Zhen
Publication year - 2021
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1029/2020jg005651
Subject(s) - primary production , fluxnet , afforestation , environmental science , atmospheric sciences , vegetation (pathology) , photosynthetically active radiation , satellite , photosynthesis , ecosystem , physical geography , geography , ecology , biology , botany , agroforestry , physics , medicine , eddy covariance , pathology , astronomy
The optimum growth temperature ( T opt ) and maximum light use efficiency ( ε max ) of terrestrial vegetation are closely related to plant photosynthesis in current and future Earth environments, yet little is known about their spatial distributions at the global scale. This study derived global maps of T opt and ε max separately, under the light use efficiency (LUE) model framework by utilizing FLUXNET measurements and satellite‐observed solar/sun‐induced chlorophyll fluorescence (SIF), as well as multiple regression and neural network regression based on environmental and biological factors. T opt is found to be positively correlated with annual mean temperature ( T ), except in cold areas with T < 9°C, where T opt stays within the range of 10°C–15°C. T opt is equal to T in tropical areas with T ≥ 25°C, but is obviously higher than T in other regions. ε max is high in regions with a large amount of diffuse radiation and increases significantly with water stress. The maps of T opt and ε max improved the global gross primary production (GPP) estimation ( R 2 = 0.83, RMSE = 1.38 g C m −2 d −1 against flux observations). The average annual GPP was 126 ± 1.5 PgC yr −1 , with a trend of 0.6 ± 0.1 PgC yr −2 during 2001–2016, faster than most previous estimates. Our study suggests that the positive anthropogenic impacts on GPP were underestimated in existing products, including cropland expansion in southern Brazil and afforestation/forest protection efforts in China and western Europe. This study also provides a potential method for unified GPP modeling under the LUE framework.