skip to main content

DOE PAGESDOE PAGES

This content will become publicly available on April 15, 2019

Title: Spatio-temporal Convergence of Maximum Daily Light-Use Efficiency Based on Radiation Absorption by Canopy Chlorophyll

Light-use efficiency (LUE), which quantifies the plants’ efficiency in utilizing solar radiation for photosynthetic carbon fixation, is an important factor for gross primary production (GPP) estimation. Here we use satellite-based solar-induced chlorophyll fluorescence (SIF) as a proxy for photosynthetically active radiation absorbed by chlorophyll (APAR chl) and derive an estimation of the fraction of APAR chl (fPAR chl) from four remotely-sensed vegetation indicators. By comparing maximum LUE estimated at different scales from 127 eddy flux sites, we found that the maximum daily LUE based on PAR absorption by canopy chlorophyll (ε$$chl\atop{max}$$), unlike other expressions of LUE, tends to converge across biome types. The photosynthetic seasonality in tropical forests can also be tracked by the change of fPAR chl, suggesting the corresponding (ε$$chl\atop{max}$$}$) to have less seasonal variation. Finally, this spatio-temporal convergence of LUE derived from fPAR chl can be used to build simple but robust GPP models and to better constrain process-based models.
Authors:
 [1] ;  [2] ;  [3] ; ORCiD logo [4] ;  [5] ;  [6] ;  [7] ;  [8] ;  [9] ;  [10] ;  [11] ;  [12] ;  [13] ;  [14] ;  [15]
  1. Univ. of Oklahoma, Norman, OK (United States). Dept. of Microbiology and Plant Biology and Center for Spatial Analysis; Columbia Univ., New York, NY (United States). Dept. of Earth and Environmental Engineering
  2. Univ. of Oklahoma, Norman, OK (United States). Dept. of Microbiology and Plant Biology and Center for Spatial Analysis; Fudan Univ., Shanghai (China). Ministry of Education Key Lab. of Biodiversity Science and Ecological Engineering and Inst. of Biodiversity Science
  3. ETH Zurich (Switzerland). Dept. of Environmental Systems Science
  4. Brookhaven National Lab. (BNL), Upton, NY (United States). Biological, Environmental & Climate Sciences Dept.
  5. Univ. of Oklahoma, Norman, OK (United States). Dept. of Microbiology and Plant Biology and Center for Spatial Analysis
  6. Inst. of Biometeorology of the National Research Council (IBIMET-CNR), Firenze (Italy)
  7. Univ. Innsbruck (Austria). Inst. of Ecology
  8. European Commission (EC) Joint Research Centre (JRC) and Directorate for Sustainable Resources, Ispra (Italy)
  9. Univ. of Twente (Netherlands). Faculty of Geo-Information Science and Earth Observation (ITC) and Dept. of Water Resources
  10. Tsinghua Univ., Beijing (China). State Key Lab. of Hydroscience and Engineering and Dept. of Hydraulic Engineering
  11. Virginia Commonwealth Univ., Richmond, VA (United States). Dept. of Biology
  12. Columbia Univ., New York, NY (United States). Dept. of Earth and Environmental Engineering
  13. Nanjing Univ. (China). Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application and International Inst. for Earth System Sciences
  14. Karlsruhe Inst. of Technology (KIT) (Germany). Dept. of Atmospheric Environmental Research and Inst. for Meteorology and Climate Research
  15. Lund Univ. (Sweden). Physical Geography and Ecosystem Science
Publication Date:
Report Number(s):
BNL-203445-2018-JAAM
Journal ID: ISSN 0094-8276
Grant/Contract Number:
SC0012704; 2013-69002-23146; 2016- 68002-24967; IIA-1301789; 80LARC17C0001; 41671421
Type:
Accepted Manuscript
Journal Name:
Geophysical Research Letters
Additional Journal Information:
Journal Volume: 45; Journal Issue: 8; Journal ID: ISSN 0094-8276
Publisher:
American Geophysical Union
Research Org:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); FLUXNET; Natural Environment Research Council (NERC) Earth Observation Data Centre (NEODC); European Space Agency (ESA); Airbus Defence and Space; National Aeronautic and Space Administration (NASA); GFZ German Research Centre for Geosciences; USDA National Inst. for Food and Agriculture (NIFA); National Science Foundation (NSF); National Natural Science Foundation of China (NNSFC)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES
OSTI Identifier:
1431443

Zhang, Yao, Xiao, Xiangming, Wolf, Sebastian, Wu, Jin, Wu, Xiaocui, Gioli, Beniamino, Wohlfahrt, Georg, Cescatti, Alessandro, Van der Tol, Christian, Zhou, Sha, Gough, Christopher, Gentine, Pierre, Zhang, Yongguang, Steinbrecher, Rainer, and Ardo, Jonas. Spatio-temporal Convergence of Maximum Daily Light-Use Efficiency Based on Radiation Absorption by Canopy Chlorophyll. United States: N. p., Web. doi:10.1029/2017GL076354.
Zhang, Yao, Xiao, Xiangming, Wolf, Sebastian, Wu, Jin, Wu, Xiaocui, Gioli, Beniamino, Wohlfahrt, Georg, Cescatti, Alessandro, Van der Tol, Christian, Zhou, Sha, Gough, Christopher, Gentine, Pierre, Zhang, Yongguang, Steinbrecher, Rainer, & Ardo, Jonas. Spatio-temporal Convergence of Maximum Daily Light-Use Efficiency Based on Radiation Absorption by Canopy Chlorophyll. United States. doi:10.1029/2017GL076354.
Zhang, Yao, Xiao, Xiangming, Wolf, Sebastian, Wu, Jin, Wu, Xiaocui, Gioli, Beniamino, Wohlfahrt, Georg, Cescatti, Alessandro, Van der Tol, Christian, Zhou, Sha, Gough, Christopher, Gentine, Pierre, Zhang, Yongguang, Steinbrecher, Rainer, and Ardo, Jonas. 2018. "Spatio-temporal Convergence of Maximum Daily Light-Use Efficiency Based on Radiation Absorption by Canopy Chlorophyll". United States. doi:10.1029/2017GL076354.
@article{osti_1431443,
title = {Spatio-temporal Convergence of Maximum Daily Light-Use Efficiency Based on Radiation Absorption by Canopy Chlorophyll},
author = {Zhang, Yao and Xiao, Xiangming and Wolf, Sebastian and Wu, Jin and Wu, Xiaocui and Gioli, Beniamino and Wohlfahrt, Georg and Cescatti, Alessandro and Van der Tol, Christian and Zhou, Sha and Gough, Christopher and Gentine, Pierre and Zhang, Yongguang and Steinbrecher, Rainer and Ardo, Jonas},
abstractNote = {Light-use efficiency (LUE), which quantifies the plants’ efficiency in utilizing solar radiation for photosynthetic carbon fixation, is an important factor for gross primary production (GPP) estimation. Here we use satellite-based solar-induced chlorophyll fluorescence (SIF) as a proxy for photosynthetically active radiation absorbed by chlorophyll (APARchl) and derive an estimation of the fraction of APARchl (fPARchl) from four remotely-sensed vegetation indicators. By comparing maximum LUE estimated at different scales from 127 eddy flux sites, we found that the maximum daily LUE based on PAR absorption by canopy chlorophyll (ε$chl\atop{max}$), unlike other expressions of LUE, tends to converge across biome types. The photosynthetic seasonality in tropical forests can also be tracked by the change of fPARchl, suggesting the corresponding (ε$chl\atop{max}$}$) to have less seasonal variation. Finally, this spatio-temporal convergence of LUE derived from fPARchl can be used to build simple but robust GPP models and to better constrain process-based models.},
doi = {10.1029/2017GL076354},
journal = {Geophysical Research Letters},
number = 8,
volume = 45,
place = {United States},
year = {2018},
month = {4}
}