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Title: Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model

Abstract

Leaf phenology in the humid tropics largely regulates the seasonality of forest carbon and water exchange. However, it is inadequately represented in most global land surface models due to limited understanding of its controls. Based on intensive field studies at four Amazonian evergreen forests, we propose a novel, quantitative representation of tropical forest leaf phenology, which links multiple environmental variables with the seasonality of new leaf production and old leaf litterfall. The new phenology simulates higher rates of leaf turnover (new leaves replacing old leaves) in dry seasons with more sunlight, which is then implemented in ORCHIDEE, together with recent findings of ontogeny-associated photosynthetic capacity, and is evaluated against ground-based measurements of leaf phenology (canopy leaf area index and litterfall), eddy covariance fluxes (photosynthesis and latent heat), and carbon allocations from field observations. Results show the periodical cycles of solar radiation and vapor pressure deficit are the two most important environmental variables that are empirically related to new leaf production and old leaf abscission in tropical evergreen forests. The model with new representation of leaf phenology captures the seasonality of canopy photosynthesis at three out of four sites, as well as the seasonality of litterfall, latent heat, and light usemore » efficiency of photosynthesis at all tested sites, and improves the seasonality of carbon allocations to leaves, roots, and sapwoods. This study advances understanding of the environmental controls on tropical leaf phenology and offers an improved modeling tool for gridded simulations of interannual CO2 and water fluxes in the tropics.« less

Authors:
 [1];  [2];  [2];  [3];  [2];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [2]
  1. Sun Yat‐Sen Univ., Guangzhou (China); Laboratoire des Sciences du Climat et de l'Environnement/IPSL, Gif‐sur‐Yvette (France); Southern Marine Science and Engineering Guangdong Lab., Zhuhai (China)
  2. Laboratoire des Sciences du Climat et de l'Environnement/IPSL, Gif‐sur‐Yvette (France)
  3. Laboratoire des Sciences du Climat et de l'Environnement/IPSL, Gif‐sur‐Yvette (France); Ludwig‐Maximilians Univ., Munich (Germany)
  4. Brookhaven National Lab. (BNL), Upton, NY (United States); The Univ. of Hong Kong, Pokfulam (Hong Kong)
  5. Laboratoire des Sciences du Climat et de l'Environnement/IPSL, Gif‐sur‐Yvette (France); Southern Marine Science and Engineering Guangdong Lab., Zhuhai (China)
  6. Northwest A&F Univ., Yangling (China)
  7. Peking Univ., Beijing (China)
  8. Sun Yat‐Sen Univ., Guangzhou (China); Southern Marine Science and Engineering Guangdong Lab., Zhuhai (China)
  9. National Inst. for Amazonian Research (INPA), Manaus (Brazil)
  10. Univ. of Exeter (United Kingdom)
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER); National Natural Science Foundation of China (NNSFC); Belgian Science Policy Office (Belspo)
OSTI Identifier:
1614972
Report Number(s):
BNL-213828-2020-JAAM
Journal ID: ISSN 1942-2466
Grant/Contract Number:  
SC0012704; 41401055; 31500357; SR/00/334
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Volume: 12; Journal Issue: 1; Journal ID: ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Amazon; tropical forest phenology; gross primary production (GPP ); litterfall; carbon allocation; carbon and water fluxes

Citation Formats

Chen, Xiuzhi, Maignan, Fabienne, Viovy, Nicolas, Bastos, Ana, Goll, Daniel, Wu, Jin, Liu, Liyang, Yue, Chao, Peng, Shushi, Yuan, Wenping, Conceição, Adriana Castro, O'Sullivan, Michael, and Ciais, Philippe. Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model. United States: N. p., 2019. Web. https://doi.org/10.1029/2018MS001565.
Chen, Xiuzhi, Maignan, Fabienne, Viovy, Nicolas, Bastos, Ana, Goll, Daniel, Wu, Jin, Liu, Liyang, Yue, Chao, Peng, Shushi, Yuan, Wenping, Conceição, Adriana Castro, O'Sullivan, Michael, & Ciais, Philippe. Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model. United States. https://doi.org/10.1029/2018MS001565
Chen, Xiuzhi, Maignan, Fabienne, Viovy, Nicolas, Bastos, Ana, Goll, Daniel, Wu, Jin, Liu, Liyang, Yue, Chao, Peng, Shushi, Yuan, Wenping, Conceição, Adriana Castro, O'Sullivan, Michael, and Ciais, Philippe. Fri . "Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model". United States. https://doi.org/10.1029/2018MS001565. https://www.osti.gov/servlets/purl/1614972.
@article{osti_1614972,
title = {Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model},
author = {Chen, Xiuzhi and Maignan, Fabienne and Viovy, Nicolas and Bastos, Ana and Goll, Daniel and Wu, Jin and Liu, Liyang and Yue, Chao and Peng, Shushi and Yuan, Wenping and Conceição, Adriana Castro and O'Sullivan, Michael and Ciais, Philippe},
abstractNote = {Leaf phenology in the humid tropics largely regulates the seasonality of forest carbon and water exchange. However, it is inadequately represented in most global land surface models due to limited understanding of its controls. Based on intensive field studies at four Amazonian evergreen forests, we propose a novel, quantitative representation of tropical forest leaf phenology, which links multiple environmental variables with the seasonality of new leaf production and old leaf litterfall. The new phenology simulates higher rates of leaf turnover (new leaves replacing old leaves) in dry seasons with more sunlight, which is then implemented in ORCHIDEE, together with recent findings of ontogeny-associated photosynthetic capacity, and is evaluated against ground-based measurements of leaf phenology (canopy leaf area index and litterfall), eddy covariance fluxes (photosynthesis and latent heat), and carbon allocations from field observations. Results show the periodical cycles of solar radiation and vapor pressure deficit are the two most important environmental variables that are empirically related to new leaf production and old leaf abscission in tropical evergreen forests. The model with new representation of leaf phenology captures the seasonality of canopy photosynthesis at three out of four sites, as well as the seasonality of litterfall, latent heat, and light use efficiency of photosynthesis at all tested sites, and improves the seasonality of carbon allocations to leaves, roots, and sapwoods. This study advances understanding of the environmental controls on tropical leaf phenology and offers an improved modeling tool for gridded simulations of interannual CO2 and water fluxes in the tropics.},
doi = {10.1029/2018MS001565},
journal = {Journal of Advances in Modeling Earth Systems},
number = 1,
volume = 12,
place = {United States},
year = {2019},
month = {12}
}

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