Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model. (10th January 2020)

• Record Type: Journal Article
• Authors: Chen, Xiuzhi; Maignan, Fabienne; Viovy, Nicolas; Bastos, Ana; Goll, Daniel; Wu, Jin; Liu, Liyang; Yue, Chao; Peng, Shushi; Yuan, Wenping; da Conceição, Adriana Castro; O'Sullivan, Michael; Ciais, Philippe
• Is Part Of: Journal of advances in modeling earth systems. Volume 12:Number 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-01-10
• Subjects: Amazon -- tropical forest phenology -- gross primary production (GPP) -- litterfall -- carbon allocation -- carbon and water fluxes; Geological modeling -- Periodicals; Climatology -- Periodicals; Geochemical modeling -- Periodicals; 551.5011
• DOI: 10.1029/2018MS001565
• Languages: English
• ISSNs: 1942-2466

Abstract

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 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. Key Points: We explore the environmental drivers to trigger off new leaf formation and old leaf shedding in Amazonian evergreen forests This model links leaf phenology with the seasonality of carbon allocation to leaves, roots, and sapwood The new phenology model leads to good representation of the seasonality of canopy photosynthesis, litterfall and latent heat