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

Xiuzhi Chen (1) , Fabienne Maignan (1) , Nicolas Viovy (1) , Ana Bastos (1) , Daniel Goll (1) , Jin Wu , Liyang Liu (1) , Chao Yue , Shushi Peng , Wenping Yuan , Adriana Castro da Conceição , Michael O'Sullivan , Philippe Ciais (1)

1 LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette]

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.

Keywords: Amazon; tropical forest phenology; gross primary production (GPP); litterfall; carbon allocation; carbon and water fluxes

Domains: Sciences of the Universe [physics]

Xiuzhi Chen, Fabienne Maignan, Nicolas Viovy, Ana Bastos, Daniel Goll, et al.. Novel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model. Journal of Advances in Modeling Earth Systems, 2020, 12, ⟨10.1029/2019MS001565⟩. ⟨insu-03721904⟩