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

TitleNovel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model
Authors
KeywordsAmazon
tropical forest phenology
gross primary production (GPP)
litterfall
carbon allocation
Issue Date2020
PublisherAmerican Geophysical Union. The Journal's web site is located at https://agupubs.onlinelibrary.wiley.com/journal/19422466
Citation
Journal of Advances in Modeling Earth Systems, 2020, v. 12 n. 1, p. article no. e2018MS001565 How to Cite?
AbstractLeaf 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.
Persistent Identifierhttp://hdl.handle.net/10722/280394
ISSN
2018 Impact Factor: 3.457
2015 SCImago Journal Rankings: 4.444

 

DC FieldValueLanguage
dc.contributor.authorChen, X-
dc.contributor.authorMaignan, F-
dc.contributor.authorViovy, N-
dc.contributor.authorBastos, A-
dc.contributor.authorGoll, D-
dc.contributor.authorWu, J-
dc.contributor.authorLiu, L-
dc.contributor.authorYue, C-
dc.contributor.authorPeng, S-
dc.contributor.authorYuan, W-
dc.contributor.authorConceição, ACD-
dc.contributor.authorO'Sullivan, M-
dc.contributor.authorCiais, P-
dc.date.accessioned2020-02-07T07:40:23Z-
dc.date.available2020-02-07T07:40:23Z-
dc.date.issued2020-
dc.identifier.citationJournal of Advances in Modeling Earth Systems, 2020, v. 12 n. 1, p. article no. e2018MS001565-
dc.identifier.issn1942-2466-
dc.identifier.urihttp://hdl.handle.net/10722/280394-
dc.description.abstractLeaf 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.-
dc.languageeng-
dc.publisherAmerican Geophysical Union. The Journal's web site is located at https://agupubs.onlinelibrary.wiley.com/journal/19422466-
dc.relation.ispartofJournal of Advances in Modeling Earth Systems-
dc.rightsJournal of Advances in Modeling Earth Systems. Copyright © American Geophysical Union.-
dc.rightsPublished version Copyright [2020] American Geophysical Union. To view the published open abstract, go to https://doi.org/10.1029/2018MS001565-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectAmazon-
dc.subjecttropical forest phenology-
dc.subjectgross primary production (GPP)-
dc.subjectlitterfall-
dc.subjectcarbon allocation-
dc.titleNovel Representation of Leaf Phenology Improves Simulation of Amazonian Evergreen Forest Photosynthesis in a Land Surface Model-
dc.typeArticle-
dc.identifier.emailWu, J: jinwu@hku.hk-
dc.identifier.authorityWu, J=rp02509-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1029/2018MS001565-
dc.identifier.scopuseid_2-s2.0-85078795330-
dc.identifier.hkuros309067-
dc.identifier.volume12-
dc.identifier.issue1-
dc.identifier.spagearticle no. e2018MS001565-
dc.identifier.epagearticle no. e2018MS001565-
dc.publisher.placeUnited States-

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