MaheuCholetCorderoMontoyaEtAl2021

Référence

Maheu, A., Cholet, C., Cordero Montoya, R., Duchesne, L. (2021) Is the annual maximum leaf area index an important driver of water fluxes simulated by a land surface model in temperate forests? Canadian Journal of Forest Research, 51(4):595-603. (Scopus )

Résumé

In land surface models, vegetation is often described using plant functional types (PFTs), a classification that aggregates plant species into a few groups based on similar characteristics. Within-PFT variability of these characteristics can introduce considerable uncertainty in the simulation of water fluxes in forests. Our objectives were to (i) compare the variability of the annual maximum leaf area index (LAImax) within and between PFTs and (ii) assess whether this variability leads to significant differences in simulated water fluxes at a regional scale. We classified our study region in southwestern Quebec (Canada) into three PFTs (evergreen needleleaf, deciduous broadleaf, and mixed forests) and characterized LAImax using remotely sensed MODIS-LAI data. We simulated water fluxes with the Canadian Land Surface Scheme (CLASS) and performed a sensitivity analysis. We found that within-PFT variability of LAImax was 1.7 times more important than variability between PFTs, with similar mean values for the two dominant PFTs, deciduous broadleaf forests (6.6 m2·m-2) and mixed forests (6.3 m2·m-2). In CLASS, varying LAImax within the observed range of values (4.0-7.5 m2·m-2) led to changes of less than 2% in mean evapotranspiration. Overall, LAImax is likely not an important driver of the spatial variability of water fluxes at the regional level. © the author(s) or their institution(s).

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@ARTICLE { MaheuCholetCorderoMontoyaEtAl2021,
    AUTHOR = { Maheu, A. and Cholet, C. and Cordero Montoya, R. and Duchesne, L. },
    JOURNAL = { Canadian Journal of Forest Research },
    TITLE = { Is the annual maximum leaf area index an important driver of water fluxes simulated by a land surface model in temperate forests? },
    YEAR = { 2021 },
    NOTE = { cited By 0 },
    NUMBER = { 4 },
    PAGES = { 595-603 },
    VOLUME = { 51 },
    ABSTRACT = { In land surface models, vegetation is often described using plant functional types (PFTs), a classification that aggregates plant species into a few groups based on similar characteristics. Within-PFT variability of these characteristics can introduce considerable uncertainty in the simulation of water fluxes in forests. Our objectives were to (i) compare the variability of the annual maximum leaf area index (LAImax) within and between PFTs and (ii) assess whether this variability leads to significant differences in simulated water fluxes at a regional scale. We classified our study region in southwestern Quebec (Canada) into three PFTs (evergreen needleleaf, deciduous broadleaf, and mixed forests) and characterized LAImax using remotely sensed MODIS-LAI data. We simulated water fluxes with the Canadian Land Surface Scheme (CLASS) and performed a sensitivity analysis. We found that within-PFT variability of LAImax was 1.7 times more important than variability between PFTs, with similar mean values for the two dominant PFTs, deciduous broadleaf forests (6.6 m2·m-2) and mixed forests (6.3 m2·m-2). In CLASS, varying LAImax within the observed range of values (4.0-7.5 m2·m-2) led to changes of less than 2% in mean evapotranspiration. Overall, LAImax is likely not an important driver of the spatial variability of water fluxes at the regional level. © the author(s) or their institution(s). },
    AFFILIATION = { Institut des Sciences de la Forêt tempérée, Université du Québec en Outaouais, Ripon, QC J0V 1V0, Canada; Direction de la recherche forestière, Ministère des Forêts, de la Faune et des Parcs du Québec, Québec, QC G1P 3W8, Canada },
    AUTHOR_KEYWORDS = { Hydrology; Land surface model; Leaf area index; Plant functional type; Temperate forest },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1139/cjfr-2020-0126 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104231997&doi=10.1139%2fcjfr-2020-0126&partnerID=40&md5=ca1158f8a29ec26ec93e2e2f98446e0b },
}

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